【摘要】 本文通过研究声发射产生机理，探索了一种基于声发射参数分析的滑动轴承故障诊断方法。首先，我们使用实验台模拟了滑动轴承的三种润滑状态，并使用声发射技术获取不同润滑状态下的数据。接着，我们对所采集到的声发射信号进行了能量均值和功率谱熵均值的计算，并提出了一种基于散度指标的滑动轴承润滑状态诊断方法。本研究采用了多参数结合的指标诊断，将该方法与单一能量参数分析法进行对比，发现单一能量参数分析法不能很好地反映出滑动轴承的润滑状态，而采用多参数结合的指标诊断方法在信号适应性和区分度方面表现更佳。因此，本研究结果为滑动轴承故障诊断提供了一种有效的方法。更多还原

【Abstract】 This article explores a fault diagnosis method for sliding bearings based on acoustic emission parameter analysis by studying the mechanism of acoustic emission generation. Firstly, three lubrication states of sliding bearings were simulated on an experimental platform, and data under different lubrication states were obtained using acoustic emission technology. Subsequently, the energy mean and power spectral entropy mean of the collected acoustic emission signals were calculated, and a method for diagnosing the lubrication status of sliding bearings based on divergence index was proposed. This study used a combination of multiple parameters for indicator diagnosis, and compared this method with the single energy parameter analysis method. It was found that the single energy parameter analysis method cannot reflect the lubrication status of sliding bearings well, while the indicator diagnosis method combining multiple parameters performs better in signal adaptability and discrimination. The research results of this article provide an effective method for fault diagnosis of sliding bearings.更多还原