1. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710049, China 2. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
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.
Flaw detection; distance and thickness measurements
Exact and efficient
Limited by the shapes of surfaces and the density or consistency of the material
Acoustic emission (AE) sensor
Crack growth, friction, delamination and matrix cracking detection
Detect, locate and characterize damage
Changes in physical properties only
Magnetic sensor
Speed, motion and position measurements; crack or large deformation detection with magnetic leakage
Efficient
Magnetic field required; expensive
Eddy-current transducer
Displacement, distance and position, oscillation and vibration measurements
Useful for demanding industrial environments; high resolution and temperature stability; high-frequency response
Only for electrically conductive materials; expensive
Accelerometer
Shock, vibration and acceleration measurements
High-frequency response; simple and reliable
Expensive
Strain gauge
Deformation and strain measurements
Cheap
Low-frequency response
Shape memory alloy
Deformation detection; active control
Fast response to change in temperature
Low-frequency response; structural fatigue and functional fatigue
Laser interferometer
Derivation or displacement measurements
High precision
Very expensive
Fiber-optic sensor
Strain, displacement, pressure and temperature measurements
Small size; high precision; immune to electromagnetic interference
Expensive
Electromagnetic acoustic transducer
Flaw detection; thickness measurements
Useful for automated inspection, and hot, cold, clean, or dry environments
Limited to metallic or magnetic products; low transduction efficiency
Piezoelectric lead zirconate titanate (PZT) element
Active sensor; vibration and crack detection
High-frequency response; cheap
Cannot be used for truly static measurements; drop in internal resistance and sensitivity at elevated temperature
PZT paint/polyvinylidene fluoride (PVDF) piezoelectric films
Vibration and crack detection
High-frequency response; cheap
Drop in internal resistance and sensitivity at elevated temperature
Laser Doppler velocimetry (LDV)
Velocity measurement
Absolute, linear with velocity and requires no pre-calibration; non-contact measurement
Expensive
Digital image correlation (DIC)
Deformation, displacement, strain, and optical flow measurements
Ease of implementation and use; non-contact measurement
? Cannot measure existing damage
Tab.1
Fig.5
Fig.6
Fig.7
Fig.8
Fig.9
Grant number
Principal investigator
Employer
Amount of award/(106 CNY)
Study period
51035007
Zhengjia HE
Xi’an Jiaotong University
2.5
2011.1–2014.12
51035008
Yimin SHAO
Chongqing University
2.4
2011.1–2014.12
51135001
Jinji GAO
Beijing University of Chemical Technology
2.9
2012.1–2016.12
51335006
Fulei CHU
Tsinghua University
3.2
2014.1–2018.12
51435006
Xuedong CHEN
Huazhong University of Science and Technology
3.2
2015.1–2019.12
51535009
Geng LIU
Northwestern Polytechnical University
2.8
2016.1–2020.12
51635004
Shuyun JIANG
Southeast University
2.8
2017.1–2021.12
51421004
Jing LIN
Xi’an Jiaotong University
12.0
2015.1–2020.12
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