Mr. Chao Sun Profile

Chao Sun

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Proceedings Article | 15 October 2021 Paper

Research on risk prediction techniques of multi-sensing pyrolytic particle electrical fire in heritage buildings based on BP neural network

Xiaobai Li, Chao Sun, Hongjun Ding

Proceedings Volume 11933, 1193306 (2021) https://doi.org/10.1117/12.2615132

KEYWORDS: Particles, Neural networks, Buildings, Epoxies, Dielectrics, Data modeling, Hazard analysis, Analytical research

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In order to detect the electrical fire hazards of distribution boxes in heritage buildings and achieve the purpose of electrical fire risk prevention, this paper has established a multi-sensing pyrolytic particle electrical fire early warning analysis model based on BP neural network, and carried out the experimental verification according to the national standard GB 14287.5 “Electrical Fire Monitoring System Part 5: Measurement Pyrolytic Particle Electrical Fire Monitor Detector”. Firstly, according to the features and rules of high temperature pyrolysis of various electrical insulating materials in distribution boxes, this paper analyzed correlation between different electrical insulating materials or wood surface temperature and risk of electrical fire hazards, and a risk analysis algorithm is established to quantify electrical fire hazards. Then, it established a BP neural network model based on the mass concentration of pyrolytic particles and VOC gas concentration. Finally, through the pyrolysis experiments of various electrical insulating materials and wood, this paper conducted data analysis and verified the algorithm model. The experimental results show that the established BP neural network analysis model is effective with mean absolute percentage error of risk prediction of about 11%. The fitting result of this model is good, and it can be applied to pyrolytic particle electrical fire detection of distribution boxes in heritage buildings.

Proceedings Article | 8 December 2020 Paper

Experimental research on typical incense interference of photoelectric smoke detector

Chen Zhong, Chao Sun, Yingcong Zhang, Hongjun Ding

Proceedings Volume 11606, 1160611 (2020) https://doi.org/10.1117/12.2585631

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This paper studies the application of smoke fire detectors in religious and sacrificial places, focusing on the influence of incense burning interference on the response performance of photoelectric smoke detectors. Based on a dual wavelength photoelectric smoke detection module, the response performance of smoke fire detector is compared through the aerosol test in the smoke test tunnel, burning incense test and four kinds of standard test fire (SH) sensitivity test in combustion chamber. According to the test data, the influence of burning incense on smoke detector is analyzed.

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