基于经验概率的训练进程建模与仿真

训练进程的真实性直接关系到模拟训练系统的训练质量和训练水平，指出简单的随机化和程序化训练进程的不足，分析了基于经验概率的训练进程产生的过程和训练进程中事件的特点，将模拟训练系统中的操作事件赋予属性特征，建立事件属性模型。根据事件发生具有随机性和必然性的特点，运用随机方法建立了训练进程仿真模型。并应用于“74-Ⅲ挖掘机模拟训练系统”。应用效果表明，模拟训练内容和训练进程更加接近实际过程，增强了模拟训练的可信度和学习者的学习兴趣，提高模拟训练的效果。     

P＆H2300XP矿用挖掘机结构件展开图形的设计与计算

介绍了P&H2300XP矿用挖掘机结构件展开图形的设计与计算在设计中,重点考虑了结构与受力分析和焊接过程的工艺要求。如:压边余量、钢板对接及钢板的后期处理。应用展开放样的基本方法一平行线法、放射线法以及三角形法等15种常用非圆曲线和展开图形,设计出能够适用于数控火焰切割机的专用系统。可以提高板金放样的产品质量和工作效率。     

A computational intelligent fuzzy model approach for excavator cycle time simulation

The tracked hydraulic excavator is one of the most versatile and widely utilised piece of earthmoving equipment. In many instances, the ‘excavator’ represents the first choice of earthmoving plant for both construction managers and estimators, since when properly employed (i.e. with a competent operator and in an appropriate working environment), it offers high production rates at economical cost. Nonetheless, predicting machine production performance is difficult; given the typical multiple operational parameters (e.g. machine weight, machine configuration, ground conditions, operator ability) that can apply. Consequently, determination of accurate cost estimates and predicted contract durations are subject to considerable inaccuracy, especially where a significant amount of site work is needed.

To address this inadequacy, this paper presents a computational intelligent ‘fuzzy’ model with the ability to forecast excavator cycle time. In this context, a cycle is defined as one complete revolution, from ‘place empty bucket in dig material’ through ‘fill bucket’, ‘move charged bucket to target’, ‘empty charged bucket’ and ‘return bucket to dig material’. The developed model is based upon 70 separate cycle time observations obtained from four plant manufacturers. These data provide a representative spread of machine cycle times since they include a range on a continuum from optimum to adverse operational parameters. Tests on the derived model identified that its accuracy was acceptable; but the accuracy could be improved using larger samples and a more comprehensive and exhaustive range of variables to predict machine cycle time.     

混合动力挖掘机动臂势能分级回收仿真研究

针对挖掘机动臂势能浪费大的问题,提出一种混合动力挖掘机动臂势能分级回收系统,该系统采用低、中、高压蓄能器进行分级势能回收。分析系统工作原理,建立动臂油缸和蓄能器能量数学模型,运用AMESim建立液压系统和控制策略,并在典型工况下进行仿真。仿真结果表明：挖掘机动臂采用低、中、高压蓄能器进行分级势能回收是可行的,该系统节能率达到40.6%,能量回收效率保持在36.1%以上。     

基于负载口独立控制的挖掘机动臂系统节能研究

针对传统挖掘机动臂液压系统能耗大、势能利用低等问题,以挖掘机动臂为研究对象,设计基于负载口独立控制的动臂液压系统。在主动型负载工况缩回工况下,对动臂液压系统进行了压力-流量特性分析,获得阀口开度与活塞杆速度的关系;采用机械动力学仿真软件ADAMS和液压系统仿真软件AMESim,分别建立传统动臂液压系统和基于负载口独立控制的动臂液压系统联合仿真模型,并对2种动臂液压系统在主动型负载工况缩回工况进行联合仿真分析。仿真结果表明：2种动臂液压系统都能获得较为线性的活塞杆运动速度,而且与传统动臂液压系统相比,基于负载口独立控制的动臂液压系统的势能利用率明显提高,提高了约44.3%。     

某挖掘机动力总成悬置系统隔振性能优化

为提高某挖掘机动力总成悬置系统隔振性能,以悬置系统的六阶固有频率和解耦率为优化目标,以悬置静刚度为设计参数,对悬置系统固有频率和解耦率进行优化。结果表明,优化后悬置系统各阶固有频率分配更加合理,垂直方向和绕曲轴方向解耦率得到显著提高。按照悬置优化方案制作样件,装车测试得到怠速和最高转速工况下的隔振率达到85%,基本满足工程实际要求。提出的优化方法对改善工程车辆动力总成悬置系统隔振性能具有一定的参考价值。     

基于谐响应分析的液压挖掘机电动化改造中电机减震结构的动态特性研究

电动液压挖掘机工作时的高频振动主要是由电机的振动引起的。为了减缓电机引起的振动,在电机安装底架与挖掘机机架连接处安装主副圈式硬质橡胶减震垫。为了确定减震垫的厚度和直径对底架谐振频率以及谐振振幅的影响,利用SolidWorks软件对底架结构进行三维建模,并利用ANSYS Workbench软件对模型进行谐响应分析,分别研究减震垫的厚度和直径对底架振动变形情况的影响。结果表明:减震垫厚度越大,谐振振幅越大,谐振频率越小;减震垫直径越大,谐振振幅越小,谐振频率越大。在当前载荷条件下,得出减震垫适宜的厚度范围为22～26 mm,直径范围为85～90 mm。研究结果为挖掘机电动化改造中动力结构减震垫的选型提供了一定的依据。     

挖掘机工作空间求解的蒙特卡洛法改进

对常规蒙特卡洛法求解挖掘机工作空间的原理、算法流程分析与仿真,发现大量随机点的分布在空间内部,边界随机点分布少,使得求解结果误差较大且效率低下。对挖掘机工作空间边界形成的内在机理分析,发现其边界的界定本质是其中两组油缸取极限值,另一组油缸为变量,而非三组油缸变量耦合,从而使得随机点的分布集中在工作空间边界。采用改进后的蒙特卡洛法对挖掘机的工作空间进行仿真,对比常规法求解,结果证明改进蒙特卡洛法求解高效且误差极小。     

挖掘机动臂定位控制特性

为适应移动机械的智能化作业和高质量作业的发展要求,提出了一种新型的挖掘机臂架位置控制策略。根据目标位置和操作速度,设计了预期的工作轨迹。利用所提出的策略,使动臂可以沿设计轨迹移动到目标位置,并保证定位精度。建立了控制策略的试验样机,并进行了相应的试验。实验结果表明:本研究工作对提高挖掘机臂架自动化作业效率和精度具有普遍意义。     

Utilizing online learning based on echo-state networks for the control of a hydraulic excavator

In this paper, we present a control framework for the control of a hydraulic excavator. An excavator can be viewed as a robotic manipulator that interacts with the environment. It follows that the control method employed to control the excavator must take into account the complex soil–tool interaction in order to achieve the desired trajectory of the manipulator. Impedance control has been proven to be effective in this aspect in that it provides an unified approach to constrained and unconstrained motion. Another important aspect when considering the automation of an excavator is the control of the hydraulic servo system. Obtaining a useful explicit model for the control of hydraulic servo systems is not a simple task due to their inherent complex nonlinearity. Therefore, control techniques that do not require an explicit representation of the plant are required. In this work, we integrate two controllers for the automation of an excavator. To control the rigid-body motion of the excavator, impedance control and sliding mode control are applied. The results are desired cylinder forces that are required to achieve the desired trajectory. Given the desired cylinder forces, an online learning control method is employed to control the hydraulic servo system so that the desired forces are generated. Echo-state networks, which are a class of recurrent neural networks, are utilized within the online learning control framework in order to learn an inverse model of the hydraulic servo system. Thus, the online learning control framework does not require an explicit model of the plant and also adapts to the plant using only the input and output signals. We present results of the proposed control framework on an excavator simulation environment that has been verified based on operation data from a real hydraulic excavator.