Academic Journal of Computing & Information Science, 2025, 8(9); doi: 10.25236/AJCIS.2025.080905.
Chunjie Zou
Hainan Vocational University, Haikou, China
With the continuous advancement of industrial intelligence, the requirements for the stable operation of automotive production line equipment are becoming increasingly higher. Addressing the shortcomings of traditional fault warning methods, such as poor real-time performance and low accuracy, this paper takes the H automotive intelligent assembly production line as the research object. It designs an intelligent monitoring and fault early warning system for automotive production line equipment based on a sensor network, neural network clustering analysis, and a Least Squares Support Vector Machine (LS-SVM) regression model. By collecting and analyzing equipment operational data in real-time, the system improves fault warning accuracy and shortens warning response time, providing effective technical support for automotive intelligent manufacturing.
Neural Network; Fault Early Warning; Intelligent Monitoring; Support Vector Machine (SVM); Predictive Maintenance
Chunjie Zou. Intelligent Monitoring and Fault Early Warning for Automotive Production Line Equipment Based on Neural Network. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 9: 34-39. https://doi.org/10.25236/AJCIS.2025.080905.
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