Academic Journal
Development and Application of a "Decomposition–Denoising"-Based Vibration-Signal Denoising System for Radial Steel Gates Under Discharge Excitation.
| Τίτλος: | Development and Application of a "Decomposition–Denoising"-Based Vibration-Signal Denoising System for Radial Steel Gates Under Discharge Excitation. |
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| Συγγραφείς: | Wang, Chen, Liu, Yakun, Wang, Wenqi, Wang, Yuan, Zhang, Di, Zhang, Kaixuan |
| Πηγή: | Applied Sciences (2076-3417); Jan2026, Vol. 16 Issue 2, p929, 23p |
| Θεματικοί όροι: | Noise control, Signal processing, Engineering, Thresholding algorithms, Signal reconstruction, Structural health monitoring, Random vibration |
| Περίληψη: | To mitigate the pervasive noise interference present in the measured vibration signals of radial steel gates and to address the limitations of conventional wavelet-threshold denoising, this study proposes a coupled "decomposition–denoising" theoretical framework for vibration-signal purification. The key novelty lies in a smooth and tunable thresholding strategy that enables controlled filtering while preserving key structural characteristics within an integrated denoising workflow. In the proposed approach, the measured signal is decomposed into intrinsic mode components using a data-driven decomposition method, noise-dominated components are identified using multiscale permutation entropy, and only these components are selectively denoised before signal reconstruction. Both qualitative and quantitative analyses conducted on synthetic signals demonstrate the effectiveness of the proposed framework and confirm the enhanced smoothness and robustness of the improved thresholding scheme. Performance is evaluated using objective measures such as signal-to-noise ratio and root-mean-square error, together with spectral-consistency checks for field measurements. Furthermore, two field-measured engineering cases involving radial steel gates substantiate the engineering applicability and generalization capability of the proposed method, showing clearer signals and more stable diagnostic-relevant indicators. Finally, the study integrates the decomposition, denoising, and parameter-selection modules into a user-oriented vibration-signal denoising system, establishing an efficient workflow for engineering signal processing and subsequent structural-health monitoring applications. [ABSTRACT FROM AUTHOR] |
| Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=20763417&ISBN=&volume=16&issue=2&date=20260115&spage=929&pages=929-951&title=Applied Sciences (2076-3417)&atitle=Development%20and%20Application%20of%20a%20%22Decomposition%E2%80%93Denoising%22-Based%20Vibration-Signal%20Denoising%20System%20for%20Radial%20Steel%20Gates%20Under%20Discharge%20Excitation.&aulast=Wang%2C%20Chen&id=DOI:10.3390/app16020929 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and Application of a "Decomposition–Denoising"-Based Vibration-Signal Denoising System for Radial Steel Gates Under Discharge Excitation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Chen%22">Wang, Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yakun%22">Liu, Yakun</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Wenqi%22">Wang, Wenqi</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Yuan%22">Wang, Yuan</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Di%22">Zhang, Di</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Kaixuan%22">Zhang, Kaixuan</searchLink> – Name: TitleSource Label: Source Group: Src Data: Applied Sciences (2076-3417); Jan2026, Vol. 16 Issue 2, p929, 23p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Noise+control%22">Noise control</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering%22">Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Thresholding+algorithms%22">Thresholding algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+reconstruction%22">Signal reconstruction</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+health+monitoring%22">Structural health monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Random+vibration%22">Random vibration</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: To mitigate the pervasive noise interference present in the measured vibration signals of radial steel gates and to address the limitations of conventional wavelet-threshold denoising, this study proposes a coupled "decomposition–denoising" theoretical framework for vibration-signal purification. The key novelty lies in a smooth and tunable thresholding strategy that enables controlled filtering while preserving key structural characteristics within an integrated denoising workflow. In the proposed approach, the measured signal is decomposed into intrinsic mode components using a data-driven decomposition method, noise-dominated components are identified using multiscale permutation entropy, and only these components are selectively denoised before signal reconstruction. Both qualitative and quantitative analyses conducted on synthetic signals demonstrate the effectiveness of the proposed framework and confirm the enhanced smoothness and robustness of the improved thresholding scheme. Performance is evaluated using objective measures such as signal-to-noise ratio and root-mean-square error, together with spectral-consistency checks for field measurements. Furthermore, two field-measured engineering cases involving radial steel gates substantiate the engineering applicability and generalization capability of the proposed method, showing clearer signals and more stable diagnostic-relevant indicators. Finally, the study integrates the decomposition, denoising, and parameter-selection modules into a user-oriented vibration-signal denoising system, establishing an efficient workflow for engineering signal processing and subsequent structural-health monitoring applications. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app16020929 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 929 Subjects: – SubjectFull: Noise control Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Engineering Type: general – SubjectFull: Thresholding algorithms Type: general – SubjectFull: Signal reconstruction Type: general – SubjectFull: Structural health monitoring Type: general – SubjectFull: Random vibration Type: general Titles: – TitleFull: Development and Application of a "Decomposition–Denoising"-Based Vibration-Signal Denoising System for Radial Steel Gates Under Discharge Excitation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Chen – PersonEntity: Name: NameFull: Liu, Yakun – PersonEntity: Name: NameFull: Wang, Wenqi – PersonEntity: Name: NameFull: Wang, Yuan – PersonEntity: Name: NameFull: Zhang, Di – PersonEntity: Name: NameFull: Zhang, Kaixuan IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 01 Text: Jan2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 16 – Type: issue Value: 2 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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