Smart Detection Technology of Serial Arc-Fault on Low Voltage Power Lines

Chi Jui Wu; Chen Hsuan Hung; Yu Wei Liu

doi:10.4028/www.scientific.net/AMR.734-737.3190

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Research on Various Algorithms in Asynchronous Network Communication System
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Robust Kalman Filtering for Descriptor Systems with Unstructured Uncertainties
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Smart Detection Technology of Serial Arc-Fault on Low Voltage Power Lines
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 734-737Smart Detection Technology of Serial Arc-Fault on...

Smart Detection Technology of Serial Arc-Fault on Low Voltage Power Lines

Abstract:

It is important to use electric power safely. Electric arcing faults on the low voltage power lines must be detected and power sources have to be shut down before fire hazards. In this paper, it suppose a method to analyze and detect arc fault characteristics. The current waveforms are different in arc fault and normal operation conditions. The discrete wavelet transform is used to obtain the spectrum characteristics of experiment data and the spectrum energy statistics can reflect the characteristics. Additionally, the values of spectrum energy are input of the back-propagation neural networks (BPNN), which can identify the arc fault efficiently. The test results have demonstrated that the proposed method is effective.

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Periodical:

Advanced Materials Research (Volumes 734-737)

Pages:

3190-3193

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.734-737.3190

Citation:

Cite this paper

Online since:

August 2013

Authors:

Chi Jui Wu, Chen Hsuan Hung, Yu Wei Liu

Keywords:

Arc-Fault Detection, Artificial Neural Network (ANN), Low Voltage Line, Wavelet Transform (WT)

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References

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