The measurement of proprioceptive accuracy:A systematic literature review

Background:Proprioceptive accuracy refers to the individual’s ability to perceive proprioceptive information,that is,the information referring to the actual state of the locomotor system,which originates from mechanoreceptors located in various parts of the locomotor system and from tactile receptors located in the skin.Proprioceptive accuracy appears to be an important aspect in the evaluation of sensorimotor functioning;however,no widely accepted standard assessment exists.In this systematic review,our goal was to identify and categorize different methods that are used to assess different aspects of proprioceptive accuracy.Methods:A literature search was conducted in 5 different databases(PubMed,SPORTDiscus,PsycINFO,ScienceDirect,and SpringerLink).Results:Overall,1139 scientific papers reporting 1346 methods were included in this review.The methods assess 8 different aspects of proprioception:(a)the perception of joint position,(b)movement and movement extent,(c)trajectory,(d)velocity,and the sense of(e)force,(f)muscle tension,(g)weight,and(h)size.They apply various paradigms of psychophysics(i.e.,the method of adjustment,constant stimuli,and limits).Conclusion:As the outcomes of different tasks with respect to various body parts show no associations(i.e.,proprioceptive accuracy is characterized by site-specificity and method-specificity),the appropriate measurement method for the task needs to be chosen based on theoretical considerations and/or ecological validity.

Tank Fire Control Systems Accuracy Assignment Based on Fuzzy Comprehensive Judgment Method

A method of accuracy assignment based on fuzzy comprehensive judgment method (FCJM) in tank fire control system is proposed. From the flowing route of the error sources and their respective correlative signals, the transfer functions of several sources are analysed by means of mathematic simulation, and FCJM is applied to obtain the cost comprehensive factor for each part of system, combining its error sensitivity factor the mathematical model is built to solve the accuracy assignment problem. Simulation result shows the proposed method can help designer of tank fire control system work out an optimal system more efficiently and more economically.

The Electrical and Mechanical Alignment and Accuracy Detection of Numerial Control Machine Tool

In the work of numerical control reformation of general machine tool, the installation and debugging of machine tool is a crucial part. For the C6132 machine tool, and make the use of electrical and mechanical alignment, parameter adjusting, numerical control lathe accuracy debugging and performance examination has been used to finish a series of tailing in the work of numerical control reformation of general machine tool. In this paper, the detailed process of electrical and mechanical alignment, parameter adjusting, numerical control lathe accuracy debugging and performance examination has been demonstrated, meanwhile, the specific operational approach of these work programs has been discussed. Therefore, the present results provides essential reference and approach for the numerical control reformation of general machine tool.

Accuracy Assignment Study of Tank Fire Control System Based on Value Analysis Method

A method of accuracy assignment based on value analysis method （VAM） in tank fire control system （TFCS） is proposed. From the analysis of primary error sources and their error transfer relationships, the mathematical model is built on the basis of VAM to solve the accuracy assignment problem. Simulation results show the validation and feasibility of the proposed method. It can help designer of tank fire control system work out an optimal system more efficiently and more economically.

Development Trend of NC Machining Accuracy Control Technology for Aeronautical Structural Parts

High-performance five-axis computer numerical control machine tools are widely used in the processing of Aeronautical Structural parts. With the increase of service life, the precision of CNC machine tools equipped by aeronautical manufacturing enterprises is declining day by day, while the new generation of aircraft structural parts are developing towards integration, large-scale, complexity, thin-walled and lightweight. It is very easy to produce dimension overshoot and surface quality defects due to unstable processing technology. The machining accuracy of aircraft structural parts is also affected by complex factors such as cutting load, cutting stability, tool error, workpiece deformation, fixture deformation, etc. Because of the complexity of structure and characteristics of Aeronautical Structural parts, the consistency and stability of cutting process are poor. It is easy to cause machining accuracy problems due to tool wear, breakage and cutting chatter. Relevant scholars have carried out a lot of basic research on NC machining accuracy control and achieved fruitful results, but the research on NC machining accuracy control of Aeronautical structural parts is still less. This paper elaborates from three aspects: error modeling method of NC machine tools, error compensation method, prediction and control of machining accuracy, and combines the characteristics of Aeronautical Structural parts, the development trend and demand of NC machining accuracy control technology are put forward.

On-orbit Geometric Calibration and Preliminary Accuracy Evaluation of GF-14 Satellite

GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Points(GCPs).In fact,space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links,of which on-orbit geometric calibration is one of the most critical links.In this paper,the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field,and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection.On this basis,the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world.The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters(RMS)in plane and 1.97 meters(RMS)in elevation.

基于计算机视觉的采摘机器人作业优化研究

为进一步提高我国采摘机器人智能化作业水平及采摘效率,基于计算机视觉应用技术展开优化研究。以采摘机器人结构组成为设计基点,运用视觉控制核心理念建立采摘机器人视觉识别处理与控制数学模型,实施相适应的采摘路径规划和系统采摘状态输出设计。同时,进行视觉采摘验证试验,结果表明:基于计算机视觉的采摘机器人系统优化正确可行,整机综合采摘效率可达94.61%,系统识别准确率与控制精度分别相对提升了6.12%和5.25%,机器人采摘成功率可提升至95.98%。因此,将计算机视觉处理技术有效应用至采摘机器人设计改进,对于类似农业采摘与收获装备开发研究可提供创新及借鉴思路,推广价值良好。

一种电学控制特性下的变量施肥装置研究

以单片机为基础,设计一种电学控制的变量施肥控制系统装置。工作时,通过系统通信总线接收上位机指令信息和地理环境数据,单片机生成实时指令,对变量施肥装置电液比例系统执行机构进行控制,并对农田中不同位置进行变量施肥控制。系统试验表明:装置进行变量施肥过程中,能够对施肥量进行精准可靠控制,施肥作业过程具有较高的可靠性,施肥控制精度误差小于4%。

挖掘机液压混合动力系统跟踪控制研究

由于挖掘机混合动力系统参数的不确定性和系统的非线性给挖掘机的跟踪控制带来了巨大的困难。对此,构建了挖掘机液压混合动力系统模型,并采用改进的自适应鲁棒控制(ARC)实现挖掘机液压混合动力系统的跟踪控制。根据挖掘机液压混合动力系统,对液压系统、挖掘机动力学和发动机进行数学建模。利用线性稳定反馈控制规律,采用改进的自适应鲁棒控制,使挖掘机液压混合动力系统具有足够大的反馈增益。最后对斗杆、动臂和铲斗的倾角进行跟踪仿真实验,给出了系统模型位置和速度的跟踪误差,并与PI控制进行比较分析。结果表明:相比于PI控制,ARC控制下的斗杆、动臂和铲斗倾角的最大振幅波动率和倾角的波动范围都有所降低,且回转位置和速度的跟踪误差超调较小。说明采用ARC控制的挖掘机混合动力系统控制方法,能够更好的补偿系统模型的非线性,具有较好的控制稳定性以及跟踪精度。

虚拟现实技术在智能插秧机中的应用

为进一步提升我国智能插秧机的作业效率与插植准确度,基于虚拟现实技术理念针对其结构设计及作业控制展开研究。在充分理解智能插秧机的结构组成与作业要求实现的基础上,运用VR控制理念,建立VR可视化设计模型平台,融入北斗定位及VR矩阵元素等核心技术,形成完整的智能插秧机作业系统,并展开有效性的插秧作业试验。试验结果表明:将虚拟现实技术应用于智能插秧机,实现了插秧作业性能的整体提升,在VR可视化的监测与调偏功能运用下,控制准确率相对提高了8.83%,合格率相对提高了6.76%,秧苗利用率亦得到明显提升,对于插秧装备的无人化和智能化及多范围、多地区推广起到了积极作用,可为类似农机装备的优化创新提供很好的思路与方向。

智能车横向跟踪控制模式切换策略及评价方法

针对智能车横向跟踪控制算法传统切换策略中模型匹配策略总是处于激活状态,占用计算资源和运动平顺性变差的问题,设计了一种基于最小二乘支持向量机(least squares support vector machine,LSSVM)的控制模式切换策略,在不同工况下根据误差判断策略切换控制模式.从安全性、舒适性和跟踪精度3个方面构建控制效果评估函数,并根据多目标优化数学模型实时执行系统最优控制量.仿真试验结果表明:该切换策略能够保证智能车在不同工况下具有优秀的横向跟踪性能,路径跟踪偏差范围为±0.1 m,横摆角速度波动范围为±2(°)/s,jerk值的范围为±10 m/s^(3),与传统的单一控制算法相比,具有更好的跟踪精度、稳定性和舒适性.

水下控制模块安装工具结构设计与对接精度分析

水下控制模块是水下生产系统的关键部件,针对水下控制模块在水下如何精准、高效、安全地实现回收和再安装工作的问题,本文设计了一种水下控制模块安装工具。对此安装工具进行了机械结构的设计,将安装工具各部分结构在工作过程中的作用进行了介绍。针对安装工具能够顺利完成水下控制模块的安装,基于安装工具各部分结构对接精度关系分析,通过数学建模与仿真分析,得到影响水下控制模块安装精度的原因,设计合理的安装精度参数。将仿真分析得到的数据与设计参数相比较,可证明水下控制模块的结构设计能满足水下控制模块的对接定位精度要求。结果表明:各精度参数满足水下控制模块安装工具设计要求,在此设计参数下安装工具能够完成水下控制模块的精确安装。

基于数学模型的造纸机水针移动控制系统优化研究

为有效应对造纸机水针移动惯性所造成的定位偏差,确保水针精准且快速移动,以拟合优化方法构建了造纸机水针移动控制数学模型。采取变速双控制中性区方法,以反复测试寻找控制中性区数值的合理范围,并针对性建立水针移动与中性区数值的数学模型,以求解控制中性区数值。实际应用验证结果表明,变速双控制中性区方法的引进使造纸机水针移动曲线变化趋向于平缓,且终止位置与设定位置误差控制于0.79%,精确度非常高;相比传统变速单控制中性区方法,水针移动响应时间缩短了25s。

基于KNN神经网络的无人机作业操控系统研究

为进一步提升我国农业植保无人机的精准作业效率,针对其操控系统展开优化研究。选定KNN神经网络算法为执行理念,以无人机作业控制原理为基础,搭建正确的过程参数动态计算模型,进行操控系统的算法实现与调控配置,并展开基于KNN神经网络的无人机喷施作业试验。试验结果表明:KNN神经网络算法下的无人机操控系统运行稳定,过程参数的分类准确率相对提高了8.00%,目标喷施流量与试验喷施流量的偏差率相对降低了5.71%,农药喷施均匀度可提升至94.75%,整机作业综合效率明显提升。此设计理念以计算机智能数据处理为出发点,对无人机的高效率全面发挥有一定的推动作用,可用于类似智能农机装备的控制系统改进与开发,具有一定的参考价值。

基于多源异构信息融合的采摘机械臂驱动控制研究

[目的]为了准确感知采摘机械臂的作业信息,提高驱动控制精度,需要对多自由度采摘机械臂的驱动控制模块进行优化设计。[方法]本研究将采摘机械臂各关节自由度、运动学以及动力学原理融合到设备结构中,完成了多自由度采摘机械臂等效模型的构建。基于构建的等效模型,确定多源传感器设备的安装位置,利用内部安装的传感器设备对机械臂的实时运行信息进行采集,获取位姿信息。同时,根据传感器的空间位置及其相互之间的作用进行信息分群,得出信息级融合结果,以此作为特征级信息融合结果的输入值,提取多源异构信息特征,并通过特征匹配完成融合操作,由此得出任意时刻采摘机械臂运行参数的检测结果。[结果]结合给定的采摘任务,计算采摘机械臂所需的驱动动力以及位姿数据,通过与当前数据的比对确定驱动控制量,利用装设的驱动控制器生成可执行的控制指令,完成驱动控制。与2种对照方法进行的对比试验显示,基于多源异构信息融合的驱动控制方法采摘机械臂的位置控制误差降低约25 mm,姿态角与驱动力控制误差分别降低了0.22°和6.32 mm,得出的控制数据更精准。[结论]由于多源异构信息融合技术能够发挥多种数据的优势,获取到更全面、更准确的位姿信息和控制数据,能够实现对目标果实的精准采摘,从而降低了采摘工作对果实的伤害,具有明显的对比优势和应用价值。

基于反步法的下肢外骨骼机器人控制研究

针对下肢外骨骼预定轨迹的控制问题,在构建了二自由度机械腿的运动学和动力学模型的基础上,提出了一种非对称液压缸负载力、伸缩量与外骨骼转动扭矩、运动角度的转化关系,采用反步法控制下肢外骨骼系统的运动轨迹。首先,采用D-H法建立了二自由度下肢外骨骼系统的运动学模型,研究了外骨骼末端执行器关节速度的变化关系,并利用拉格朗日动力学方程推导了外骨骼动力学的数学模型;然后,使用了液压缸负载力控制为机械腿运动提供了相应的扭矩,进而控制了下肢外骨骼的运动姿态;其次,针对下肢外骨骼运动时的高精度要求,利用反步法控制理论,建立了阀控非对称缸系统,结合下肢外骨骼动力学系统整体的状态空间方程,利用下肢外骨骼液压伺服系统控制了下肢外骨骼进行预定轨迹运动;最后,对AMESim软件与Visual Studio软件进行了联合仿真,对比分析了PID控制与反步法控制的精度问题。研究结果表明:针对下肢外骨骼预定轨迹控制,反步法控制误差最大值为2°,对比传统PID控制,误差降低了67%;设计的反步法控制器对于下肢外骨骼具有良好的控制精度。

基于Pix4Dmapper软件的大疆Phantom4 RTK正射影像图精度分析

针对无人机正射影像图精度分析,提出一种基于Pix4Dmapper软件的大疆Phantom4 RTK正射影像图精度分析方法。该方法以大疆精灵4 RTK为例,利用Pix4Dmapper软件对其飞行的照片数据进行解算,针对同一作业区域比较了3D倾斜摄影飞行模式和2D正射飞行模式所产生的正射影像在平面精度和高程精度上的差异;分析了低空飞行模式下,采用像控点参与解算对成果精度的影响。实验结果表明,Phantom4 RTK在低空2D正射影像飞行模式下可以达到免像控生产正射影像图和地形图的要求,为无人机正射影像图精度分析提供了一种新思路。

薄壁零件数控加工质量的提升策略

薄壁零件在机械制造中的应用越来越广泛,但其加工难度较大。提升薄壁零件的数控加工精度,可以改善零件质量,提高生产率,降低费用,进而推动先进设备制造业的发展。文章分析影响薄壁零件数控加工质量的因素,包括加工工艺、外部荷载、温度系数及刀具等,并提出提高加工质量的措施,如合理选用刀具、选择合理的切削用量和技术方案、保证尺寸的精度以及适当延长切削时间等。

马铃薯智能清选控制系统设计与试验

针对北方寒地黏重土壤种植区马铃薯机械化收获后存在大量土块导致马铃薯清选困难等问题,研发了以机器视觉技术为基础的马铃薯智能清选控制系统,由图像采集、伺服电机、主控计算机、步进电机和伺服控制器等模块组成。同时,建立了清选控制系统模型,设计了清选装置,并进行控制系统试验研究。通过单因素试验分析伺服电机转速与识别模型的准确度之间的关系,得出最优的伺服电机转速。结果表明:当伺服电机转速为500r/min时,马铃薯清选的平均准确率为96.83%。同时,控制系统满足马铃薯清选需求,实现了马铃薯的智能清选,可为马铃薯田间清选装置的后续研发提供参考。

基于GA改进ANN算法的车载网控系统故障诊断

车载网控系统是保证运行安全的一类重要控制设备,也是确保系统稳定运行的核心部件。为了提高车载网控系统故障诊断效率,通过遗传算法(GA)具有的全局寻优功能来实现对神经网络初始阈值与权值的优化,把寻优结果代到神经网络内完成训练过程;使ANN泛化方法具有的映射性能获得充分利用可以防止产生局部极小值情况,获得更高的分类精度;利用实例分析方式测试车载故障诊断过程的有效性。研究结果表明:采用GA改进ANN算法可以有效优化平均误差及数据正确率,有效降低迭代次数,表明可以通过GA改进ANN方法来提升神经网络运算性能。经过遗传算法优化处理的ANN在训练过程中可以获得比初始ANN更快时收敛速率。