Vertical Track Geometry Monitoring Using Inertial Sensors and Complementary Filters

Author:

Escalona José L.1

Affiliation:

1. University of Seville, Sevilla, Spain

Abstract

This paper describes a computational procedure to obtain the vertical railroad track irregularities using the signals of an accelerometer and a gyroscope (IMU, inertial measurement unit) installed on a bogie of a railway vehicle. The procedure is designed to be implemented in a real-time on-board track geometry measurement system. The paper includes algorithms for constant and variable forward velocity of the laboratory vehicle. In each case, individual numerical methods to obtain the track vertical irregularities from the accelerometer signal and the gyroscope signal are presented. In addition a sensors fusion algorithm based on the concept of complementary filters is presented. In the sensors fusion algorithm the gyroscope’s based irregularity is used to measured low spatial frequencies while the accelerometer’s based irregularity is used to measure the high spatial frequencies. The numerical examples are developed on the basis of a synthesized irregular track profile that is numerically obtained from a known PSD (power spectral density) used in the railway industry. In the numerical tests the measured acceleration and angular velocity are corrupted with a bias error and a Gaussian white noise to account for the sensors errors. The numerical results compare the original irregularity profile with the measured profile in the space and frequency domains using the PSD and coherence function. Results include the algorithms for a constant and a variable forward velocity of the laboratory vehicle. A good agreement is found.

Publisher

American Society of Mechanical Engineers

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data measurement system for track panel vibrations;THE 6TH INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENT, EPIDEMIOLOGY AND INFORMATION SYSTEM (ICENIS) 2021: Topic of Energy, Environment, Epidemiology, and Information System;2023

2. Review of Data Analytics for Condition Monitoring of Railway Track Geometry;IEEE Transactions on Intelligent Transportation Systems;2022-12

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