Design and condition monitoring method of an edge computing-based intelligent bearing dust cover

Abstract

As the core component of rotating machinery, the health status of rolling bearings directly affects the safe operation of the equipment. The traditional bearing condition monitoring method relies on cloud data processing, which has problems such as high data transmission delay and bandwidth consumption, making it difficult to meet the requirements of industrial sites. To solve these problems, this paper proposes an intelligent bearing dust cover and condition monitoring system based on edge computing method. An intelligent dust-proof cover hardware structure integrating multiple sensors(vibration, temperature, speed) is designed. The data acquisition and pre-processing unit is integrated into the bearing end, and a miniaturized monitoring structure based on edge computing method is constructed to carry out feature extraction and fault diagnosis and reduce the amount of data uploaded to the cloud. This method can ensure the accuracy of fault identification and effectively improve the real-time and reliability of the monitoring system.This study provides a new technological path and research direction for predictive maintenance of equipment in industrial environments.