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Proceedings Paper

Detection of arc fault based on frequency constrained independent component analysis
Author(s): Kai Yang; Rencheng Zhang; Renhao Xu; Yongzhi Chen; Jianhong Yang; Shouhong Chen
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Paper Abstract

Arc fault is one of the main reasons of electrical fires. As a result of weakness, randomness and cross talk of arc faults, very few of methods have been successfully used to protect loads from all arc faults in low-voltage circuits. Therefore, a novel detection method is developed for detection of arc faults. The method is based on frequency constrained independent component analysis. In the process of the method derivation, a band-pass filter was introduced as a constraint condition to separate independent components of mixed signals. In the process of the independent component separations, although the fault mixed signals were under the conditions of the strong background noise and the frequency aliasing, the effective high frequency components of arc faults could be separated by frequency constrained independent component analysis. Based on the separated components, the power spectrums of them were calculated to classify the normal and the arc fault conditions. The validity of the developed method was verified by using an arc fault experimental platform set up. The results show that arc faults of nine typical electrical loads are successfully detected based on frequency constrained independent component analysis.

Paper Details

Date Published: 6 March 2015
PDF: 7 pages
Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94461X (6 March 2015); doi: 10.1117/12.2180859
Show Author Affiliations
Kai Yang, Huaqiao Univ. (China)
Rencheng Zhang, Huaqiao Univ. (China)
Renhao Xu, Xiamen Univ. of Technology (China)
Yongzhi Chen, Huaqiao Univ. (China)
Jianhong Yang, Huaqiao Univ. (China)
Shouhong Chen, Huaqiao Univ. (China)


Published in SPIE Proceedings Vol. 9446:
Ninth International Symposium on Precision Engineering Measurement and Instrumentation
Junning Cui; Jiubin Tan; Xianfang Wen, Editor(s)

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