Research on real-time detection method of transmission poles during vehicle driving based on artificial intelligence

Fan Kuang; Yanchao Cao; Ting Yang; Jianghua Hu; Cheng Zhang

doi:10.1117/12.2640482

19 October 2022 Research on real-time detection method of transmission poles during vehicle driving based on artificial intelligence

Fan Kuang, Yanchao Cao, Ting Yang, Jianghua Hu, Cheng Zhang

Author Affiliations +

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 122943Q (2022) https://doi.org/10.1117/12.2640482
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

The maintenance of power transmission lines is an important part in avoiding potential safety hazards and protecting residents’ electricity use. Currently the inspection of power transmission poles mainly relies on manual positioning, which is not efficient. To improve the efficiency in the positioning of poles, this research proposes a real-time detection method for power transmission poles based on video streaming media and AI algorithms. The method obtains the real-time status of roadsides by sending video streams through the onboard camera and receiving streams through OpenCV and utilizes YOLO, DeepSORT and a fault-tolerant algorithm to detect, track and count power transmission poles. The result of test data shows that the proposed method could not only detect the poles along roadside with good precision but also count the poles accurately with a success rate of over 90%, which could greatly assist in the inspection of power transmission poles.

Citation Download Citation

Fan Kuang, Yanchao Cao, Ting Yang, Jianghua Hu, and Cheng Zhang "Research on real-time detection method of transmission poles during vehicle driving based on artificial intelligence", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 122943Q (19 October 2022); https://doi.org/10.1117/12.2640482

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