| Mechanical and Electrical Engineering |
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| Faults diagnosis and classification based on fault-tolerant theory for continuously variable transmission |
| HAN Ling, LU Yan hui, AN Ying, TIAN Li yuan |
1. School of Mechatronic Engineering, Changchun University of Technology, Changchun 130021, China;
2. College of Automotive Engineering, Jilin University, Changchun 130022, China;
3. College of Automotive Engineering, Hunan University, Changsha 410000, China |
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Abstract The fault vectors were extracted by feature extraction of continuously variable transmission (CVT) based on the improved artificial colony algorithm combining with least squares support vector machine in order to fulfill the requirements about on-line fault diagnosis and classification of CVT. The fault predicting models of clamping force and ratio were established. The faults location and identification classification were based on predicting models. Parts of fault feature vectors for second cylinder pressure, ratio, and actuator were extracted to simulation by Matlab. The classification of feature vectors after the fault-tolerant controlled was analyzed by simulation curve change trend. CVT was built hardware-in-the-loop simulation by fault-tolerant with Matlab/Simulink. Results showed that the probability of continue working reached 98.728% by using the method for fault-CVT, and the needs of CVT reliability and stability for the online fault diagnosis were meeted.
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Published: 28 October 2016
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基于容错理论无级变速器故障诊断分类
为了实现无级变速器(CVT)在线故障诊断及分类需求,基于改进人工蜂群算法结合最小二乘向量机,提取无级变速器故障特征向量,建立夹紧力与速比故障预测模型,按照预测模型进行故障定位、分类辨识.针对从动油缸压力、速比、执行机构等故障的特征向量进行Matlab仿真,分析经容错控制分类后的故障特征向量仿真曲线变化趋势.通过容错控制在Matlab/Simulink中建立无级变速器硬件在环仿真动态模型.结果说明,采用该方法,无级变速器故障诊断经容错可继续工作概率达98.728%,满足无级变速器在线故障诊断可靠性及稳定性的需求.
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