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...

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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
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Online Access:http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2021.03.002
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Summary: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.
ISSN:1000-128X