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RESEARCH PAPER
Real-Time Fault Monitoring Method for Logistics Vehicles Based on Chaotic Ant Colony Algorithm
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1
Hebei Professional College of Politics Science and Law, China
 
2
Shijiazhuang Institute of Railway Technology, China
 
 
Submission date: 2024-11-22
 
 
Final revision date: 2025-01-08
 
 
Acceptance date: 2025-03-26
 
 
Online publication date: 2025-04-02
 
 
Publication date: 2025-04-02
 
 
Corresponding author
Liang Wang   

Shijiazhuang Institute of Railway Technology, China
 
 
 
HIGHLIGHTS
  • This study proposes a real-time fault monitoring method for logistics vehicles.
  • The fault signal was identified on the basis of building logistics vehicle fault tree.
  • The theory of support vector machines was employed to derive low-dimensional features.
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ABSTRACT
Abstract: To improve the safety of logistics vehicle transportation, this study proposes a real-time fault monitoring method for logistics vehicles based on chaotic ant colony algorithm. Firstly, take a typical engine malfunction as an example. Identify fault signals based on logistics vehicle fault tree. Then, use support vector machine theory to extract time-domain low dimensional features from vehicle fault information. Finally, real-time fault monitoring of logistics vehicles is achieved based on chaotic ant colony optimization algorithm. The experiment shows that the monitoring accuracy of this method is always above 94.0%, and the monitoring signal transmission delay varies between 444ms - 627ms, indicating that this method has high monitoring accuracy and efficiency, and has high application value.
eISSN:2956-3860
ISSN:1507-2711
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