Group Intelligence Perception Applied in the Electromechanical Equipment Fault Intelligent Diagnosis Support System

Abstract

The paper designs a fault diagnosis and monitoring system for electromechanical equipment based on group intelligence perception technology. The system uses the Internet of Things technology to establish a fault feature selection and fault diagnosis model for electromechanical equipment. At the same time, the system uses micro-electromechanical system sensors to realize real-time monitoring of electromechanical equipment, and realizes the collection and upload of status data and fault data of base electromechanical equipment. The design of this system allows all parties involved in electromechanical equipment such as users, manufacturers, maintainers, and industry experts to break through the constraints of time and space. All relevant parties can communicate in real time on the problems of the equipment, so that the electromechanical equipment can be more efficiently automated and intelligently maintained.