Research on Classification Performance of Circuit Breaker Vibration Signal Based on Fuzzy C-Means Clustering Analysis

Bin Li; Shuang Li; Xu Chen Lu

doi:10.4028/www.scientific.net/AMR.960-961.1352

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 960-961Research on Classification Performance of Circuit...

Research on Classification Performance of Circuit Breaker Vibration Signal Based on Fuzzy C-Means Clustering Analysis

Abstract:

With permanent magnetic actuator monostable circuit breaker as the research object, it gets three different running status signal data, normal circuit breaker closing state , break-brake spring single loss and Institutions unsmooth Through constructing data acquisition platform. The performance of the three methods of feature extraction is compared, short-time Fourier transform, wavelet packet energy entropy and Hilbert huang transform, through fuzzy c-means clustering analysis algorithm. Through the comparative study, it is concluded that adopt wavelet packet transform method to get the best classify performance of time-frequency entropy vector .

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Periodical:

Advanced Materials Research (Volumes 960-961)

Pages:

1352-1355

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.960-961.1352

Citation:

Cite this paper

Online since:

June 2014

Authors:

Bin Li*, Shuang Li, Xu Chen Lu

Keywords:

Circuit Breaker, Classification Performance, Fuzzy C-Clustering Analysis, Mechanical Vibration Signal

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* - Corresponding Author

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