互补总体经验模态分解方法在回转窑故障检测中的应用

Research on Complementary Ensemble Empirical Mode Decomposition in Fault Diagnosis of Rotary Kiln

针对经验模态分解(EMD)方法和集合经验模态分解(EEMD)方法的不足,提出了一种基于互补总体经验模态分解(CEEMD)的回转窑大齿圈径向位移信号分析方法。CEEMD不仅能解决单纯EMD的"模式混叠"问题,还能抑制EEMD中白噪声所造成的影响。以实际的大齿圈径向位移信号为研究对象,发现CEEMD方法提取的固有模态函数(IMF)中包含有与筒体工频一致的特征谐波(KH),并且提取效果要优于EEMD和EMD。最后,将大齿圈径向位移信号的CEEMD结果与其他回转窑检测方法的结果进行对比,确定了KH的幅值与筒体热弯曲故障的评定参数之间的关系,验证了CEEMD方法应用在回转窑故障检测上的可行性。

For this problem of the shortcomings of the EMD method and the EEMD method,a new method for analyzing radial displacement signal of the girth gear of rotary kiln based on CEEMD is proposed. Not only can CEEMD solve the"mode mixing"problem of EMD,but also suppress the influence of white noise in EEMD. By examining the real radical displacement of the girth gear,it is found that the intrinsic modal function extracted by the CEEMD method contains the kiln characteristic harmonic which is consistent with the shell working frequency. The result extracted by CEEMD is better than that from EEMD and EMD.Finally,the relationship between the amplitude of kiln characteristic harmonic and the evaluation parameter of bending on the shell are determined by comparing the results of the CEEMD with other detection methods. It verifies the correctness of the CEEMD method in fault detection of rotary kiln.