基于QH-ITD和AMCKD的滚动轴承故障诊断研究

Research on fault diagnosis of rolling bearing based on QH-ITD and AMCKD

由于滚动轴承早期微弱故障易受噪声影响导致难以对故障进行诊断。针对原固有时间尺度(ITD)和三次样条插值改进ITD算法的不足以及最大相关峭度解卷积(MCKD)算法的滤波器长度参数选取困难的问题,提出基于四次Hermite插值改进的ITD(QH-ITD)算法和利用变步长网络搜索参数寻优改进MCKD(AMCKD)算法。该方法首先利用QH-ITD算法对原滚动轴承故障信号进行分解运算,然后利用峭度指标和互相关系数筛选相应的分量信号进行重构,再利用AMCKD算法中对重构信号进行降噪处理,最后利用Teager-Kaiser能量算子进行解调处理,提取出故障特征信息并判断故障类型。通过人工模拟的滚动轴承损伤故障诊断实验和全寿命周期的轴承早期微弱故障诊断实验,验证了所提方法可以有效地对滚动轴承的早期微弱故障进行诊断识别。

It is difficult to diagnose the early weak fault of rolling bearing because it is easily affected by noise.In view of the shortcomings of the original ITD and cubic spline interpolation improved ITD algorithm and the difficulty in selecting the filter length parameters of the maximum correlation kurtosis decomposition(MCKD)algorithm,an improved ITD(QH-ITD)algorithm based on the quartic Hermite interpolation and an improved MCKD(AMCKD)algorithm based on variable step length search parameters optimization are proposed.Firstly,QH-ITD algorithm is used to decompose the fault signal of the original rolling bearing,then the kurtosis index and the correlation number are used to screen the corresponding component signals for reconstruction,then the AMCKD algorithm is used to reduce the noise of the reconstructed signal,finally,the Teager-Kaiser energy operator is used for demodulation,the fault characteristic information is extracted and the fault type is determined.It is verified that the proposed method can effectively diagnose and identify the early weak fault of the rolling bearing by simulating the damage fault diagnosis experiment and the early weak fault diagnosis experiment of the bearing with the whole life cycle.