Robot Remote Monitoring and Fault Diagnosis Based on Industrial Internet of Things

Abstract

In order to realize the remote monitoring of robots, a remote monitoring platform for industrial robots is designed based on the browser/server (B/S) architecture. Through this platform, users can check the real-time running parameters and running status of robots in any place with network. The Industrial Internet of Things scheme of remote platform system is proposed to adopt three-layer structure: on-site “perception layer,” information “transmission layer,” and remote data service center. The data acquisition controller of the whole system and the core part of the sensor layer is designed. The data acquisition controller adopts the embedded platform design, which can be directly connected with the control cabinet of the industrial robot to read the running status of the robot in real time, monitor the alarm and warning data, and it is transmitted to the local server and remote service center in the first time. At the same time, the robot can receive the control command of the server for remote debugging and fault maintenance. Aiming at the data model of industrial machinery parts, a fault prediction method based on BP neural network algorithm is proposed. According to the needs of the target algorithm and the analysis of the measurement results, an attempt is made to obtain a more feasible fault diagnosis and early warning method. Through the remote monitoring system, fault early warning and corresponding troubleshooting methods are realized.