主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

Fire Science and Technology ›› 2020, Vol. 39 ›› Issue (12): 1770-1772.

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Study on the application of neural network on transformer substation fire management

LI Fu-qiang, QU Hang, XU Ning-yi, ZHU Wen-chao   

  1. Ningbo power supply company of State Grid Zhejiang Electric Power Co., Ltd., Zhejiang Ningbo 315000, China  

  • Online:2020-12-15 Published:2020-12-15

Abstract:

In order to improve the fire management of transformer substation, the video and image flame feature extraction and identification are achieved. The stream data of video surveillance is accessed. The flame identification model based on convolution neural network is built. The flame features are real time identified, and early warning and forecast are performed. Experiments showed that, the method can extract the flame feature automatically, and efficiently improve the accuracy of flame identification with complex background, with good robustness and generalization ability, and have great application prospect in the fire management of transformer substation.  

Key words:

convolution neural network, flame identification, transformer substation, fire management