A New Intelligent Fault Recognition Method for Rotating Machinery

Abstract:

In this paper, a novel method to recognize rotor fault pattern was proposed based on rank-order morphological filter, harmonic window decomposition, sample entropy and grey incidence. At first, the line structure element was selected for rank-order morphological filter to denoise the original signal. Then, the six feature frequency bands which contain the typical fault information were extracted by harmonic window decomposition that needs not decomposition; and sample entropy of each band was calculated. Finally, these sample entropies could serve as the feature vectors, the grey incidence of different rotor vibration signals was calculated to identify the fault pattern and condition. Practical results show that this method can be used in fault diagnosis of rotating machinery effectively.

• Periodical: Advanced Materials Research (Volumes 706-708)
• Pages: 1705-1708
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.706-708.1705
• Online since: June 2013
• Authors: Wen Bin Zhang, Yan Ping Su, Jie Min, Yan Jie Zhou
• Keywords: Fault Recognition, Grey Incidence, Harmonic Window Decomposition, Rank-Order Morphological Filter, Rotating Machinery, Sample Entropy

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