Basic research on machinery fault diagnostics: Past, present, and future trends
Базовые исследования по диагностике неисправностей машин: прошлое, настоящее и будущие тенденции
2017-11-06
SCID: 54.1/2p6us3fx
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fault mechanismintelligent diagnosticsmachinery fault diagnosissensor technique and signal acquisitionsignal processing
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Abstract (AI)
Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.
Key Findings
1
High-value machineries require condition monitoring and fault diagnosis to ensure designed functions and performance throughout their lifetime.
2
Machinery fault diagnosis research has rapidly grown in recent years due to increasing machinery complexity and scale.
3
The paper identifies future trends and challenges in basic theory and practical engineering applications of machinery fault diagnosis.
4
The paper organizes recent R&D trends into four main areas: fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics.
5
The review highlights special contributions of Chinese scholars to the field of machinery fault diagnostics.
Research Object
Machinery fault diagnosis (the field/system of diagnosing faults in engineering machines and high-value machineries)
Research Subject
Core research aspects and trends in machinery fault diagnosis: fault mechanisms, sensor and signal acquisition techniques, signal processing methods, and intelligent diagnostic approaches including their basic theory and practical engineering applications
Publication Details
Publication Date
2017-11-06
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