Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)

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Study on Lifetime Prediction of Locking Block Based on Artificial Intelligence

Authors
Jun Cao1, Jianghong Gan2, *, Hui Guan3
1State Key Lab of Digital Manufacturing Equipment and Technology, HUST-SANY Joint Lab of Advanced Manufacturing, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
2Wuhan Railway Vocation College of Technology, Wuhan, China
3College of Languages and Culture, Northwest A&F University, Xianyang, Shaanxi Province of China, China
*Corresponding author. Email: cao96qc@126.com
Corresponding Author
Jianghong Gan
Available Online 7 May 2024.
DOI
10.2991/978-94-6463-419-8_15How to use a DOI?
Keywords
locking blocks; artificial intelligence; data processing; lifetime prediction
Abstract

Data analysis and data prediction based on artificial intelligence technology have a wide range of applications in daily production and life. Predicting the lifetime of the locking block enables train maintenance personnel to understand the current and future status of trains, and to develop targeted maintenance programs as well as rational train dispatching, so as to promote the realization of condition repair of the train braking system. After analysis and comparison of the mainstream prediction methods at present, the team decides to take artificial intelligence technology as the core, and mathematical models and intelligent algorithms as specific means to achieve the prediction of locking block lifetime and of maintenance timing.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
Series
Atlantis Highlights in Computer Sciences
Publication Date
7 May 2024
ISBN
10.2991/978-94-6463-419-8_15
ISSN
2589-4900
DOI
10.2991/978-94-6463-419-8_15How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jun Cao
AU  - Jianghong Gan
AU  - Hui Guan
PY  - 2024
DA  - 2024/05/07
TI  - Study on Lifetime Prediction of Locking Block Based on Artificial Intelligence
BT  - Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
PB  - Atlantis Press
SP  - 115
EP  - 120
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-419-8_15
DO  - 10.2991/978-94-6463-419-8_15
ID  - Cao2024
ER  -