Research on Track Irregularity Detection Algorithm Based on Data Fusion

Aiming at the problem of track irregularity detection method and accuracy, a strap-down inertial navigation technology was proposed. A quaternion based "mathematical platform" was built. By integrating odometer and radio frequency tag, the mileage position information was corrected; By int...

Full description

Saved in:
Bibliographic Details
Main Authors: Yi LI, Huan BAI, Yuanming LIU
Format: Article
Language:zho
Published: Editorial Department of Electric Drive for Locomotives 2021-05-01
Series:机车电传动
Subjects:
Online Access:http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.03.002
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849729353489842176
author Yi LI
Huan BAI
Yuanming LIU
author_facet Yi LI
Huan BAI
Yuanming LIU
author_sort Yi LI
collection DOAJ
description Aiming at the problem of track irregularity detection method and accuracy, a strap-down inertial navigation technology was proposed. A quaternion based "mathematical platform" was built. By integrating odometer and radio frequency tag, the mileage position information was corrected; By integrating accelerometer and gyroscope data of inertial measurement unit(IMU), the axle attitude was calculated; By using complementary filtering algorithm for data fusion, and using chaotic-enhanced fruit flyoptimization algorithm (CFOA) for filtering, the wheel axle three-dimensional attitude data expressed by Euler angle was obtained, and then fitted to realize the track irregularity detection. Practice shows that the data fusion detection algorithm proposed in this paper can effectively realize the track irregularity detection, improve the detection accuracy, and provide basic data for track maintenance.
format Article
id doaj-art-e4d2fdffcde74c958bb8842e9729dfbf
institution DOAJ
issn 1000-128X
language zho
publishDate 2021-05-01
publisher Editorial Department of Electric Drive for Locomotives
record_format Article
series 机车电传动
spelling doaj-art-e4d2fdffcde74c958bb8842e9729dfbf2025-08-20T03:09:15ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2021-05-0191520920529Research on Track Irregularity Detection Algorithm Based on Data FusionYi LIHuan BAIYuanming LIUAiming at the problem of track irregularity detection method and accuracy, a strap-down inertial navigation technology was proposed. A quaternion based "mathematical platform" was built. By integrating odometer and radio frequency tag, the mileage position information was corrected; By integrating accelerometer and gyroscope data of inertial measurement unit(IMU), the axle attitude was calculated; By using complementary filtering algorithm for data fusion, and using chaotic-enhanced fruit flyoptimization algorithm (CFOA) for filtering, the wheel axle three-dimensional attitude data expressed by Euler angle was obtained, and then fitted to realize the track irregularity detection. Practice shows that the data fusion detection algorithm proposed in this paper can effectively realize the track irregularity detection, improve the detection accuracy, and provide basic data for track maintenance.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.03.002track irregularityirregularity detectionSINSdata fusionCFOAattitude calculation
spellingShingle Yi LI
Huan BAI
Yuanming LIU
Research on Track Irregularity Detection Algorithm Based on Data Fusion
机车电传动
track irregularity
irregularity detection
SINS
data fusion
CFOA
attitude calculation
title Research on Track Irregularity Detection Algorithm Based on Data Fusion
title_full Research on Track Irregularity Detection Algorithm Based on Data Fusion
title_fullStr Research on Track Irregularity Detection Algorithm Based on Data Fusion
title_full_unstemmed Research on Track Irregularity Detection Algorithm Based on Data Fusion
title_short Research on Track Irregularity Detection Algorithm Based on Data Fusion
title_sort research on track irregularity detection algorithm based on data fusion
topic track irregularity
irregularity detection
SINS
data fusion
CFOA
attitude calculation
url http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.03.002
work_keys_str_mv AT yili researchontrackirregularitydetectionalgorithmbasedondatafusion
AT huanbai researchontrackirregularitydetectionalgorithmbasedondatafusion
AT yuanmingliu researchontrackirregularitydetectionalgorithmbasedondatafusion