摘要
为了在非平稳状态下的机电系统故障诊断及趋势预测中合理地选择信号分析方法,对短时傅立叶变换、小波分析和希尔波特-黄变换这3种分析非平稳信号较为有效的方法进行了研究。通过对一个仿真典型信号的分析结果进行比较,验证了3种方法的有效性和各自特点,并分析了产生差异的原因,探讨了它们各自适合的应用场合。
In order to select a proper method of the signal's analysis in the fault diagnosis and trend prediction of mechanical and electrical system under non-stationary states, three methods, effective in the analysis of non-stationary signals, are studied. They are short-time Fourier transformation, Wavelet Analysis and Hilbert-Huang transformation. Through the comparison of the analytic results of a simulated typical signal, the validity and characteristic of each method are confirmed, and the causes of differences are analyzed. Furthermore, the suitable application situation for each method are discussed.
出处
《北京机械工业学院学报》
2004年第3期1-6,共6页
Journal of Beijing Institute of Machinery
基金
国家自然科学基金项目[项目编号:50375017]
北京市自然科学基金项目[项目编号:3042006]