拓本
信号(编程语言)
小波
断层(地质)
振动
控制理论(社会学)
定子
小波包分解
转子(电动)
噪音(视频)
信号处理
工程类
算法
计算机科学
小波变换
希尔伯特-黄变换
声学
人工智能
电子工程
机械工程
物理
地质学
数字信号处理
计算机视觉
图像(数学)
滤波器(信号处理)
地震学
程序设计语言
控制(管理)
作者
Yanxue Wang,Richard Markert,Jiawei Xiang,Weiguang Zheng
标识
DOI:10.1016/j.ymssp.2015.02.020
摘要
Multi-component extraction is an available method for vibration signal analysis of rotary machinery, so a novel method of rubbing fault diagnosis based on variational mode decomposition (VMD) is proposed. VMD is a newly developed technique for adaptive signal decomposition, which can non-recursively decompose a multi-component signal into a number of quasi-orthogonal intrinsic mode functions. The equivalent filtering characteristics of VMD are investigated, and the behavior of wavelet packet-like expansion is first found based on fractional Gaussian noise via numerical simulations. VMD is then applied to detect multiple rubbing-caused signatures for rotor–stator fault diagnosis via numerical simulated response signal and practical vibration signal. A comparison has also been conducted to evaluate the effectiveness of identifying the rubbing-caused signatures by using VMD, empirical wavelet transform (EWT), EEMD and EMD. The analysis results of the rubbing signals show that the multiple features can be better extracted with the VMD, simultaneously.
科研通智能强力驱动
Strongly Powered by AbleSci AI