完全ASTFA方法及其在转子碰摩故障诊断中的应用

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摘要在进行自适应最稀疏分析（Adaptive and sparsest time-frequency analysis,ASTFA）时需要人为地选定分量带宽控制参数，选用不当会引起模态混淆，针对ASTFA的这种缺陷，利用总体平均经验模态分解（Ensembleempirical mode decomposition, EEMD）的自适应性，提出完全自适应最稀疏分析（Complete adaptive and sparsest time-frequency analysis ，CASTFA）方法。CASTFA以EEMD分解出来的分量为参考，自适应地确定。仿真结果结果表明CASTFA能够抑制ASTFA方法的模态混淆现象，且分解效果优于EEMD方法。将CASTFA方法应用于转子碰摩故障诊断，结果表明了本方法的有效性。

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	程军圣
	刘贞涛
	杨宇

关键词 ：完全自适应最稀疏时频分析, 模态混淆, 转子碰摩

Abstract：of a parameter of controlling a component’s bandwidth must be determined artificially When using adaptive and sparsest time-frequency analysis (ASTFA) .A improper will lead to the problem of mode mixing.Complete adaptive and sparsest time-frequency analysis( CASTFA) was proposed to restrain such a drawback of ASTFA.CASTFA use the intrinsic mode function(IMF) generated by ensembleempirical mode decomposition (EEMD) as reference to adaptively determine the .the simulation example showed the CASTFA can restraining the mode mixing of ASTFA,and perform better than EEMD in restraining mode mixing.The practical rotor rubbing fault diagnosis result turned out that CASTFA is efficient.

Key words： complete adaptive and sparsest time-frequency analysis;mode mixing rotor rubbing

收稿日期: 2016-08-08 出版日期: 2018-02-15

引用本文:

程军圣,刘贞涛,杨宇. 完全ASTFA方法及其在转子碰摩故障诊断中的应用[J]. 振动与冲击, 2018, 37(4): 165-169.
Cheng Junsheng2,Liu Zhentao, Yang Yu. Complete adaptive and sparsest analysis and its application to rotor rubbing fault diagnosis. JOURNAL OF VIBRATION AND SHOCK, 2018, 37(4): 165-169.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2018/V37/I4/165

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