Structure Health Diagnosis of Metro Rail Track by Using Vibration Mappings and Machine Learning

This abstract presents the methodology for the evaluation of metro rail tracks which can be used to produce a vibration map, also it is very fundamental for track maintenance, where we predict vehicle body vibration [2] based on deep learning, which represents one of the newest areas in the Artificial Intelligence field. As we all know, in the entire world the evaluation of track quality had been through established track geometry standards. However, these types of standards may not be capable of detecting some abnormality of track geometry conditions that can cause vehicle body vibration. These vibrations also shake up nearby residents; measurements are carried out to evaluate the risk for structural integrity. With the help of SolidWorks software and structure, health diagnosis using Ansys software integration with experimental data for feature extraction used EEMD and for classification apply artificial neural network (ANN) where a model is proposed to make an accurate and point-wise prediction, due to which we can achieve optimal performance. This case study is based on the Delhi metro, for track health monitoring system was installed on several trains running on the green line in the underground which aims to improve the maintenance process. The early detection [1] and surveillance of defects help to extend the service life of the tracks and it also reduced operating costs. A data acquisition system is used to analyze the continuously recorded measurements (vehicle body vibration), which consist of vertical bogie acceleration and surrounding noise, for example with a frequency of 22 kHz. In particular, achieving optimal performance, and exploring the internal mechanism of the model, structural configuration, and inner states are mostly studied. However, ANN-LSTM can predict vertical vehicle-body vibration below 10 Hz and lateral vehicle-body vibration below 1 Hz. The above analysis shows that the performance of metro rail tracks by using the vehicle body vibration method acts as a performance-based model which evaluated the index of track quality.