基于声发射信号特征提取技术的滑动轴承故障诊断

Sliding Bearing Fault Diagnosis Based on Acoustic Emission Signal Feature Extraction Technology

滑动轴承是汽轮机中的一个重要支撑部件,保持滑动轴承的正常工作,能减少设备工作损失以及维修的成本,因此,对滑动轴承进行实时监测以及故障诊断是有必要的。声发射技术作为一项动态无损检测方法,对信号反应更敏感,可以对设备进行持续监测,很适合用来对设备进行实时监测以及故障诊断。从声发射信号的产生机理出发,通过分析证明了声发射信号能量变化可以表示出轴承的摩擦状态,然后构筑了3个新的特征参数,来对声发射信号进行分析,并通过试验证明了其可以反应出当时的摩擦状态,而且比传统的特征参数要更加灵敏。

Sliding bearings are an important supporting component in steam turbines.Maintaining the normal operation of sliding bearings can reduce equipment loss and maintenance costs.Therefore,real-time monitoring and fault diagnosis of sliding bearings are necessary.As a dynamic non-destructive testing method,acoustic emission technology is more sensitive to signal response and can continuously monitor equipment,making it suitable for real-time monitoring and fault diagnosis of equipment.This article starts from the generation mechanism of acoustic emission signals and proves through analysis that the energy change of acoustic emission signals can represent the friction state of bearings.Then,three new feature parameters are constructed to analyze the acoustic emission signals,and experiments have shown that they can reflect the friction state at that time and are more sensitive than traditional feature parameters.