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英文原文Recent Advances in Remote Coal Mining Machine Sensing, Guidance, and TeleoperationJ. C. Ralston, D. W. Hainsworth, D. C. Reid, D. L. Anderson, and R. J. McPheeCSIRO Exploration and MiningPO Box 883, Kenmore Q 4069,Australia. j.ralstoncat.csiro.auAbstractThis paper presents some recent applications of sensing, guidance and telerobotic technology in the coal mining industry. Of special interest is the development of semi or fully autonomous systems to provide remote guidance and communications for coal mining equipment. We consider the use of radar and inertial based sensors in an attempt to solve the horizontal and lateral guidance problems associated with mining equipment automation. We also describe a novel teleoperated robot vehicle with unique communications capabilities, called the Numbat, which is used in underground mine safety and reconnaissance missions.1.0 IntroductionAustralia has excellent coal resources with a good long-term potential for wealth generation. However the Australian mining industry is currently facing a number of unique economic challenges, as well as expectations to meet increased safety requirements and strict environmental mandates. A real need therefore exists to find methods to increase coal production and improve mining efficiency while ensuring the safety of mine personnel. To this end, the CSIRO Mine Equipment Automation group is involved in developing and applying modern automation systems to coal mining machinery. Mining automation technology has significant potential to provide more accurate mining methods, incorporate sensing to improve productivity and minimise equipment damage, and to increase personnel safety by removing them from dangerous machinery and environments1,2.An area in which modern automation technology can provide significant productivity and safety improvements is in the area of remote machine guidance. This requires the development of automated systems that are capable of sensing the material to be mined as well as guiding the mining machine to a designated target heading. These two underlying guidance scenarios are known as the horizon and lateral control problems3,4. Any practical automated system also requires integrated communication capabilities in order to transfer information on the status of the underground environment and mining equipment in real-time.Section 2 introduces ground penetrating radar (GPR) as a coal-thickness sensor for application in the horizon control problem and describes its application to a longwall coal mining operation. In Section 3, an internal navigation system (INS) is presented as a solution for the lateral control problem. Section 4 presents a novel teleoperated field robot, called the Numbat, which is used for underground mine safety and reconnaissance activities. Numbats real-time communication capabilities are used to convey information as to the condition of an underground mine in situations where it could be too hazardous for manual exploration.2.0 Ground Penetrating Radar for Horizon ControlThis section describes the development of a GPR system for measuring coal thickness in coal mining operations. Although GPR has significant potential for depth measurement, the raw signals are frequently complicated and so cannot be readily interpreted by mining personnel. We show how real-time digital signal processing plays a key role in transforming the raw radar signals into a form that can be readily understood. We also indicate some of the unique challenges encountered when implementing a radar processing system in a harsh coal mining environment.2.1 Coal Seam Horizon SensingIn an underground coal mining operation, there is an optimal roof and floor coal thickness that is required to provide sufficient structural support while maximising product extraction and avoiding unnecessary product waste5. If the remnant coal is too thick, permanently unrecoverable coal is left. If the layer remaining in the roof is too thin, it can greatly increase the risk of roof fall. Mining hard rock instead of coal also greatly increases the risk of machine damage. Figure 1 shows a cross sectional view of a typical underground mining operation, where the goal is to keep the mining machine in the coal seam by following an optimal mining horizon. In order to realise this objective, a method is required to determine the depth of coal.Figure 1: The horizon control problem. Here the underlying objective is to keep the mining machine in the coal seam to in order to maximise coal recovery. The black bands represent coal and the textured zones represent tuff.2.2 Existing Coal Depth SensorsThere are two main classes of coal depth sensing systems: reactive and predictive3. Reactive coal depth sensors are based on detecting changes in operational characteristics when a coal-rock interface is encountered. Reactive methods include monitoring cutting drum current, sensing changes in machine vibration signatures, and the use of instrumented cutting picks. The underlying limitation with reactive methods is that they rely on the actual penetration of the coal- rock interface, in which case it is too late to prevent product dilution and machine damage. Unlike reactive methods, predictive sensors attempt to estimate the distance from the machine to the coal-rock interface. The most common predictive method uses a gamma radiation sensor to estimate the coal depth by exploiting the radioactivity of host strata typically found with coal deposits. The natural gamma sensors can work well in specific situations but require up to 30 seconds to obtain a reliable depth measurement. Such a delay can impact severely on coal mining operations. This limitation motivated the search for alternative predictive sensing methods.2.2 GPR as a Depth SensorGPR has found special application for subsurface characterisation in civil engineering, ordinance detection, and geotechnical fields6,7,8. The central attraction of GPR is that it is non-invasive and non-destructive, and can provide instantaneous imaging of subsurface features.The basic principle of GPR involves transmitting energy into the ground and then measuring the reflections arising from the interface of materials with different dielectric values. The magnitude of the received reflection is dependent on the ground conductivity and permittivity, the size and shape of the target, and the difference between dielectric constants at a boundary. Voids, cavities, and other dielectric interfaces represent discontinuities that can give rise to pulse echoes. The geological features typically found in coal-bearing strata are particularly amenable to radar imaging. This is because coal has a relatively low conductivity and high dielectric constant with respect to its host strata.To date GPR has not been widely used the coal mining industry for coal depth measurement. This is largely because of the practical issues associated with making sensitive electronic equipment suitable for a rugged and hazardous coal mining environment and because of the complex nature of the radar signals returns from a GPR system. A key requirement in the successful implementation of a coal measurement system is the use of signal processing to transform the raw radar data into a form that can immediately utilised by non-expert personnel. Most commercial GPR systems are not suited to underground coal mining and do not provide automated real-time processing capabilities, and consequently rely on trained operators to manually interpret the raw radar data in an off-line capacity9.Figure 2 shows typical raw GPR output with the sensor directed into free space. The main peak represents an antenna-air coupling characteristic. Clearly additional processing of the raw radar data is required in order to provide coal depth estimates for horizon control.Figure 2: Snapshot of raw GPR signal showing radar-air coupling characteristic.2.3 GPR Signal Model and ProcessingGPR-based coal thickness sensors rely on measuring the propagation delay from the sensor to the coal-rock interface propagation delay and knowledge of the local coal geology. We first derive a model for the received radar signal by considering the physical arrangement of the imaging scenario. The resulting set of equations lead to the associated processing tasks.2.3.1 Radar Signal ModelThe received radar signal can be modelled as2where W0(t) is the radar-air coupling pulse, W(m) is a lumped impulse response of the radar, M specifies the temporal support of the (two-sided) wavelet, and Nk(t) is an independent noise process for time t=0,T-1, and radar stretch index k=0,1,. The sequence Nk(t) includes sensor and timing jitter noise. The sequence Rk(t) is given by where ak (n) is the magnitude of the echo and tk(n) is the pulse time delay for n=0,pk-1. The signal Rk(t) is analogous to the reflectivity series found in seismic imaging10. Note also that this is an approximation since the pulse shape can vary depending on the material being imaged.Equation (1) represents the convolution of the basic pulse wavelet with the (scaled) reflection coefficients. In a given radar signal observation Zk(t), there may be on pk interfaces present. The underlying goal is to estimate tk(n) and pk, and in particular the first reflection, from observations of Zk(t) for all k. Figure 3 shows typical raw radar data, Zk(t), arranged as a sonar- style plot for t = 0,479 and k = 0, 999.Figure 3: Array of raw GPR data. The vertical axis represents time delay and the horizontal axis shows adjacent radar data while the sensor is held in a stationary position.2.3.2 Radar Signal ProcessingFigure 4 shows the four basic stages involved in processing the raw radar data: pre-processing, filtering, detection, and estimation. This includes time-varying gain for path loss compensation, suppression of radar-air coupling characteristic, wavelet deconvolution, delay and displacement omain filtering, short-term ensemble averaging, energy detection and peak location.Figure 4: Block diagram showing processing applied to the raw GPR data to provide coal depth estimates.Preprocessing StageThere are two preprocessing steps used. The first step is to apply an exponential gain to the received signal to compensate for the radar signal attenuation characteristic through earth material. This time-varying gain considerably extends the dynamic range of the system and has the effect of removing the time dependency of ak(t) in Equation (2). The second preprocessing step is to remove the transmitter-air/receiver coupling characteristic. An estimate of W0(t) in Equation (1) is made during initial system calibration by computing an ensemble average of Zk(t) over k assuming statistical stationarity of the raw returns over a nominated calibration interval.Filtering StageSince the movement of the mining machine is very slow with respect GPR sampling rate, Doppler effects are negligible and so is a good approximation for n = 10 20 adjacent raw returns. This property permits lowpass filtering in the displacement domain, which serves to suppress artifacts arising from radar timing jitter. Lowpass filtering in the time/delay domain also proves particularly effective in suppressing the effects of sensor noise and machine vibration. To improve the detection power, the radar data is deconvolved with a regularised inverse11 obtained from a suitable estimate of the basic radar wavelet W(t). The small phase shift introduced for causality reasons is accounted for in the processed data.Detection StageThe processed data is passed through a detection stage to determine potential dielectric interfaces. A time-domain sliding window energy detector is implemented at each instant k. The output of the energy detector is then compared to a threshold previously determined empirically from field tests and calibration. If the detector output exceeds the given threshold, an estimate of the average two-way travel time is then made by computing the median of the resulting set of (sequentially ranked) indices within the domain of the energy window. An estimate of pk is obtained by noting the number of distinct sets of peaks in a given realisation. This strategy represents a simple yet effective method for detecting the coal-tuff interface in an automatic manner, as well as being computationally efficient to facilitate real-time implementation.Depth Estimation StageGiven that the first echo represents the two way travel time for the coal-rock interface, an estimate of the coal depth is given by for n=0,pk-1, where ec 4.5 for coal. The processed radar data leads to a greatly simplified representation and thus acceptance of the technology to mining personnel. The data can also be meaningfully employed in more tracking and control schemes. It is important to note, however, that the radar data is subject to a wide variety of aberrations from the basic radar model: Nonlinearities, multiple reflections, heterogeneity variation, moisture variation, sensor and mining machine vibration, operator misuse, and sensor placement all contribute to measurement error2.2.4 GPR Longwall ApplicationThe GPR unit was applied to an underground coal mining machine known as a longwall shearer. The primary purpose of our tests was to establish whether the radar unit could be used as a sensor for horizon control in a coal mining scenario. To this end the GPR-based sensor was mounted on a longwall shearer at Dartbrook, NSW, Australia. The particular underground scenario had a problem that offered a long term potential for an automatic coal thickness measurement system. The floor of the seam being extracted consisted of a weathered clay layer with a high ash content (80%). There was real benefit in cutting as close to the floor as possible as the coal immediately above the tuff layer was of high quality. However, if the tuff layer was mined, the ash content of the product increased dramatically.The GPR processing system as a whole consists of three main components: the wideband (800 MHz) bistatic impulse radar, the data processing unit, and the visualisation system2. This antenna configuration produces a 5 ns data stretch, which results in high-resolution short-range (150 cm) echo data12. The complete GPR system was first assembled and tested on the surface. It was then transported underground and mounted on the longwall shearer as seen in Figure 5. The terms of the exemption for the operation of the GPR underground specified that the equipment could only be operated during maintenance periods.Figure 5: The GPR processing and display unit mounted on the longwall shearer.2.4.1 Test ProcedureTesting involved making coal thickness measurements in the area between the horizontal push rams of adjacent roof supports. The longwall shearer was moved to a position on the face where the remnant coal thickness exceeded the radars nominal penetration depth. The radar unit was placed directly on the surface of the coal and the returns recorded. Figure 6 shows GPR echoes from an undisturbed region where the coal-rock interface was out of the GPR range (greater than 300 mm).Figure 6: Raw radar output display in the case where the coal-rock interface is out of the range of the radar. No reflection is observed.A test bench was constructed to manually establish a local floor horizon within the range of the instrument. Figure 7 shows the raw radar data at 100 mm coal thickness with the horizontal axis representing the coal-rock interface. The coal-tuff interface can be clearly seen in where the coal thickness is within the range of the sensor.Figure 7: Output from the GPR display unit in the presence of a coal-rock interface approximately 100 mm below the surface.Considerations for Underground UseSpecial design and construction considerations were necessary in order to make the radar processing system suitable for use in the harsh coal mining environment. In addition, the system need operate in the presence of potentially explosive gases. The signal processing module and display screen are housed in a ruggedised flameproof enclosure with a viewable window as shown in Figure 8. Of special interest is the use of a non-metallic flameproof enclosure for the radar transmitter-receiver assembly. Clearly this was necessary as the use of a metallic enclosure would not permit transmission of the radar signals. The radar enclosure is made of a ruggedised carbon-based alloy of a sufficiently low dielectric constant so that the radar signals are not adversely attenuated, and is interconnected with the main flameproof via an armoured cable.Figure 8: Flameproof enclosure to house the signal processing anddisplay components of the GPR system.The GPR system must operate with as little operator intervention as possible (ideally none), be physically robust, comply to strict intrinsically safety requirements, and facilitate remote software maintenance and data retrieval. As a result, the operator “interface” is limited to four ruggedised push buttons to select calibration and other control.2.6 GPR SummaryGPR has the potential to solve an important coal depth estimation problem in the mining industry. A GPR processing system for coal depth measurement has been designed, built, and evaluated on a coal mining machine. The first generation radar measurement system developed provides data acquisition, processing, and visualisation of coal thickness estimates in real-time, as well as remote data communication facilities. Experiments conducted show that there exists a positive correlation between the coal-rock interface and known geology. The continued development of radar signal processing techniques is the key to improving the reliability and utility of the measurement system.3.0 Inertial Navigation Systems for Highwall MiningHighwall mining is an important method of coal mining in which a remotely controlled mining machine is driven into a coal seam that has been exposed by previous open cut operation. A continuous haulage system is use to carry the coal from the miner to an open-air installation for stockpiling and transport. The highwall mining process forms a series of nominally parallel, unsupported drives. Figure 9 shows a highwall mining machine in operation.Figure 9: A highwall mining machine creating a drive into an exposed coal seam.3.1 The Need for Lateral GuidanceIt is vital that the coal pillars remaining between adjacent drives are capable of supporting the overburden structure. This mining method is totally reliant on effective remote control. Straight, parallel openings at the tightest separation consistent with geotechnical design can only be achieved if the mining machines position and heading can be determined and controlled remotely. Figure 10 shows a plan view highlighting the lateral guidance problem associated with highwall coal mining.A number of methods have been proposed for lateral guidance of highwall mining machines. Laser surveying offers the potential for accurate longwall machine position determination but site- dependent issues such as visibility and line of sight mean that a general approach is not possible. Some opto/mechanical borehole-type surveying methods have been considered but also suffer from practical implementation difficulties because of the need for high accuracy angle measurements in a very inhospitable environment. Special purpose triangulation systems using radio propagation cannot achieve the required machine positional accuracy using the low frequencies required to penetrate the overburden. The limitations associated with the existing methods strongly suggest the need for a positional sensing system that requires only a minimal external infrastructure.20m500m Figure 10: The lateral control scenario encountered in highwall mining. The goal is to maintain a target heading in order to optimise coal recovery and ensure pillar integrity.3.0 INS for Lateral GuidanceThe use of an INS-based sensor can be used to provide absolute position of the mining machine without the need for any external positional information. A complete review of INS operational principles is outside the scope of this paper15,16. Modern inertial sensors have no moving parts and use solid state optical gyroscopes and accelerometers. This results in an inertial sensor that is highly resistant to vibration but internally requires more computation to produce heading and position data. By mounting the INS on the mining machine it would be theoretically feasible to follow a given target heading taken from a mine plan.Most inertial units are used in one of two modes to provide either a full three-dimensional position survey or an azimuth-heading reference system (AHRS). The disadvantage of operating the INS survey mode is that it is necessary to frequently stop the unit to perform a zero velocity update (ZUPT) to allow the INS to trim accumulated accelerometer errors13,14. Even if the ZUPT requirement is stringently observed, the accumulation of residual errors will cause the position accuracy to degrade with time. All inertial-based systems drift because position is obtained by doubly integrating accelerometer outputs to provide a position estimate. These operations produce errors that increase with time. Figure 11 shows the magnitude of two-dimensional positioning error caused by INS drift characteristics over a 12-hour test period. The data was obtained while the INS was executing oscillatory motion about a fixed point on a gimble table. The large positional errors represent uncertainty in heading information which serves to limit the maximum allowable drive penetration depth. Figure 12 shows the direct penalty in terms of loss of recoverable coal that is incurred as a result of INS heading/azimuth uncertainty. The loss of potential coal recovery, coupled with production delays arising from INS ZUPT requirements, mean that no practical systems currently use guidance based solely on INS derived position.3.1 Navigation using INS and OdometryAn alternative approach is to combine INS heading information with an external along track distance measurement in order to derive relative machine position. In this mode of operation, the INS does not require ZUPTing and heading accuracy can be maintained over extended periods. Since heading information is obtained by a single integration of the angular velocity output of the high accuracy ring laser gyros, it is therefore more accurate than surveyed position and much less susceptible to drift. This method facilitates periodic corrections of the INS indicated position by zeroing accumulated errors using independent position fixes.Figure 11: Results of an experiment demonstrating the 2D positional error arising from INS. The gimble-mounted INS unit was executing oscillatory motion about a fixed point over a 12-hour period.Work has been carried out using an INS in AHRS mode in highwall mining guidance using an odometer as the external along track distance sensor. Heading deviation is defined as the difference between the designed or desired heading for a particular highwall entry and the miner heading, which in this case is provided by an INS. The miner heading, and therefore heading deviation, is a function of along track distance which in this application can be measured by sensors external to, and independent of, the INS. The miner progressive cross track deviation can be calculated as the integral of the sine of heading deviation with respect to along track distance. The progressive cross track distance describes the path of the miner relative to the designed path. If the cross track deviation, designed heading and entry separation are known for two adjacent entries, it is a simple matter to compute pillar thickness at any point along the entries.Figure 12: Impact on recoverable coal as a result of INS heading uncertainty.3.2 Guided Continuous Miner ApplicationThe combined INS and odometry lateral guidance system has been used on a production highwall mining system at the Moura mine, Queensland, Australia. The system allows the position and path of the highwall miner to be displayed graphically and numerically in real-time to an operator. The thicknesses of adjacent pillars are inferred from the mapping software. The operator has access to instantaneous values of along track, heading deviation, cross track deviation and pillar thickness. Figure 13 is a plan view of the lateral guidance software, which shows both mined and planned drives. The desired drive headings are shown as a dotted lines and cross-hatched region represents drives that have been mined.The introduction of the lateral guidance system has increased resource recovery by 40% and virtually eliminated the incidence of unplanned drive intersections. Drive penetration depths over 500 meters are now routinely and reliably obtained, as compared with previous drive depths of less than (an inconsistent) 300 metres. Cross track errors in drive entries of the order of 500mm after 500m penetrations have been achieved using the system.Figure 13: Highwall miner operators display screen showing the actual path of the mining machine (cross hatched region) compared with the designed path (dotted region) for adjacent drives.3.3 INS SummaryThe use of INS for lateral guidance of a mining machine was investigated. It is concluded that drift, accuracy, and operational limitations mean that it is unlikely that miner guidance can be based on INS alone. However, heading information combined with along track measurement (odometry) can give accurate guidance and control. The need for guidance is well appreciated by the industry. Heading information, and in general orientation, can be combined with along track measurements to derive cross track deviation, and therefore the lateral position and path of the miner. The path of the miner in the vertical plane can be derived from pitch information in a similar manner. Applications of the INS-based lateral control system on three separate production highwall mining operates have proven the validity of the approach. Significant improvements in productivity and safety have resulted from the application of the INS-based lateral guidance system.4.0 The Numbat Mine Safety VehicleOne of the most significant problems following a mine incident is a lack of knowledge regarding the geological integrity and environmental condition of the mine. This uncertainty, coupled with a reluctance to compromise personnel safety, invariably leads to losses in mining productivity and may even cost lives17,18.The Numbat mine emergency response vehicle was developed by the CSIRO following the Moura mine explosion in 198619,20. It is a remotely controlled vehicle used to convey information on the condition of underground mines in situations where it is too hazardous for manual exploration.The primary purpose of the Numbat project is to provide rescue teams with immediate information on underground mine conditions after an emergency incident.Sending the Numbat vehicle into hazardous areas instead/ahead of mining rescue teams not only minimises risk to personnel, but also provides an invaluable source of information regarding the mines environmental state21.The Numbat integrates a diverse range of communications, actuation, mobility, power, control and software technologies. The Numbat system consists of a mobile surface control station and a remotely controlled mine emergency surveying vehicle. Recent upgrades and improvements to the Numbats hardware, software, and mechanical design have been made to enhance the capabilities of the vehicle. A special emphasis has been placed on increased system modularity, re- configurability, and ease of maintenance.Figure 14 shows the configuration and interconnectivity of the Numbat vehicle and surface station core functionality. The vehicle computers act as slaves with respect to the surface computer. All computers are ruggedised to withstand vibration and harsh treatment. An optical fibre link provides bi-directional communications between the surface station and the Numbat. Three x86- based computers running real-time UNIX are used for real-time control and processing; one in the surface control station and two mounted in the Numbat vehicle.4.1 Surface Control StationThe Numbat is remotely controlled in real-time from a portable control station located near the mine entry. The air-conditioned control station houses all of the computers, communication racks, video display units, and monitoring equipment required in teleoperating the Numbat vehicle.Figure 15 shows an inside view of the control station, which readily accommodates 3-4 people and maintenance equipment.Figure 15: An inside view of the Numbat surface control station.An operator controls the Numbat through the use of video cameras, joystick, control panel, and graphic user interface located in the control station. The surface station is used to remotely control all aspects of the vehicle. It is also responsible for the management of the graphic user interface (GUI) and a real-time audio uplink/downlink to the vehicle. The main operator GUI is shown in Figure 16. The environmental conditions of the mine, telemetry data, two-way audio, system status, and video information are constantly relayed from the vehicle to the surface station.Normal navigation uses four video cameras mounted on the Numbat vehicle. The Numbat can also be controlled directly via a plug-in control module on the vehicle.Figure 16: The main operator GUI for Numbat teleoperation.4.2 The Numbat VehicleThe Numbat is an eight-wheeled vehicle with a base measuring 2.5 x 1.65 metres. It is designed to traverse rough terrain and operate in extremely harsh underground mining environments. A picture of the Numbat vehicle is shown in Figure 17. Pairs of wheels mounted on rocker arms move independently over rough surfaces. Vehicle direction is achieved through skid steering.This configuration serves to keep all wheels on the ground while the vehicle is traversing rough terrain. The vehicle is designed so that it can propel itself across water obstacles and flooded roadways.There are a number of gases encountered in underground mines which, in certain concentrations, will explode if given a source of ignition. As a result, all components of the Numbat are internally isolated and enclosed in a sealed body that is pressurised with nitrogen.The control and functionality of the Numbat is distributed across two computers located in the front and rear of the vehicle. The rear computer is responsible for the cable reeling control system, the mobility and steering (traction) control system, and for controlling the environmental monitoring package. The front computer is responsible for activating emergency breakers, system power management, lights, real-time audio communications, and camera pan and tilt movement.Figure 17: The Numbat mine emergency response vehicle.The traction control system uses two velocity control systems to provide steering and mobility for the Numbat. The control systems are distributed to separately control the left and right hand pairs of wheels. The vehicle has considerable traction that enables it to traverse rough terrain. Failsafe braking is achieved through the use of energise- to-release braking mechanisms.4.3 Onboard Sensing EquipmentThe Numbat uses two main classes of sensors to survey the environmental condition and infrastructure of the mine, namely atmospheric transducers and video cameras. The Numbat also has a number of other onboard sensors for monitoring vehicle attitude, hardware status, power supply condition, and so on.The Numbat has an onboard gas analysis package to provide information on the environmental condition of the mine. The gas analysis package constantly performs analyses to determine concentrations of methane, oxygen, carbon monoxide, carbon dioxide, and hydrogen in the vicinity of the vehicle. Other important environmental parameters such as internal and external temperature, atmospheric pressure, and ventilation air speed are also monitored. This information is then relayed and displayed to operators in the surface control station. The Numbat vehicle has four video cameras mounted for remote guidance. Two of the cameras are fixed and permanently face the front and rear of the vehicle. The rear camera proves to be particularly useful for monitoring the status of the cable reeling system. The two other cameras are mounted in a turret that is remotely panned and tilted as required for guidance by the operator.An active thermography (infrared) system is also being evaluated to enable the Numbat to see through smoke and dust. Airborne disturbances in underground mines frequently obscure conventional camera images, making remote navigation and guidance extremely difficult. The need for an active thermography system arises because the surfaces in underground mines do not always exhibit sufficient thermal differentiation to permit sufficient terrain perception.A non-contact proximity laser scanner (PLS) was used with the Numbat to evaluate the possibility of autonomous or semi-autonomous navigation capability. The laser range finder was mounted onto the Numbats turret and evaluated at underground mine test track at CSIRO in clear conditions. Figure 18 shows the laser range finder data as the Numbat approached a junction in the test track. The range sensor provided a navigation headlight range of approximately 50 meters. The white region of the image represents open area ahead of the vehicle that is scanned by the laser.The clarity of the returned data clearly indicates the potential for autonomous navigation and path finding. The Numbat was always intended to be a teleoperated vehicle to assist mines rescue teams as distinct from a fully autonomous robot. It should be noted, however, that partial autonomy is not technically inconceivable given current mapping and collision avoidance technologies22.Figure 18: Returned laser range finder data as the Numbat negotiates a junction. The data can readily be used for navigation and path finding.4.4 Optical Fibre Communications LinkOne of the more interesting aspects of the Numbat is the form of communications link. The Numbat frequently needs to drive several kilometers into the mine in order to reach the incident site. This need, coupled with strict intrinsically safe equipment requirements, essentially precludes the use of conventional trailing-type communication cables or radio beacons. To meet these link requirements, the Numbat communication system employs optical fibre technology.The Numbat communication system uses an umbilical-based communications system consisting of 10 Kilometre length of Teflon strengthened optical fibre.Optical fibre communication racks and protocol converters are located in the surface control station and the Numbat vehicle. This link provides an independent, high bandwidth, low-latency communications system. The optical fibre is surprisingly robust and has proven to be reliable media for communications. The Numbat communications system currently uses four independent colour video channels and one T1 (1.54 Mbits/sec) data channel. The communications system has sufficient bandwidth to support up to 32 colour video channels.The data communication channel provides the backbone for system message passing and audio services between the surface and vehicle computers. To maximise connectivity and modularity, the communications are configured to provide a UTP Ethernet port-to-port network. This arrangement also permits ease of system maintenance and makes the addition of devices such as inertial navigation units, laser imaging systems, or manipulators possible.4.5 Optical Fibre Payout SystemThe optical fibre payout control system is responsible for feeding out and feeding in a trailing optical fibre. Figure 19 shows the cable payout arm, which is mounted at the rear of the vehicle.The control system maintains the correct tension on the optical fibre when the vehicle is in motion and at rest. The payout system uses a cascade of two separate control systems: one for control at the payout arm and the other for management at the reeler drum. This is required as the fibre tension at the payout arm is much less than that required for winding on the reeler drum. The caterpillar wheel mounted on the fibre payout arm provides the necessary tension conversion between the two systems.The payout control system infers fibre tension via the angle of tension arms, which are mounted on the payout arm and near the internal drum assembly. The fibre payout system must also accountfor a nonlinear relationship between the fibre tension and the measured tension arm angle. The cable payout distance is transduced via an encoder mounted on the caterpillar drive. The payout arm uses an independent control system for angular position.Figure 19: The fibre payout arm located at the rear of the vehicle.Figure 20 shows the drum assembly located in the centre of the Numbat vehicle. The fibre tension is maintained by the drum and tension arm control systems. In order to allow the transfer of optical signals across the rotational interface between the drum and the internal communications network, the Numbat uses a novel fibre optic rotary joint.Figure 20: The automatic optical fibre reeling system showing the drum assembly and diamond bar reeving mechanism.4.6 Software SystemFigure 21 shows an overview of the software model employed in the mbat project. Considerable effort has been made to make software as odular and eliable as possible. The software system utilises the concept of a various system tasks, called workers. The point of a mission critical system is to recognize that software failures might occur and design the system as much as possible toFigure 21: Block diagram showing internal structure of software flow and management. A similar software control paradigm is utilised for the vehicle and surface programs.survive them in some intelligent way. For reasons of robustness and safety, the Numbat software uses a number of integrity monitors and watchdog functions.The Central ExecutiveThe central executive is responsible for the flow control and management of the system. All requests are submitted to the central executive via a message queue structure, which mediates to resolve the appropriate response. While all requests must go through the central executive, the underlying implementation of this function is quite efficient and therefore does not result in the bottleneck found on some centralised control systems. The advantages of this control paradigm are that it is simple, highly deterministic, and easy to reconfigure as necessary.The WorkerA number of tasks need to be simultaneously performed by the computer systems: Servicing of socket oriented communications, reading from and writing to a variety of hardware devices, integrity monitoring, updating control algorithms and so on. Many of these functions may delay or block awaiting data, and so the use of traditional cyclic executives or polling would require additional timing, synchronisation and scheduling mechanisms in order to achieve the desired result. Instead, the Numbat software uses a multithreaded approach, scheduled via a real-time UNIX operating system. While the central executive has complete access to all worker resources, individual workers are restricted to use to their own resources. Each worker is therefore acts as an independent thread of execution with a pre-assigned execution priority.Message Queuing and ControlThe message queue approach provides a powerful priority based mechanism for inter-thread, process and system communication. Synchronous and asynchronous requests from internal and external sources are enqueued in the receive message queue (and thus never lost). These requests are subsequently delivered, in priority order, to the central executive in a simple and uniform manner. The message queue approach also facilitates the introduction of new components into the system function with minimal effort. Outgoing messages to other computers are managed in a similar fashion.4.7 Numbat SummaryThe Numbat draws together a diverse range of sensing, communications, control, mobility, powering, and real-time software technologies. These components are integrated and managed in software through an efficient rule-based scheduling executive. Considerable emphasis has been given to the resolution of software modularity to provide system determinism and robustness. A key feature of the Numbat is its unique communication link which provides both real-time control of the Numbat vehicle as well as relaying information to the control station concerning the condition of the immediate environment.5.0 ConclusionThe coal mining environment presents a unique set of theoretical and practical challenges for mining equipment automation. To date, most emphasis on mining automation has focused on a sensor-based, computer-assisted, machine control, communication and guidance systems. Here the operational tasks are shared between a remotely-located human operator and a multi-sensor processing and display system, providing a so-called “man-in-the-loop” control. This technology naturally involves the integration of communication systems, position and navigation, process engineering, mapping, monitoring and troubleshooting utilities, and control and guidance systems. This has been successfully applied to a highwall mining operations,The automation task naturally requires the use of a diverse range of sensors and systems in order to deliver useful guidance and communication systems. Highly robust software is also required to integrate, process, display, and communicate such data. Integrated multisensor sensor systems are seen to be the key in providing reliable solutions to the underlying lateral and horizon control problems. Two sensors were discussed in detail, namely ground penetrating radar and inertial navigation systems, which can be used to maintain the mining operation in the coal seam through lateral and horizon guidance. Both of these sensing technologies have been successfully used in real coal mining scenarios. A novel teleoperated robot was also presented which serves in a novel role for mine safety and remote surveying tasks.REFERENCES1 D. W. Hainsworth, “Automatic Horizon Control of Coal Mining Equipment”, Proceedings of the 4th International Symposium on Mine Mechanisation and Automation, July 1997, Brisbane, Australia, pp. B6:11-19.2 J. C. Ralston and D. W. Hainsworth, “Application of Ground Penetrating Radar for Coal Depth Measurement”, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 99), Vol. 4, pp. 2275-78, March, 1999 (Phoenix, Arizona).3 G. L. Mowrey, “Promising Coal Interface Detection Methods”, Mining Engineering, January, pp134-138, 1991.4 D. C. Reid, D. W. Hainsworth, and R. J. McPhee, “Lateral Guidance of Highwall Mining Machinery Using Inertial Navigation”, 4th Intnl. Symp. on Mine Mechanisation and Automation, July 6-9, pp B6:1 11 Brisbane, Australia (1997).5 S. L. Bessinger and M. G. Nelson, (1993) “Remnant Roof Coal Thickness Measurement with Passive Gamma Ray Instruments in Coal Mines”, IEEE Transactions on Industry Applications, Vol 29, No 3, May/June pp562-565.6 J. C. Cook, “Radar Transparencies of Mine and Tunnel Rocks”, Geophysics, Vol. 40, No. 5, pp. 865 85, 1975.7 G. L. Mowrey, C. W. Ganoe and W. D. Monaghan, “A Radar-Based Highwall Rib- Thickness Monitoring System”, Society for Mining, Metallurgy, and Exploration, Inc. Transactions, Vol. 298, pp. 1865 70, 1997.8 D. J. Daniels, D. J. Gunton and H. E. Scott, “Introduction to Subsurface Radar”, IEE Proceedings, Vol. 35, Pt. F, No. 4, August 1988, pp. 277 320.9 R. L. Chufo, “An Electromagnetic Spatial/ Spectral Sensor for Geological Measurements”, Proceeedings of the 6th International Conference on Ground Penetrating Radar (GPR 96), September 1996, pp. 545 547.10 E. A. Robinson and S. Treitel, Geophysical Signal Analysis (Prentice-Hall, New Jersey, 1980).11 L. L. Sharf, Statistical Signal Processing (Addison-Wesley, New York, 1991).12 W. Murray, C. Lewis C., Z. Yang and J. Pollock, “Development of High Resolution GPR Hardware in the Frequency Range 300Mhz 3.5GHz”, Proceedings of the 6th International Conference on Ground Penetrating Radar (GPR96), September 30, Sendai, Japan, pp 509-510 (1996).13 J. J. Sammarco, “Field Evaluation of the Modular Azimuth and Positioning System (MAPS) for a Continuous Mining Machine”, Bureau of Mines Information Circular 9354, pp1-14 (1993).14 W. H. Schiffbauer, “Pursuit of Accurate Navigation and Control of Continuous Mining Systems for Coal Mining”, 4th Intnl. Symp. on Mine Mechanisation and Automation, July 6- 9, Brisbane, Australia, pp B6:33-46 (1997).15 C. Broxmeyer, Inertial Navigation Systems, (McGraw-Hill, New Jersey, 1964).16 P. E. Hall, “The Evolution Continues: Ring Laser Gyro (RLG) Navigation Systems for Helicopters”, Vertiflite, Vol 34, March/April, pp 22-25 (1988)17 J. C. Ralston and D. W. Hainsworth. “The Numbat: A remotely controlled mine emergency response vehicle”, Proceedings of the International Conference on Field and Service Robotics, pp. 48-55,Canberra, Australia, December 1997.18 D. W. Hainsworth and M. R. Stacey, Mine Emergency Survey Vehicle: Numbat, Proc. 25th International Conference of Safety in Mines Research Institutes, Pretoria, RSA, September 13-17, pp7-18, 1993.19 M. R. Stacey, D. W. Hainsworth and D. C. Reid, An Optical Cord Deployment and Retrieval System for Remote Vehicle Communication, Proc 16th Aust. Conf. on Optical Fibre Technology, Adelaide, Dec 1-4, pp 398-401, 1991.20 D. W. Hainsworth, C. W. Mallett, and M. R. Stacey, Project Numbat - An Emergency Mine Survey Vehicle, Proc. Third National Conference on Robotics, Melbourne Australia, June, pp 91-98, 1990.21 C. W. Mallet, A. Sellers and P. Mackenzie-Wood, “Managing the Risk in Mine Emergency Response by Application of Automation Technologies”, Proc. Fourth International Symposium on Mine Mechanisation and Automation, Brisbane, pp. B9:17-25, July. 1997.22 M. Herbert, C. Thorpe and A. Stentz, Intelligent unmanned ground vehicles (Kluwer academic, 1997)33中文译文煤矿机械遥感、制导与遥操作研究进展J. C. Ralston, D. W. Hainsworth, D. C. Reid, D. L. Anderson, and R. J. McPheeCSIRO Exploration and MiningPO Box 883, Kenmore Q 4069,Australia.j.ralstoncat.csiro.au摘要本文介绍了传感、制导和遥操作机器人技术在煤矿工业中的一些最新应用。特别令人感兴趣的是为煤矿设备提供远程指导和通信的半自主或全自主系统的开发。我们考虑使用雷达和惯性传感器，试图解决与采矿设备自动化相关的水平和横向制导问题。我们还描述了一种新型的具有独特通信能力的遥控机器人车辆，称为Numbat，用于地下矿山安全和侦察任务。1.0简介澳大利亚拥有优良的煤炭资源，具有良好的长期创富潜力。然而，澳大利亚采矿业目前正面临着一些独特的经济挑战，以及满足更高安全要求和严格环境要求的期望。因此，在保证煤矿人员安全的前提下，寻找提高煤炭产量、提高采矿效率的方法是十分必要的。为此，CSIRO矿山设备自动化集团参与了现代自动化系统在煤矿机械上的开发和应用。采矿自动化技术在提供更精确的采矿方法、结合传感以提高生产率和最大限度地减少设备损坏以及通过将其应用危险机械和环境中提高人员安全方面具有巨大潜力。现代自动化技术能够显著提高生产率和安全性的一个领域是远程机器导航。这就需要开发自动化系统，能够感知要开采的材料，并将采矿机引导到指定的目标巷道。这两种潜在的制导方案称为水平和横向控制问题。任何实用的自动化系统也需要综合通信能力，以便实时传输有关地下环境和采矿设备状态的信息。第二节介绍了探地雷达（GPR）作为煤层厚度传感器在水平控制问题中的应用，并描述了其在长壁采煤作业中的应用。第三节介绍了一种解决横向控制问题的内导航系统。第四节介绍了一种新型遥控野战机器人，称为Numbat，用于地下矿山安全和侦察活动。Numbat的实时通信能力用于在人工勘探可能过于危险的情况下传送有关地下矿井状况的信息。2.0 用于水平控制的探地雷达本节介绍了在煤矿作业中测量煤厚度的探地雷达系统的开发。尽管探地雷达在深度测量方面有很大的潜力，但原始信号往往很复杂，因此采矿人员很难对其进行解释。我们展示了实时数字信号处理如何在将原始雷达信号转换成易于理解的形式方面发挥关键作用。我们还指出了在恶劣的煤矿环境中实现雷达处理系统时遇到的一些独特挑战。2.1 煤层层位传感在地下采煤作业中，需要有一个最佳的顶煤和底板煤厚度，以提供足够的结构支撑，同时最大限度地提高煤炭回收率，避免不必要的煤炭浪费。如果残煤太厚，则留下永久不可回收的煤。如果残留在顶板的煤层太厚，会大大增加顶板坠落的风险。开采坚硬岩石而不是煤炭也大大增加了机器损坏的风险。图1显示了一个典型的地下开采作业的横截面图，其目标是通过遵循最佳开采层位将采矿机保持在煤层中。为了实现这一目标，需要一种确定煤层深度的方法。图1 地平线控制问题。这里的基本目标是使连采机保持在煤层中，以最大限度地提高煤炭回收率。黑色带代表煤，纹理带代表凝灰岩2.2 现有煤深传感器煤深传感系统主要有两类：反应式和预测式。反应式煤深传感器是基于在遇到煤岩界面时检测操作特性的变化。反应性方法包括监控切割滚筒电流、感知机器振动信号的变化以及使用仪表化切割镐。反应法的潜在局限性在于，它们依赖于煤岩界面的实际渗透，在这种情况下，防止产品稀释和机器损坏为时已晚。与反应式方法不同的是，预测传感器试图估计从机器到机器的距离煤岩界面。最常见的预测方法是使用伽马辐射传感器，通过利用通常与煤层一起发现的寄主地层的放射性来估计煤层深度。自然伽马传感器可以在特定情况下很好地工作，但需要30秒才能获得可靠的深度测量。这种延误会严重影响煤矿开采作业。这一局限性促使人们寻找替代的预测传感方法。2.3 探地雷达作为深度传感器探地雷达在土木工程、地质探测和岩土工程领域中发现了地下特征描述的特殊应用探地雷达的中心吸引力在于它是非侵入性和非破坏性的，并且可以提供地下特征的瞬时成像。探地雷达的基本原理是将能量传输到地面，然后测量不同介电常数材料界面的反射。地震的震级 接收到的反射取决于地面电导率和介电常数、目标的大小和形状以及边界处介电常数之间的差异。空洞、空腔和其他介质界面代表了可能产生脉冲回波的不连续性。通常在含煤地层中发现的地质特征特别适合雷达成像。这是因为煤的导电性相对较低，相对寄主地层的介电常数较高。迄今为止，探地雷达还没有广泛应用于煤矿行业的煤深测量。这主要是因为使敏感电子设备适用于崎岖和危险的煤矿环境的实际问题，以及探地雷达系统返回的雷达信号的复杂性。成功实施煤炭测量系统的关键要求是使用信号处理将原始雷达数据转换为非专家人员可以立即使用的形式。大多数商用探地雷达系统不适用于地下煤矿开采，也不提供自动实时处理能力，因此依靠训练有素的操作员以离线能力手动解释原始雷达数据9。图2显示了传感器指向自由空间的典型原始探地雷达输出。主峰代表天线的气耦合特性。显然，需要对原始雷达数据进行额外处理，以便为水平控制提供煤炭深度估计。图2：显示雷达气耦合特性的原始探地雷达信号快照2.4 探地雷达信号模型与处理基于探地雷达的煤厚传感器依赖于测量从传感器到煤岩界面的传播时延和对当地煤岩地质的了解。首先考虑成像场景的物理布局，推导了接收到的雷达信号模型。由此产生的一组方程导致相关的处理任务。2.4.1雷达信号模型接收到的雷达信号可以建模为2其中W0（t）是雷达-空气耦合脉冲，W（m）是雷达的集中脉冲响应，m指定（双侧）小波的时间支持，并且Nk（t）是时间t=0，t-1和雷达拉伸指数k=0,1，的独立噪声过程，。序列Nk（t）包括传感器和定时抖动噪声。序列Rk（t）由下式给出 式中，ak（n）是回波的幅度，tk（n）是n=0，pk-1的脉冲时间延迟。信号Rk（t）类似于地震图像10中发现的反射率序列。另请注意，这是一个近似值，因为脉冲形状可能会因成像的材料而异。方程（1）表示基本脉冲小波与（标度）反射系数的卷积。在给定的雷达信号观测Zk（t）中，可能存在0npk接口。基本目标是根据所有k的Zk（t）观测值估计k（n）和pk，特别是第一反射。图3显示了典型的原始雷达数据Zk（t），布置为声纳式的t=0，479和k=0，999图。图3：原始探地雷达数据阵列。纵轴表示时间延迟，横轴表示传感器保持在静止位置时相邻的雷达数据2.4.2雷达信号处理 图4：显示原始探地雷达数据处理的方框图，以提供煤炭深度估计图4显示了处理原始雷达数据的四个基本阶段：预处理、滤波、检测和估计。这包括用于路径损耗补偿的时变增益、雷达-空气耦合特性抑制、小波反褶积、延迟和位移域滤波、短期集合平均、能量检测和峰值定位。预处理阶段有两个预处理步骤。第一步是对接收到的信号应用指数增益，以补偿雷达信号通过地球物质的衰减特性。这种时变增益极大地扩展了系统的动态范围，并且具有去除等式（2）中ak（t）的时间依赖性的效果。第二个预处理步骤是去除发射机-空气/接收机耦合特性。方程（1）中W0（t）的估计值是在初始系统校准期间通过计算k上Zk（t）的集合平均值得出的，假设在指定校准间隔内原始收益的统计平稳性过滤级。由于采矿机的运动相对于探地雷达的采样率非常缓慢，多普勒效应可以忽略不计，因此Z轴是=1020相邻原始收益的一个很好的近似值。这种特性允许在位移域进行低通滤波，以抑制由雷达定时抖动引起的伪影。在时间/延迟域中的低通滤波也被证明在抑制传感器噪声和机器振动的影响方面特别有效。为了提高探测能力，对雷达数据进行去卷积处理，得到一个正则化逆11，该逆11是由对基本雷达子波W（t）的适当估计得到的。在处理的数据中考虑了由于因果关系而引入的小相移。检测阶段处理后的数据通过检测级来确定潜在的介电接口。在每个时刻k实现时域滑动窗口能量检测器。然后将能量检测器的输出与先前根据现场测试和校准经验确定的阈值进行比较。如果检测器输出超过给定的值，则通过计算能量窗域内所得到的一组（顺序排列的）指数的中值来估计平均双向行程时间。通过记录给定实现中不同峰集的数量来获得pk的估计。该方法是一种简单有效的煤凝灰岩界面自动检测方法，计算效率高，便于实时实现。深度估算阶段假设第一个回波代表煤岩界面的双向传播时间，则煤炭深度的估计值由n=0，pk-1给出，其中c4.5表示煤炭。经过处理的雷达数据大大简化了表示，从而使采矿人员接受了该技术。这些数据还可以有意义地用于更多的跟踪和控制方案。然而，需要注意的是，雷达数据会受到基本雷达模型的各种像差的影响：非线性、多次反射、异质性变化、湿度变化、传感器和采矿机振动、操作员误用以及传感器放置都会导致测量错误2。2.5 探地雷达长壁应用探地雷达装置被应用于地下连采机被称为长壁连采机。我们测试的主要目的是确定雷达装置是否可以用作煤矿开采场景中地平线控制的传感器。为此，基于探地雷达的传感器安装在澳大利亚新南威尔士州达特布鲁克的长壁连采机上。特殊的地下场景存在一个问题，为自动煤厚度测量系统提供了长期潜力。正在开采的煤层底板由高灰分（80%）的风化粘土层组成。由于凝灰岩层正上方的煤炭质量很高，因此在尽可能靠近地面的地方进行切割确实有好处。然而，如果开采凝灰岩层，产品的灰分含量会急剧增加。探地雷达处理系统作为一个整体由三个主要部分组成：宽带（800兆赫）双基地脉冲雷达、数据处理单元和可视化系统。这种天线配置产生5 ns的数据拉伸，从而产生高分辨率的短程（150 cm）回波数据12。整个探地雷达系统首先在地面进行了组装和测试。然后将其运至地下，安装在长壁连采机上，如图5所示。地下探地雷达操作豁免条款规定，设备只能在维护期间操作。图5：安装在长壁连采机上的探地雷达处理和显示装置2.5.1试验程序测试包括在相邻顶板支架的水平推压闸板之间的区域进行煤厚测量。将长壁连采机移动到工作面上残余煤厚度超过雷达标称穿透深度的位置。雷达装置被直接放置在煤的表面，并记录返回的数据。图6显示了未受干扰区域的探地雷达回波，其中煤岩界面超出探地雷达范围（大于300 mm）。图6：煤岩界面超出雷达范围时的原始雷达输出显示未观察到反射建造了一个试验台，以便在仪器范围内手动建立局部地板水平。图7显示了100 mm煤厚的原始雷达数据，水平轴代表煤岩界面。在传感器范围内的煤厚度处，可以清楚地看到煤与凝灰岩的界面。图7：地面以下约100 mm处存在煤岩界面时，探地雷达显示装置的输出2.6 地下使用注意事项为了使雷达处理系统适用于恶劣的煤矿开采环境，有必要进行特殊的设计和施工考虑。此外，系统需要在存在潜在爆炸性气体的情况下运行。信号处理模块和显示屏安装在坚固的隔爆外壳中，外壳上有一个可视窗口，如图8所示。特别值得注意的是，雷达收发组合件采用非金属隔爆外壳。显然这是必要的，因为使用金属外壳不允许雷达信号传输。雷达外壳由具有足够低介电常数的加固碳基合金制成，以使雷达信号不会受到不利衰减，并通过铠装电缆与主隔爆系统互连。图8：用于容纳探地雷达系统信号处理和显示部件的隔爆外壳探地雷达系统必须在尽可能少的操作员干预下运行（理想情况下没有），具有物理健壮性，符合严格的本质安全要求，并便于远程软件维护和数据检索。因此，操作员“界面”仅限于四个坚固的按钮来选择校准和其他控制。2.7探地雷达概要探地雷达有可能解决采矿业中一个重要的煤深估算问题。设计、建造了一个用于煤深测量的探地雷达处理系统，并在连采机上进行了评估。开发的第一代雷达测量系统提供实时数据采集、处理和煤炭厚度估计的可视化，以及远程数据通信设施。实验表明，煤岩界面与已知地质存在正相关关系。雷达信号处理技术的不断发展是提高测量系统可靠性和实用性的关键。3.0 高壁采矿惯性导航系统高壁开采是一种重要的采煤方法，它是将遥控连采机放入先前露天开采的煤层中。连续运输系统用于将煤炭从矿工运至露天装置进行储存和运输。高壁采矿过程形成了一系列名义上平行、无支撑的驱动器。图9显示了正在运行的高壁连采机。图9:高壁连采机暴露的煤层中形成驱动力3.1横向引导的必要性相邻驱动之间的煤柱能够支撑覆盖层结构，这一点至关重要。这种采矿方法完全依赖于有效的远程控制。只有通过远程确定和控制连采机的位置和掘进，才能在最紧密的间隔处实现与岩土工程设计一致的直线平行开口。图10显示了突出与高壁采煤相关的横向导向问题的平面图。针对高壁连采机的侧向导向，提出了多种方法。激光测量提供了精确确定长壁机位置的潜力，但与位置相关的问题，如能见度和视线，意味着一般方法是不可能的。一些光/机械钻孔类型的测量方法已被考虑，但由于在非常不适宜的环境中需要高精度的角度测量，因此也存在实际实施困难。使用无线电传播的特殊用途三角测量系统无法使用穿透覆盖层所需的低频率达到所需的机器位置精度。与现有系统相关的限制方法强烈建议需要一个位置传感系统，只需要一个最小的外部基础设施。贯入深度500m图10：高壁开采中遇到的横向控制情景。目标是保持一个目标航向，以优化煤炭回收率并确保煤柱完整性。3.2 横向制导惯导系统使用基于INS的传感器可以提供采矿机的绝对位置，而不需要任何外部位置信息。INS操作原理的全面审查不在本文件15、16的范围内。现代惯性传感器没有运动部件，使用固态光学陀螺仪和加速度计。这就产生了一种惯性传感器，它具有很强的抗振动能力，但在内部需要更多的计算来产生航向和位置数据。通过在采矿机上安装惯性导航系统，从理论上讲，遵循从采矿计划中获取的给定目标航向是可行的。大多数惯性元件用于两种模式中的一种，以提供全三维位置测量或方位航向参考系统（AHRS）。操作INS测量模式的缺点是需要经常停止装置以执行零速度更新（ZUPT），以允许INS修正累积的加速计误差13,14。即使严格遵守ZUPT要求，残余误差的累积也会导致位置精度随时间降低。所有基于惯性的系统都会漂移，因为位置是通过双积分加速度计输出来获得的，以提供位置估计。这些操作会产生随时间增加的错误。图11显示了在12小时的试验期间，由惯性导航系统漂移特性引起的二维定位误差的大小。该数据是在惯导系统绕转台上一固定点作振荡运动时获得的。较大的位置误差代表了航向信息的不确定性，从而限制了最大允许驱动穿透深度。图12显示了INS航向/方位不确定性导致的可采煤炭损失方面的直接罚款。潜在煤炭回收的损失，加上INS ZUPT要求引起的生产延迟，意味着目前没有任何实际系统使用完全基于INS导出位置的制导。3.3 利用惯性导航和里程计导航另一种方法是将惯导航向信息与外部沿轨道距离测量相结合，以获得相对机器位置。在这种操作模式下，惯导系统不需要，航向精度可以长期保持。由于航向信息是由高精度激光陀螺角速度输出的一次积分得到的，因此它比被测位置更精确，更不易受漂移的影响。该方法通过使用独立的位置固定将累积误差归零，从而有助于惯性导航系统指示位置的周期性校正。二维定位误差时间图11：一个实验的结果证明了由惯性导航系统引起的二维位置误差。安装在支架上的惯性导航装置在12小时内围绕一个固定点作振荡运动在高壁采矿制导系统中，采用惯性导航系统的AHRS模式，使用里程表作为外部沿轨距离传感器。航向偏差是指特定高壁巷道的设计或所需航向与矿工航向之间的差异，在这种情况下，由惯性导航系统提供。矿工航向，因此航向偏差，是沿轨道距离的函数，在本应用中，可由INS外部传感器测量，且独立于INS。矿机横向逐步偏差可以计算为沿轨道距离方向偏差正弦值的积分。累进交叉轨道距离描述了矿工相对于设计路径的路径。如果已知两个相邻巷道的横道偏差、设计导坑和巷道间距，则计算沿巷道任意点的矿柱厚度是一件简单的事情。不确定性资源可恢复程度例如：3.5m宽车道，矿柱最小宽度3.0m，掘进长度350m方位不确定度成本图12:INS航向不确定性对可采煤炭的影响3.4 导向连续连采机应用组合惯性导航和里程计横向制导系统已用于澳大利亚昆士兰州莫拉矿的生产高壁采矿系统。该系统允许高壁连采机的位置和路径以图形和数字实时显示给操作员。相邻矿柱的厚度由绘图软件推断。操作员可以获得沿轨道、航向偏差、交叉轨道偏差和矿柱厚度的瞬时值。图13是横向制导软件的平面图，显示了已开采和计划的驱动器。所需的驱动器标题显示为虚线，交叉阴影区域表示已挖掘的驱动器。横向导向系统的引入使资源回收率提高了40%，并且几乎消除了非计划驾驶交叉口的发生率。与之前小于（不一致的）300米的掘进深度相比，现在常规可靠地获得了500米以上的掘进深度。使用该系统，在500米穿透后，驱动入口的交叉跟踪误差约为500毫米。图13:操作员显示屏，显示采矿机的实际路径（交叉阴影区域）与相邻驱动器的设计路径（虚线区域）的比较3.5 摘要研究了惯导系统在连采机侧向制导中的应用。结论是，漂移、精度和操作限制意味着矿工制导不太可能仅基于惯性导航系统。然而，航向信息与沿航迹测量（里程计）相结合可以提供精确的制导和控制。对指导的需要得到了业界的充分认可。航向信息和一般方位信息可与沿轨道测量相结合，得出横向轨道偏差，从而得出矿工的横向位置和路径。矿工在垂直面上的路径可以类似的方式从俯仰信息中导出。基于惯导系统的侧向控制系统在三个独立生产的高壁开采作业中的应用证明了该方法的有效性。基于惯导系统的侧向制导系统的应用大大提高了生产率和安全性。4.0 Numat矿山安全车矿山事故后最重要的问题之一是缺乏对矿山地质完整性和环境条件的了解。这种不确定性，再加上不愿危及人身安全，必然导致采矿生产率下降，甚至可能导致生命损失17,18。Nubat矿场应急响应车是由CSIRO在1986年穆拉矿场爆炸后开发的。它是一种远程控制的交通工具，用于在人工勘探过于危险的情况下传送有关地下矿山状况的信息。Nubat项目的主要目的是在紧急事件发生后，为救援队提供有关地下矿井状况的即时信息。将Nubat
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