基于SA-EMD-PNN的柱塞泵故障诊断方法研究

A fault diagnosis method of a plunger pump based on SA-EMD-PNN

为了提高柱塞式液压泵的故障诊断效率和准确性,提出了SA-EMD-PNN柱塞泵故障诊断方法。提取各种状态下振动信号的特征参数,并对所提取特征参数进行敏感度分析(SA),找出敏感度较高的特征参数;对原始故障信号进行经验模态分解(EMD)结合,构造新的故障信号,再提取敏感度高的特征参数;将所提取特征参数以向量的形式输入概率神经网络(PNN)进行训练和测试。实验表明,SA-PNN方法能快速、有效的诊断出柱塞泵故障,减少诊断时间;而SA-EMD-PNN能在SA-PNN的基础上提高正确率。

In this paper, a plunger pump fault diagnosis method based on SA-EMD-PNN was proposed to improve the speed and accuracy of plunger pump fault diagnosis. First, feature parameters were extracted under a various states, and the sensitivity of the feature parameters was analyzed. Then, EMD was used to break down the original signal and reconstruct new signal. Feature parameters were extracted with higher sensitivity from the new fault signal. Finally, vectors with feature parameters that have the higher sensitivity were constituted. The vectors were used to train PNN. The trained PNN was used to diagnose the fault of a plunger pump. Experiment showed that SA-PNN can quickly and accurately diagnose the fault of the plunger pump. And compared to SA-PNN,the SA-EMD-PNN can has higher diagnosis accuracy.