Abstract
In view of the problems of low detection accuracy, long detection time, and inability to monitor fault data in real time in the fault detection of traditional machinery and equipment, this paper studies the identification and fault detection of industrial machinery based on the Internet of Things (IoT) technology. By using Internet of Things technology to build a mechanical equipment fault detection system, Internet of Things technology can better build diagnostic and early warning modules for the system, so as to achieve the goal of improving the accuracy of equipment fault detection, shortening equipment fault detection time, and remotely monitoring equipment. The fault detection system studied in this paper has an accuracy rate of more than 93.4% to detect different types of fault. The use of Internet of Things technology is conducive to improving the accuracy of mechanical equipment fault detection and realizing real-time monitoring of equipment data.
Reference22 articles.
1. Deep feature generating network: A new method for intelligent fault detection of mechanical systems under class imbalance;Pan;IEEE Transactions on Industrial Informatics.,2020
2. A deep adversarial transfer learning network for machinery emerging fault detection;Li;IEEE Sensors Journal.,2020
3. Fault detection and diagnosis of industrial robot based on power consumption modeling;Sabry;IEEE Transactions on Industrial Electronics.,2019
4. Fault detection of mechanical equipment failure detection using intelligent data analysis;Kovito;Journal of Systems Engineering and Information Technology, JOSEIT.,2022
5. Knowledge-based fault diagnosis in industrial Internet of Things: A survey;Chi;IEEE Internet of Things Journal.,2022