Real-Time Fault Monitoring Method for Logistics Vehicles Based on Chaotic Ant Colony Algorithm

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.