A disease detection method for tunnel water leakage based on Bayesian reasoning

Ze Gao; Baoxian Wang; Nana He; Wei Zheng

doi:10.1117/12.3039733

4 September 2024 A disease detection method for tunnel water leakage based on Bayesian reasoning

Ze Gao, Baoxian Wang, Nana He, Wei Zheng

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132593Z (2024) https://doi.org/10.1117/12.3039733
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

This paper introduces a method for detecting tunnel water leakage diseases by combining the YOLOv8 network with a Bayesian reasoning model. Initially, the YOLOv8 network is utilized to construct a dual detection model for identifying the tunnel water leakage diseases and leakage-prone area. Subsequently, a tunnel water leakage disease screening model was constructed based on Bayesian reasoning. By employing the probability weight of the leakage-prone area, the confidence of the tunnel water leakage disease, and the probability weight of the prone area have tunnel water leakage diseases are combined to ultimately obtain the probability of tunnel water leakage diseases, this probability will be used to reduce false alarms in the detection results. Experimental testing using actual tunnel data demonstrates that compared to the YOLOv5 and YOLOv8_m networks, the proposed model achieves an increase in mAP by 7.37% and 1.64% respectively, effectively validating the model's efficacy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ze Gao, Baoxian Wang, Nana He, and Wei Zheng "A disease detection method for tunnel water leakage based on Bayesian reasoning", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132593Z (4 September 2024); https://doi.org/10.1117/12.3039733

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