Fault Diagnosis of Rotating Machinery: A Review and Bibliometric Analysis

• Main Authors: Jiayu Chen, Cuiying Lin, Di Peng, Hongjuan Ge
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Reliability and maintainability; prognostics and health management; condition-based maintenance; bibliometric and network analysis
• Online Access: https://ieeexplore.ieee.org/document/9290017/

Fault diagnosis of rotating machinery (FDRM) has attracted continuous attention because of its great importance to industrial engineering, promoting the healthy and prosperous development of the field. A large number of literature reviews on FDRM have been reported, including signal processing methods in FDRM; artificial intelligence techniques in FDRM; fault diagnosis of bearings, gearboxes and induction motors; and others with broader areas of focus. Using bibliometric techniques, this paper provides objective insight and presents a comprehensive review of FDRM. The review begins with rigorous bibliometric analyses of 2532 published studies. These analyses enable mapping the scope and structure of the discipline, discovering the established collaboration patterns among countries and institutions, and identifying authoritative papers and authors. In addition, a deep analysis of the co-citation network allows graphically classifying the key research topics, illustrating their evolution over time, and identifying the current research interests and potential future research directions. The findings in this paper provide an overall picture of the development of FDRM from 1998 to 2019 and a robust roadmap for future investigations in this field.