Research on noise reduction method of centrifugal pump coupling fault signal based on LMD-FE-IWT

Abstract Aiming at the problem that the coupling fault signal of centrifugal pump presents the complexity of mutual coupling due to the mutual influence of various fault components, and it is easy to be affected by the surrounding environmental noise, which leads to the difficulty of noise reduction, the LMD-FE-IWT noise reduction method is proposed. This method first utilizes local mean decomposition (LMD) to adaptively decompose the vibration signal, and calculates the fuzzy entropy of each component. According to fuzzy entropy, the components are divided into two categories: disordered and ordered. After the improved wavelet threshold denoising of the disordered component, it is reconstructed with the ordered component to achieve the denoising effect. By analying the simulation signal and experimental data, the results show that, the proposed method outperforms other methods, with improvements in signal-to-noise ratio by 55.95%, 48.86%, and 31.71% for the simulation signal noise reduction. The effect is significant, enabling the effective extraction of characteristic frequencies associated with different faults for the experimental signal noise reduction.

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Publication Details

Journal
Measurement Science and Technology
Published
2024-10-17
DOI
https://doi.org/10.1088/1361-6501/ad880f
Citations
2
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.66
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Research on noise reduction method of centrifugal pump coupling fault signal based on LMD-FE-IWT

Houlin Liu, Wen Qiang Xu, Liang Dong, Li Xiao et al.
2 citations
Measurement Science and Technology
Advanced Sensor and Control Systems
0.66
article

Research on noise reduction method of centrifugal pump coupling fault signal based on LMD-FE-IWT

Houlin Liu, Wen Qiang Xu, Liang Dong, Li Xiao, Ma Haochen
article en
2 citations

Abstract

Abstract Aiming at the problem that the coupling fault signal of centrifugal pump presents the complexity of mutual coupling due to the mutual influence of various fault components, and it is easy to be affected by the surrounding environmental noise, which leads to the difficulty of noise reduction, the LMD-FE-IWT noise reduction method is proposed. This method first utilizes local mean decomposition (LMD) to adaptively decompose the vibration signal, and calculates the fuzzy entropy of each component. According to fuzzy entropy, the components are divided into two categories: disordered and ordered. After the improved wavelet threshold denoising of the disordered component, it is reconstructed with the ordered component to achieve the denoising effect. By analying the simulation signal and experimental data, the results show that, the proposed method outperforms other methods, with improvements in signal-to-noise ratio by 55.95%, 48.86%, and 31.71% for the simulation signal noise reduction. The effect is significant, enabling the effective extraction of characteristic frequencies associated with different faults for the experimental signal noise reduction.

Measurement Science and TechnologyVol. 36(1)
Jiangsu University (CN), Jiangsu University of Science and Technology (CN)
Openalex Percentile: Top 29%
Advanced Sensor and Control Systems
0.66
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