6 March 2015 Detection of arc fault based on frequency constrained independent component analysis
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Proceedings Volume 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation; 94461X (2015) https://doi.org/10.1117/12.2180859
Event: International Symposium on Precision Engineering Measurement and Instrumentation, 2014, Changsha/Zhangjiajie, China
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.
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Kai Yang, Kai Yang, Rencheng Zhang, Rencheng Zhang, Renhao Xu, Renhao Xu, Yongzhi Chen, Yongzhi Chen, Jianhong Yang, Jianhong Yang, Shouhong Chen, Shouhong Chen, } "Detection of arc fault based on frequency constrained independent component analysis ", Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94461X (6 March 2015); doi: 10.1117/12.2180859; https://doi.org/10.1117/12.2180859
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