Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters
Acoustic emission (AE) can be applied to identify crack propagation and damage of materials and structures. However, few studies investigate the multifractal regularity and compressive strength prediction for concrete using AE parameters. Therefore, the major objective of this research is to perform...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/6683878 |
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| _version_ | 1832546793070526464 |
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| author | Zhiqiang Lv Annan Jiang Jiaxu Jin Xiangfeng Lv |
| author_facet | Zhiqiang Lv Annan Jiang Jiaxu Jin Xiangfeng Lv |
| author_sort | Zhiqiang Lv |
| collection | DOAJ |
| description | Acoustic emission (AE) can be applied to identify crack propagation and damage of materials and structures. However, few studies investigate the multifractal regularity and compressive strength prediction for concrete using AE parameters. Therefore, the major objective of this research is to perform multifractal analysis of damage and develop support vector machine (SVM) for strength prediction based on AE parameters. Meanwhile, fuzzy c-means (FCM) was implemented to identify damage mechanisms. The results showed that the level of damage can be revealed qualitatively and quantitatively by analyzing morphology and parameters of multifractal. In particular, the multifractal parameter α0 has the ability to identify critical damage and primary failure surface. Moreover, damage mechanisms were further distinguished by FCM. Finally, the results showed that the parameters of AE can further expand the application of AE for predicting compressive of concrete. SVM prediction results using AE parameters perform higher precision than the artificial neural network (ANN). Furthermore, a significant reduction in sample size uses AE parameters to predict concrete strength. |
| format | Article |
| id | doaj-art-2b93559c5d6949a58d1a9acbe08e8e70 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-2b93559c5d6949a58d1a9acbe08e8e702025-02-03T06:47:01ZengWileyAdvances in Civil Engineering1687-80861687-80942021-01-01202110.1155/2021/66838786683878Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission ParametersZhiqiang Lv0Annan Jiang1Jiaxu Jin2Xiangfeng Lv3School of Transportation Engineering, Dalian Maritime University, Dalian, Liaoning 116026, ChinaSchool of Transportation Engineering, Dalian Maritime University, Dalian, Liaoning 116026, ChinaSchool of Civil Engineering, Liaoning Technical University, Fuxin, Liaoning 123000, ChinaSchool of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaAcoustic emission (AE) can be applied to identify crack propagation and damage of materials and structures. However, few studies investigate the multifractal regularity and compressive strength prediction for concrete using AE parameters. Therefore, the major objective of this research is to perform multifractal analysis of damage and develop support vector machine (SVM) for strength prediction based on AE parameters. Meanwhile, fuzzy c-means (FCM) was implemented to identify damage mechanisms. The results showed that the level of damage can be revealed qualitatively and quantitatively by analyzing morphology and parameters of multifractal. In particular, the multifractal parameter α0 has the ability to identify critical damage and primary failure surface. Moreover, damage mechanisms were further distinguished by FCM. Finally, the results showed that the parameters of AE can further expand the application of AE for predicting compressive of concrete. SVM prediction results using AE parameters perform higher precision than the artificial neural network (ANN). Furthermore, a significant reduction in sample size uses AE parameters to predict concrete strength.http://dx.doi.org/10.1155/2021/6683878 |
| spellingShingle | Zhiqiang Lv Annan Jiang Jiaxu Jin Xiangfeng Lv Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters Advances in Civil Engineering |
| title | Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters |
| title_full | Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters |
| title_fullStr | Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters |
| title_full_unstemmed | Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters |
| title_short | Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters |
| title_sort | multifractal analysis and compressive strength prediction for concrete through acoustic emission parameters |
| url | http://dx.doi.org/10.1155/2021/6683878 |
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