基于小波包样本熵和SVM的水泵机组振动故障诊断

Vibration Analysis and Fault Diagnosis of Water Pump Unit Based on Wavelet Packet Sample Entropy and SVM

用小波包样本熵提取出水泵机组各个振动状态下的样本熵值作为支持向量机(SVM)的特征向量,然后用特定的SVM分类器进行分类训练,在此基础上对机组振动故障进行识别,为验证本方法的准确度,通过立式水泵机组实验平台进行大量的实验并对其做出了定量定性分析,实验结果表明这种基于小波包样本熵和SVM水泵机组振动故障诊断方法具有较高的可信度。

Wavelet packet sample entropy is used to extract the pump units in every vibration state of sample entropy value as the feature vectors of support vector machine （ SVM）, and then the SVM classifier is used to classify. Then on this basis, the fault diagnosis of the unit vibration is carried out. In order to verify the effect of this method in practical production, a lot of experiments were done on the experiment platform of vertical pump units. The experimental results show that the pump unit vibration fault diagnosis method has high reliability.