Research on Intelligent Diagnosis of Railway Turnout Based on FastDTW under Big Data Monitoring

Abstract

Turnout equipment is a key component to ensure the safe operation of trains. How to identify turnout faults is one of the important tasks of railway engineering departments and electrical departments. We used fast dynamic time warping (FastDTW) algorithm to analyze the similarity of mechanical characteristic data during turnout actions, and then realized the intelligent diagnosis of turnout faults under the background of big data. Experiments show that the algorithm for predicting turnout faults based on FastDTW is an accurate and effective method, which can improve the key technology of intelligent monitoring and early warning of the whole process of turnout movement.