A novel Bayesian optimal detector-based approach for determining the first arrival time of wire breakage-induced near-wall acoustic wave in PCCPs

Abstract

Wire breakage in prestressed cylinder concrete pipes (PCCPs) due to various factors, such as corrosion, hydrogen embrittlement, material defects and overload, may lead to structural failure. Real-time detection of acoustic waves generated by wire breakage is possible using fiber optic sensors. Accurate determination of the first arrival time (FAT) of acoustic wave is vital for localizing wire breakages. A novel method based on the Bayesian optimal detector is proposed to automatically identify the FAT of near-wall acoustic wave. The FATs are subsequently fed into a localization model of wire breakage. The localization results are compared for the FAT of the proposed method and human subjective picking via model tests. The results show that compared with human subjective picking, the wire breakage localization of the proposed method can ensure the accuracy of the results. The maximum errors of the longitudinal and circumferential positions of the proposed method are 0.15 m and 0.02 m, respectively. The experimental results demonstrate that the FATs determined by the Bayesian optimal detector enable the accurate localization of wire breakage with noisy measurements. The proposed method overcomes the limitation of traditional picking methods in determining the FAT, which provides a promising tool for real-time monitoring of wire breakage in PCCPs.