Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm
In this paper, a novel composite fault diagnosis method combining adaptive feature mode decomposition (FMD) and minimum noise amplitude deconvolution (MNAD) is proposed. Firstly, chaos mapping and leader mutation selection strategy were introduced to improve the Northern Goshawk algorithm (NGO), and...
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ftdoajarticles:oai:doaj.org/article:138ef8837989452db8f5237645f1f489 2023-05-15T17:43:04+02:00 Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm Sen Yu Jie Ma 2022-11-01T00:00:00Z https://doi.org/10.3390/pr10122532 https://doaj.org/article/138ef8837989452db8f5237645f1f489 EN eng MDPI AG https://www.mdpi.com/2227-9717/10/12/2532 https://doaj.org/toc/2227-9717 doi:10.3390/pr10122532 2227-9717 https://doaj.org/article/138ef8837989452db8f5237645f1f489 Processes, Vol 10, Iss 2532, p 2532 (2022) chaotic leadership Northern Goshawk optimization feature mode decomposition minimum noise amplitude deconvolution feature extraction sparse pulse and cyclicstationarity composite fault Chemical technology TP1-1185 Chemistry QD1-999 article 2022 ftdoajarticles https://doi.org/10.3390/pr10122532 2022-12-30T19:30:31Z In this paper, a novel composite fault diagnosis method combining adaptive feature mode decomposition (FMD) and minimum noise amplitude deconvolution (MNAD) is proposed. Firstly, chaos mapping and leader mutation selection strategy were introduced to improve the Northern Goshawk algorithm (NGO), and a chaotic leadership Northern Goshawk optimization (CLNGO) algorithm was proposed. The advantages of the CLNGO algorithm in convergence accuracy and speed were verified by 12 benchmark functions. Then, a new index called sparse pulse and cyclicstationarity (SPC) is proposed to evaluate signal sparsity. Finally, SPC is used as the fitness function of CLNGO to optimize FMD and MNAD. The optimal decomposition mode n and filter length of FMD, and filter length L and noise ratio <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math> of MNAD are selected. The CLNGO-FMD is used to decompose signal into different modes. The signal is reconstructed based on the kurtosis criterion and the CLNGO-MNAD method is used to reduce the noise of the reconstructed signal twice. The experimental results show that the proposed method can achieve the enhancement of weak features and the removal of noise to extract the fault feature frequency adaptively. Compared with EMD, VMD, MOMEDA, MCKD and other methods, the proposed method has better performance in fault feature frequency extraction, and it is effective for the diagnosis of single faults and composite faults. Article in Journal/Newspaper Northern Goshawk Directory of Open Access Journals: DOAJ Articles Processes 10 12 2532 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
chaotic leadership Northern Goshawk optimization feature mode decomposition minimum noise amplitude deconvolution feature extraction sparse pulse and cyclicstationarity composite fault Chemical technology TP1-1185 Chemistry QD1-999 |
spellingShingle |
chaotic leadership Northern Goshawk optimization feature mode decomposition minimum noise amplitude deconvolution feature extraction sparse pulse and cyclicstationarity composite fault Chemical technology TP1-1185 Chemistry QD1-999 Sen Yu Jie Ma Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
topic_facet |
chaotic leadership Northern Goshawk optimization feature mode decomposition minimum noise amplitude deconvolution feature extraction sparse pulse and cyclicstationarity composite fault Chemical technology TP1-1185 Chemistry QD1-999 |
description |
In this paper, a novel composite fault diagnosis method combining adaptive feature mode decomposition (FMD) and minimum noise amplitude deconvolution (MNAD) is proposed. Firstly, chaos mapping and leader mutation selection strategy were introduced to improve the Northern Goshawk algorithm (NGO), and a chaotic leadership Northern Goshawk optimization (CLNGO) algorithm was proposed. The advantages of the CLNGO algorithm in convergence accuracy and speed were verified by 12 benchmark functions. Then, a new index called sparse pulse and cyclicstationarity (SPC) is proposed to evaluate signal sparsity. Finally, SPC is used as the fitness function of CLNGO to optimize FMD and MNAD. The optimal decomposition mode n and filter length of FMD, and filter length L and noise ratio <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ρ</mi></semantics></math> of MNAD are selected. The CLNGO-FMD is used to decompose signal into different modes. The signal is reconstructed based on the kurtosis criterion and the CLNGO-MNAD method is used to reduce the noise of the reconstructed signal twice. The experimental results show that the proposed method can achieve the enhancement of weak features and the removal of noise to extract the fault feature frequency adaptively. Compared with EMD, VMD, MOMEDA, MCKD and other methods, the proposed method has better performance in fault feature frequency extraction, and it is effective for the diagnosis of single faults and composite faults. |
format |
Article in Journal/Newspaper |
author |
Sen Yu Jie Ma |
author_facet |
Sen Yu Jie Ma |
author_sort |
Sen Yu |
title |
Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
title_short |
Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
title_full |
Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
title_fullStr |
Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
title_full_unstemmed |
Adaptive Composite Fault Diagnosis of Rolling Bearings Based on the CLNGO Algorithm |
title_sort |
adaptive composite fault diagnosis of rolling bearings based on the clngo algorithm |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/pr10122532 https://doaj.org/article/138ef8837989452db8f5237645f1f489 |
genre |
Northern Goshawk |
genre_facet |
Northern Goshawk |
op_source |
Processes, Vol 10, Iss 2532, p 2532 (2022) |
op_relation |
https://www.mdpi.com/2227-9717/10/12/2532 https://doaj.org/toc/2227-9717 doi:10.3390/pr10122532 2227-9717 https://doaj.org/article/138ef8837989452db8f5237645f1f489 |
op_doi |
https://doi.org/10.3390/pr10122532 |
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Processes |
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10 |
container_issue |
12 |
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2532 |
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1766145087214977024 |