基于声发射技术的铁路重载货车滚动轴承故障诊断研究

Research on Fault of Railway Rolling Bearing Based on Acoustic Emission Technique

通过声发射检测技术对铁路重载货车滚动轴承故障进行不解体诊断,利用小波包分析技术对采集到的声发射信号进行分解和重构,提取故障信号的能量特征向量,将处理后的特征向量输入到BP神经网络进行滚动轴承故障模式识别,进而判断轴承是否发生故障以及故障的类型。经过使用大量的实际滚动轴承实验数据进行验证,其结果都表明了使用本文的方法的有效性。

With the aid of acoustic emission detection technology, fault diagnosis of rolling bearing of heavy trucks on the railway is performed without disassembly, acoustic emission signals collected by using wavelet packet analysis technology decompased and reconstructed, energy feature vectors of fault signal extracted, the processed feature vectors input into BP neural network for the rolling bearing fault pattern recognition, and thus, all these may determine whether the bearing is faulty and which type the fault belongs to. Through the validation with a large number of actual experimental data of rolling bear- ing, the results show that the use of the proposed method is effective.