Fault Diagnosis and Condition Monitoring in Mechanical and Dynamic Systems
Summary
Fault diagnosis and condition monitoring underpin the reliability and safety of rotating machinery, automotive drivetrains, power-generation turbines and other dynamic systems. By tracking key indicators—such as vibration signatures, acoustic emissions, temperature and strain—engineers can detect early signs of wear, imbalance, misalignment or bearing defects. Contemporary approaches span model-based schemes, data-driven analytics and hybrid frameworks that fuse physical principles with machine learning. Signal-processing techniques convert raw sensor outputs into diagnostic features, while prognostic algorithms forecast remaining useful life to enable predictive maintenance. Recent advances include adaptive filtering, time–frequency decomposition and digital-twin integration, all aimed at distinguishing fault signatures under variable operating conditions. This global effort responds to mounting demand for zero-downtime operations, reduced life-cycle costs and enhanced safety across industries.
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Fault Diagnosis and Condition Monitoring in Mechanical and Dynamic Systems publication trend
The graph below shows the total number of articles in fault diagnosis and condition monitoring in mechanical and dynamic systems across all publications each year (not limited to Nature Index journals).
Technical terms
Condition monitoring: Continuous observation of machine health using sensor data to detect anomalies.
Feature extraction: Transformation of raw signals into representative metrics for diagnosis.
Variational Mode Decomposition (VMD): Adaptive technique that decomposes a signal into finite, bandwidth-limited components.
Maximum Correlation Kurtosis Deconvolution (MCKD): Method that enhances periodic impulses in a signal by optimising kurtosis.
Intrinsic Mode Function (IMF): Component of a decomposed signal possessing well-behaved instantaneous frequency characteristics.
References
- Rolling Element Fault Diagnosis Based on VMD and Sensitivity MCKD. IEEE Access (2021).
- A Review on Vibration-Based Condition Monitoring of Rotating Machinery. Applied Sciences (2022).
- A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery. Entropy (2019).
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