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Complete ensemble local characteristic-scale decomposition and its applications to rotor fault diagnosis
Author(s): 
Pages: 637-646
Year: Issue:  4
Journal: Journal of Vibration Engineering

Keyword:  fault diagnosismode mixinglocal characteristic-scale decompositionCELCDEEMD;
Abstract: 作为对经验模态分解(EMD)的改进,局部特征尺度分解(LCD)也有类似EMD的模态混淆问题.基于噪声辅助分析的总体平均经验模态分解(EEMD)和完备的EEMD(CEEMD)等是抑制分解模态混淆的有效途径.然而此类方法伪分量较多、得到的分量未必满足IMF分量定义等.针对此,提出了一种完备的总体平均局部特征尺度分解(CELCD),并通过仿真信号将CELCD方法与CEEMD进行了对比,结果表明CELCD能够有效抑制LCD模态混淆,而且在抑制伪分量的产生,提高正交性和分量的精确性等方面具有一定的优越性.最后论文将CELCD方法应用于转子碰摩故障的诊断,结果表明了方法的有效性.
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