A state of the art in digital twin for intelligent fault diagnosis

Abstract

The intelligent manufacturing and digital technologies have rapidly advanced with the advent of the industry 4.0 era, placing higher demands on the stability, reliability, and safety of industrial equipment. Fault diagnosis (FD), a crucial step ensuring the regular operations, its accuracy and efficiency directly influence the stable operation of the equipment and economic benefits. With the progress of the artificial intelligence (AI) technology, data-driven FD methods have been developing in the area of intelligence, i.e., the intelligent fault diagnosis (IFD). Recently, a new solution is provided for IFD. That is the digital twin (DT), a technology serving as a bridge connecting the physical and virtual worlds. Numerous researchers have published studies on the use of DT technology for IFD of equipment. This paper analyzes 260 articles from 2017 to 2024, offering a systematic discussion of DT, IFD, and the application of DT in IFD. Firstly, the concepts, key technologies, and application scenarios of DT and IFD are described in detail; then, the application of DT technology in the field of IFD is emphasized; finally, this paper summarizes the existing problems and challenges, puts forward suggestions to solve the issues, and looks forward to the future development. This work is expected to provide valuable references and utilization for researchers in related fields, as well as, promoting the further development and application of DT technology in the IFD domain.