拖拉机液压机械无级变速箱换段过程液压故障诊断  

Hydraulic failure diagnosis of tractor hydro-mechanical continuously variable transmission in shifting process

作　　者：王光明[1] 张晓辉[1] 朱思洪[2] 张海军[2] 史立新[2] 钟成义[2,3] 

机构地区：[1]山东农业大学机械与电子工程学院,泰安271018 [2]南京农业大学工学院,南京210031 [3]农业部南京农业机械化研究所,南京210014

出　　处：《农业工程学报》2015年第6期25-34,共10页Transactions of the Chinese Society of Agricultural Engineering

基　　金：农业部948计划资助项目(2010-Z18);江苏省科技支撑计划资助项目(BE2014134);江苏省产学研联合创新资金资助项目(BY2014128-04);山东农业大学博士后科研经费(76463)

摘　　要：为了提高拖拉机液压机械无级变速箱换段品质的稳定性和换段系统的工作可靠性,提出一种针对其离合器液压系统的故障诊断方法。该文基于南京农业大学自主研发的液压机械无级变速箱,通过试验获得正常及4种典型故障模式下换段过程的60组压力、流量数据。基于Fisher准则与核方法,对处理后的样本进行学习,并基于粗糙集理论与特征向量法,分别对样本的属性集及训练样本集进行精简。通过随机选取训练样本集与测试样本集并进行多次分类取平均的方法对算法的鲁棒性进行了测试。结果表明,针对全部60组试验样本,所使用算法可实现正常及4种故障模式的正确分类,且在随机样本测试中,正常及4种典型故障模式下的算法平均识别率分别为99.67%、100%、99%、98%、99%,具有较高的鲁棒性。该研究对提高液压机械无级变速箱的自动化水平及推动其在国产拖拉机中的应用提供了参考。Unlike conventional mechanical transmission with manual shift, the hydro-mechanical CVT（continuously variable transmission） shifts from one range to another automatically under the control of hydraulic system, however, some faults of this hydraulic system can affect the establishment of clutch engagement pressure and affect the shift quality further. In order to improve the reliability of the hydro-mechanical CVT in shifting process and avoid safety accident, the problem of fault diagnosis on this hydraulic system was studied in this paper. First, a measurement and control system for the hydro-mechanical CVT was built, including the transmission, clutch hydraulic control system, sensors, transmission control unit and IPC（industrial personal computer）. Software developed under Labview can build the communication between the IPC and the sensors, and record the feedback data from sensors to the table file with a frequency of 62.5 Hz. Then, 5 fault modes were defined in this paper, i.e. normal state, piston seizure, seal ring damage, oil passages clog and pipeline sealing failure. Through experiments, 60 groups of feedback data from pressure gauges and flowmeter with different fault modes were acquired. Thirty groups of the testing data were selected as training samples and the other 30 groups were selected as testing samples. For each sample, 6 kinds of statistic features such as root mean square value of sample data in a second were calculated. Because any combination of the 6 statistic features could not classify the fault sample directly in a low-dimensional space, it was necessary to map the sample to a higher dimensional space and to find the hyperplane of demarcation. So, a projection vector was calculated using the method of kernel based on the rule of Fisher. According to this projection vector, the sample data which was difficult to classify in original space could be transferred to feature space, in which the sample data could be classified with a simple linear function. After the kernel calculatio

关 键 词：农业机械 拖拉机 故障诊断 无级变速 粗糙集 核方法 

分 类 号：S219.032.1[农业科学—农业机械化工程]