当前位置: X-MOL 学术IEEE Trans. Instrum. Meas. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Linear and Quadratic Time-Frequency Analysis of Vibration for Fault Detection and Identification of NFR Trains
IEEE Transactions on Instrumentation and Measurement ( IF 5.6 ) Pub Date : 2020-11-01 , DOI: 10.1109/tim.2020.2998888
Jyoti Barman , Durlav Hazarika

The work reported in this article aims at developing a simple sensor-based system that detects and identifies faults of a train. Four different trains are considered for analysis as suggested by the Northeast Frontier Railway (NFR) authorities. For this purpose, an embedded system containing an ADXL335 sensor is used to capture the vibration of a railway track during the movement of a train over the track. The embedded system transfers the captured signals from ADXL335 to a laptop. These signals are processed using linear time–frequency transform (wavelet transform) in conjunction with quadratic time–frequency transform (Wigner–Ville transform) to find out whether there are any faults and thereby quantify the quality of the moving trains. Wheel-flat fault is detected for one train with the wheel position and the bogie number. This is a low-cost technique as the method involves only one ADXL335 sensor and an Arduino development board, and the software used for the analysis is python that is an open-source and platform-independent software.

中文翻译:

用于 NFR 列车故障检测和识别的振动的线性和二次时频分析

本文报道的工作旨在开发一个简单的基于传感器的系统,用于检测和识别列车故障。根据东北边境铁路 (NFR) 当局的建议,考虑对四种不同的列车进行分析。为此,包含 ADXL335 传感器的嵌入式系统用于捕获火车在轨道上移动期间铁路轨道的振动。嵌入式系统将捕获的信号从 ADXL335 传输到笔记本电脑。这些信号使用线性时频变换(小波变换)结合二次时频变换(Wigner-Ville 变换)进行处理,以找出是否存在任何故障,从而量化运动列车的质量。用车轮位置和转向架号检测一列火车的车轮扁平故障。
更新日期:2020-11-01
down
wechat
bug