Research on Information Matrix of Highway Electromechanical System Based on Deep Convolutional Neural Networks

Health monitoring, intelligent management and the maintenance of highway electromechanical systems are the basis and prerequisite for the control of intelligent transportation equipment. Therefore, a method of constructing and classifying the condition information matrix of highway electromechanical system based on convolutional neural network is proposed. This method converts the electric power and electrical information collected by the electromechanical power distribution group of the Taizhou Bridge Highway into an information matrix method from time series, using convolutional neural network to classify and predict subsystem faults. The results show that the data processing method of the information matrix has an efficiency optimization effect on the identification of regional faults. At the same time, the construction based on the information matrix improves the scalability of the big data maintenance of the electromechanical system.