Online train identification and speed estimation method based on optical fiber vibration signals

Abstract

The invention discloses an online train identification and speed estimation method based on optical fiber vibration signals, and belongs to the field of the data-driven fault diagnosis. The method comprises the following steps of: (1) obtaining the eigenvalue energy entropy for data classification by short-time Fourier transform after performing smooth filtering on the fiber vibration signals collected by each sampling point; (2) classifying eigenvalue of each sampling point online to determine whether there is a suspected train signal after calculating a threshold offline by the unsupervisedlearning algorithm; (3) finding signals that satisfy a train characteristic model in the suspected train signals by modeling characteristics of the train; and (4) obtaining the real-time position andthe speed of the train by performing the improved global piecewise polynomial fitting on the train signals. According to the online train identification and speed estimation method based on optical fiber vibration signals, the problem of fault diagnosis and tracking for unlabeled data under an interference condition is solved based on the fiber vibration signals.

Description

technical field [0001] The invention relates to an online train identification and speed estimation method based on optical fiber vibration signals, belonging to the field of data-driven fault diagnosis. Background technique [0002] In recent years, with the rapid development of my country's high-speed rail business, the mileage of high-speed rail has continued to increase, and the safety protection along the railway has become a key issue that needs to be solved urgently. Dangerous or malicious acts such as illegally destroying or crossing the railway guardrail, placing foreign objects on the track, etc., will bury serious safety hazards for railway operations and cause huge losses to social public property. [0003] At this stage, in order to achieve intrusion detection, the commonly used methods include light wave detection, pulse electronic fence detection, vibration cable detection, vibration optical fiber detection, video intelligent analysis technology, etc. Among t...

AI Technical Summary

Problems solved by technology

For fault diagnosis with interference, the interference will inevitably lead to the transformation of the original fault identification problem into a nonlinear classification problem. At the same time, in the case of large interference, it will also cause problems such as signal flooding, thereby reducing the accuracy of the algorithm.

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