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Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm
Joint Authors
Xiao, Maohua
Wang, Weichen
Wang, Kaixin
Zhang, Hengtong
Zhang, Wei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-03
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
With the rapid development of high-power tractor, the fault diagnosis of high-power tractor has become more and more important for ensuring the operating safety and efficiency.
PSO is an iterative optimization evolutionary algorithm, which can iterate through different particles to find the optimal solution.
However, there is only one population in the standard PSO algorithm, and the information exchange between the populations is relatively single, which can easily lead to the stagnation of the development of the population.
In this paper, due to high-power tractor diesel engine fault complexity, fault correlation, and multifault concurrency, a multigroup coevolution particle swarm optimization BP neural network for diesel engine fault diagnosis method was proposed.
First, the USB-CAN device was used to collect data of 8 items of the diesel engine under five different working conditions, and the data was parsed through the SAE J1939 protocol; then, the BP neural network was reconstructed, and a competitive multiswarm cooperative particle swarm optimizer algorithm (COM-MCPSO) was used to optimize its structure and weights.
Finally, the data of optimized neural network under five different fault conditions show that, compared with BP neural network and PSO optimized BP neural network, the fault diagnosis of COM-MCPSO optimized BP neural network not only improves the network training speed, but also enhances generalization ability and improves recognition accuracy.
American Psychological Association (APA)
Xiao, Maohua& Wang, Weichen& Wang, Kaixin& Zhang, Wei& Zhang, Hengtong. 2020. Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm. Shock and Vibration،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1212753
Modern Language Association (MLA)
Xiao, Maohua…[et al.]. Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm. Shock and Vibration No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1212753
American Medical Association (AMA)
Xiao, Maohua& Wang, Weichen& Wang, Kaixin& Zhang, Wei& Zhang, Hengtong. Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1212753
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212753