摘要
针对经验模态分解(EMD)易产生模态混叠现象的问题,提出了一种基于经验小波变换(EWT)的回转窑托轮振动信号分析方法。EWT根据频域极大值点对傅里叶频谱进行划分,自适应地构造小波滤波器组以提取傅里叶频谱中的调幅-调频(AM-FM)函数,能够有效防止模态混叠的出现。仿真实验和托轮振动信号的研究表明:EWT提取的AM-FM函数中包含信号的特征模态,其分解结果优于EMD。最后将托轮振动信号的EWT结果与其他回转窑检测方法结果进行对比,验证了EWT在回转窑故障检测中的正确性。
According to the problem of empirical mode decomposition(EMD)easily causing virtual modes,an analysis method of vibration signal of rotary kiln roller based on empirical wavelet transform(EWT)is proposed.The Fourier spectrum has been cut into segments by EWT through extracting the maximal value in the frequency domain,thereby adaptively constructing a wavelet filter bank to extract the amplitude-modulation(AM-FM)function in the Fourier spectrum,which can effectively eliminate modal aliasing.The simulation experiment and research on the vibration signal of the roller show that the AM-FM functions extracted by EWT contain the characteristic mode of the signal,and its decomposition result is better than EMD.Finally,the EWT results of the roller vibration signal are compared with the results of other rotary kiln detection methods,which verifies the correctness of EWT in fault detection of rotary kiln.
作者
胡航宇
张云
HU Hangyu;ZHANG Yun(School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan 430070,China;Testing Center of Rotary Kiln for National Building Materials Industry,Wuhan University of Technology,Wuhan 430070,China)
关键词
经验小波变换
回转窑
托轮
特征模态
经验模态分解
empirical wavelet transform
rotary kiln
roller
characteristic mode
empirical mode decomposition
作者简介
胡航宇(1994-),男,湖北武汉人,武汉理工大学机电工程学院硕士研究生.
