A Railway Health Monitoring Method Based on Distributed Fiber Optic Vibration Sensing System

Abstract

The invention discloses a railway health monitoring method based on a distributed optical fiber vibration sensing system. The railway health monitoring method comprises steps of using an existing communication optical fiber which is paved along a railway to perform sensing, capturing vibration information along the railway after a train passes, using data to constitute a waterfall plot which uses a gray scale to express intensity along a timeline, adopting a rim extraction algorithm based on dynamic planning to extract a track generated by a moving train after wavelet decomposition filtering is performed, marking off two areas, wherein one area is before the track and the other area is after the track, performing time frequency analysis on the track area and areas before and after the track, extracting a wheeltrack vibration characteristic frequency spectrum and a steel rail resonance characteristic frequency spectrum, obtaining wheeltrack vibration characteristic frequency and steel rail resonance characteristic frequency through a characteristic spectrum extraction algorithm, constantly repeating a monitoring process to obtain a change of a steel rail vibration characteristic along the time, and establishing a corresponding database. Newly collected data is compared with data inside the database and the database is updated, and health monitoring on the train and the steel rail is realized.

Description

technical field

[0001] The invention relates to the technical field of optical fiber sensing, in particular to a railway health monitoring method based on a distributed optical fiber vibration sensing system. Background technique

[0002] The safety of railway operation has always been a major issue related to economic development and personal safety. In order to ensure the safety and smoothness of railway transportation and improve operational efficiency, it is necessary to monitor the health status of railways in real time. However, the electrical sensing elements currently used have poor moisture-proof and anti-electromagnetic interference capabilities, and are unstable under harsh monitoring conditions. When used in complex monitoring environments for a long time, faults such as zero point drift are prone to occur, which greatly On the other hand, the transmission distance of electrical signals in the channel is very short, it is difficult to form a large-scale sensor n...

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