Fire point location technology in high concentration smoke environment of transmission line in mountainous area
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1.State Grid Inner Mongolia Eastern Power Co., Ltd., Hohhot 010020,China; 2.State Grid Inner Mongolia East Electric Power Co., Ltd. Electric Power Science Research Institute, Hohhot 010020,China; 3.State Grid Inner Mongolia East Electric Power Co., Ltd. Hulunbuir Company Inner Mongolia, Hulunbuir 021000,China

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TU18,TN102

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    Abstract:

    Aiming at the problems that the current inspection and monitoring methods cannot accurately identify the fire area below 10 m2 square meters in the high-concentration smoke environment, and it cannot accurately identify the mountain fire in the low-lying area, the fire location technology of the transmission line in the high-concentration smoke environment was studied based on the integrated inertial navigation multi-data fusion. This technology combines and fuses multi-source monitoring data such as satellite remote sensing and inertial navigation data of transmission lines in mountainous areas by using federated filter. An adaptive threshold detection algorithm was designed for ignition points based on context judgment and absolute threshold method, and implement the extraction of ignition point information for transmission lines in mountainous areas. A multi band optoelectronic composite detection target recognition method was designed combining PSO algorithm and BP neural network to achieve the recognition of fire point targets on transmission lines in mountainous areas under high concentration smoke environment. Location of transmission lines in mountainous areas fire point location method based on laser ranging, fire point location of transmission lines in mountainous areas in high smog environment is realized. The experimental test results indicate that the design technology is effective for fire points (10 m2 above the fire area), fire points in plain areas (10 m2 The fire area below), and the fire point in low-lying areas (10 m2 above the fire area). The positioning accuracy of the above three situations is higher than 99.5%.

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  • Received:
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  • Online: January 13,2025
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