Industrial mechanical equipment fault detection and high-performance data analysis technology based on the Internet of Things

Issue title: High-Performance Computing

Guest editors: Achyut Shankar

Article type: Research Article

Authors: Ding, Dawei

Affiliations: Independent Scholar, China | E-mail: m13853338501@163.com

Correspondence: [*] Corresponding author: Independent Scholar, China. E-mail: m13853338501@163.com.

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.

Keywords: Equipment fault detection, industrial machinery, Internet of Things technology, neural network algorithm, energy consumption

DOI: 10.3233/IDT-240177

Journal: Intelligent Decision Technologies, vol. 18, no. 4, pp. 3171-3184, 2024