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Contents lists available at ScienceDirectTunnelling and Underground Space Technologyjournal homepage: /locate/tustTunnellingandUndergroundSpaceTechnology95(2020)103148Roadheader A comprehensive reviewSuraj Deshmukha, A.K. Rainaa, V.M.S.R. Murthyb, R. Trivedia, R. Vajreaa CSIR-Central Institute of Mining and Fuel Research, Unit I, 17/C Telangkhedi Area, Civil Lines, Nagpur, Maharashtra 440001, Indiab Department of Mining Engineering, IIT(ISM), Dhanbad, Jharkhand 826001, IndiaA R T I C L E I N F OKeywords:Roadheader Mechanical excavation TunnellingReviewA B S T R A C TMechanical excavators are preferred to conventional drilling and blasting as blasting poses several regulatory and operational issues. The roadheader is a machine for excavating rock in mining and civil construction pro- jects. It is a hybrid machine, with better manoeuvrability than that of tunnel boring machines. It can cut rocks even up to 160 MPa, if laminated or fractured, in dierent tunnel proles and adapts easily to changing op- erational conditions. A comprehensive survey of literature pertaining to varied aspects of the roadheader is presented in this paper. This review classies literature on roadheaders into multiple classes and sub-classes and identies important parameters that dene roadheader eciency and the risk factors involved in its deployment. We also provide an account of recent technological additions that help collect data on roadheader performance during operations. Such data has the potential to rapidly improve roadheader design.1. IntroductionThe roadheader (RH) is the most widely used underground partial- face mechanical excavator. Roadheaders were rst developed to me- chanically excavate coal in the early 1950s. Later, their use was ex- tended to civil constructions where RHs were extensively used for ex- cavating railway tunnels, roadways, sewers, and diversion tunnels in soft and moderately hard ground conditions. Since 1970, they have been used in civil industries to form main haulage drifts, roadways, cross-cuts etc. and, in mining industries, to mine soft rock, coal, in- dustrial minerals and evaporitic rocks.The roadheader is a hybrid mechanical excavator and consists of a boom-mounted rotating cutting head with a conveyor for broken rocks Fig. 1. A crawler travelling track moves the entire machine forward into the rock face. High mobility, advance rates, reliability, low strata dis- turbance, safety and low labour deployment are some of the advantages of the RH. The main advantage of the roadheader is its high cuttingpower density provided by the small diameter of its cutting drum. This gives the RH the cutting edge over other mechanical excavators. Recent advances have made RHs more ecient in hard rock tunnelling. In- crease in machine weight, size, automation and remote-control fea- tures, cutterhead and boom positioning, advances in hydraulic and electrical systems, muck pick and loading systems, ecient cutter head and metallurgical advances in cutterhead design are some of the changes that mark the development of the RH over time.The development of the RH over time and with application to harder rocks are provided in Fig. 2.It is evident from Fig. 2 that eort has been focussed on developing RHs for higher strength rocks. However, with the improvements, the weight of the RH has also increased which points to the fact that the compressive strength of the rock and the weight of machine are strongly related. This conclusion also highlights the drawback that, with higher weight of the machine, the handling problem increases.2. Classication of roadheadersTucker (1985) classied roadheaders by their weight and the compressive strength of the rocks that they can cut. Thus, RHs with a weight of up to 30 tonnes and a cutting capability of up to 70 MPa were categorised as light duty. Those with weights of up to 3445 tonnes with compressive strength 100 MPa were medium duty while those that were over 45 tonnes with compressive strength of 150 MPa could be classied as heavy-duty RH. Atlas Copco-Eickho suggested another Corresponding author.E-mail address: rainajicimfr.nic.in (A.K. Raina)./10.1016/j.tust.2019.103148R08e8ce6i-v7e7d984/Apr2il021091E9l;seRveiceerivLetdd.iAnllrervigishetdsrfeosremrv2e0d.September 2019; Accepted 13 October 2019TunnellingandUndergroundSpaceTechnology95(2020)103148S. Deshmukh, et pressive strength installed power in KW energy transfer ratio optimum specic energy diametertensile strength brittleness indexcPk SEopt DtBIrock mass cuttability index rock quality designation series quadratic programmingRMCI RQD SQPLS-DYNA advanced general-purpose multiphysics simulation soft- wareNATMnew Austrian tunneling method PFC2Dparticle ow code 2-dimensional MLPmultilayer perceptron system ANNarticial neural networkKSOFMkohonen self-organising feature mapGPgenetic programmingGEPgene expression programmingDAQdata acquisition processUPDSultra-wideband pose detection systemAbbreviationsroadheaderproportional integral derivative controller power control centreinstantaneous cutting rate rock mass brittleness index specic energyvertical rock cutting rig uniaxial compressive strength rock penetration index vibration analysis programme analysis systemNomenclatureShort termsRH PID PCC ICR RMBI SE VRCR UCS RPI VAP ANSYSFig. 1. Schematic diagram of a typical roadheader (drawn after /product_applications/road-header/ (Accessed on 10.09.2019).21classication according to weight for the RH (Schneider, 1988). RHs of 20 tonnes come under class 0, 2030 tonnes in Class I etc. Neil et al. (1994) classied the RH on the basis of cutting action into longitudinal type milling/borer/axial head and transverse type ripping head.Apart from this Jian and Hao (2008) proposed a summary of key technological issues in mechanized mining with a boom-type RH, and also proposed an alternative classication, based on the rational matching of working parameters. Boom-type roadheaders were classi- ed as small size (up to 30 tonnes), mid-size (between 30 and 70 tonnes) and large size (between 70 and 120 tonnes). Roadheader classication as recorded by dierent authors is given in Table 1.3. A classication of literature on roadheadersPublished literature on the RH can be classied into at least 11 groups as presented in Fig. 3. It is evident from Fig. 3 that literature has focussed on dierent aspects of the RH, ranging from cutter head design and pick conguration, to performance prediction, risk and failure analyses, dust suppression and positioning, using various analytical techniques such as regression and articial intelligence. These classes of literature are discussed in further detail in this review. As far as pos- sible, we have kept a historical perspective in the review to provide an understanding of the shifting trends in research on various aspects of roadheaders.3.1. Design of roadheader cutters/cutting headMechanical rock and coal excavation machines, such as road- headers, drum shearers and continuous miners, excavate rock material using a number of picks mounted on their cutting heads or drums. The shape of the cutting head and the conguration of the picks inuence the performance of roadheaders. So, literature gives importance to the design of the cutting head.Evans (1972) suggested that, by imposing force on picks, line spacing between the picks controls the cross-section area swept by the picks. Hurt and MacAndrew (1981) concluded that, by providing equal pick spacing, force variations can be maintained at a minimum level. Hurt et al. (1982), after analysing force balance, surmised that cir- cumferential pick spacing must be kept equal around the cutting head periphery. Hurt and MacAndrew (1985) suggested that, in order to balance pick force, applying graded lacing at corner cutting is desirable. Hekimoglu and Fowell (1991) introduced tramming of the tool holder to obtain equal circumferential pick spacing for 360 and over. Eyyuboglu (2000) suggested that the most reliable angles of wrap were 360 and 776. The most important parameter in the cutting drum periphery is pick spacing. For eective cutting and for applying picks appropriate for the strata, the parameters used are indexed in Table 2. It is evident, from Table 2, that line spacing and pick imposition have received greater attention in pick conguration. In engineeringparameters, area and sweep volume have been used most.Hekimoglu (1991) compared longitudinal and transverse cutting heads to show that consistency of product size is likely higher in the transverse type while arcing. In the case of the longitudinal type RH, the exertion of pick force is comparatively low while arcing and low- ering. Eyyuboglu and Bolukbasi (2005) investigated the eect of cir- cumferential pick spacing on the cutting head and conducted a force balance analysis by taking dierent engineering parameters into ac- count. Their studies showed that no signicant dierence existed be- tween the two cutting heads during the simulation. Shiyong (2005) established a programme based on the laneway and working para- meters of the EBJ-132A roadheader to trace cutting head position and concluded that pick spacing plays an important role when designing a cutter head to attack eectively in dierent cutting conditions.Fowell et al. (1987) concluded that the pick locking device inu- ences tool performance and the economical way of achieving drag pick cutting eciency is to recover worn and damaged tools. Alvarez et al. (2003) conducted an experimental study over two dierent types of roadheaders (45 KW and 15 t) to excavate a gallery, taking specic energy, cutting rate and tool wear into account. Their results showed that both types of cutting head work properly. Chupin and Bolobov (2019) suggested a high temperature thermomechanical treatment be applied to 35KhGSA steel which is mainly used for sandstone cutting.Fig. 2. Correlation between weight and compressive strength (drawn after Schneider, 1988; Tucker, 1985).The result shows that there is a total increase of 23% in hardness and 38% of wear reduction as compared to the case in the conventional heat treatment process.Kotwica et al. (2010) developed a cutter head trajectory for hard rock mining that underwent a eld test on the KR150 roadheader and is an adaptable modernisation of the cutter head. Kotwica (2011) eval- uated the problem encountered with the tangential rotary pick of the boom and presented a solution to counter the rapid wearing of the picks using appropriately placed water jets on the cutter head. Mezyk et al. (2019) developed a cutter drum powertrain system which includes a permanent magnet inside the cutting drum. The new system showed improved dynamic performance but experienced increased vibration during cutting. The focus is then on the angular velocity of the cutting drum which allows better control over cutting drum angular speed.Hurt and Morris (1985) developed a computerized cutter head de- sign for the roadheader that was also implemented on the Dosco-MK3 heavy-duty roadheader which worked successfully, worldwide. Rostami et al. (1994) developed a computer programme for optimizing the de- sign of the cutterhead to improve machine performance and produc- tion. Average cutting force applied by the cutter head is simulated by Fn = APb where Fn is the normal force, P is the penetration and A and b are the coecients determined by the cutting test. Fowell et al. (1994) predicted the performance of drag tools by taking compressive strength as a major parameter. Tiryaki et al. (2001) developed a computer aided design programme to design the cutting head and improve its life span. Before designing, a laboratory test was conducted for triple tracking to access vibration analysis through a programme (VAP). Ergin and Acaroglu (2007) developed a computer programme to dene road- header stability with both cutting head types on the basis of four states: turning around the vertical axis, turning to the side, turning to the back and sliding. Li et al. (2012) derived a dynamic equilibrium equation for the performance of the boom-type cutter head using ANSYS/LS-DYNA software to simulate the cutting process and achieve main kinematic parameters and found that the cutting performance of the machine is also dependent on machine characteristics such as machine weight, machine power, cutter head type and types of cutter. It was found that the transverse type cutter head with mini-disc cutters could increase roadheader stability in hard rock conditions.In spite of these developments, cutterhead selection and cutting tool conguration are still very dicult to assess. Cutter head selection is also based on the performance under dierent geological conditions.3.2. Inuence of geology on roadheader performanceSeveral rock properties aect the cutting force of a RH. Uniaxial Compressive Strength (UCS), Brazilian Tensile Strength (BTS), quartz content, Ratio of UCS to BTS, and Cone indenter hardness, tangent Youngs modulus, density, porosity, static elasticity modulus, shore scleroscope hardness, specic energy, rock quality designation, Rock mass cuttability index, Cercher abrasivity index and point load strength, are some of the parameters of rock that are found to inuence RH performance. The roadheader can cut fractured or closely jointed rocks of up to 160 MPa of UCS that has a bearing on the consistent development of roadheader machine power and weight (Pandey et al., 2017). Bilgin et al. (1997) investigated the geological factors, con- struction method and the physical and mechanical properties of rock formations on two dierent roadheaders viz. ALPINE ATM 75 and EICKHOFF ET 250. Thuro and Plinninger (1999) developed a correla- tion between geological parameters, cutting performance and bit wear to predict tunnel stability for major tunneling projects. Thuro (2003) proposed a correlation between geological parameters, cutting perfor- mance and bit wear to determine tunnel stability.Yilmaz (2005) determined that the ratio of uniaxial compressive strength to tensile strength and compared the same with the cutting eciency of drag pick cutting. He observed an increase in cutting ef- ciency in rocks with higher brittleness. Ebrahimabadi et al. (2012)TunnellingandUndergroundSpaceTechnology95(2020)103148S. Deshmukh, et al.Table 1Classication of Roadheaders.Tucker (1985)Atlas Copco-Eickho (Schneider, 1988)Neil et al. (1994)YearWeight (tonnes)Compressive strength of rock to be cut (MPa)ClassWeight (T)Longitudinal TypeTransverse Type19609400 75Fig. 3. Classication of Roadheader literature.claimed a universal model to access roadheader performance for all kinds of rock strata with the help of the rock mass brittleness index (RMBI). They related intact and rock mass characteristics to machine performance. Pandey et al. (2017) concluded that the impact of the physico-mechanical properties of the rock mass are the most inuen- cing parameters impacting the performance of the roadheader.Bilgin et al. (2004) investigated geological impact on a 90KW shielded roadheader with respect to site conditions, rst with hor- izontal phase and, next, with a 9 inclination, and concluded that the inclination helps to increase ICR from 10 to 25 m3/h. The results show that ICR increases with respect to increase in water content from 3.5 to 11 l/min when plastic limit and the amount of Al2O3 content of the rock is low. Li (2000) developed a mathematical model based on the forces acting on the cutting head. According to him forces on structurally complicated and uncomplicated seams are distributed according to Rayleigh and Chi-sup functions. Wen-liang (2013) derived a kinematicmodel based on the elevation of the site and the turning mechanism of the roadheader.3.3. Cutting performanceCutting performance is a term used in underground excavation to illustrate the inuence of cutting rate and cutter wear parameters in dierent geological conditions. Several studies such as coordinate transfer, laboratory trials to access cutting rate, stability while cutting, comparison between performance of dierent types of roadheader etc. can be traced in literature.Fowell and McFeat-Smith (1976) conducted a lab test on in situ samples to monitor the performance of DOSCO RH for the construction of roadway drivage of Blackhall colliery, County Durham. The me- chanical parameters of RH were also correlated with rock mass prop- erties and discussed the factors inuencing the cutting performanceTunnellingandUndergroundSpaceTechnology95(2020)103148S. Deshmukh, et al.Table 2Pick spacing parameters.Sl. No.AuthorsPick congurationTEngg. parametersT12345678910123451Evans (1972)222Roxborough (1973)223Hurt and MacAndrew (1981)324Hurt et al. (1982)525Hekimoglu (1991)226Hurt and Morris (1985)627Hurt and MacAndrew (1985)528Hekimoglu (1995)439Fowell and Johnson (1981)2110Eyyuboglu (2000)01Total Cites4232662322316632219Pick conguration: 1. Pick spacing, 2. Lacing type - Graded lacing, 3. Circumferential pick spacing, 4. Equal spacing, 5. Line spacing (picks), 6. Pick imposition, 7. Lacing, 8. Pick grouping, 9. Pick force, 10. Boom force; T is total.Engineering (Engg.) parameters: 1. Area, 2. Sweep volume, 3. Angle of wrap, 4. Torque, 5. Specic energy.respectively. They dened the specic energy as a ratio of the cutter- head power and ICR. However, the classication in terms of RQD proposed by them showed lot of scatter. McFeat-Smith and Fowell (1977) developed a curvilinear regression equation of sedimentary rocks to describe the cutting rate, tool wear and chip size of the debris based on laboratory test with actual cutting performance of RH. Fowell and Johnson (1981) presented performance prediction of boom type tunneling machine by taking cutting rate and tool consumption from intact rock properties into account. Their work briey touches the utilization factors and parameters inuencing the cutting performance for the assessment of a particular project. However, Bilgin et al. (2004) observed that performance criterion of the Mcfeat, Smith and Fowell is biased towards the joint density. Additionally, the models presented by Rostamiet al. (1994) and Rostamiet al. (1994) have received more at- tention due to the fact that the sand model incorporates full scale cut- ting test and identies energy transfer coecient that has a bearing on the roadheader utilization.Guo et al. (2002) developed an equation using coordinate transfer by employing pick locus, velocity and acceleration of longitudinal cutting head. Using simulation, he showed that pick velocity and ac- celeration increase rapidly with rotation velocity. Hekimoglu and Ozdemir (2004) carried out laboratory trials to simulate the actual cutting position and angle of wrap in tool lacing and investigated that higher RPM might give poor performance due to higher tool force in the presence of greater angle of wrap. Bilgin et al. (2005) proposed statis- tical analysis to assess the net advance cutting rate on the basis of a laboratory tests on big blocks of rocks with a linear cutting machine.Keles (2005) conducted a study on the medium weight milling type roadheader (MK-2B) by carrying out a physico mechanical test which, in turn, shows that the ICR instantaneous cutting rate has a strong correlation with specic energy. Acaroglu and Ergin (2005) determined the stability of the roadheader using a computer programme and in- vestigated the eect of dierent cutting shapes. They concluded that the increase in tilt angle may negatively aect the sliding momentum of all cutting states. Acaroglu and Ergin (2006) developed a model to determine the stability state of the roadheader by examining the turning moment of the vertical axis, turning to the side, turning to the back and sliding to observe the Stability Index for dierent modes of cutting. Their results showed that turning about the vertical axis is one of the most critical states while arcing.Fu et al. (2019) developed a pose detection method on the basis of an ultra-wide band pose detection system (UPDS). The UPDS system is used to access data related to heading, rolling and pitch angles. The UPDS involves three positioning algorithms: Indirect positioning algo- rithm (IPA-D), Taylor series expansion algorithm (Taylor-D), and Chan positioning algorithm (Chan-D). The comparison shows that IPA-Dgives more precise results in both narrow and long roadways.Though the cutting performance of roadheaders is a critical factor, the literature available is not adequate to address all types of road- headers and under dierent conditions. Future research may need to focus on a coherent understanding of the cutting eciency of various types of roadheaders under dierent geological conditions to enable informed decision making on the choice of roadheader to be deployed in specic situations.3.4. Roadheader positioning and vibration diagnosisThe positioning of the boom is critical to achieve high production rate. To monitor and control the cutting section, attention has to be given to the positioning of the boom-type roadheader. Any mismatch in the cutting action may result in vibrations that ultimately aect the performance of the RH. The positioning of the roadheader thus plays an important role in the reliability of the roadheader.Li and Han (2008) proposed a parallel link, work coordinate system through a coordinate transformation matrix that is relative to the tunnel coordinate for regulating forward and inverse problems to achieve better automatic control, monitoring the cutting section and instruct tunnel operations. Du et al. (2012) proposed an error encounter strategy of the pose of the boom type RH to work more eciently by including adjustment of boom, shovel and support to reduce error and correction of cutting position contour.Tao et al. (2017) developed an iGPS multipoint measuring system to assess even slight deections and displacements of the roadheader on the basis of a random error transfer equation. Tao et al. (2018) devised an iGPS-based single station, multipoint, time-shared position and at- titude measurement system through coordinate measurement. Further, they used the error transfer equation, deduced from mathematical modelling and random error modelling theory, to have better control on the positioning of the RH.Vibration monitoring is very important for RH structure and design optimization as well as for researching fault diagnosis. The machine vibration correlates well with RH performance and thus determines its reliability. In the era of full mechanization, data from various sensors along with mathematical models are employed for vibration diagnosis. Li and Wu (2008) obtained a sinusoidal harmonic motion based on ADAMS vibration analysis module. They observed that 20 Hz, 29 Hz, 120 Hz and 134 Hz are the sensitive frequencies that determine the displacement response and mechanism of cutting of a RH. Jianguang (2012) established a mathematical model to analyse amplitude and frequency of components vibration of RH. Li et al. (2013) determined the vibration characteristics of RH by Lagrangian-Laplace transforma- tion, natural frequency and three orders vibration mechanism is used tocalculate the displacement response of longitudinal type RH with the help of pseudo-excitation method.Ma and Liu (2013) developed a model to determine the motor ex- citation force on the star wheel loader. They determined RH failure position by analysing vibration, stress and strain of the rotation plate. Liet al. (2013) developed a load identication method based on vi- bration and stress signals by taking rock sample cut by EBZ260 RH. They obtained the results by determining a relation between average energy of vibration, acceleration and average stress that provided in- direct measurement of dynamic load.Dolipski et al. (2014) proposed a model on the basis of discrete structure for the analysis of vibration of masses acting on the centre part of the boom, the extendable part (telescope) and a reduction gear with transverse cutting heads and showed that the excitation of vibra- tion is the eect of rock cutting. Liu et al. (2015) developed a multibody dynamic theory model for the bearing plate to assess vibration char- acteristics, which resulted in a frequency response diagram for RH system vibration and the load analysis of the bearings. Cheluszka and Mann (2019) developed a photogrammetric method to access cutter- head vibration using: an accelerometer mounted on the cutting head and high-speed camera connected with TEMA 3D software. The velo- cities and cutting moment recorded by the accelerometer and high- speed camera is used to determine acceleration. The method was then applied to two dierent cutterheads perpendicular to the oor.3.5. Roadheader design and implementationThe unique design and construction of the RH provides various advantages such as reduced directional constraints and thus exibility to deal with cutting conditions with lowering, undercutting, lifting and arcing, without hampering operational stability. The contributions to the design of present day roadheaders are summarised below.Hurt and MacAndrew (1981) conducted investigations into the cutting tool and concluded that tools do not cut eectively in a cutting line. Tools that can withstand the rough conditions without breaking or cracking was the focus for Zhang and Zhang (2005). They introduced a casting technique design in the S200M RH to prevent forging blank, casting crack, shrinkage cavity and slag inclusion. Such a technique that denes the constructional quality of making a mould for a specic purpose is referred to as a constructing principle for roadheader design.Rostami et al. (1994) developed a computer program for roadheader design optimization and performance prediction, and used it to check a heavy-duty roadheader of the 100-ton weight class (AM-105). They found that the excavation rate was 40 to 100 ton/hr in such heavy-duty roadheaders.Performance in eld situations, however, depends not only on the rate of excavation, but also on the removal of debris. Zhang et al. (2013) showed that roadheader shovel design determines lifting and dumping performance and delineated the design parameters to choose the perfect design for further computing. The performance of shipping sectors is also determined by the shovel board parameters of road- header. Burkov et al. (2014) focused on the advantages of the road- header feeder, and the importance of designing the crank and rod mechanism of the roadheader. Another issue that had to be resolved was dust generated during operations. Barham and Buchanan (1987) suggested a roadheader system with a water jet of up to 700 bar pres- sure to improve the cutting performance of a boom-type roadheader with low dust, increased pick life and reduced vibration. Seeing what is being excavated helps improve performance. Orteu and Devy (1991) suggested that colour image segmentation, automatic image classica- tion, camera calibration and 3D scenes be used to select cutting per- formance, to separate rich ore from waste at the cutting stage.4. Roadheader, its performance and prediction indicesThe prediction of cutting performance for any type of excavating conditions, or rock formation in which the machine is deployed, is one of the main factors determining the economics of a mechanized mining operation. The instantaneous cutting rate or ICR has widely been ap- plied and modied for specic places. Progress over a period of time or on hourly basis is also taken as a performance predictor but includes several other factors that may not represent cutting.Gollick (1999) compared the dierences in the performance of roadheaders of the past with those of more recent times to predict mining rate. Gehring (1989) proposed a performance prediction model based on the performance of a 250-KW transverse type Roadheader. Bilgin et al. (1990) proposed a performance prediction test based on the in-situ observation of many tunnelling and mining projects, and sug- gested a performance prediction model. Copur et al. (1998) developed a performance prediction model based on the variety of geologicalTable 3Roadheader performance prediction models.Sl.Author/yearModelComments1 Gehring (1989)2 Bilgin et al. (1990)3 Rostami et al. (1994)ICR 719 c0.78ICR =ICR = 1739 c1.130.28P (0.974)ICR = SE 0.0023RPIICR = k P250 kW transverse type RH,230 kW axial type RHRMCI =3 ()RMCIIn-situ observationsRQD 2c 100ICR to specic energy relation4Copur et al. (1998)27.511 eRock and RH cutting5 Thuro and Plinninger (1999)ICR = 75.7 14.3lnc 132 kW RH0.37UCS6 Balci et al. (2004)For d = 5 mm, ICR = 0.8P 0.86For d = 9 mm,ICR = 0.8 PEnergy transfer ratio7Keles (2005)ICR =0.41UCS0.67c 0.5737ICR and rock properties (MK2B Milling type RH)8 Ebrahimabadi et al. (2011b)5.56RMBI + 0.60a 8.17 ICR = 3 +Axial type RH (DOSCO MD 1100);0.18SE28.57SE92.82RMBI = eBI (RQD)39 Ebrahimabadi et al. (2012)ICR = 35.22e 0.54 |logRMBI|For axial type10 Comakli et al. (2014)11 Kahraman and Kahraman (2016)12 Choudhary et al. (2017)ICR = k P 0.88t 0.54n 25.01ICR = 0.18SE3 + 28.57SE 92.82100ICR = +SESmall scale linear cutting tests, Cerchar abrasivity test & physic mechanical testsCorrelation of physico-mechanical properties with ICR values (11 equations)75 Kw Dosco RH=formations and the equation derived to estimate RH cutting rate which shows that heavy duty RH can cut rock formations with UCS from 100 MPa to 160 MPa in closely jointed or fractured rocks. They de- termined that, for evaporitic rocks, ICR 27.511 e0.0023 RPI where ICR is the instantaneous cutting rate, RPI is the rock penetration index and e is the base of natural logarithm. Thuro and Plinninger (1999) derived a prediction model based on the performance of a 132 KW RH.=Ning and Zhang (2004) established a mathematical model of cor- relation between working parameters and laneway section dimensions to analyse working mechanism and cutting unit. Balci et al. (2004) dened k as the energy transfer ratio, usually assumed as 0.8 for roadheaders. Keles (2005) determined the instantaneous cutting rate (ICR) of the boom type, medium weight milling type roadheader (MK- 2B) by regression analysis to correlate ICR and rock properties and established that ICR is having highest correlation with lab cutting specic energy i.e. (R2 0.8411). Rostami et al. (1994) concluded that the specic energy (SE) method is a simple procedure for quick per- formance prediction for the RH. Sutoh et al. (2010) developed a data- base from dierent sites for the performance prediction of the 300 KW heavy weight transverse type roadheader.SE=Ebrahimabadi et al. (2011a) developed a performance prediction model based on discontinuity orientation and specic energy SE on the DOSCO MD 1100 roadheader and showed that ICR may successfully be used for performance prediction. Ebrahimabadi et al. (2011b) devel- oped a performance prediction model for medium duty RH based on Rock Mass Brittleness Index (RMBI) and showed that the RMBI is highly correlated with the instantaneous cutting rate (ICR). Abdolreza and Siamak (2013) developed an empirical relation based on rock mass properties and machine parameters to predict roadheader performance. Comakli et al. (2014) suggested a performance prediction model (ICR k P ) on the basis of small scale linear cutting tests, the Cerchar abrasivity test and physico-mechanical tests, where the regression model is derived for the specic energy (SE) of a metallic ore. Kahraman and Kahraman (2016) developed performance prediction for the Dosco Mk-2B roadheader using multiple regression analysis by comparing physico-mechanical properties with ICR values. It was found that point load test and water absorption by weight have a high cor- relation coecient i.e. R = 0.89.Yasar and Yilmaz (2017) developed a performance prediction modelbased on vertical cutting rig (VRCR) to investigate optimum cutting condition, also performing several cutting tests were recorded on the core samples collected by two roadheader sites. Cheluszka et al. (2017) conducted studies on the dynamic loading cutting condition of the transverse cutting head and developed a correlation between load and energy, including angular speed of cutting to regulate speed by adding an inverter drive system with changing supply voltage frequency of an asynchronous motor. Table 3 summarises information about some im- portant RH performance prediction models.It was found that it is very dicult and expensive to determine specic energy (SE) from small-scale or full-scale cutting tests. This is why some researchers investigated the relation between SE and rock properties to suggest empirical equations for estimating SE. Correlating SE with UCS and BTS, for some rock and ore types, shows that the relation between SE and the product of UCS and BTS has a better cor- relation coecient than that of the relation between SE and both UCS and BTS respectively.4.1. Roadheader component usage and automationAs mentioned earlier the roadheader has various components or assemblies such as cantilever link, telescopic boom, drum, cutting picks and conveyor unit. The components have been evolving over time, especially for reducing manual operations by automation. This section will provide a brief overview of the literature that led to the evolution of the components for automation.Raoux and Janti (1986) developed a computerised sensingtechnique to perform on-line image processing and boom control in a potash mine in Spain to detect mineral distribution from the face. Jin- hua (2004) deliberated on the status of mines in China wherein rapid drivages and bolt support technologies were taken into account to run highly mechanized coal mines. Wang et al. (2011) analysed key tech- niques such as cantilever excavator, cutting ability, section monitor, the design of the critical component, arrangement and stabilization of roadheader excavation.Most experimental work for roadheader automation focused on underground coal excavation, remote control and real time monitoring. Gao et al. (2011) developed an automatic control of swing speed, motor current, hardness of coal based on PID and reported a 5% control pre- cision according to coal industry standard MT/T971-2005. They claimed a novel electrical control system for the boom-type roadheader for automatic control of laneway section, autodetection of body section, traction and speed regulation.Wu et al. (2011) developed a remote monitoring control system for the roadheader with the help of PCC, an industrial computer, the Linux operating system and mine loop network. They also developed an au- tomatic protection system which responded within 20.6 ms in com- parison to the required automation protection time of 0.1 s.Wang and Song (2012) developed a mathematical model that in- cluded a relationship between the mechanical and electrical parameters of the RH, for control automation to drive a robot roadheader that, in turn, resulted in a consistent control system design. Suyu et al. (2013) devised a remote-control system for fully mechanized machines, with real time monitoring, with an option for remote fault diagnosis and alarm. Roman et al. (2015) developed a remote control-based road- header system with inbuilt infrared sensor to reduce emergency situa- tions encountered during an outburst of coal that improved the position reliability of the roadheader. In order to improve the visual control of the operator they deployed an infrared sensor in the system. Dolipski et al. (2015) proposed a PID controller-based rotational cutting speed control system to reduce energy consumption by transverse road- headers. Tian et al. (2015) introduced a dynamic characteristics-based transfer function model for automation in cutting and proling control systems for roadheaders. Heyduk and Joostberens (2017) designed an angular speed control system based on cRIO and cDAQ devices (Na- tional Instruments) and simulated the results in both normal and emergency conditions.4.2. Risk analysis and failure analysisRisk analysis is an integral method of investigation while deploying the RH in a project. Since, the cost of equipment is quite high and its failure during operations can lead to signicant losses, risk analysis provides a basis for decision making. Moreover, since the operation of the RH is continuous, failure in components like link, crank, hydraulics and gear misalignment also pose a risk to operations.Ma et al. (2012) conducted a survey using a risk matrix method to analyse the risk of the boom-type roadheader in a subway tunnel. Sabanov et al. (2018) proposed a risk assessment method of the road- header for comparing the advantages and disadvantages of selective extraction of limestone in an Estonian mine and also discussed the sustainability of the roadheader in risky conditions. Ye et al. (2009) proposed a modern spectrum analysis method to diagnose the failure of the roadheader in adverse geological conditions while using real time information through the internet to detect failure in advance.To supervise the machine automatically, Xu et al. (2010) developed a remote monitoring and control system to supervise roadheader ap- plication whose main purpose is to assess failure and generate alarm in such a situation. Wu et al. (2011) implemented an operational failure mechanism to diagnose the physical properties of the roadheaders hardware and software through real time monitoring. Yang et al. (2012) introduced black box hardware with a SQLite embedded data- base for fault diagnosis and determination of machine life cycle.4.3. Roadheader dust suppressionExposure to dust in mining continues to be a major risk to the health of workers. Dust particles such as coal dust, silica dust and other nely powdered materials, can damage lungs and airways. To overcome such problems, dust suppression technology has been introduced.Wang et al. (2013) developed a new foam preparation system and application method in the Zhuxianzhuang coal mine, China to over- come dust generated by the RH. Their results showed that respirable dust exposures were reduced from 540.2 mg/m3 to 84.3 mg/m3 with the application of foam.To study the mechanism more eectively, Han et al. (2014) used computational uid dynamics (CFD) to simulate the air owing eld and distribution of particles ejected by the sprayer mounted on the cutter head. The results showed that the eect of ventilation on the droplets is faint in gentle breeze conditions. Lu et al. (2015) developed a foam preparation method with a jet device using a venturi foam generator to reduce threat to workers health. They also report that the eciency in suppressing total dust and respirable dust were 85.7% and 88.1% at driver position. Liu et al. (2017) investigated a water jet eect of the roadheader on rock breakage by reducing cutting torque and thrust force by maximizing cutting eciency while achieving 70% dust suppression. Wang et al. (2019) developed a 3D CFD model and pro- posed a dust mitigation strategy to address respirable dust emission characteristics. Joy 12CM27 continuous miner is used for eld in- vestigation and it was found that the total exposure level of dust is greater than 500 mg/m3. The main reason behind dust emission was blunt picks and missing nozzles. The model results in 90% control over dust characteristics.4.4. Simulation of roadheader performanceSimulation includes the merging of various new techniques that bridge the gap between conventional and new innovative techniques. Simulation includes computational uid dynamics (CFD), series quad- ratic programming (SQP), multi objective optimization, MATLAB si- mulation such as Taylor series expansion and proportional integral derivative (PID), nite element simulation (FEM), particle ow code (PFC), multi-layer perceptron (MLP) and Caery transform. Simulations by such methods have been used to address a multitude of issues per- taining to the RH. Several mathematical methods have been used by dierent authors and complex equations addressing RH issues have been solved with the help of MATLAB as summarised in Table 4.Sullivan and Van Heerden (1993) reviewed the numerical modelling by computational uid dynamics to tackle the dust generated by RH in underground coal mining. Zhang and Yang (2005) carried out a study on load uctuation on the cutting head with the help of series quadratic programming (SQP), which optimized the bit arrangement and reduced uctuation of load.Zhang and Zeng (2005) proposed a multi objective optimization strategy to decrease energy consumption and load uctuation on the cutting head by taking the average performance of picks and number of cutting picks. Li et al. (2013) proposed a nite element method (FEM) that simulates the dynamic properties of coal and rock aecting the cutting load. They claimed that their analysis provides a methodology to select cutting head in dierent geological conditions. Hongxiang et al. (2013) developed a PFC2D model to study rock fragmentation by RH pick and concluded that damage in hard rock is more remarkable than in soft rock. Chuanming (2013) proposed a multi body dynamic analysis method for the planetary reducer for the roadheader arm with the help of Pro/E and ADAMS Software(s).Han et al. (2014) proposed a particle tracking technology based on computational uid dynamics (CFD). They showed that, under the normal forced ventilation, the droplets will drift to return towards the air side and the concentration of droplets in other parts around the cutting head decreases. Wang et al. (2014) suggested an environment friendly remote-control system to enhance labour safety and also de- veloped a numerical simulation of cutting head swing type of transverse type RH.Zhixin and Dawei (2015) established a multi-body dynamic model for the longitudinal RH to examine vertical vibration, by simulating hydraulic damping with vertical amplitude of cutting head on the basis of ADAMS software. Wu et al. (2015) established a mathematical model, based on boom position and the behaviour of boom positioning movement. Their simulations are based on measurements taken by laser proler which show that the error from a 25 m distance of measurement is 0.0823 m on the X-Axis. In the case of roll angle, however, the measurement error is 2.0184 which satises measurement accuracy requirements. Seker and Ocak (2017) proposed a performance predic- tion of the roadheader on the basis of 6 dierent machine learning al- gorithms such as Zero R, random forest (RF), Gaussian process, linear regression, logistic regression and multi-layer perceptron (MLP).4.5. Intelligent methods and their useIn order to bridge the gap between conventional and automatic handling, performance rating, laneway mapping or in the broad con- cept of predicting performance, articial intelligence (AI) plays a vital role. Articial intelligence includes gene algorithm, fuzzy logic, TakagiSugeno (TS) fuzzy method, Kohonen self-organizing feature (KSOFM) and genetic programming (GP).Acaroglu (2006) implemented an analytical hierarchy process, a multiple attribute decision making method, to select the most suitable roadheader for the Cayirhan Coal Basin. Zhang et al. (2008) developed optimization of the cutting head based on a genetic algorithm and a multi-objective fuzzy method, which resulted in reliability enhance- ment and better energy utilization of the RH. Jasiulek et al. (2011) presented an articial neural network machine control system for betterTable 4MATLAB-based analysis and simulations for performance prediction of roadheaders.Author(s)Main focusCommentsLi and Han (2008)Wavelet packet analysis methodDisintegrated signal of cutting direction, reconstructed dominating components of vibrationsfrom wavelet packets through a power spectrum Li et al. (2009)Prole cutting model of roadheaderSpace kinematic and system simulationLi et al. (2009)Load model based on force analysis of cutting headLoad curve and resultant forces acting on the horizontal cutting head simulationWang et al. (2009)Proportional integral derivative (PID)Simulated for electric and hydraulic control system and resulted in good quality control Mu et al. (2011)Positioning of boom by controlling cutting armSimulation of automatic compensation for cutting section, analyzing lifting and swingactions of cutting armXiaohua and Jiyang (2013)Dynamic model based on mechanical-hydrauliccouplingDened the relationship between lifting and turning moment of the boom. Their results show that the vibration of the lifting moment is greater than in turningCheluszka and Gawlik (2016)Dynamic model based on the dierent subassemblies of RHSolved 19 non-linear ordinary dierential equations of the 2nd order to assess the result of vibrating massesFu et al. (2017)Ultra-wideband pose detection system (UPDS) tocreate 3D coordinates systemProposed a fusion positioning algorithm based on Caery transform and Taylor series expansion to yield the approximate coordinates in X, Y and Z direction.machine performance and quick response to sudden changes in ma- chine operation. Jasiulek and wider (2013) developed an articial intelligence system to determine the angular speed of the cutter jib while cutting roadway drivages. Yazdani-Chamzini et al. (2013) de- veloped a RH performance prediction model using the TakagiSugeno (TS) fuzzy system that is based on subtractive clustering and is capable of deriving the uncertainty and complexity between rock properties and roadheaders.Wang and Zhang (2013) proposed a fuzzy control model for direc- tional adjustment and forward control for improving the excavation procedure. Avunduk et al. (2014) devised a performance prediction model for roadheader study by ANN including a data set of UCS, RQD and measured ICR. They demonstrated that ANN provides a better so- lution than do empirical models.Salsani et al. (2014) concluded that the predictive capability of articial neural network is better than multiple variable regression analysis for the performance prediction of the RH while studying geo- logical and geotechnical characteristics of site conditions. Ebrahimabadi et al. (2015) suggested a Neural network based cutting performance (ICR) of a medium duty roadheader in the Tabas coal mine which includes the multi-layer perceptron (MLP) and Kohonen self-or- ganizing feature map (KSOFM). They stated that the MLP predicts more reliably while KSOFM is an ecient way to understand system beha- viour. Faradonbeh et al. (2017) developed a genetic programming (GP) and gene expression programming (GEP) based model to predict roadheader performance by employing instantaneous cutting rate (ICR), uniaxial compressive strength, Brazilian tensile strength, rock quality designation, inuence of discontinuity orientation and specic energy. Asadi et al. (2017) proposed an ANN model on the basis of a data set gathered by taking three major parameters that inuence bit wear viz. brittleness index, RQD and instantaneous cutting rate.Wang and Wu (2019) Developed a cutter trajectory planning section to experience the cutting of a tunneling machine. The Design includes multisensor parameters, the environment of roadway section which is modelled by grid method. The ant colony algorithm is used to plan the optimal cutting trajectory. The algorithm is iterated 50 times which gives comparatively better result than particle swarm optimization.5. Case historiesSimmons (1993) conducted a comparative analysis of the perfor- mance of RHs versus tunnel blasting in which 2 RHs from dierent manufacturers were used in the excavation of top heading and re- corded. Study estimated a pull of 33.6 m by tunnel blasting as com- pared to 36 m/day while avoiding any major disturbances in the rockmass in case of a Roadheader. Thuro and Plinninger (1998) de- termined bit consumption rate and low cutting performance of RHs in connection with the geological features available in 4 cases of Germany having dierent geologies and involved average performance based on the maximum values of UCS and bit consumption. They reported that soft rock formations were associated with problems of water intrusion and delay in removal of debris with RH haulage system and hence the cutting performance reduced.Thuro et al. (2002) determined that weathered rocks assume key importance as excavation turn out to be labour-intensive along with associated problems. They suggested that investigations to nd re- lationships between excavation parameters, rock strength properties and geological parameters rather than introducing a new classication system for excavability. They also showed the possibilities to measure geotechnical parameters for rockmass excavation by drill blast and cutting by Roadheader. During a case study in Zeulenroda Germany sewerage tunnel, a 130 kW RH performance was estimated by taking work kJ/m3 (excavated) vs. cutting performance m3/h into account. The best correlation coecient was observed was R2 = 89%. In case of drilling and blasting ammonium-nitrate and gelatin were used and work (kJ/m3) vs. explosive consumption (kg/m3) were correlated. Thecorrelation coecient was calculated to be R2 = 67%.Genis et al. (2007) studied the geotechnical conditions of Dorukhan Tunnel, Zonguldak, Turkey. During observations, they found that for the excavation of phyllite/heavily broken phyllite, tectonic breccia and moderately weathered granodiorite smooth blasting and Roadheader as excavation method was better. Tunnel geometry used by them included top heading of 1.52 m and a bench of up to 2 m, respectively. Rock- mass quality was determined in terms of RMR, Q System, GSI, RMi and NATM methods. Authors concluded that the rock mass properties and numerical modelling are not exact methods to dene the tunnel beha- vior. They further concluded that for the renement of both the models back analysis is the only alternative while taking results of instruments installed into account.Mauriya et al. (2010) described the Himalayan region tunneling project including mainly hydro-power, water supply and sewerage tunnels. They found that drilling and blasting remains dominant option over mechanical excavation. Paper reviews the challenges in tunneling, geological problems in case of thrust zone, shear zone, folded rock se- quence in-situ stresses, rock cover and ingress of water, in detail. They also observed that tunneling rate with conventional drill and blast method varies from 7.5 m to 81 m on monthly average basis depends on lithology and geometry of the tunnel. Hong (2010) summarized the development of mechanised roadway technology, from the past 40 years, in China, taking existing problems such as dust control e- ciency, component reliability and automatic control into account, to develop the appropriate technology.Ocak and Bilgin (2010) studied the site condition of Istanbul Ka- dikoyKartal metro tunnels and compared mechanical excavation by roadheader to drilling and blasting. They showed that the production rate of the RH is 218.3 m3/day whereas drill and blast were found to produce 187 m3/day. Choudhary et al. (2017) reported a study of a 75 KW Dosco RH in two dierent coal mines, 2 m high and 4.5 m wide on the rst location, and 2.8 m high and 4.2 m wide at the second, which showed that the roadheader was performing below predicted levels. The main reasons for underperformance identied by them were inecient muck disposal, poor workmanship, lighting and insucient ventilation.Brino et al. (2013) from a study in Gypsum mines observed that the selection of excavation method is dened by the orebody morphology and characteristics. They reported that in that Gypsum mining RH costs were less than that of drilling and blasting and is the best suited method. They recommended optimisation of fuel consumption along with use of conveyor belts for sustainable operations with RH. Mohammadzadeh and Ebrahimabadi (2016) dened a risk matrix to compare drilling blasting and RH excavation and identied that RH application has a lower risk in comparison to blasting. They also sug- gested that transverse type cutterhead is better than the longitudinal one. They, in order to eliminate operational issues pertaining to RHs, even recommended realignment of tunnels so that hard rock forms the bottom of tunnel. Comakli (2019) monitored the performance of RH in terms of ICR, CAI and other mechanical tests of eight dierent cold storage cavern excavations in pyroclastic rocks. They developed a new relationship between the UCS and RH performance for rocks up to a UCS of 10 MPa.6. Current and future trends of developmentDespite the advantages, the RH has some disadvantages such as high pick consumption rate in very abrasive rocks, making excavation un- economical due to frequent bit changes with increased machine vi- brations and maintenance costs (Copur et al., 1998). Liu et al. (2019) developed a roadheader-assisted coal cutter (RACC) specically used for extracting coal on the basis of tensile failure. A new method called cutting inside and spalling outside was also discovered on the basis of column model and beam model respectively. The results show that tensile stress causes more deection in column model than compressivestress in beam model, comparatively 20% of improvisation in the ex- cavation is experienced. Cheluszka et al. (2019) developed an auto- matic control system for the roadheader cutting head to access the actual cutting speed. This technique includes a software control system on the basis of the frequency convertor. The feedback system gives text results by varying with assumed control limits in case of cemented or sand blocks.It is known that the cost of the RH is quite high. Machine selection is performed on the basis of tunnel dimensions and ground conditions that, in turn, determine production rate and bit consumption. Deployment of the RH is mainly dependent on how eectively the performance rating is investigated. Accordingly, if not selected as per geological conditions, the consequences can be economically detri- mental to projects deploying the RH. Hence, machine performance must be predicted before starting tunnelling with a RH to make op- erations protable, productive and competitive. Considering the ver- satile nature of the RH, it is expected that such machines will be cus- tomised to excavate hard to very hard rock formations also. This would mean balancing the power to weight ratios of the machines i.e. the weight of the machines should not increase exponentially. The focus should thus shift to improving the cutter head and the picks. The picks will need to be analysed for their performance in harder rocks. With the use of modern high strength materials in the picks, the possibilities using the RH to cut hard rocks can become a reality. The cutting me- chanism in such types of rocks will need to be revisited with respect to the material used, as well as the spacing and orientation of the picks.Technological advancement directly becomes an integral part of excavation in todays mining and underground space development. Advancement is not only in design and management systems but also the new properties and computer systems to perform intellectual and even creative functions.7. ConclusionsThe roadheader is a versatile machine that can be deployed in the partial face excavation of soft to moderate hard rocks. There are sig- nicant references in the published domain that address various issues pertaining to the roadheader. These references can be classied as: machine design, cutter head design, pick spacing and orientation, ma- chine stability, dust suppression, automation, risk analysis and appli- cation of advanced mathematics and neural networks. A comprehensive account of such classes has been given and discussed in the paper. From the cited references it can be deduced than over a signicant period of time RHs have advanced from simple to complex system that can be deployed, even in moderately strong rocks. The performance prediction and monitoring methods have also evolved simultaneously. The ad- vancement in RH has a bearing on economics feasibility as there is a weight-power conict in such machines. Latest IoT based monitoring methods that provide continuous data on various machine and perfor- mance parameters can provide more insight into designing a RH that is in turn with the requirements of individual projects.Declaration of Conict of InterestThe authors declared that there is no conict of interest in this publication.AcknowledgementAuthors are thankful to the Director CSIR-CIMFR for his permission to publish the paper. Thanks are due to Ministry of Power, Government of India and Central Power Research Institute for research grant NPP/ 2016/HY/1/13042016. Thanks are due to Gita and KP Madhu for suggestions and editorial corrections.Appendix A. Supplementary materialSupplementary data to this article can be found online at https:/ /10.1016/j.tust.2019.103148.ReferencesAbdolreza, Y.C., Siamak, H.Y., 2013. A new model to predict roadheader performance using rock mass properties. J. Coal Sci. Eng. (China) 19 (1), 5156.Acaroglu, O., Ergin, H., 2005. 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Modern Manuf. Eng. 3, 014.可从ScienceDirect获取内容列表隧道与地下空间技术期刊主页：/location/tust隧道与地下空间技术95（2020年）103148掘进机-全面审查Suraj Deshmukha, A.K. Rainaa, V.M.S.R. Murthyb, R. Trivedia, R. Vajreaa印度马哈拉施特拉邦那格浦尔土木工程Telangkhedi地区17/C，CSIR中央采矿和燃料研究所，邮编：440001b采矿工程系，IIT（ISM），Dhanbad，Jharkhand 826001，印度文章关键词：掘进机机械开挖隧道审查摘要机械挖掘机优于传统的钻孔和爆破，因为爆破带来了几个管理和操作问题。掘进机是矿山和民用建筑工程中开挖岩石的机器。它是一种混合机械，具有比隧道掘进机更好的机动性。它能在不同的隧道中切割出160兆帕的岩石，如果分层或断裂，并且很容易适应变化的操作条件。本文综述了与掘进机各方面有关的文献。本文将有关掘进机的文献分为多个类和子类，并确定了影响掘进机部署的重要参数和风险因素。我们还提供了一个最新的技术补充，帮助收集数据的掘进机运行期间的性能。这些数据具有快速改进掘进机设计的潜力。1. 简介快速城市化增加了运输和基础设施对隧道的需求。传统的隧道施工采用钻爆法。然而，在城市环境中运输和使用爆炸物引起了人们的关注。爆破产生令人烦恼的地面振动和有毒烟气。此外，在采用可控爆破措施的情况下，采用爆破的隧道掘进率较低，且对母岩体的破坏明显。为了克服这些问题，机械挖掘机用于采矿和施工相关用途。掘进机是应用最广泛的地下分面机械挖掘机。掘进机是20世纪50年代早期第一种用于以机械方式开采煤的掘进机。随后，它们的使用倾向于民用建筑，其中RHs广泛用于在软弱和中等硬地面条件下挖掘铁路隧道、道路、下水道和导流隧道。自1970年以来，它们在民用工业中被用于形成主要的运输巷道、巷道、交叉路口等，在矿业中被用于开采软岩、煤、工业矿物和蒸发岩。掘进机是一种混合式机械挖掘机，由一个安装在动臂上的旋转切割头和一个输送破碎岩石的输送机组成，图1。履带式移动轨道将整个机器向前推进进入岩面。高机动性、超前率、可靠性、低层扰动、安全性和低人工部署是RH的一些优点。掘进机的主要优点是截割滚筒直径小，截割功率密度高。这使RH比其他机械挖掘机更有优势。最近的进展使RHS在坚硬岩石掘进方面更有见地。机械重量、尺寸、自动化和遥控特性、刀头和动臂定位、液压和电气系统的进步、料斗和装载系统的进步、刀具头的成熟和刀头设计的冶金进步是RH随着时间的推移而发展的一些变化。图2中提供了RH随时间的发展以及在较硬岩石中的应用。从图2可以明显看出，工作重点是开发高强度岩石的RHs。然而，随着改进，相对湿度的重量也增加了，这表明岩石的抗压强度和机器的重量密切相关。这一结论还突出了一个缺点，即随着机器重量的增加，处理问题会增加。2. 掘进机分类Tucker（1985）根据其重量和可切割岩石的抗压强度对掘进机进行了分类。因此，重量高达30吨、切割能力高达70兆帕的RHs被归类为轻型。重量高达34-45吨、抗压强度为100 MPa的为中型，而重量超过45吨、抗压强度为150 MPa的为重型RH。Atlas Copco-Eikhoff建议根据RH的重量进行*对应作者。电子邮件地址：rainajicimfr.nic.in (A.K. Raina)./10.1016/j.tust.2019.1031482019年4月4日收到；2019年9月20日收到订正表格；2019年10月13日接受0886-7798/ 2019 Elsevier有限公司。版权所有。隧道与地下空间技术95（2020年）103148S.Deshmukh等人抗压强度装机功（KW）能量传递比最佳比能量直径抗拉强度脆性指数cPk SEopt DtBI岩体可切割性指数岩石质量标志序列二次规划序列二次规划RMCI RQD SQPLS-DYNA高级通用多物理仿真软件NATM新奥法 PFC2D二维粒子流代码MLP 多层感知器系统ANN人工神经网络KSOFMkohonen自组织特征图GP遗传程序设计GEP基因表达式编程DAQ数据采集过程UPDS超宽带姿态检测系统缩写掘进机比例积分微分控制器功率控制中心瞬时切削率岩体脆性指数特定能量立式凿岩机单轴抗压强度岩石贯入指数振动分析程序分析系统命名法短期RH PID PCC ICR RMBI SE VRCRUCS RPI VAP ANSY图1.典型掘进机示意图（在/product_applications product_applications/road-header/之后绘制（访问时间2019年9月10日）。13另一种分类（Schneider，1988）。20吨的RHs归为0级，2030吨归为I级等。Neil等人（1994）根据切削作用将RHs分为纵向铣削/镗床/轴向头和横向裂土头。除此之外，Jian和Hao（2008）总结了RH型臂架机械化开采的关键技术问题，并基于工作参数的合理匹配，提出了另一种分类方法。动臂式掘进机分为小型（最多30吨）、中型（30至70吨）和大型（70至120吨）。不同作者记录的掘进机分类见表1。3.掘进机文献分类如图3所示，有关RH的已发表文献至少可分为11组。从图3可以明显看出，文献集中在RH的不同方面，从刀盘设计和截齿配置，到性能预测、风险和故障分析、灰尘抑制和定位，使用各种分析技术，如回归和人工智能。这类文献将在本综述中进一步详细讨论。在可能的情况下，我们在回顾中保持了历史的观点，以便了解掘进机各个方面研究的变化趋势。3.1掘进机切割器/切割头的设计机械岩石和煤炭挖掘机械，如掘进机、滚筒采煤机和连续采煤机，使用安装在其切割头或滚筒上的多个镐来挖掘岩石材料。截割头的形状和截齿的配置影响着掘进机的性能。因此，文献对切割头的设计给予了重视。Evans（1972）提出，通过对截齿施加力，截齿之间的线间距控制截齿扫过的横截面积。Hurt和MacAndrew（1981）得出结论，通过提供相等的截齿间距，可以将力的变化保持在最小水平。Hurt等人（1982）在分析力平衡后，推测在切割头周围，圆周截齿间距必须保持相等。Hurt和MacAndrew（1985）认为，为了平衡截齿力，在切角处采用分级系带是可取的。Hekimoglu和Fowell（1991）引入了刀架的牵引，以获得360及以上的等周向截齿间距。Eyyuboglu（2000）提出最可靠的包角为360和776。截齿间距是截齿滚筒外围最重要的参数。对于有效切割和适用于地层的截齿，使用的参数如表2所示。从表2中可以明显看出，在截齿配置中，行距和截齿施加受到了更多的关注。在工程参数中，面积和扫描体积的使用最多。Hekimoglu（1991）对纵向和横向切割头进行了比较，以表明产品尺寸的一致性在横向类型中可能更高，同时起弧。在纵向类型RH的情况下，起弧和低速时，截齿力的施加相对较低。Eyyuboglu和Bolukbasi（2005）研究了环形截齿间距对切割头的影响，并通过考虑不同的工程参数进行了力平衡分析。他们的研究表明，在模拟过程中，两个切割头之间没有显著差异。Shiyong（2005）根据EBJ-132A掘进机的巷道和工作参数制定了一个跟踪切割头位置的程序，并得出结论，在设计切割头以在不同切割条件下有效攻击时，截齿间距起着重要作用Hekimoglu（1991）对纵向和横向切割头进行了比较，以表明产品尺寸的一致性在横向类型中可能更高，同时起弧。在纵向类型RH的情况下，起弧和低速时，截齿力的施加相对较低。Eyyuboglu和Bolukbasi（2005）研究了环形截齿间距对切割头的影响，并通过考虑不同的工程参数进行了力平衡分析。他们的研究表明，在模拟过程中，两个切割头之间没有显著差异。Shiyong（2005）根据EBJ-132A掘进机的巷道和工作参数制定了一个跟踪切割头位置的程序，并得出结论，在设计切割头以在不同切割条件下有效攻击时，截齿间距起着重要作用。图2.重量与抗压强度的相关性（施耐德，1988年后绘制；塔克，1985年）。结果表明，与常规热处理工艺相比，硬度提高23%，磨损减少38%。Kotwica等人（2010年）开发了硬岩开采的刀盘轨迹，该轨迹在KR150掘进机上进行了现场试验，是刀盘的适应性现代化。Kotwica（2011）评估了动臂切向旋转截齿遇到的问题，并提出了一种解决方案，通过在刀盘上适当放置水射流来对抗截齿的快速磨损。Mezyk等人（2019年）开发了一种切割滚筒动力系统，该系统在切割滚筒内包括一个永久磁铁。新系统的动态性能有所改善，但在切削过程中振动增加。然后重点放在切割滚筒的角速度上，这样可以更好地控制切割滚筒的角速度。Hurt and Morris (1985) 开发了一种用于掘进机的计算机化刀盘设计，该设计也在Dosco-MK3重型掘进机上实施，该掘进机在全球范围内成功运行。Rostami等人（1994）开发了一个优化刀盘设计的计算机程序，以提高机器性能和生产效率。刀盘施加的平均切削力由Fn=APb模拟，其中Fn是法向力，P是穿透力，A和b是切削试验确定的系数。Fowell等人（1994）通过将抗压强度作为主要参数来预测阻力工具的性能。Tiryaki等人（2001）开发了一个计算机辅助设计程序来设计切割头并提高其使用寿命。在设计之前，进行了三重跟踪的实验室试验，以便通过程序（VAP）进行振动分析。Ergin和Acaroglu（2007）开发了一个计算机程序，根据四种状态定义两种切割头类型的掘进机稳定性：绕垂直轴转动、转向侧面、转向背面和滑动。Li等人（2012）利用ANSYS/LS-DYNA软件对切削过程进行仿真，得出了动臂式刀盘性能的动态平衡方程，得到了主要运动学参数，发现机床的切削性能还与机床重量、机床功率、刀具等机床特性有关刀头类型和刀具类型。结果表明，采用微型圆盘刀的横向式刀盘可以提高掘进机在硬岩条件下的稳定性。尽管有了这些发展，刀盘的选择和刀具配置仍然很难评估。刀盘的选择也基于不同地质条件下的性能。3.2.地质条件对掘进机性能的影响几种岩石性质影响RH的切削力。单轴抗压强度（UCS）、巴西抗拉强度（BTS）、石英含量、UCS与BTS之比、锥形压头硬度、切线杨氏模量、密度、孔隙率、静态弹性模量、肖氏硬度、比能、岩石质量指标、岩体可切割性指数、Cercher耐磨性指数和点荷载强度是岩石的一些参数，这些参数会影响RH性能。掘进机可切割高达160 MPa UCS的断裂或紧密节理岩石，这与掘进机功率和重量的持续发展有关（Pandey等人，2017）。Bilgin等人（1997）研究了地质因素、施工方法以及两种不同掘进机上岩层的物理力学性质，即。阿尔卑斯ATM 75和艾克霍夫ET 250。Thuro和Plininger（1999）建立了地质参数、切削性能和钻头磨损之间的关系，以预测主要隧洞工程的隧洞稳定性。Thuro（2003）提出了地质参数、切削性能和钻头磨损之间的相关性，以确定隧道稳定性。Yilmaz（2005）测定了单轴抗压强度与抗拉强度之比，并与截齿截割效率进行了比较。他观察到脆性较高的岩石的切割效率有所提高。隧道与地下空间技术95（2020年）103148S.Deshmukh等人表1掘进机分类Tucker (1985) Atlas Copco-Eickho (Schneider, 1988) Neil等人 (1994)年份重量（吨）待切割岩石的抗压强度（MPa）等级重量（T）纵向式横向式19609400 75图3.掘进机文献分类Ebrahimabadi等人（2012）提出了一个通用模型，借助岩体脆性指数（RMBI）评估各种岩层的掘进机性能。它们将完整的岩体特征与机器性能联系起来。Pandey等人（2017）得出结论，岩体物理力学性质的影响是影响掘进机性能的最重要参数Bilgin等人（2004）研究了90KW屏蔽式掘进机在现场条件下的地质影响，首先是水平阶段，其次是9倾角，结果表明，当岩石塑性极限和Al2O3含量较低时，ICR随含水量的增加而增加，从3.5升/分钟增加到11升/分钟。Li（2000）根据作用在切割头上的力建立了一个数学模型。根据him，结构复杂和不复杂煤层上的力按瑞利函数和Chi sup函数分布。Wen-liang (2013)基于场地标高和掘进机转向机构推导了运动学模型。3.3.切割性能切削性能是一个用于地下开挖的术语，用于说明不同地质条件下切削速度和刀具磨损参数的影响。文献中可追溯到一些研究，如坐标转换、切削速度的实验室试验、切削时的稳定性、不同类型掘进机性能的比较等。Fowell和McFeat-Smith（1976）对现场样品进行了实验室试验，以监测DOSCO RH在达勒姆县布莱克霍尔煤矿巷道掘进施工中的性能。文中还对RH的力学参数与岩体性质进行了关联，并分别讨论了影响切削性能的因素。隧道与地下空间技术95（2020年）103148S.Deshmukh等人表2选择间距参数。序号 作者 选择配置 T 工程参数 T12345678910123451Evans (1972)222Roxborough (1973)223Hurt and MacAndrew (1981)324Hurt et al. (1982)525Hekimoglu (1991)226Hurt and Morris (1985)627Hurt and MacAndrew (1985)528Hekimoglu (1995)439Fowell and Johnson (1981)2110Eyyuboglu (2000)01总计4232662322316632219选择配置：1.选择间距，2.系带式-分级系带，3.圆周截齿间距，4.等间距，5.行距（点），6.选择实施，7.系带，8.选择分组，9.选择力，10.悬臂力；T是总数。工程参数：1.面积，2.扫描体积，3.包角，4.扭矩，5.比能 他们将特定能量定义为刀盘功率和ICR的比率。然而，他们提出的RQD分类显示出很大的分散性。McFeat-Smith和Fowell（1977）根据RH实际切削性能的实验室试验，建立了沉积岩的曲线回归方程，以描述切削速度、刀具磨损和碎屑尺寸。Fowell和Johnson（1981）提出了从完整岩石特性考虑切削速度和刀具消耗的悬臂掘进机性能预测。他们的工作直接涉及影响特定项目评估切削性能的利用系数和参数。然而，Bilgin等人（2004）观察到，Mcfeat、Smith和Fowell的性能标准偏向于接头密度。此外，Rostami等人（1994）和Rostami等人（1994）提出的模型受到了更多关注，因为砂土模型包含了全尺寸切割试验，并确定了对掘进机利用率有影响的能量传递系数。Guo等人（2002）利用截齿轨迹、纵向截割头的速度和加速度建立了坐标转换方程。通过仿真，他证明了截齿速度和加速度随转速的增加而迅速增加。Hekimoglu和Ozdemir（2004）进行了实验室试验，以模拟实际切削位置和缠绕角度，并研究了较高的转速可能会导致较差的性能，因为在存在较大缠绕角度的情况下，较高的刀具力。Bilgin等人（2005年）提出了一项统计分析，以评估使用线性切割机对大块岩石进行的实验室试验的基础上的净推进切割率。Keles（2005）通过进行物理力学试验，对中等重量铣削式掘进机（MK-2B）进行了研究，结果表明，ICR瞬时切削速度与特定能量有很强的相关性。Acaroglu和Ergin（2005）使用计算机程序确定了掘进机的稳定性，并研究了不同切割形状的影响。他们得出结论，倾斜角度的增加可能会对所有切削状态的滑动动量产生负面影响。Acaroglu和Ergin（2006）开发了一个模型来确定掘进机的稳定性状态，通过检查垂直轴的转动力矩、转向侧面、转向背部和滑动来观察不同切割模式的稳定性指数。他们的结果表明，绕垂直轴转动是起弧时最关键的状态之一。Fu等人（2019）在超宽带姿态检测系统（UPDS）的基础上开发了一种姿态检测方法。UPDS系统用于访问与航向、横摇和俯仰角有关的数据。UPDS涉及三种定位算法：间接定位算法（IPA-D）、泰勒级数展开算法（Taylor-D）和Chan定位算法（Chan-D）。比较结果表明，IPA-D在窄巷和长巷中的计算结果都比较精确。虽然掘进机的切割性能是一个关键因素，但现有文献不足以解决所有类型的掘进机和不同条件下的问题。未来的研究可能需要集中在对不同地质条件下各种类型的掘进机的切割效率的一致理解上，以便在特定情况下对掘进机的选择做出明智的决策。3.4.掘进机定位与振动诊断动臂的定位对于实现高生产率至关重要。为了监控切割段，必须注意动臂式掘进机的定位。切割操作中的任何不匹配都可能导致振动，最终影响RH的性能。因此，掘进机的定位对掘进机的可靠性起着重要的作用。Li and Han（2008）提出了一种平行连接、工作坐标系，通过一个相对于隧道坐标的坐标变换矩阵来调节正逆问题，以实现更好的自动控制、监控切割断面和指导隧道作业。Du等人（2012）提出了一种RH型动臂姿态的误差遭遇策略，通过调整动臂、电铲和支架来减少误差并修正切割位置轮廓，从而更有效地工作。Tao等人（2017）开发了iGPS多点测量系统，以根据随机误差传递方程评估掘进机的轻微弯曲和位移。Tao等人（2018）通过坐标测量设计了一种基于iGPS的单站、多点、分时位置和位置测量系统。此外，他们还利用数学建模和随机误差建模理论推导出的误差传递方程，更好地控制相对湿度的定位振动监测对RH结构和设计优化以及故障诊断研究具有重要意义。机器振动与相对湿度性能密切相关，因此决定了其可靠性。在完全机械化的时代，各种传感器的数据和数学模型被用于振动诊断。Li和Wu（2008）基于ADAMS振动分析模块获得了正弦简谐运动。他们观察到，20Hz、29Hz、120Hz和134Hz是决定RH位移响应和切削机理的敏感频率。Jianguang（2012）建立了一个数学模型来分析RH部件振动的振幅和频率。Li等人（2013）通过拉格朗日-拉普拉斯变换确定了RH的振动特性，利用固有频率和三阶振动机构，借助伪激励法计算了纵向型RH的位移响应。Ma和Liu（2013）开发了一个模型来确定星形轮式装载机上的电机牵引力。他们通过分析旋转板的振动、应力和应变来确定RH的失效位置。Li等人（2013）通过采集EBZ260 RH切割的岩石样本，开发了基于振动和应力信号的载荷识别方法。他们通过测定平均振动能量、加速度和平均应力之间的关系得出了结果，这些关系提供了动态载荷的直接测量。Dolipski等人（2014）提出了一个基于离散结构的模型，用于分析作用在动臂中心部分、伸缩部分（望远镜）和带有横向切割头的减速齿轮上的质量的振动，并表明振动的激励是岩石切割的影响。Liu等人（2015）开发了轴承板的多体动力学理论模型，以评估振动特性，得出了RH系统振动的频率响应图和轴承的负载分析。Cheluszka和Mann（2019）开发了一种获取刀盘振动的摄影测量方法：安装在刀盘上的加速计和与TEMA 3D软件相连的高速摄像机。利用加速度计和高速摄像机记录的速度和切削力矩来确定加速度。然后将该方法应用于垂直于地板的两个不同的刀盘。3.5.掘进机设计与实施RH的独特设计和结构提供了各种优势，例如减少了方向限制，因此能够灵活地处理降低、底切、提升和起弧的切割条件，而不会影响操作稳定性。对当今掘进机设计的贡献总结如下。Hurt和MacAndrew（1981）对切割工具进行了调查，得出结论：工具在切割线上切割效果不佳。能够承受恶劣环境而不断裂或开裂的工具是Zhang和Zhang（2005）关注的焦点。他们介绍了S200M RH的铸造工艺设计，以防止锻造毛坯、铸造裂纹、缩孔和夹渣。这种技术定义了为特定目的制造模具的结构质量，被称为掘进机设计的结构原则。Rostami等人（1994）开发了掘进机设计优化和性能预测的计算机程序，并将其用于100吨级重型掘进机（AM-105）的校核。他们发现这种重型掘进机的挖掘速度为40至100吨/小时。然而，现场情况下的性能不仅取决于挖掘速度，还取决于碎片的清除。Zhang等人（2013）指出，掘进机铲运机的设计决定了提升和倾倒性能，并描绘了设计参数，以选择完美的设计进行进一步计算。掘进机的铲板参数也决定了航运部门的业绩。Burkov等人（2014）重点介绍了掘进机给料机的优点，以及设计掘进机曲柄连杆机构的重要性。另一个必须解决的问题是操作过程中产生的灰尘。Barham和Buchanan（1987）建议采用高达700 bar压力的水射流掘进机系统，以改善悬臂式掘进机的切割性能，降低粉尘，延长截齿寿命，减少振动。查看正在挖掘的内容有助于提高性能。Orteu和Devy（1991）建议使用彩色图像分割、自动图像分类、摄像机校准和3D场景来选择切割性能，在切割阶段从废物中分离富矿。4.掘进机及其性能和预测指标预测任何类型的挖掘条件或机器所在岩层的切割性能是决定机械化采矿作业经济性的主要因素之一。瞬时切削率（ICR）已广泛应用于特定场所。一段时间内或每小时的进度也被视为绩效预测指标，但包括可能不代表削减的其他几个因素。Gollick（1999）比较了过去和最近时期掘进机性能的差异，以预测采矿率。Gehring（1989）提出了一种基于250kw横向式掘进机性能的性能预测模型。Bilgin等人（1990）提出了一种基于许多隧道和采矿项目现场观测的性能预测试验，并提出了性能预测模型。Copur等人（1998）开发了一个基于地质地层变化的性能预测模型，并导出了估算RH切割速率的公式，该公式表明，在紧密节理或裂隙岩石中，重型RH可以切割UCS为100 MPa至160 MPa的岩层。表3掘进机性能预测模型序号作者/年份公式批注1Gehring (1989)ICR=719C0.78250kW横向式RHICR=1739c1.13230kW轴向式RH2Bilgin等人（1990）ICR=0.28P0.974RMCI现场观测;RMCI=c(RQD100)233Rostami等人（1994）ICR=kPSEICR与特定能量的关系4Copur等人 (1998)ICR=27.511e0.0023RPI岩石和掘进机切割5Thuro and Plinninger (1999)ICR=75.7-14.3lnc132kWRH6Balci等人 (2004)For d=5mm,ICR=0.8P0.37UCS0.86;For d=9mm,ICR=0.8P0.41UCS0.67能量传递比7Keles (2005)ICR=163.93c-0.5737ICR和岩石特性（MK2B铣削类型RH）8 Ebrahimabadi等人 (2011b)ICR=5.56RMBI+0.60a-8.17;ICR=-0.18SE3+28.57SE-92.82轴向式RH（DOSCO MD 1100）；RMBI=eBI（RQD100）39Ebrahimabadi等人(2012)ICR=35.22e-0.54|logRMBI|轴向式10Comakli等人(2014)ICR=kPSE小型线切割试验、Cerchar耐磨性试验和物理机械试验11Kahraman and Kahraman(2016)ICR=-0.88t-0.54n+25.01物理机械性能与ICR值的相关性（11个方程式）12Choudhary等人(2017)ICR=-0.18SE3+28.57SE-92.8275kWDosco RH= 他们确定，对于蒸发岩，ICR=27.511*e0.0023*RPI，其中ICR是瞬时切割速率，RPI是岩石穿透指数，e是自然对数的基数。Thuro和Plinninger（1999）基于132kW RH的性能推导了一个预测模型。Ning和Zhang(2004)建立了工作参数与巷道断面尺寸相关性的数学模型，分析了工作机理和切割单元。Balci等人（2004）将k定义为能量传输比，通常假设掘进机的能量传输比为0.8。Keles（2005）通过回归分析确定了吊杆式、中等重量铣削式掘进机（MK-2B）的瞬时切削率（ICR），以关联ICR和岩石性质，并确定ICR与实验室切削特定能量的相关性最高，即（R*R=0.8411）。Rostami等人（1994）得出结论，特定能量（SE）方法是快速预测相对湿度性能的简单方法。Sutoh等人（2010）从不同地点开发了一个数据库，用于300 KW重型横向式掘进机的性能预测。东南= Ebrahimabadi等人（2011a）开发了一个基于DOSCO MD 1100掘进机不连续方向和特定能量SE的性能预测模型，并表明ICR可成功用于性能预测。Ebrahimabadi等人（2011b）开发了基于岩体脆性指数（RMBI）的中型RH性能预测模型，并表明RMBI与瞬时切削率（ICR）高度相关。Abdolreza和Siamak（2013）开发了一种基于岩体性质和机器参数的经验关系式，用于预测掘进机性能。Comakli等人（2014）提出了基于小规模线性切割试验、Cerchar耐磨性试验和物理力学试验的性能预测模型（ICR=kP/se），其中针对金属矿石的特定能量（SE）推导了回归模型。Kahraman和Kahraman（2016）开发了Dosco的性能预测Mk-2B掘进机物理力学性能与ICR值的多元回归分析。结果表明，点荷载试验与重量吸水率有很高的相关系数，R=0.89。Yasar和Yilmaz（2017）开发了一个性能预测模型利用垂直切割试验机（VRCR）研究了最佳切割条件，并对两个掘进机现场采集的岩芯样品进行了多次切割试验。Cheluszka等人（2017）对横向切割头的动态负载切割条件进行了研究，并建立了负载和能量之间的关系，包括切割角速度，通过增加变频驱动系统来调节速度，改变异步电机的供电电压频率。表3总结了一些重要的相对湿度性能预测模型的信息。研究发现，从小规模或全规模切割试验中确定特定能量（SE）非常困难且成本高昂。这就是为什么一些研究人员调查了硒和岩石性质之间的关系，提出了估算硒的经验公式。对某些岩石和矿石类型，将硒与UCS和BTS进行相关分析，结果表明，硒与UCS和BTS的乘积的相关系数比硒与UCS和BTS的关系好。4.1.掘进机组件的使用和自动化如前所述，掘进机具有各种部件或组件，如悬臂连杆、伸缩臂、滚筒、截齿和输送装置。这些组件随着时间的推移而不断发展，特别是为了通过自动化减少手动操作。本节将简要概述导致自动化组件发展的文献。Raffoux和Janti（1986）开发了一种计算机化传感技术，用于在西班牙钾盐矿进行在线图像处理和吊杆控制，以检测工作面上的矿物分布。Jin-hua（2004）审议了中国煤矿的现状，其中考虑了快速掘进和锚杆支护技术来运行高度机械化的煤矿。Wang等人（2011）分析了悬臂挖掘机、截割能力、断面监测、关键部件设计、掘进机布置及稳定性等关键技术。掘进机自动化的实验工作主要集中在井下采煤、远程控制和实时监控方面。Gao等人（2011）根据煤炭行业标准MT/T971-2005，开发了一种基于PID的摆动速度、电机电流、煤硬度的自动控制方法，控制精度为5%。他们提出了一种新型的悬臂式掘进机电气控制系统，用于巷道断面的自动控制、车身断面的自动检测、牵引和调速。Wu等（2011）利用PCC工控机、Linux操作系统和矿井环网，开发了掘进机远程监控系统。他们还开发了一个自动保护系统，该系统在20.6 ms内响应，与所需的0.1 s自动保护时间相比。Wang和Song（2012）开发了一个数学模型，其中包括RH的机械和电气参数之间的关系，用于控制自动驱动机器人掘进机，从而实现一致的控制系统设计。Suyu等人（2013）设计了一种用于综采机械的远程控制系统，具有实时监控功能，可选择远程故障诊断和报警。Roman等人（2015）开发了一种基于远程控制的掘进机系统，内置红外传感器，以减少煤突出期间遇到的紧急情况，从而提高掘进机的位置可靠性。为了改善操作员的视觉控制，他们在系统中部署了一个红外传感器。Dolipski等人（2015）提出了一种基于PID控制器的旋转切削速度控制系统，以降低横向掘进机的能耗。Tian等人（2015）介绍了一种基于动态特性的传递函数模型，用于掘进机切割和成型控制系统的自动化。Heyduk和Joostberens（2017）设计了一个基于cRIO和cDAQ设备（国家仪器）的角速度控制系统，并对正常和紧急情况下的结果进行了模拟。4.2.风险分析和故障分析风险分析是在项目中部署相对湿度的一种完整的调查方法。由于设备的成本很高，在运行过程中发生故障会导致重大损失，因此风险分析为决策提供了依据。此外，由于右侧的操作是连续的，连杆、曲柄、液压系统和齿轮错位等部件的故障也会给操作带来风险。Ma等人（2012年）使用风险矩阵法进行了一项调查，以分析地铁隧道中悬臂掘进机的风险。Sabanov等人（2018）提出了掘进机风险评估方法，用于比较爱沙尼亚矿山选择性开采石灰石的优缺点，并讨论了掘进机在风险条件下的可持续性。叶等（2009）提出了一种现代谱分析方法，在利用互联网实时信息提前检测故障的同时，对不良地质条件下的掘进机故障进行诊断。为了自动监控机器，Xu等人（2010）开发了一个远程监控系统来监控掘进机的应用，其主要目的是在这种情况下评估故障并发出警报。Wu等人（2011）实现了一种操作故障机制，通过实时监控来诊断掘进机硬件和软件的物理特性。Yang等人（2012）介绍了带有SQLite嵌入式数据库的黑匣子硬件，用于故障诊断和确定机器生命周期。4.3.掘进机扬尘在采矿过程中接触粉尘仍然是工人健康的一个主要风险。粉尘颗粒，如煤尘、硅尘和其他细粉材料，会损害肺部和呼吸道。为了克服这些问题，人们引入了抑尘技术。 Wang等人（2013）在中国朱仙庄煤矿开发了一种新的泡沫制备系统和应用方法，以克服RH产生的粉尘。他们的结果表明，使用泡沫后，呼吸性粉尘暴露从540.2 mg/m减少到84.3 mg/m。为了更有效地研究机理，Han等人（2014）使用计算流体动力学（CFD）模拟了安装在刀盘上的喷雾器喷射出的空气流场和颗粒分布。结果表明，在微风条件下，通风对雾滴的影响很小。Lu等人（2015）开发了一种泡沫制备方法，使用文丘里泡沫发生器的喷射装置，以减少对工人健康的威胁。他们还报告，在驾驶员位置，抑制总粉尘和呼吸性粉尘的效率分别为85.7%和88.1%。Liu等人（2017）研究了掘进机的水射流对岩石破碎的影响，通过最大限度地提高切割效率来降低切割扭矩和推力，同时实现70%的粉尘抑制。Wang等人（2019）开发了一个三维CFD模型，并提出了一个粉尘缓解策略，以解决可吸入性粉尘排放特征。久益12CM27连续采煤机用于现场调查，发现粉尘总暴露水平大于500 mg/m。粉尘排放的主要原因是截齿钝和喷嘴缺失。该模型的结果是90%的粉尘特性控制。4.4.掘进机性能模拟模拟包括各种新技术的融合，这些新技术弥补了传统技术和创新技术之间的差距。模拟包括计算流体动力学（CFD）、串联四元规划（SQP）、多目标优化、MATLAB模拟，如泰勒级数展开和比例积分微分（PID）、有限元模拟（FEM）、粒子流代码（PFC）、多层感知器（MLP）和Caffery变换。通过这种方法进行的模拟已被用于解决RH的许多问题。不同的作者使用了几种数学方法，并在MATLAB的帮助下解决了解决相对湿度问题的复杂方程，如表4所示。 Sullivan和Van Heerden（1993）回顾了通过计算流体动力学进行的数值模拟，以解决地下煤矿开采中RH产生的粉尘问题。Zhang和Yang（2005）利用序列二次规划（SQP）对切削头上的载荷波动进行了研究，优化了钻头布置，降低了载荷波动。 Zhang和Zeng（2005）提出了一种多目标优化策略，通过选取截齿的平均性能和截齿数来降低截割头的能耗和负荷波动。Li等人（2013）提出了一种有限元法（FEM），用于模拟煤和岩石在切削载荷作用下的动态特性。他们声称他们的分析提供了在不同地质条件下选择切割头的方法。Hongxiang等人（2013）开发了一个PFC2D模型，用RH-pick研究岩石破碎，并得出结论，硬岩中的损伤比软岩中更显著。Cuanming（2013）利用Pro/E和ADAMS软件，提出了掘进机臂行星减速器的多体动力学分析方法。 Han等人（2014）提出了一种基于计算流体动力学（CFD）的粒子跟踪技术。他们发现，在正常的强制通风条件下，液滴会漂移回到空气侧，而切割头周围其他部位的液滴浓度会降低。Wang等人（2014）提出了一种环境友好的远程控制系统，以提高劳动安全性，并开发了横向式RH切割头摆动式的数值模拟。 Zhixin和Dawei（2015）在ADAMS软件的基础上，通过模拟切割头垂直振幅的液压阻尼，建立了纵向RH的多体动力学模型，以检验垂直振动。Wu等人（2015）基于动臂位置和动臂定位运动行为建立了数学模型。他们的模拟基于激光测量仪的测量结果，测量距离为25米，X轴上的误差为0.0823米。然而，在滚转角的情况下，测量误差为2.0184，满足测量精度要求。Seker和Ocak（2017）基于Zero R、随机森林（RF）、高斯过程、线性回归、logistic回归和多层感知器（MLP）等6种不同的机器学习算法，提出了掘进机的性能预测。4.5.智能方法及其应用为了弥合常规和自动处理、性能评级、巷道测绘或预测性能的广泛概念之间的差距，人工智能（AI）发挥着至关重要的作用。人工智能包括基因算法、模糊逻辑、TakagiSugeno（TS）模糊方法、Kohonen自组织特征（KSOFM）和遗传规划（GP）。 Acaroglu（2006）采用层次分析法（一种多属性决策方法）为卡伊尔汗煤盆地选择最合适的掘进机。Zhang等人（2008）开发了基于遗传算法和多目标模糊方法的切割头优化，从而提高了RH的可靠性和更好的能源利用率。Jasiulek等人（2011）提出了一种人工神经网络机器控制系统，以提高机器性能并快速响应机器操作的突然变化。表4基于MATLAB的掘进机性能预测分析与仿真作者 主要焦点 评论Li and Han (2008)小波包分析法切割方向的分解信号，通过功率谱重构了小波包振动的主导分量Li et al. (2009)掘进机断面切割模型空间运动学与系统仿真Li et al. (2009)基于切削头受力分析的载荷模型水平切割头载荷曲线及合力模拟Wang et al. (2009)比例积分微分(PID)对电液控制系统进行了仿真，取得了良好的控制效果 Mu et al. (2011)通过控制切割臂定位吊臂截割段自动补偿仿真，分析截割臂的升降和摆动动作Xiaohua and Jiyang (2013)基于机械-液压耦合的动力学定义起重臂的提升和转动力矩之间的关系。结果表明，提升力矩的振动比转向力矩的振动大Cheluszka and Gawlik (2016)基于RH不同组件的动力学模型求解19个二阶非线性常微分方程，以评估振动质量的结果Fu et al. (2017)建立三维坐标系的超宽带姿态检测系统（UPDS）提出了一种基于Caffery变换和Taylor级数展开的融合定位算法，得到X、Y、Z方向的近似坐标.Jasiulek和wider（2013）开发了一个人工智能系统，用于确定切割巷道掘进时切割机臂架的角速度。Yazdani Chamzini等人（2013）使用TakagiSugeno（TS）模糊系统开发了一个RH性能预测模型，该系统基于减法聚类，能够得出岩石特性和掘进机之间的不确定性和复杂性。 Wang和Zhang（2013）提出了方向调整和正向控制的模糊控制模型，以改进开挖过程。Avunduk等人（2014）设计了一个用于人工神经网络掘进机研究的性能预测模型，包括UCS、RQD和实测ICR数据集。他们证明了人工神经网络比经验模型提供了更好的解决方案。 Salsani等人2014）得出结论，在研究场地条件的地质和岩土特征时，人工神经网络的预测能力优于多元回归分析。Ebrahimabadi等人（2015）提出了一种基于神经网络的Tabas煤矿中型掘进机截割性能（ICR），包括多层感知器（MLP）和Kohonen自组织特征图（KSOFM）。他们指出MLP预测更可靠，而KSOFM是了解系统行为的有效方法。Faradonbeh等人（2017）开发了基于遗传编程（GP）和基因表达式编程（GEP）的模型，通过采用瞬时切削率（ICR）、单轴抗压强度、巴西抗拉强度、岩石质量指标、不连续方向和特定能量的影响来预测掘进机性能。Asadi等人（2017）提出了一个基于数据集的人工神经网络模型，该数据集收集了影响钻头磨损的三个主要参数，即：。脆性指数、RQD和瞬时切削率。 Wang和Wu（2019）开发了刀具轨迹规划部分，以体验掘进机的切割。设计包括多传感器参数、巷道断面环境的网格化建模。采用蚁群算法规划最优切削轨迹。该算法迭代50次，得到了比粒子群算法更好的结果。5.案例 Simmons（1993）对RHs与隧道爆破的性能进行了对比分析，其中来自不同制造商的2台RHs用于顶部导坑开挖并记录。研究估计隧道爆破的牵引力为33.6 m，而不是36 m/天，同时避免了掘进机对岩体的任何重大干扰。Thuro和Plinninger（1998）确定了RHs的钻头消耗率和低切削性能，这与德国4个不同地质情况下的地质特征有关，涉及基于UCS和钻头消耗最大值的平均性能。他们报告说，软岩层与水侵入和RH运输系统清除碎屑延迟的问题有关，因此切割性能降低。 Thuro等人（2002）确定，风化岩石具有关键重要性，因为挖掘工作以及相关问题都是劳动密集型的。他们建议研究挖掘参数、岩石强度特性和地质参数之间的关系，而不是引入新的挖掘分类系统。他们还展示了通过钻孔爆破和掘进机切割测量岩体开挖岩土参数的可能性。在Zeulenroda德国污水隧道的案例研究中，通过考虑工作kJ/m3（开挖）与切割性能m3/h，估算了130kW相对湿度性能。最佳相关系数为R2=89%。在钻孔和爆破的情况下，使用硝酸铵和明胶，并将功（kJ/m3）与炸药消耗量（kg/m3）进行关联。相关系数R2为67%。 Genis等人（2007）研究了土耳其宗古尔达克Dorukhan隧道的岩土条件。在观察中，他们发现对于千枚岩/重破碎千枚岩、构造角砾岩和中风化花岗闪长岩的开挖，光面爆破和掘进机作为开挖方法更好。他们使用的隧道几何结构包括顶部导坑1.52 m和台阶2 m。采用RMR、Q系统、GSI、RMi和新奥法对岩体质量进行了评价。作者得出结论，岩体性质和数值模拟不是确定隧道行为的精确方法。他们进一步得出结论，对于这两种模型，在考虑安装仪器的结果时，反分析是唯一的选择。 Mauriya等人（2010）描述了喜马拉雅地区隧道工程，主要包括水电、供水和污水隧道。他们发现钻孔和爆破仍然是机械开挖的主要选择。本文详细地评述了隧道施工面临的挑战，逆冲带、剪切带、褶皱岩体、地应力、岩石覆盖层和进水等地质问题。他们还观察到，根据隧道的岩性和几何形状，采用常规钻爆法的隧道掘进速度每月平均从7.5 m到81 m不等。Hong（2010）总结了过去40年来我国机械化道路技术的发展情况，考虑到扬尘控制效率、部件可靠性和自动控制等存在的问题，开发出合适的技术。 Ocak和Bilgin（2010）研究了伊斯坦布尔Ka-dikoy-Kartal地铁隧道的现场条件，并将掘进机机械开挖与钻孔和爆破进行了比较。他们发现，RH的产量为218.3 m3/天，而钻孔和爆破的产量为187 m3/天。Choudhary等人（2017）报告了一项关于两个不同煤矿75 KW Dosco RH的研究，第一个位置高2 m，宽4.5 m，第二个位置高2.8 m，宽4.2 m，这表明掘进机的性能低于预测水平。他们发现的表现不佳的主要原因是淤泥处理不充分、工艺差、照明和通风不足。 Brino等人（2013）在石膏矿的研究中观察到，开挖方法的选择取决于矿体形态和特征。他们报告说，在这方面，石膏开采的相对湿度成本低于钻探和爆破，是最合适的方法。他们建议优化燃料消耗，同时使用传送带，以实现RH的可持续运行。Mohammadzadeh和Ebrahimabadi（2016）定义了一个风险矩阵来比较钻孔爆破和RH开挖，并确定RH应用与爆破相比具有较低的风险。他们还提出横向式刀盘比纵向式刀盘好。为了消除与RHs有关的操作问题，他们甚至建议重新排列隧道，使坚硬的岩石形成隧道底部。Comakli（2019）监测了RH在ICR、CAI和其他力学试验方面的性能，这些试验是针对火成碎屑岩中8个不同的冷藏洞穴挖掘进行的。他们开发了一种新的UCS和RH性能之间的关系，适用于UCS高达10兆帕的岩石。6.当前和未来的发展趋势尽管有这些优点，但RH也有一些缺点，例如在非常磨蚀的岩石中，截齿消耗率高，由于频繁更换钻头，机器振动和维护成本增加，使得挖掘不经济（Copur等人，1998）。Liu等人（2019）开发了一种掘进机辅助采煤机（RACC），专门用于在拉伸破坏的基础上开采煤炭。在柱模型和梁模型的基础上，分别提出了一种内切外剥的新方法。结果表明，柱模型中拉应力比梁模型中压应力引起更多的变形，相对而言，20%的变形是即兴发生的。Cheluszka等人（2019）开发了掘进机切割头自动控制系统，以获取实际切割速度。该技术包括基于变频器的软件控制系统。对于胶结或砂块，反馈系统通过改变假定的控制极限给出文本结果。众所周知，RH的成本相当高。根据隧道尺寸和地面条件进行机器选择，进而决定生产率和钻头消耗。相对湿度的部署主要取决于如何有效地调查绩效等级。因此，如果不根据地质条件进行选择，其后果可能对部署RH的项目造成经济上的不利影响。因此，在开始使用RH掘进之前，必须预测机器性能，以使操作更具可行性、生产效率和竞争力。考虑到RH的可用性，预计此类机器也将被用于挖掘坚硬到非常坚硬的岩层。这意味着平衡机器的功率重量比，即机器的重量不应呈指数增长。因此，重点应转向改进刀盘和截齿。需要分析镐在较硬岩石中的性能。随着现代高强度材料在镐中的应用，使用RH切割坚硬岩石的可能性可以成为现实。此类岩石的切割机制需要根据所用材料以及截齿的间距和方向进行重新研究。在今天的采矿和地下空间开发中，技术进步直接成为挖掘的一个组成部分。先进性不仅体现在设计和管理系统上，而且体现在新的性能和计算机系统上，以实现智能甚至创造性的功能。7.结论掘进机是一种多功能机械，可用于软至中硬岩石的局部工作面开挖。在已发布的域中有一些重要的参考文献，它们解决了与掘进机相关的各种问题。这些参考资料可分为：机器设计、刀盘设计、截齿间距和方向、机器稳定性、防尘、自动化、风险分析以及高等数学和神经网络的应用。本文对这类问题作了全面的论述。从引用的参考文献可以推断，在相当长的一段时间内，RHs已经从简单的系统发展到复杂的系统，甚至可以部署在中等强度的岩石中。性能预测和监控方法也在不断发展。RH的ad-VAN水泥与经济可行性有关，因为这种机器中存在着重量功率控制。最新的基于物联网的监测方法，提供各种机器和性能参数的连续数据，可以更深入地了解RH的设计，进而满足各个项目的要求。利益冲突声明作者声明，本出版物不存在利益冲突。确认作者感谢CSIR-CIMFR主任允许发表论文。感谢印度电力部、印度政府和中央电力研究院的研究资助NPP/2016/HY/1/13042016。感谢Gita和KP Madhu的建议和编辑更正。附录A.补充材料本文的补充数据可以在网上找到：/10.1016/j.tust.2019.103148.参考文献Abdolreza, Y.C., Siamak, H.Y., 2013. 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