Novel Fault Diagnosis Method for Rolling Bearing Based on Voiceprint Recognition With FasterNet‐CAM.
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| Title: | Novel Fault Diagnosis Method for Rolling Bearing Based on Voiceprint Recognition With FasterNet‐CAM. |
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| Authors: | Puzhou, Wang1,2 (AUTHOR), Yanghui, Lin3 (AUTHOR), Yejun, Li4 (AUTHOR), Yin, Li1 (AUTHOR), Yingkui, Gu1 (AUTHOR) guyingkui@163.com |
| Source: | Quality & Reliability Engineering International. Jul2025, Vol. 41 Issue 5, p1675-1688. 14p. |
| Subjects: | Fault diagnosis, Roller bearings, Feature extraction, Chemical apparatus, Judgment (Psychology) |
| Abstract: | Contact measuring tools are not suitable in some specific working environments, such as high temperature or chemical metallurgical equipment, when non‐contact sensors should be considered. In this study, a rolling bearing fault diagnosis method based on voiceprint recognition is proposed. The original signal is converted into a Mel‐spectrum that can characterize the voiceprint characteristics which based on the features of human hearing, the idea of partial convolution is used for further feature extraction, and then input into the enhanced FasterNet network for classification. The Group‐CAM is integrated with the FasterNet network to confirm the significant portions of the voiceprint associated with the decision, thereby conforming the validity of the model's judgment throughout the recognition process. The experimental results show that the proposed method has an accuracy of 99.4%, a reasoning time of 4.48 s, and a throughput of 223.3 fps after iteration, which is optimal in the compared experiment, indicating that the model meets the lightweight requirement and can identify the acoustic signals of faulty bearings effectively. The method also intuitively highlights the key parts of the acoustic signals, which ensures that the decision‐making process of the model is transparent and trustworthy and enhances the interpretability and reliability of the diagnostic process. [ABSTRACT FROM AUTHOR] |
| Copyright of Quality & Reliability Engineering International is the property of Wiley-Blackwell 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.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Novel Fault Diagnosis Method for Rolling Bearing Based on Voiceprint Recognition With FasterNet‐CAM. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Puzhou%2C+Wang%22">Puzhou, Wang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yanghui%2C+Lin%22">Yanghui, Lin</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yejun%2C+Li%22">Yejun, Li</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yin%2C+Li%22">Yin, Li</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yingkui%2C+Gu%22">Yingkui, Gu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> guyingkui@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Quality+%26+Reliability+Engineering+International%22">Quality & Reliability Engineering International</searchLink>. Jul2025, Vol. 41 Issue 5, p1675-1688. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Roller+bearings%22">Roller bearings</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Chemical+apparatus%22">Chemical apparatus</searchLink><br /><searchLink fieldCode="DE" term="%22Judgment+%28Psychology%29%22">Judgment (Psychology)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Contact measuring tools are not suitable in some specific working environments, such as high temperature or chemical metallurgical equipment, when non‐contact sensors should be considered. In this study, a rolling bearing fault diagnosis method based on voiceprint recognition is proposed. The original signal is converted into a Mel‐spectrum that can characterize the voiceprint characteristics which based on the features of human hearing, the idea of partial convolution is used for further feature extraction, and then input into the enhanced FasterNet network for classification. The Group‐CAM is integrated with the FasterNet network to confirm the significant portions of the voiceprint associated with the decision, thereby conforming the validity of the model's judgment throughout the recognition process. The experimental results show that the proposed method has an accuracy of 99.4%, a reasoning time of 4.48 s, and a throughput of 223.3 fps after iteration, which is optimal in the compared experiment, indicating that the model meets the lightweight requirement and can identify the acoustic signals of faulty bearings effectively. The method also intuitively highlights the key parts of the acoustic signals, which ensures that the decision‐making process of the model is transparent and trustworthy and enhances the interpretability and reliability of the diagnostic process. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Quality & Reliability Engineering International is the property of Wiley-Blackwell 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: 10.1002/qre.3750 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1675 Subjects: – SubjectFull: Fault diagnosis Type: general – SubjectFull: Roller bearings Type: general – SubjectFull: Feature extraction Type: general – SubjectFull: Chemical apparatus Type: general – SubjectFull: Judgment (Psychology) Type: general Titles: – TitleFull: Novel Fault Diagnosis Method for Rolling Bearing Based on Voiceprint Recognition With FasterNet‐CAM. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Puzhou, Wang – PersonEntity: Name: NameFull: Yanghui, Lin – PersonEntity: Name: NameFull: Yejun, Li – PersonEntity: Name: NameFull: Yin, Li – PersonEntity: Name: NameFull: Yingkui, Gu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 07488017 Numbering: – Type: volume Value: 41 – Type: issue Value: 5 Titles: – TitleFull: Quality & Reliability Engineering International Type: main |
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