Fault Diagnosis for Rotating Machinery Based on Dimensionless Indices: Current Status, Development, Technologies, and Future Directions

Operational safety and reliability have become increasingly paramount in large and complex rotating machinery in industrial manufacturing. Recent strides in data-driven fault diagnosis have significantly advanced the fields of machinery health assessment, fault identification, and prediction. This review delves into the existing literature on fault diagnosis technology for rotating machinery, categorizing the various diagnostic approaches. It further examines the evolution of fault diagnosis technology based on dimensionless indices and elucidates the five latest progressions of foundational theories: the design and optimization of dimensionless indices, extraction and features of mutual dimensionless indices, fault diagnosis technology based on dimensionless indices and artificial immune system, fusion technology of dimensionless indices in time and frequency domains, and datasets. The applications of fault diagnosis technology based on dimensionless indices in the petrochemical industry, high-speed railway, shipping and aerospace are discussed. Future directions for research are outlined across six key areas: more excellent dimensionless indices, rapid and efficient detectors, fault analysis for small-sample fault events, theoretical systems of time–frequency domain fusion diagnosis, fault diagnosis with standardized test database, and expert knowledge base. This comprehensive review bridges the research gap by systematically examining the roles and applications of dimensionless indices in the fault diagnosis of rotating machinery.