Real-Time Φ-OTDR Vibration Event Recognition Based on Image Target Detection

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 3; p. 1127
• Main Authors: Yang, Nachuan, Zhao, Yongjun, Chen, Jinyang
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 02.02.2022; MDPI
• Subjects: Algorithms; Barbed wire; Cancellers; Computer vision; Datasets; Equipment and supplies; False alarms; Fiber Optic Technology; Fiber optics; Fourier transforms; Frames per second; High speed rail; High speed trains; Image enhancement; Localization; Machine vision; Neural networks; Noise; phase-sensitive optical time-domain reflectometer; Razors; Real time; real-time processing; Sensors; Signal processing; target detection; Vibration; Warning systems; phase-sensitive optical time-domain reflectometer; target detection; real-time processing; computer vision
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22031127

Accurate and fast identification of vibration signals detected based on the phase-sensitive optical time-domain reflectometer (Φ-OTDR) is crucial in reducing the false-alarm rate of the long-distance distributed vibration warning system. This study proposes a computer vision-based Φ-OTDR multi-vibration events detection method in real-time, which can effectively detect perimeter intrusion events and reduce personnel patrol costs. Pulse accumulation, pulse cancellers, median filter, and pseudo-color processing are employed for vibration signal feature enhancement to generate vibration spatio-temporal images and form a customized dataset. This dataset is used to train and evaluate an improved YOLO-A30 based on the YOLO target detection meta-architecture to improve system performance. Experiments show that using this method to process 8069 vibration data images generated from 5 abnormal vibration activities for two types of fiber optic laying scenarios, buried underground or hung on razor barbed wire at the perimeter of high-speed rail, the system mAP@.5 is 99.5%, 555 frames per second (FPS), and can detect a theoretical maximum distance of 135.1 km per second. It can quickly and effectively identify abnormal vibration activities, reduce the false-alarm rate of the system for long-distance multi-vibration along high-speed rail lines, and significantly reduce the computational cost while maintaining accuracy.