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- Title
Sliding Dispersion Entropy-Based Fault State Detection for Diaphragm Pump Parts.
- Authors
Zhou, Chengjiang; Jia, Yunhua; Bai, Haicheng; Xing, Ling; Yang, Yang
- Abstract
Aiming at the disadvantages of low trend, poor characterization performance, and poor anti-noise performance of traditional degradation features such as dispersion entropy (DE), a fault detection method based on sliding dispersion entropy (SDE) is proposed. Firstly, a sliding window is added to the signal before extracting the DE feature, and the root mean square of the signal inside the sliding window is used to replace the signal in the window to realize down sampling, which enhances the trend of DE. Secondly, the hyperbolic tangent sigmoid function (TANSIG) is introduced to map the signals to different categories when extracting the DE feature, which is more in line with the signal distribution of mechanical parts and the monotonicity of the degradation feature is improved. For noisy signal, the introduction of locally weighted scatterplot smoothing (LOWESS) can remove the burrs and fluctuations of the SDE curve, and the anti-noise performance of SDE is improved. Finally, the SDE state warning line is constructed based on the 2σ criterion, which can determine the fault warning point in time and effectively. The state detection results of bearing and check valve show that the proposed SDE improves the trend, monotonicity, and robustness of the state tracking curve, and provides a new method for fault state detection of mechanical parts.
- Subjects
ROOT-mean-squares; CHECK valves; DISPERSION (Chemistry); TANGENT function
- Publication
Coatings (2079-6412), 2021, Vol 11, Issue 12, p1536
- ISSN
2079-6412
- Publication type
Article
- DOI
10.3390/coatings11121536