Research on Intelligent Maintenance Technology for Industrial Internet Equipment

With the integration of the new generation of information technology and traditional industries, industrial Internet equipment is moving towards automation and intelligence. The rapid development of information technology has also brought many security and management challenges. Research on industrial Internet intelligent security operation and maintenance technology can effectively improve the reliability and operation efficiency of equipment and reduce labor costs. This paper takes the rotating bearing equipment as an example, uses random forest and other algorithms to evaluate the equipment safety decline state, and uses the long-short-term neural network model (LSTM) to predict the degradation state of the equipment, and uses less resources for equipment operation and maintenance to avoid failures lead to serious consequences. At the same time, the classification model can resist false data injection to some extent, which shows the effectiveness of the work in this paper.