Research on three-dimensional visualization monitoring and fault diagnosis method of laser cleaning equipment

In order to improve the real-time, precision and intelligence of laser cleaning equipment condition monitoring and fault alarm, a 3D visualization real-time monitoring and fault warning method based on digital twin is proposed. First, a geometric model was established using SolidWorks, lightweighted by 3DS MAX, and the construction of behavioral model was completed in Unity3D; then, a three-dimensional visualization state monitoring platform was built by using MySQL database for real-time communication of the data and mapping it to the model; then, a multi-scale one-dimensional convolutional neural network model, and take the laser cleaning equipment collaborative robot motor as the experimental object, and compare it with a variety of networks to verify the effectiveness and superiority of the model. Finally, the results are summarized and visualized in the monitoring interface to provide maintenance personnel with intuitive information to make effective maintenance decisions, providing a new way of thinking for the predictive maintenance of laser cleaning equipment.