Research on hard points height prediction method based on BP neural network

Qingqin Yang; Qi Zhang; Zhuo Zhang; Dixiang Chen; Mengchun Pan; Wenwu Zhou; Yuan Ren; Hao Ma; Lihui Liu

doi:10.1117/12.2686683

10 August 2023 Research on hard points height prediction method based on BP neural network

Qingqin Yang, Qi Zhang, Zhuo Zhang, Dixiang Chen, Mengchun Pan, Wenwu Zhou, Yuan Ren, Hao Ma, Lihui Liu

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 1275936 (2023) https://doi.org/10.1117/12.2686683
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

The magnetic levitation track uses the contact rail and the collector shoe to form a loop to provide power to the car. When there are hard points on the contact rail, they will affect the power supply process. In order to effectively supervise the height of the contact rail hard points and carry out railway maintenance in a timely manner, the effective prediction of the contact rail hard points height are achieved by constructing a BP neural network dual-channel regression model. According to the signal characteristics, determine the parameters design the parameters of the BP neural network model. Reasonably divide it into training, verification and testing data sets. Finally complete the prediction of the hard points height based on the trained model. The results show that the proposed method for predicting the height of the hard points of the contact rail based on BP neural network can realize the quantitative detection of the height of the hard points under different working conditions.

Citation Download Citation

Qingqin Yang, Qi Zhang, Zhuo Zhang, Dixiang Chen, Mengchun Pan, Wenwu Zhou, Yuan Ren, Hao Ma, and Lihui Liu "Research on hard points height prediction method based on BP neural network", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 1275936 (10 August 2023); https://doi.org/10.1117/12.2686683

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available