Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM
The axial length of pipe defects is not linear with the reflection coefficient, which is difficult to identify the axial length of the defect by the reflection coefficient method. Continuous Hidden Markov Model (CHMM) is proposed to accurately classify the axial length of defects, achieving the obje...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2016-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20165906001 |
| _version_ | 1818645635702718464 |
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| author | Chen Le Wang Yuemin Geng Haiquan Deng Wenli Ye Wei |
| author_facet | Chen Le Wang Yuemin Geng Haiquan Deng Wenli Ye Wei |
| author_sort | Chen Le |
| collection | DOAJ |
| description | The axial length of pipe defects is not linear with the reflection coefficient, which is difficult to identify the axial length of the defect by the reflection coefficient method. Continuous Hidden Markov Model (CHMM) is proposed to accurately classify the axial length of defects, achieving the objective of preliminary quantitative evaluation. Firstly, wavelet packet decomposition method is used to extract the characteristic information of the guided wave signal, and Kernel Sliced Inverse Regression (KSIR) method is used to reduce the dimension of feature set. Then, a variety of CHMM models are trained for classification. Finally, the trained models are used to identify the artificial corrosion defects on the outer surface of the pipe. The results show that the CHMM model has better robustness and can accurately identify the axial defects. |
| first_indexed | 2024-12-17T00:33:53Z |
| format | Article |
| id | doaj.art-637faf2d127e4b028c853da04b2433b8 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-17T00:33:53Z |
| publishDate | 2016-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-637faf2d127e4b028c853da04b2433b82022-12-21T22:10:12ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01590600110.1051/matecconf/20165906001matecconf_icfst2016_06001Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMMChen LeWang YueminGeng HaiquanDeng WenliYe WeiThe axial length of pipe defects is not linear with the reflection coefficient, which is difficult to identify the axial length of the defect by the reflection coefficient method. Continuous Hidden Markov Model (CHMM) is proposed to accurately classify the axial length of defects, achieving the objective of preliminary quantitative evaluation. Firstly, wavelet packet decomposition method is used to extract the characteristic information of the guided wave signal, and Kernel Sliced Inverse Regression (KSIR) method is used to reduce the dimension of feature set. Then, a variety of CHMM models are trained for classification. Finally, the trained models are used to identify the artificial corrosion defects on the outer surface of the pipe. The results show that the CHMM model has better robustness and can accurately identify the axial defects.http://dx.doi.org/10.1051/matecconf/20165906001 |
| spellingShingle | Chen Le Wang Yuemin Geng Haiquan Deng Wenli Ye Wei Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM MATEC Web of Conferences |
| title | Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM |
| title_full | Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM |
| title_fullStr | Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM |
| title_full_unstemmed | Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM |
| title_short | Quantitative Evaluation of Defect Based on Ultrasonic Guided Wave and CHMM |
| title_sort | quantitative evaluation of defect based on ultrasonic guided wave and chmm |
| url | http://dx.doi.org/10.1051/matecconf/20165906001 |
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