基于超限学习机的轴向柱塞泵滑靴磨损故障诊断

Fault Diagnosis of Sliding Shoe Wear of Axial Piston Pump Based on ELM

为了提高故障诊断的分类准确度并减少分类时间,运用一种新的分类器即超限学习机(ELM)对轴向柱塞泵滑靴磨损进行故障诊断与识别。采集轴向柱塞泵正常工作状态和不同滑靴磨损工作状态下的信号;对采集到的信号进行预处理,提取出8维的特征向量;运用ELM和其他分类器分别对其进行诊断与识别。对比试验结果表明,新的方法故障诊断准确度高且诊断速度快。

In order to improve the classification accuracy of fault diagnosis and reduce the classification time,a new classifier,namely ELM(Extreme Learning Machine)was proposed to diagnose and identify sliding shoe wear of the axial piston pump.Signals of the axial piston pump of the normal working state and the different sliding shoe wear were collected.The signal was preprocessed and a 8-dimensional feature vector was extracted.ELM and others were used to diagnose and identify the sliding shoe wear of axial piston pump.The results show that ELM has higher accuracy and diagnosis speed.