Journal
MECHANISM AND MACHINE THEORY
Volume 94, Issue -, Pages 9-27Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mechmachtheory.2015.08.001
Keywords
Intrinsic characteristic-scale decomposition (ICD); Non-stationary signal; Rotating machinery; Fault signature analysis
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Funding
- National Natural Science Foundation of China [11172078]
- Important National Basic Research Program of China (973 Program) [2012CB720003]
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A new method called intrinsic characteristic-scale decomposition (ICD) is proposed in this paper, which is particularly suitable for processing the nonlinear and non-stationary time series. When fault occurs in gearbox and rolling bearing, the measured vibration signals would exactly present non-stationary characteristics. ICD, a new self-adaptive time-frequency analysis method, can decompose the non-stationary signal into a series of product components (PCs). Therefore, it is possible to diagnose gearbox and rolling bearing fault. In this paper, the ICD method is introduced and the decomposition performance is compared with LMD method. The results demonstrate that ICD has the advantages at least in running time, alleviating the mode mixing problem and restraining the end effect. The ICD method is applied to the practical gear and rolling bearing fault diagnosis. The results demonstrate that the proposed method is effective in the fault signature analysis of the rotating machinery. (C) 2015 Elsevier Ltd. All rights reserved.
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