Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer
This paper addresses the issue of detecting welding defects in steel plates during the welding process by proposing a method that combines the laser vibrometer with transient feature extraction technology. The method employs a high-resolution laser vibrometer to collect vibration signals from excite...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/11/12/1193 |
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| author | Yu Du Xinke Xu Longbiao Zhao Dijian Yuan Jinwen Wang |
| author_facet | Yu Du Xinke Xu Longbiao Zhao Dijian Yuan Jinwen Wang |
| author_sort | Yu Du |
| collection | DOAJ |
| description | This paper addresses the issue of detecting welding defects in steel plates during the welding process by proposing a method that combines the laser vibrometer with transient feature extraction technology. The method employs a high-resolution laser vibrometer to collect vibration signals from excited weld plates, followed by feature extraction and analysis for defect detection and identification. The focus of the research is on the optimization and application of the transient extraction transform algorithm, which plays a crucial role in signal feature extraction for defect recognition. By optimizing the short-time Fourier transform, we further propose the use of the transient extraction transform algorithm to effectively characterize and extract transient components from defect signals. To validate the proposed algorithm, we compare the defect recognition performance of several algorithms using quantitative metrics such as Rényi entropy and kurtosis. The results indicate that the proposed method yields a more centralized time–frequency representation and significantly increases the kurtosis of transient components, providing a new approach for detecting welding defects in steel plates. |
| format | Article |
| id | doaj-art-caad65aa0bcf4cef813e162c90b00fe0 |
| institution | DOAJ |
| issn | 2304-6732 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj-art-caad65aa0bcf4cef813e162c90b00fe02025-08-20T02:39:41ZengMDPI AGPhotonics2304-67322024-12-011112119310.3390/photonics11121193Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser VibrometerYu Du0Xinke Xu1Longbiao Zhao2Dijian Yuan3Jinwen Wang4College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, ChinaCollege of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, ChinaNaval Research Institute, Fengtai District, Beijing 100072, ChinaCollege of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, ChinaCollege of Metrology Measurement and Instrument, China Jiliang University, Hangzhou 310018, ChinaThis paper addresses the issue of detecting welding defects in steel plates during the welding process by proposing a method that combines the laser vibrometer with transient feature extraction technology. The method employs a high-resolution laser vibrometer to collect vibration signals from excited weld plates, followed by feature extraction and analysis for defect detection and identification. The focus of the research is on the optimization and application of the transient extraction transform algorithm, which plays a crucial role in signal feature extraction for defect recognition. By optimizing the short-time Fourier transform, we further propose the use of the transient extraction transform algorithm to effectively characterize and extract transient components from defect signals. To validate the proposed algorithm, we compare the defect recognition performance of several algorithms using quantitative metrics such as Rényi entropy and kurtosis. The results indicate that the proposed method yields a more centralized time–frequency representation and significantly increases the kurtosis of transient components, providing a new approach for detecting welding defects in steel plates.https://www.mdpi.com/2304-6732/11/12/1193laser Doppler vibrometerdefect detectiontime–frequency analysistransient extraction transformation |
| spellingShingle | Yu Du Xinke Xu Longbiao Zhao Dijian Yuan Jinwen Wang Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer Photonics laser Doppler vibrometer defect detection time–frequency analysis transient extraction transformation |
| title | Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer |
| title_full | Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer |
| title_fullStr | Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer |
| title_full_unstemmed | Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer |
| title_short | Study on the Transient Extraction Transform Algorithm for Defect Detection in Welded Plates Based on Laser Vibrometer |
| title_sort | study on the transient extraction transform algorithm for defect detection in welded plates based on laser vibrometer |
| topic | laser Doppler vibrometer defect detection time–frequency analysis transient extraction transformation |
| url | https://www.mdpi.com/2304-6732/11/12/1193 |
| work_keys_str_mv | AT yudu studyonthetransientextractiontransformalgorithmfordefectdetectioninweldedplatesbasedonlaservibrometer AT xinkexu studyonthetransientextractiontransformalgorithmfordefectdetectioninweldedplatesbasedonlaservibrometer AT longbiaozhao studyonthetransientextractiontransformalgorithmfordefectdetectioninweldedplatesbasedonlaservibrometer AT dijianyuan studyonthetransientextractiontransformalgorithmfordefectdetectioninweldedplatesbasedonlaservibrometer AT jinwenwang studyonthetransientextractiontransformalgorithmfordefectdetectioninweldedplatesbasedonlaservibrometer |