基于局域均值分解的行星齿轮箱故障诊断方法

Fault diagnosis of planetary gearbox based on local mean decomposition

在低转速工况下,容易出现行星齿轮箱故障的微弱信号和强信号难以分离的情况,导致行星齿轮箱存在微弱故障诊断精度较差的问题,为此,提出了一种基于局域均值分解(LMD)的行星齿轮箱故障诊断方法。首先,采用DASP数据采集系统,采集了行星齿轮箱不同工况下的振动信号,采用平移不变量小波降噪方法,对其振动信号进行了降噪处理;然后,采用局域均值分解方法分解了其振动信号,分别采用了能量算子和循环频率对其进行了解调处理,获取了微弱故障信号分量所对应的幅值和相位调制信息,准确提取了行星齿轮箱的微弱故障信号特征;最后,采用最小二乘支持向量机(LSSVM)识别了齿轮箱不同故障特征,判断了行星齿轮箱的运行状态,实现了行星齿轮箱的故障诊断。研究结果表明:采用基于LMD的方法,可以对行星齿轮箱的微弱异常信号及强异常信号进行准确诊断,获得满意的行星齿轮箱故障诊断结果,有效保障行星齿轮箱的安全、稳定运转。

To solve the problem that weak signal and strong signal of planetary gearbox fault were difficult to be separated at low speed,which led to poor diagnosis accuracy of planetary gearbox weak fault,a planetary gearbox fault diagnosis method based on local mean decomposition(LMD)was proposed.Firstly,data acquisition&signal processing(DASP)data acquisition system was used to collect vibration signals of planetary gearbox under different working conditions,and the vibration signals were denoised by translation invariant wavelet denoising method.Then the vibration signal was decomposed according to the local mean decomposition method,and the energy operator and cycle frequency were respectively used to demodulate the vibration signal.The amplitude and phase modulation information corresponding to the weak fault signal components were obtained,and the characteristics of the weak fault signal of the planetary gearbox were accurately extracted.Finally,least square support vector machine(LSSVM)was used to identify different fault features,judge the running state of planetary gearbox,and realize the fault diagnosis of planetary gearbox.The research results show that the proposed method can accurately diagnose the weak abnormal signals and strong abnormal signals of planetary gearboxes,and obtain satisfactory fault diagnosis results of planetary gearboxes.It can effectively ensure the safe and stable operation of planetary gearboxes when applied in practical production.