Telecommunications Science ›› 2022, Vol. 38 ›› Issue (5): 95-103.doi: 10.11959/j.issn.1000-0801.2022065

• Research and Development • Previous Articles     Next Articles

Anti-collision online early warning method for construction machinery around transmission line

Chaojie CHEN1, Wei XIE1, Linwei HE1, Qiang TIAN1, Runping HE2, Zhefei WANG2   

  1. 1 State Grid Shanghai Electric Power Company Qingpu Power Supply Company, Shanghai 201799, China
    2 Shanghai Siliang Electronic Technology Co., Ltd., Shanghai 201415, China
  • Revised:2022-04-08 Online:2022-05-20 Published:2022-05-01
  • Supported by:
    Science and Technology Project of State Grid Corporation(SGSHQP00HBJS2102101)

Abstract:

The transmission line has long transmission distance and complex channel environment.Impacts caused by large construction machinery occur from time to time.The existing anti-collision monitoring scheme of transmission line mainly depends on manual implementation, which not only consumes a lot of human resources, but also is difficult to ensure the monitoring coverage.Therefore, an anti-collision on-line early warning method for construction machinery around the transmission line was proposed.This method innovatively used intelligent sensors and compressed sensing algorithm to realize the automatic on-line early warning of construction machinery threats in the transmission line channel.The pixel distribution characteristics, shape characteristics and distance characteristics of the target were collected by the camera module and microwave ranging module, and transmitted to the background.The background server used the established offline feature target database to realize the research and judgment results of the target through compressed sensing algorithm, and sent out early warning to the threatening target in time.The experimental results show that the recognition accuracy of the proposed algorithm can reach 96.34%, and can provide reliable early warning results for the transmission inspection department.

Key words: anti-collision of transmission line, online monitoring, feature recognition, compressed sensing

CLC Number: 

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