Performance reliability evaluation of the feature vector in one-dimensional components based on the grey system theory
According to the selection and evaluation of low strain stress wave signal feature for one-dimensional components damage detection, define the quantitative information entropy based on probability theory and mathematical statistical theory and information entropy, build the feature vector of stress...
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Published in | 2015 12th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Vol. 1; pp. 207 - 211 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.07.2015
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Abstract | According to the selection and evaluation of low strain stress wave signal feature for one-dimensional components damage detection, define the quantitative information entropy based on probability theory and mathematical statistical theory and information entropy, build the feature vector of stress wave signal with the quantitative information entropy based on the time-window, by using the multi-parameter correlation analysis method of the grey system theory, raise the evaluation model of feature vector. This method is tested using stress wave of pile detection, the experimental results show that the feature vector of the quantitative information entropy has advantages in synthetic performance. The evaluation method raised in this paper can be widely applied to detect damage and defects of one-dimensional components like pile foundations, beam structures and mechanical rotators. |
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AbstractList | According to the selection and evaluation of low strain stress wave signal feature for one-dimensional components damage detection, define the quantitative information entropy based on probability theory and mathematical statistical theory and information entropy, build the feature vector of stress wave signal with the quantitative information entropy based on the time-window, by using the multi-parameter correlation analysis method of the grey system theory, raise the evaluation model of feature vector. This method is tested using stress wave of pile detection, the experimental results show that the feature vector of the quantitative information entropy has advantages in synthetic performance. The evaluation method raised in this paper can be widely applied to detect damage and defects of one-dimensional components like pile foundations, beam structures and mechanical rotators. |
Author | Liu Yumei Wagan, Raja Asif Kang Weixin Li Jingde |
Author_xml | – sequence: 1 surname: Kang Weixin fullname: Kang Weixin organization: College of Information and Communication Engineering, Harbin Engineering University, 150001, China – sequence: 2 surname: Li Jingde fullname: Li Jingde organization: College of Information and Communication Engineering, Harbin Engineering University, 150001, China – sequence: 3 surname: Liu Yumei fullname: Liu Yumei organization: College of Information and Communication Engineering, Harbin Engineering University, 150001, China – sequence: 4 givenname: Raja Asif surname: Wagan fullname: Wagan, Raja Asif organization: College of Information and Communication Engineering, Harbin Engineering University, 150001, China |
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Snippet | According to the selection and evaluation of low strain stress wave signal feature for one-dimensional components damage detection, define the quantitative... |
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SubjectTerms | evaluation Feature extraction Information entropy Reliability Strain Stress the grey system theory the quantitative information entropy time-window Wavelet packets |
Title | Performance reliability evaluation of the feature vector in one-dimensional components based on the grey system theory |
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