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毕业设计(论文)外文资料翻译学 院专业机械设计制造及其自动化学生姓名 班级学号外文出处International Journal of Industrial Ergonomics 38 (2008) 715725外文资料Modeling of the handarm system for impact loadingin shear fastener installationDepartment of Mechanical and Aerospace Engineering, Room No. 330, Engineering Research Laboratory, 1870 Miner Circle,University of Missouri-Rolla, Rolla, MO 65401, USADepartment of Engineering Management and Systems Engineering, University of Missouri-Rolla, Rolla, MO 65401, USAReceived 2 October 2007; accepted 3 October 2007Available online 26 November 2007AbstractThe aim of this study is to model the handarm system during fastening operation using shear fasteners. This fastening operation has considerable dynamic forces caused by the impact delivered to the handarm at the end of the operation because of fastener shear-off.The handarm is modeled as a rotational single-degree-of-freedom system. The values of the model parameters are obtained using the magnitude of compliance spectrum calculated from the measured torque and angular displacement data, which are obtained while installing fasteners on a fixtured experimental setup, and by a non-linear least-square curve fitting technique. The experimental setupfacilitates transferring the torque from a torque driver to a fastening tool handle held by the subject. The identified parameter values arefound consistent for the trials conducted under same test conditions. Strong agreements are seen between the predicted responses usingthe model and the measured responses.Relevance to industryThis study is useful in tool selection and workplace design for assembly shop floors where hand-held power tools are commonly used.It demonstrates a systematic approach in predicting the motion of an operators handarm for a given torque impulse produced by afastening tool. The predicted motion can be used for further analysis to determine the detrimental effect it may have in causing cumulative trauma disorders.2007 Published by Elsevier B.V.Keywords:Biomechanics; Compliance; Handarm model; Fastening operation1. IntroductionPowered hand tools such as nut-runners, screwdrivers and drills require the operator to react to the tools dynamic forces. For many types of power tools, both electric and pneumatic, the greatest source of dynamic force is a sudden change in the applied torque of the tool.This could be the result of a fastener reaching the end of its travel or a part of the fastener shearing-off at the end of the operation. The reaction of the handarm to a torque impulse is dependent upon the condition of the handarm immediately before and after the impulse. The muscles of the handarm system holding the tool generate appropriate reaction to the torque at the end of the operation. In reacting to the impulsive torque, the operator contracts the muscles of the handarm system and positions the body in such a manner so as to maintain the dynamicequilibrium.This muscle contraction is generally non-isometric in nature. The nature of such muscle contractions is believed to have potential of causing injuries like reduction in strength and onset of muscle soreness (Komi and Buskirk, 1972; Komi and Rusko, 1974).Biomechanical studies of the handarm system in response to continuous excitation forces have used dynamic-system models with one to four degrees of freedom for calculating the response of the handarm based on mechanical properties like impedance and ARTICLE IN PRESS /locate/ergon 0169-8141/$ - see front matterr2007 Published by Elsevier B.V.doi:10.1016/j.ergon.2007.10.012Corresponding author. Tel.: +1 573 341 6557. E-mail address:asjdkd (A. Joshi).compliance (Gurram et al., 1995, 1996; Reynolds and Soedel, 1972; Reynolds and Keith, 1977; Reynolds and Falkenberg, 1982; Suggs, 1972; Suggs and Mishoe, 1975).These methods use a frequency range of 102000 Hz in the analysis and they apply to the cases of periodic and random vibrations produced by tools like sanders and grinders that continuously generate forces to excite vibrations for a relatively long period of time. However,these models do not apply well to the impulsive-type forces/torques generated by fastening tools. The typicalrange of frequencies for dynamic responses in these tools is in the range of 025 Hz (Armstrong et al., 1999; Kihlberg, 1995; Kihlberg et al., 1995; Oh and Radwin, 1997, 1998; Oh et al., 1997; Starck and Pyykko, 1986). Other studies have used surface electromyography as a means to studythe effects of reaction forces and torques acting on the hand (Freivalds and Eklund, 1993; Kihlberg et al., 1993; Radwin et al., 1989). However, these studies do not model the handarm system and require a large number of experiments to deduce the relationship between the probability of causing injuries and factors such as tool type and handarm posture. Previous attempts to model the handarm response to impulsive torques are based on the response of the handarm under conditions of maximum exertion (Lin et al., 2001, 2003a, b). This resulted in an underestimation of the hand deflection and an overestimation of the contact force between the hand and the tool when using real tools. The aim of the study as described in the present paper isto develop a biomechanical model to understand the response of the handarm system to impulsive torque encountered in fastening operation with shear fasteners.The study includes the modeling of a simulated fixture as a two-degree-of-freedom system and the response of the handarm using a one-degree-of-freedom system. The developed handarm system model will be useful in designing and/or selecting power tools to minimize the forces/torques and resultant motions encountered by the operators as well as comparing ergonomic risks associated with different tools. The model can predict the motion of the handarm and allow the tool to be designed to minimize the hand movement, thus reducing the associated ergonomic risks.2. MethodsTo model the response of the handarm system one naturally thinks of an experiment with the subject using an actual tool performing real operations. However, acquiring data in such a completely free-moving experiment would require modeling the complex tool dynamics as well as the complex handtool interactions, which would require collecting a large amount of data including the applied forces/torques and the resultant translational/rotational displacements. This process is not only expensive but it often results in widely varying parameter values from trial to trial under same test conditions. Hence, an experimental setup to simulate the actual working conditions has to be built which would transfer the same forces/torques to the handarm system as a real tool would but in a more manageable manner. In this study, an experimental setup has been designed such that the torque from a real tool is transferred directly to the test subject and the system response is determined using a fixtured tool handle. This has the advantage that the subject responds to all torques generated from the securing of a fastener until the fastener shears off.2.1. Experimental setupThe experimental setup is shown inFig. 1. The source of torque input is the torque driver, which is an actual tool as shown on the left side ofFig. 1, while the fixtured handle of the test tool as shown on the right side ofFig. 1is gripped by the test subject to measure the response.2.2. Tool modelingThe study starts with modeling of the test tool. The response of the test tool is obtained by manually providing impulsive torques to the test tool without the subject holding the test tool. The measured compliance is used to determine the degree of the system necessary to model the dynamics of the test tool. The magnitude of the frequency spectrum of the compliance as shown inFig. 4is given by the ratio of measured angular displacement to the input torque for the test tool. It shows two distinct natural frequencies below the upper-bound frequency of 20 Hzused in the analysis. Based on the frequency spectrum of the compliance, a two-degree-of-freedom system model is chosen for the test tool. This model is shown schematically inFig. 5, wheretis the torque input.The dynamic equation of this system is given byThe frequency spectrum of the systems compliance isgiven byWhereThe frequency spectrum of the compliance of the test tool is computed from the Fast Fourier Transforms of the encoder data and the torque sensor data. The unknown parameters of the system shown inFig. 5and Eq. (1) are determined by curve fitting of Eq. (2) to the frequency spectrum of the measured compliance. A non-linear least square curve-fitting algorithm is used to compute the values of the model parameters. Eq. (3) is the objective function that is minimized to determine the model parameters by using the GaussNewton method of Optimization.where F(x,xdata) is a vector-valued function and ydatais associated with the measured data.In the case of this study, the vector-valued function Fis the compliance of the tool model given by Eq. (2). This function is optimized through an iteration process about the vector x starting from a set of initial guesses x0of values for the model parameters to minimize the objectivefunction. The data is the compliance in Eq. (2) calculated from the measured rotation and torque data. The vector of parameters used for the model given by Eq. where T designates the transpose. The algorithm starts with x0 as the starting point for optimization of the function F and iteratively searches for the global minimum of function G using the GaussNewton optimization technique to determine the best curve fit in a least-square sense.2.3. Design of experiment for handarm modelingAfter acquiring the dynamic model of the test tool,subjects are tested to determine the model of the handarm system. They were instructed to grip the test tool handle as needed to simply maintain the position of the handle. For this study, two male subjects participated in the experiment. Both were students and free from any kind of health problems related to the hand, arm, or shoulder that could affect the results of this study. The same two subjects were used to perform additional sets of experiments to validate the model and to test the repeatability of the model results. Prior to the tests, the subjects had installed numerous fasteners with the actual tool in a variety of postures so that they became familiar with the grip and push forces necessary to operate the torque driver. For the experiments, the subject held the test tool handle in neutral posture while a researcher secured a fastener using the torque driver. The model parameters for the handarmsystem of the subject were determined by measuring the subjects handarm response to the torque input provided by the torque driver. Five trials were conducted for each subject.The fastening operation lasts for about one second. The operation consists of three parts during which the response of the subjects handarm to the imposed torque alternates between active (voluntary) and passive (involuntary) components as shown in Fig. 6(a). Fig. 6(b)shows thecorresponding response. The portion of data when the fastener is running down and reaches the end of its travel is the torque build-up period, i.e. period (I) inFig. 6(a). This portion of data is an active component because the subject is fighting the torque to prevent the test tool from rotating.The second portion of data, i.e. period (II), corresponds to the fastener shearing off, resulting in sudden rise in the torque. This period is of very short duration (approximately 0.15 s) in which the excessive torque overpowers the resistance offered by the subjects hand and the hand rotates in the direction of the imposed torque. In this period of 0.15 s from the peak torque, the response of the subject can be considered involuntary and hence be modeled as a passive dynamic system (Boff and Lincoln,1988). Followed by this period is an active component, i.e.period (III) inFig. 6(a), during which the subject forces the test tool back to its original position while the tool shutsoff, reducing the torque to zero. The analysis is based on modeling the handarm system as a passive system during period (II) and determines the values of model parameters using the passive component of the measured data.To select the data for analysis the following procedure is adopted: the starting point of the torque curve is determined by the slope of the ramp from the torque profile shown inFig. 6(a). A line is constructed using the slope of the ramp and is projected on the time axis to determine the starting point of time for the torque and the response data used for modeling. The transient oscillation seen in the torque plot after the end of operationin Fig. 6(a)is due to the dynamic characteristics of the torque sensor. It is removed from the torque data in the analysis, and the torque in the tool shut-off period is considered zero. The torque and response data used in the analysis are shown inFig7. 3. ResultsThis section provides the results for modeling the system and verification of the modeling technique.3.1. Tool modelingThe values of the tool model parameters obtained from each of five trials along with the average values of the identified parameters of the test tool are shown in Table 1.The magnitude plot of the frequency spectrum of the measured compliance and the fitted curve based on the model for one of the trials is shown inFig. 11.3.2. Handarm modelingThere were five trials of the experiment conducted for each subject in neutral posture. The values of the handarm model parameters for the five trials and their averages for each subject performing fastening operation in neutral posture with a pistol-grip tool are listed inTable 2.Based on these values, the natural frequency calculated for subject 1 is 3.25 Hz and the natural frequency calculated for subject 2 is 3.85 Hz.4. DiscussionThis study has provided a method of dynamic modeling, experimental design, and data analysis for the human handarm, which is considered as a dynamic system, in response to the torque generated due to the shear-off of a fastener at the end of the fastening operation. In this study, the handarm model is identified as a single-degree-offreedom system.It can be observed from Table 2, that the identified values of model parameters are fairly consistent for all thetrials for both subjects tested. The subjects tested in this study are similar in height and weight. This may explainwhy no large variations in the predicted values of the parameters are found. More trials need to be conducted with subjects that vary more substantially in height and weight, in order to determine variations in the model parameters between subjects. The grip force is not considered in this study, and the subjects are asked to grip the handle just hard enough to maintain the position of the test tool. The natural frequencies of the handarm system for the two subjects determined by using the derived model parameters are slightly less than that reported in a previous study (Lin et al., 2001), which shows the natural frequency of a handarm to be around 4 Hz. This may be due to the fact that the subjects are holding the test tool with anominal grip force just enough to maintain the position,which in turn results in reduction of the stiffness of the handarm system.The derived model parameters are used to predict the response of the subject by using Eq. (6) and measuring the torque using the same testing conditions. In reacting to the impulsive torque which arises due to the fastener shearoff, the subject tends to respond passively for a small time duration of about 0.15 s, i.e. period (II) inFig. 6(a), from the peak torque value when the torque overpowers the subjects resistance to imposed torque. That period is followed by an active response, which is period (III) in Fig. 6(a), when the subject forces the test tool back to the starting position. Previous studies have indicated that it is safe to assume that within a period of 0.15 s the human response can be considered passive (Boff and Lincoln,1988). Hence, for predicting the response of the subject using the identified model parameter values only the passive portion of response is used. However, this period can vary between subjects and even within a subject depending upon the number of repetitions of the operation.There is a tendency for subjects to anticipate the forcing and brace actively as is observed by Armstrong et al.(1999).Previous studies analyzing the handarm response for impulsive torques measured the response under the condition of maximum grip with the use of a simulated physical tool instead of a real tool (Lin et al., 2001, 2003a, b).It resulted in an underestimation of the handarm deflection and an overestimation of the interface forcebetween the tool and the hand when using a real tool. The method of data acquisition and analysis in the present study allows for identification of the handarm system parameters under conditions more representative of the real-world practice. As the torque driver in this study is an actual tool, the torque exerted on the test tool is also more representative of the real world. Thus, the method closely resembles the real-world working conditions experienced by an operator on the shop floor. By changing the torque drivers and test tools in Fig. 1, different tools can be compared for their dynamic and ergonomic effects on the operator handarm system. Currently, the relation between the causes of cumulative trauma disorders and mechanical model parameters is not well understood. The relative contribution of force/torque,deflection, and operation repetition to the occurrence of injuries is not yet quantified. This is a three-part problem.First, it is difficult to quantify the system parametersassociated with changing posture, tool, fixture, etc. Second,due to the cumulative nature of handarm disorders it takes months or even years to detect resulting injuries.Third, it is not yet possible to quantify specific risk factor(s)that cause ergonomic injuries. NIOSH has publishedseveral studies attempting to categorize the risk factor(s).It divides the risk factors into four categories: high force, high repetition; high force, low repetition; low force,high repetition; and low force, low repetition (NIOSH,1997). However, the range of each of these four categories is not clearly defined. If correlations between the force/repetition and the resulting injury are to be determined,it is imperative that the modeling and analysis techniques used to measure and predict the deflections and handtool interface forces be accurate and repeatable. The techniques discussed in this paper provide good correlations between the predicted and the measured angular rotation as shown inTable 3. The tests conducted to checkits repeatability also yield strong correlations between the predicted and the measured angular rotation. This proves that the developed techniques can be used effectively to model the handarm system. The derived model can be used to compare different tools, postures, fasteners, etc.using the predicted angular rotation as a metric of comparison.ARTICLE IN PRESSThe modeling technique presented in the paper can effectively predict the response of the subject to impulsive torque produced by a fastening tool used for fastening of shear-type fasteners. The angular rotation of the handarm system can be used as an objective indicator of the discomfort of the operators as shown in previous studies (Kihlberg et al., 1993; Lindqvist, 1993). Hence, the method discussed in the present study can be used to compare different tools and postures for the perceived discomfort of the operator by measuring the torque produced by the tools and using the modeling technique described in the present paper to calculate the angular rotation of the hand-arm. The experiments presented in this study have provided a proof of concept of modeling and analysis techniques that can be used to study the dynamics of the handarm system.Further experiments will be needed to assess the effect of posture on the parameters of the handarm system model and to investigate the effects of tools, fasteners and operation repetitions on the model parameters. The prediction of the hand deflection can be used as a measure to compare different tools and fasteners as well as different postures for various subject populations. This would be helpful to design of tools, fasteners and workplaces for minimizing hand deflection, thus reducing the ergonomic risks involved.AcknowledgmentsThis project is supported by the Center for Aerospace Manufacturing Technologies, which is funded by the Air Force Research Laboratories under Contract no. FA8650-04-C-5704.The authors would like to thank Leslie Hoeckelman, Lynn Braunschweig, Jeffery Kilwin and Bryan Dods of Boeing Company for their valuable help during the course of this project.ReferencesArmstrong, T.J., Bir, C., Foulke, J., Martin, B., Finsel, L., Sjoe Gaard,G., 1999. Muscle responses to stimulator torque reactions of hand-heldpower tools. Ergonomics 42, 146159.Boff, K., Lincoln, J., 1988. Engineering Data Compendium: HumanPerception and Performance, vols I and II. Wright-Patterson Air ForceBase, OH.Freivalds, A., Eklund, J., 1993. Reaction torques and operator stress whileusing powered nut runners. Applied Ergonomics 24, 158164.Gurram, R., Rakheja, S., Gouw, G., 1995. Biodynamic response of thehuman handarm system subject to sinusoidal and stochasticexcitations. International Journal of Industrial Ergonomics 16,135145.Gurram, R., Rakheja, S., Boileau, P., Gouw, G., 1996. Development of agrip force dependent handarm vibration model. Central EuropeanJournal of Public Health 40, 6568.Kihlberg, S., 1995. Biodynamic response of the handarm system tovibration from an impact hammer and a grinder. International Journalof Industrial Ergonomics 16, 18.Kihlberg, S., Kjellberg, A., Lindbeck, L., 1993. Pneumatic tool torquereaction: reaction forces, displacement, muscle activity and discomfortin the handarm system. Applied Ergonomics 24, 16173.Kihlberg, S., Kjellberg, A., Lindbeck, L., 1995. Discomfort frompneumatic tool torque reaction: acceptability limits. InternationalJournal of Industrial Ergonomics 15, 417426.Komi, P.V., Buskirk, E.R., 1972. Effect of eccentric and concentric muscleconditioning on tension and electrical activity of human muscle.Ergonomics 15, 417434.Komi, P.V., Rusko, H., 1974. Quantitative evaluation of mechanical andelectrical changes during fatigue loading of eccentric and concentric work.Scandinavian Journal of Rehabilitation Medicine Suppl. 3, 121126.Lin, J.H., Radwin, R.G., Richard, T.G., 2001. Dynamic biomechanicalmodel of the hand and arm in pistol grip power handtool usage.Ergonomics 44 (3), 295312.Lin, J.H., Radwin, R.G., Fronczak, F.J., Richard, T.G., 2003a. Forcesassociated with pneumatic power screwdriver operation: statics anddynamics. Ergonomics 45, 11611177.Lin, J.H., Radwin, R.G., Richard, T.G., 2003b. A single-degree-offreedom dynamic model predicts the range of human responses toimpulsive forces produced by power hand tools. Journal of Biomechanics 36, 18451852.Lindqvist, B., 1993. Torque reaction in angled nut runners. AppliedErgonomics 24, 174180.Oh, S.A., Radwin, R.G., 1997. The effects of power hand tool dynamicsand workstation design on handle kinematics and muscle activity.International Journal of Industrial Ergonomics 20, 5974.Oh, S.A., Radwin, R.G., 1998. The influence of target torque and build-uptime on physical stress in right angle nut runner operation. Ergonomics41, 188206.Oh, S.A., Radwin, R.G., Fronczak, F.J., 1997. A dynamic mechanicalmodel for hand force in right angle nut runner operation. HumanFactors 39, 497506.Radwin, R.G., Van Bergeijk, E., Armstrong, T.J., 1989. Muscle response topneumatic hand tool torque reaction forces. Ergonomics 32, 655673.Reynolds, D.D., Falkenberg, R.J., 1982. Three- and four-degrees-offreedom models of the vibration response of the human hand. In:Brammer, A.J., Taylor, W. (Eds.), Vibration Effects on the Hand andArm in Industry. Wiley Publications, New York, pp. 117132.Reynolds, D.D., Keith, R.H., 1977. Handarm vibration, part I:analytical model of the vibration response characteristics of the hand.Journal of Sound and Vibration 51, 237253.中文翻译在剪切紧固件安装中对冲击载荷的手臂系统建模 机械及航天工程，房号330，工程研究实验室，1870矿工圈处，密苏里 - 罗拉，罗拉，MO65401，美国 工程管理和系统工程，密苏里 - 罗拉，罗拉，MO65401，美国 收到2007年10月2日; 2007年接受10月3日摘要本研究的目的是使用剪切紧固件紧固操作过程中手臂系统进行建模。这种紧固操作有所造成的影响相当大的动态力，因为紧固件的剪切销传递到手臂的动作结束。手臂被建模为单自由度的旋转系统。所获得的从测得的扭矩和角位移数据，这些数据得到而计算符合频谱幅值安装在一个夹具固定的实验装置的紧固件，并通过非线性最小二乘曲线拟合技术。实验装置便于从驱动扭矩传递的扭矩由主体保持的紧固工具手柄。所识别的参数值是发现同样的测试条件下进行的试验是一致的。强大的协议所使用的预测响应之间可见模型和测量的响应。行业关联这项研究是在工具的选择和工作场所设计的装配车间地板，其中手持式电动工具常用有用。它展示了一个系统化的方法在预测操作者的手臂的运动由一个产生一个给定的转矩冲动紧固工具。所预测的运动，可用于进一步的分析，以确定有害影响它极有可能导致累积性创伤失调。关键词：Biomechanics; Compliance; Handarm model; Fastening operation介绍1电动工具，如固定扳手，螺丝刀和演练要求经营者作出反应的工具 动态力。对于许多类型的电动工具，既电动和气动，动力的最大来源力是在工具的所施加的转矩的突然变化。这可能是一个紧固件达到其结束时的结果旅游或紧固件剪切过的部分在本月底操作。手臂的转矩的反应冲动是依赖于手臂的条件紧接在之前和之后的冲动。手臂系统持有该工具生成相应的在操作结束时的反应转矩。反应的冲动扭矩，操作员合约的在手臂系统和在位置的身体的肌肉这样的方式，以便保持动态平衡。 这种肌肉收缩一般是不等距的，相信这样的肌肉收缩的性质 有伤及如减少潜在的 强度和性肌肉酸痛（科米和巴斯柯克的， 1972;科米和鲁斯科，1974）。在手臂系统的生物力学研究应对不断激发部队使用1至4度的动态系统模型 用于计算手臂的自由响应根据机械性能，如阻抗.这些方法使用的10-2000赫兹的频率范围分析它们适用于定期的案件由像桑德斯和工具随机产生的振动磨床，不断地产生力来激发振动在相对长的时间周期。典型频率在这些工具的动态响应范围是 在0-25赫兹的范围内（Armstrong等人，1999; Kihlberg， 1995; Kihlberg等人，1995;哦和RADWIN，1997，1998; Oh等人，1997;斯达克和Pyykko，1986）。 其他研究已经用表面肌电图作为学习的一种手段反应力和作用于扭矩的影响手（弗赖瓦尔兹和埃克伦德，1993; Kihlberg等人，1993; RADWIN等人，1989）。导致手偏转的低估和手之间的接触力的高估该工具使用真实的工具时。该研究为在本论文中所描述的目的，是 开发一个生物力学模型，以了解 在手臂系统的响应扭矩冲动 在紧固操作与剪切紧固件遇到的问题。 研究内容包括模拟夹具的建模作为双自由度的系统和响应手臂采用单自由度的系统。 该发达的手臂系统模型将在有用设计和/或选择的电动工具，以尽量减少力/力矩和所遇到的合成运动运营商以及相关比较符合人体工程学的风险用不同的工具。该模型可以预测的运动手臂，允许该工具被设计为最大限度地减少手部动作，从而降低了相关的符合人体工程学的风险。2. Methods方法建模的手臂系统1的响应自然地认为使用一个实验物体的执行真正的实际操作工具。然而，收购在这样一个完全自由移动的实验数据会需要建模的复杂工具动力学以及复杂的手工工具的相互作用，这将需要收集大量的数据，包括所施加的 力/转矩和所得到的平移/旋转位移。 这个过程不仅昂贵，但它结果往往很大，从试验不同的参数值以相同的测试条件下试验。因此，实验设置模拟实际工作条件必须是建成这将同一势力/扭矩传输到手臂系统作为一个真正的工具，但会以更管理的方式。在这项研究中，实验装置已被设计为使得从一个真实工具的扭矩是直接传送到测试对象和系统响应用夹具固定工具手柄来确定。这具有这样的主题响应所有扭矩的优势从紧固件的紧固产生的，直到拉链剪了。2.1. 实验装置该实验装置如图所示。 输入转矩为转矩驱动程序，它是一个实际的工具如图所示。 而此固定手柄如图所示的测试工具。 实验装置 扭矩驱动器由旋转过程中的限制测试，以便其惯性有对测得的结果无影响，但它被允许沿紧固如此的轴线翻译它的一端可以继续参与与紧固件直到紧固件剪了。数据采集设备由转矩传感器和旋转编码器。反作用扭矩传感器用于测量从扭矩驾驶员传递的转矩最终的测试工具。该编码器测量角度测试仪的旋转。转矩传感器及编码器是通过PCI-DAS6402连接到PC/500016数据采集板进行数据采集 样本/秒。在实验设置中，空气软管连接于测试工具，并从它垂直悬挂。空气软管阻尼刀具的运动。使用这种夹具固定设置，受试者的肌肉活动时，突然扭矩 改变媲美，如果他/她是用了在一个真正的紧固作业的实际工具。一个典型的扭矩周期和相应的角位移（响应）对于所研究的紧固操作的工具都显示在 图中，如图所示2.2. 建模工具建模工具基于所述合规性，一个频谱被选择用于测试的两自由度的系统模型 工具。这个模型是示意性示出的扭矩输入。两自由度模型的测试工具。 该系统的动态方程为 该系统的合规性的频谱由下式给出 刀具从的快速傅立叶变换的计算编码器数据和扭矩传感器的数据。未知该系统的参数所示inFig 5。 （1）是由方程的曲线拟合来确定。 （2）将频率光谱测量的合规性。一个非线性至少平方曲线拟合算法来计算模型参数的值。式。 （3）是物镜即最小化来确定模型函数通过使用高斯 - 牛顿方法的参数优化。该算法开始于X0作为起点函数“F”和迭代优化搜索函数的全局最小值“G”采用高斯 - 牛顿优化技术来确定最佳的曲线适合在最小平方意义。2.3. 实验手臂建模设计 获得测试工具的动态模型后，受试者进行测试，以确定手臂的模型制度。他们奉命抓地力测试工具手柄为需要简单地保持在手柄中的位置。为本研究中，两名男科参加了实验。两人都是学生和 不受任何健康相关的问题手，手臂，肩膀或可能影响本研究的结果。同样的两个主题用于执行的额外实验组，以验证模型和测试模型结果的可重复性。在此之前的测试中，受试者已经安装了无数紧固件在各种姿势的实际工具，以便他们熟悉了抓地力和推动力量操作扭矩螺丝刀必要的。在实验中，受试者保持的检测工具手柄在中立姿势而抵押研究员使用紧固件的 扭矩的驱动程序。模型参数的手臂被检体系统是通过测量确定的检者的手臂响应于所述扭矩输入提供由转矩驱动程序。五个试验是对每个进行的。紧固操作持续约一秒钟。该操作包括三个部分在此期间，反应受试者的手臂给施加的扭矩候补委员活跃的（自愿）和被动（非自愿） 数据的部分，当紧固件被耗尽，并到达其行程的末端是扭矩积聚期，即周期（一）inFig。图6。这数据的部分是有源元件由于受战斗的转矩，以防止测试工具旋转。数据的第二部分，即周期（）中，对应于紧固件剪切断，导致突然上升，扭矩。这个时期是很短的时间（约0.15次），其中的过大的扭矩击败了由被检者的手和手提供阻力旋转所施加的转矩的方向。在这种从峰值扭矩的响应0.15秒钟时间 主题可以被认为是不自主的，因而是建模为一个被动的动态系统（博夫和林肯，1988）。随后这期间是活性成分，即 期（III）的inFig。图6（a） 所示，在此期间，受强制测试工具返回到其原始位置，同时该工具自动关关闭，从而将扭矩为零。该分析是基于在建模手臂系统为被动式系统期间（II）和确定的模型参数的值使用测得的数据的无源部件。 要选择用于分析的数据下列程序是采纳：扭矩曲线的起始点是通过坡道从转矩斜率确定简介显示inFig6。A线是利用构建的斜坡的斜率，并且预计在时间轴上以确定的时间的起点的转矩和的应答数据用于建模。瞬态振荡操作结束后看到的扭矩情节图6（a）是由于的动态特性扭矩传感器。它是从扭矩数据删除分析，并在刀具切断期间的转矩是认为是零。在所使用的扭矩和响应数据分析显示inFig。 7。3结果本节提供的结果进行建模系统和验证建模技术。3.1建模工具 从所获得的工具模型参数的值每五个试验中随着的平均值确定测试工具的参数示于表1中。 的频谱的幅度图 基于所测量的合规性和拟合曲线 。3.2手臂建模有实验五项试验的进行在中性姿态每个主题的值手臂模型参数的五项试验及其平均值在每一个主题进行紧固作业中立的姿态用手枪握工具列于表2。基于这些值，固有频率计算题目1是3.25 Hz和计算的固有频率对于主体2是3.85赫兹。4讨论 这项研究提供了动态建模的方法，实验设计和数据分析对于人手臂，这被认为是一个动态系统，在响应于由于剪切销产生的转矩紧固件在紧固操作结束。在这项研究中，手臂模型被确定为一个单度offreedom系统。它可以从表2中可以观察到的，所识别的模型参数值是所有的相当一致试验两个语文科目测试。在这个测试的科目研究是在身高和体重相似。这也许可以解释为什么没有大的变化的预测值参数被发现。更多的试验需要进行与该变化较大幅度的高度和科目重量，以确定变化模型学科之间的参数。握力是不认为在这项研究中，与主体被要求抓地力手柄刚好够硬，以保持该位置测试工具。在手臂系统的自然频率通过使用派生模型确定的二级学科参数比报道的前一略小于研究（Lin等，2001），它显示了固有频率 一个手臂的是大约4赫兹。这可能是由于在事实上，受试者都抱着测试工具，具有标称握力刚够维持仓位，这又导致在还原的刚度的手臂系统。派生模型参数被用来预测响应通过使用公式的主题。 （6）与测使用相同的测试条件下的转矩。在反应冲动的扭矩而产生是由于在拉链shearoff，受试者倾向于对于一个小的时间被动地作出反应停留时间为约0.15秒，即，期间（II）inFig。图6（a）所示，从当转矩击败峰值扭矩值的受的阻力施加扭矩。这一时期是其次是一个积极的反应，当主体强制测试工具回起始位置。先前的研究已经表明，它是安全的假设，一个时期的0.15 S中的人内响应可以认为是被动（博夫和林肯，1988）。因此，对于预测对象的响应使用所识别的模型参数值只响应的无源部分被使用。然而，这一时期 可以科目，甚至在一个主体之间变化根据操作的重复次数。有科目预见的强迫倾向和支撑主动作为由Armstrong等观察。（1999）。以往的研究对手臂响应分析冲动的扭矩测量下的响应 最大的抓地力与使用模拟的条件物理的工具，而不是一个真正的工具（Lin等，2001年，2003年a，b）所示。它导致了手臂的低估挠度和界面力估计过高使用真实工具时，工具和手之间。该数据采集和分析在目前的方法研究允许鉴定手臂系统的条件比较有代表性的参数下 现实世界的实践。 在这项研究中的扭矩驱动器是一个实际的工具，作用于测试工具的扭矩也更代表现实世界的。因此，该方法密切类似经历的真实世界工作条件通过在车间操作员。通过改变转矩驱动程序和测试工具图。 1，不同的工具可以是比较了他们的活力和符合人体工程学的效果操作者手臂系统。 目前，累积的原因之间的关系外伤性疾病和力学模型参数不很好地理解。力/力矩的相对贡献，偏转，并重复操作的发生伤还没有量化。这是一个三部分的问题。首先，它是难以量化的系统参数不断变化的姿势，工具，夹具等。二联，由于手臂障碍的累积性质，它需要几个月甚至几年的时间来检测造成的伤害。第三，它是没有可以量化的特定风险因子（次）导致人体工程学的伤害。NIOSH已出版一些研究试图进行分类的危险因素（S）。它除危险因素分为四类：高力，高重复;高动力，低重复;力低，高重复;和力低，低重复（NIOSH，1997）。然而，每一个这四类的范围没有明确的规定。如果力之间/相关性重复，将所得的伤害是待确定，当务之急是建模和分析技术用于测量和预测偏差和手工具界面部队是准确的，可重复的。该在本文中讨论的技术提供和预测之间的良好关系 测角旋转的示于表3。进行检查测试它的重复性也产生之间的强相关性预测的和测量的角旋转。这证明所开发的技术，可以有效地用于建模手臂系统。导出的模型可以用于比较不同的工具，姿势，紧固件等使用预测的角转动，作为一个度量比较。ARTICLE IN PRESS该文件中提出的建模技术可以有效地预测受冲击的响应通过用于紧固的紧固工具产生的转矩剪切型紧固件。手臂的角度旋转系统可以用来作为一个客观指标经营者的不适如在以往的研究（Kihlberg等人，1993;林克韦斯特，1993）。因此，该方法在本研究中所讨论，可用于比较不同的工具和姿势的感觉不舒服操作员通过测量产生的转矩的的工具和使用中所描述的建模技术本文件计算的角旋转手臂。在本研究中提出的实验提供了一个建模和分析技术的概念证明 可用于研究的手臂系统的动态特性。进一步的实验中，将需要进行评估的效果姿势的手臂系统模型中的参数和调查工具，紧固件的影响，操作重复次数上的模型参数。该 手偏转的预测可以用作衡量比较不同的工具和紧固件以及不同姿势为各学科群体。这将是 有帮助的工具，紧固件和工作场所设计最小化手偏转，从而降低了人体工程学涉及的风险。5结论 在本文描述的方法可以预测手臂响应于所述角旋转由于紧固件的剪切销在产生脉冲扭矩用手持式电动工具的紧固操作结束。手臂的动态响应该脉冲转矩被建模为单自由度的惯性springdamper系统。为了确定的参数值手臂模型，实验使用进行夹具式安装设计，让下将予收购数据类似条件的车间。 合规从测得的扭矩计算的光谱幅度和角旋转，以及一个非线性最小二乘曲线拟合算法被用来推断该模型参数值。模型参数的值分别从一致性试验，以试验为两个考试科目。基于为模型参数，谐振得到的值频率计算主题1为3.25赫兹和主题2为3.85赫兹。所获得的手臂系统模型为显示有预测的和之间良好的一致性测量的角度旋转在这两个验证和重复性测试。 致谢该项目支持的中心航天制造技术，它是由空气资力合同项下的研究实验室。 FA8650-04-C-5704。 作者要感谢Hoeckelman， 林恩不伦瑞克，杰弗瑞Kilwin和布赖恩多兹过程中，波音公司提出宝贵的帮助这个项目的。参考文献Armstrong, T.J., Bir, C., Foulke, J., Martin, B., Finsel, L., Sjoe Gaard,G., 1999. 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