<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Detection and analysis of series arc in low-voltage switchboards have significant meaning for preventing the electrical fires. However, the conventional current and voltage methods have low a sensitivity to sense the minute arc discharge, leading to the fail operation of arc fault circuit interrupter. Therefore, this paper dealt with the application of non-conventional methods, including the ultra-violet (UV), acoustic emission (AE), and transient earth voltage (TEV) sensor in arc detection, for the purpose of improving the detection sensitivity and reducing the potential electric fires. Three types of typical arc faults in low-voltage switchboards were simulated and the actual detection environment was configured. From the results, the wavelength of UV light emitted from arc was 200–400 nm and the arc-induced AE signal had a frequency range of 40–600 kHz. The TEV signals generated from three types of arc faults presented different frequency spectrums, based on which the time-frequency map was used to classify the fault type.</p></abstract>

Detection and analysis of series arc in low-voltage switchboards have significant meaning for preventing the electrical fires. However, the conventional current and voltage methods have low a sensitivity to sense the minute arc discharge, leading to the fail operation of arc fault circuit interrupter. Therefore, this paper dealt with the application of non-conventional methods, including the ultra-violet (UV), acoustic emission (AE), and transient earth voltage (TEV) sensor in arc detection, for the purpose of improving the detection sensitivity and reducing the potential electric fires. Three types of typical arc faults in low-voltage switchboards were simulated and the actual detection environment was configured. From the results, the wavelength of UV light emitted from arc was 200–400 nm and the arc-induced AE signal had a frequency range of 40–600 kHz. The TEV signals generated from three types of arc faults presented different frequency spectrums, based on which the time-frequency map was used to classify the fault type.

Detection and analysis of series arc using non-conventional methods in low-voltage switchboards

Department of Electrical and Electronics Engineering

Physical Engineering Division, National Forensic Service Daegu Institute

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Detection and analysis of series arc in low-voltage switchboards have significant meaning for preventing the electrical fires. However, the conventional...

Detection and analysis of series arc using non-conventional methods in low-voltage switchboards

Publicado en línea: 19 sept 2018

Páginas: 317 - 322

Recibido: 28 may 2018

DOI: https://doi.org/10.2478/jee-2018-0045

Palabras clave
series arc, non-conventional methods, ultra-violet, acoustic emission, transient earth voltage, time-frequency map

© 2018 Guoming Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Detection and analysis of series arc using non-conventional methods in low-voltage switchboards

Publicado en línea: 19 sept 2018

Páginas: 317 - 322

Recibido: 28 may 2018

DOI: https://doi.org/10.2478/jee-2018-0045

Palabras claveseries arc, non-conventional methods, ultra-violet, acoustic emission, transient earth voltage, time-frequency map

© 2018 Guoming Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
series arc, non-conventional methods, ultra-violet, acoustic emission, transient earth voltage, time-frequency map