Digital Twin-Driven Condition Monitoring System for Traditional Complex Machinery in Service - Weiming Yin; Yefa Hu; Guoping Ding; Xuefei Chen (Machines, 2025)
Improvement in the intelligence and reliability of traditional complex machinery in service (TCMIS) is a prerequisite to guarantee the safety and stable production of these manufacturing enterprises. Existing studies on condition monitoring of TCMIS typically suffer from an insufficient volume of data, incomplete consideration of issues, low monitoring accuracy, and lack of long-term validity. This paper proposes to utilize Digital Twin (DT) technology to construct a new generation of intelligent condition monitoring systems and take the coal mill of a coal-fired power plant as an example for practical illustration. The results of the study show that the method used in this paper is 96% for fault diagnosis, which is higher than the level in existing studies, and the practical application effect in coal-fired power plants also proves the effectiveness of this study. This study can provide program references for the development of intelligent transformation of TCMIS, and also provide technical support for the application and promotion of DT technology in this field.