基于噪声小波包络谱的主轴承磨损故障诊断

来源期刊：中南大学学报(自然科学版)2003年第4期

论文作者：吕琛 王桂增 叶昊 黄晓中

文章页码：459 - 462

关键词：故障诊断;噪声;小波分析;包络谱;磨损;主轴承

Key words：fault diagnosis; noise; wavelet analysis; envelope spectrum; abrasion; main bearing

摘    要：传统的基于振动信号的内燃机主轴承磨损故障诊断中安装传感器以及提取故障特征频率很繁琐,为此,提出了基于噪声和正交小波监测往复式活塞发动机滑动主轴承磨损故障的一种新方法.利用Symlets小波分析将测得的机体噪声信号变换到时频域,得到含有内燃机主轴承间隙磨损状态的时频信息.主轴承磨损故障会使机体噪声信号的高频成分增加,而且高频滤波成分特征与内燃机的冲击过程相对应,所以,需选择合适的高频带加以提取并进行包络谱分析.通过声级计测取了代表主轴承4类间隙磨损程度的噪声信号,发现2个特征频率处的能量对间隙磨损状态比较敏感,均随着磨损量的增加而增加.通过该方法,可利用机体噪声信号监测主轴承的磨损状态.

Abstract: In order to avoid the difficulty of installing vibration sensors and extracting characteristic frequency vectors on the traditional vibration-based abrasion faults diagnosis of main bearing of ICE (Internal Combustion Engine), this paper presents an approach of monitoring the abrasion fault of main bearing with noise signal and orthogonal wavelet transform. Symlets wavelet analysis is used to transform the noise signal of ICE into timefrequency domain that includes the time-frequency information of gap abrasion condition of main bearing. The abrasion fault of main bearing can result in the characteristic change of high frequency band, which is also corresponding to the shock process of ICE. Consequently, it is necessary to select appropriate high frequency band to extract and make its envelope spectrum. The noise signal samples, which represent the extent of abrasion under four gap conditions of main bearing, were detected during the process of test. As a result, the energy values of two characteristic frequencies are found to be very sensitive to gap abrasion conditions of main bearing, and increase along with the increment of gap abrasion. The aim of monitoring gap abrasion conditions of main bearing can be realized by this approach. The result shows that it is feasible and effective.