Rotating Machinery Fault Diagnosis Under Time-Varying Speeds: A Review
Beijing University of Technology · Beijing University of Chemical Technology
Abstract
Rotating machinery often works under time-varying speeds, and nonstationary conditions as well as harsh environments make its key parts, such as rolling bearings and gears, prone to faults. Therefore, a number of fault diagnosis methods including nonstationary signal processing methods and data-driven methods have been developed. This paper presents a comprehensive review on the fault diagnosis of rotating machinery under time-varying speeds proposed mainly during the last five years. First, spectrum analysis-based methods, including order tracking, cyclic spectrum correlation and generalized demodulation, are reviewed. Second, the time-frequency analysis (TFA) methods in machinery fault diagnosis are divided…
Citation impact
- FWCI
- 33.41
- Percentile
- 100%
- References
- 210
Authors
3Topics & keywords
- Fault (geology)
- Time–frequency analysis
- Feature extraction
- Computer science
- Signal processing
- Control engineering
- Demodulation
- Engineering