Traceable Correction Method for the Online Measurement System of Train Wheelset Profile Based on Neural Network

Online measurement system of train wheelset profile can automatically measure the wheelset size of all trains passing through the detection zone and timely pre-alarm the oversized wheelset to ensure the safe and smooth operation of the train. In this paper, the main technologies of wheelset size online detection at home and abroad are retrieved, and the problems are analyzed, such as data accuracy is difficult to maintain for a long time, the detection index is imperfect, and the dynamic and static calibration of the system has different in practical applications. Also through analyzing the main sources of detection error from the detection principle and application conditions, expounding the influence of radial runout, and axial displacement on measurement results emphatically, a parameter tracing method based on neural network is proposed and key calibration steps and engineering application examples are also given.

• Record URL:
  • https://doi.org/10.1007/978-981-15-2866-8_61
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9789811528651
• Supplemental Notes:
  • © Springer Nature Singapore Pte Ltd. 2020.
• Corporate Authors:

  Springer Singapore

  152 Beach Road
  Singapore,     189721
• Authors:
  • Fang, En-quan
  • Qin, Jie
  • Geng, Li-li
  • Li, Xiang
  • Wang, Zhipeng
• Conference:
  • 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT 2019)
  • Location: Qingdao , China
  • Date: 2019-10-25 to 2019-10-27
• Publication Date: 2020-4

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 639-650
• Monograph Title: Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019: Rail Transportation System Safety and Maintenance Technologies
• Serial:
  • Lecture Notes in Electrical Engineering
  • Volume: 640
  • Publisher: Springer
  • ISSN: 1876-1100

Subject/Index Terms

• TRT Terms: Accuracy; Alarm systems; Detection and identification technologies; Neural networks; Railroad wheelsets
• Subject Areas: Railroads; Vehicles and Equipment;

Filing Info

• Accession Number: 01928519
• Record Type: Publication
• ISBN: 9789811528651
• Files: TRIS
• Created Date: Aug 23 2024 4:53PM