基于冲击信号的滑动轴承摩擦故障监测方法

针对滑动轴承声发射（AE）信号干扰严重、故障信号难分离、轴承摩擦故障监测难的问题,从不同信号的激励源作用形式出发,根据冲击信号的工作脉冲特征,建立了分离相对容易的干扰信号与轴承摩擦故障的联系,提出一种基于干扰信号监测滑动轴承故障的方法。首先,依靠K均值奇异值分解（K SVD）字典对冲击特征的捕捉能力,确定冲击脉冲产生的时刻；为了锐化和增强冲击信号,通过Hilbert包络解调出冲击包络信号。其次,引入钟形脉冲参数,通过钟形脉冲拟合单个冲击包络信号,并进一步推导出冲击包络信号的强度简化计算公式,用于滑动轴承接触摩擦故障识别。最后通过实验模拟了滑动轴承切断供油后的轴瓦摩擦过程,与AE传统特征相比,所提特征更容易识别轴承的早期摩擦故障,能够完整描述轴承的摩擦的全过程,且计算效率更高,为滑动轴承接触摩擦故障诊断提供了一种新的途径。 

Friction fault detection methods based on impact signal for plain bearing

Aiming at the problem of plain bearing acoustic emission (AE) signal interference seriously, fault signal separation difficulty, friction fault monitoring difficulty, based on the pulse characteristic of impact signal, a method based on shock signals to monitor plain bearing faults was proposed, which established the relation between impulse signal and bearing friction fault. Firstly, the K means singlular value decomposition (K SVD) dictionary was used to capture impact characteristics, and the time of impact pulse generation was determined. In order to sharpen and enhance impact signal, the impact envelope signal was demodulated by the Hilbert envelope. Secondly, the bell pulse parameter was introduced to fit the single impact envelope signal, and the simplified formula of the strength of the impact envelope signal was further deduced, which was applied to the contact friction fault identification of the plain bearing. Finally, the friction fault of plain bearing was simulated by cutting off oil supply channels. Comparing with the traditional characteristics of AE, the proposed algorithm were easier to identify early friction fault and higher computational efficiency and can completly describe bearing friction process. So, the proposed algorithm provides a new way for the plain bearing contact friction fault diagnosis.