Bearing fault diagnosis optimization of probabilistic neural network based on artificial jellyfish search algorithm

Xiangtong Yan; Youkun Xiong; Jian Zhang; Penghui Dong

doi:10.1117/12.2689409

7 September 2023 Bearing fault diagnosis optimization of probabilistic neural network based on artificial jellyfish search algorithm

Xiangtong Yan, Youkun Xiong, Jian Zhang, Penghui Dong

Author Affiliations +

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127903A (2023) https://doi.org/10.1117/12.2689409
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

The reliability and accuracy are low when the traditional method is used for fault diagnosis of shearer bearing. It was proposed that bearing fault diagnosis of shearer based on artificial jellyfish search (JS) optimized probabilistic neural network (PNN). The vibration signals of different states of bearings are identified and classified. The artificial jellyfish search algorithm is used to optimize the smoothing factor of the probabilistic neural network model. Finally, the optimized model is used for fault diagnosis. The experimental results show that the diagnostic accuracy of the probabilistic neural network model optimized by the artificial jellyfish search algorithm is higher than that of the traditional probabilistic neural network model and particle swarm optimization probabilistic neural network model, with an accuracy of 95.4%.

Citation Download Citation

Xiangtong Yan, Youkun Xiong, Jian Zhang, and Penghui Dong "Bearing fault diagnosis optimization of probabilistic neural network based on artificial jellyfish search algorithm", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127903A (7 September 2023); https://doi.org/10.1117/12.2689409

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