Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection
Coal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the nonstation...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/283606 |
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| author | Wei Liu Kai He Qun Gao Cheng-yin Liu |
| author_facet | Wei Liu Kai He Qun Gao Cheng-yin Liu |
| author_sort | Wei Liu |
| collection | DOAJ |
| description | Coal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the nonstationary characteristics in vibration signals of the tail boom support of the longwall mining machine in this complicated environment, the empirical mode decomposition (EMD) is used to decompose the raw vibration signals into a number of intrinsic mode functions (IMFs) by which the initial feature vector matrices can be formed automatically. By applying the SVD algorithm to the initial feature vector matrices, the singular values of matrices can be obtained and used as the input feature vectors of SVMs classifier. The analysis results of vibration signals from the tail boom support of a longwall mining machine show that the method based on EMD, SVD, and SVM is effective for coal-gangue interface detection even when the number of samples is small. |
| format | Article |
| id | doaj-art-195a7bc97e4745f2bab057c63c9d075d |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-195a7bc97e4745f2bab057c63c9d075d2025-02-03T05:59:03ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/283606283606Application of EMD-Based SVD and SVM to Coal-Gangue Interface DetectionWei Liu0Kai He1Qun Gao2Cheng-yin Liu3School of Information and Electronics Engineering, Shandong Institute of Business and Technology, Yantai 264005, ChinaSchool of Information and Electronics Engineering, Shandong Institute of Business and Technology, Yantai 264005, ChinaSchool of Information and Electronics Engineering, Shandong Institute of Business and Technology, Yantai 264005, ChinaSchool of Information and Electronics Engineering, Shandong Institute of Business and Technology, Yantai 264005, ChinaCoal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the nonstationary characteristics in vibration signals of the tail boom support of the longwall mining machine in this complicated environment, the empirical mode decomposition (EMD) is used to decompose the raw vibration signals into a number of intrinsic mode functions (IMFs) by which the initial feature vector matrices can be formed automatically. By applying the SVD algorithm to the initial feature vector matrices, the singular values of matrices can be obtained and used as the input feature vectors of SVMs classifier. The analysis results of vibration signals from the tail boom support of a longwall mining machine show that the method based on EMD, SVD, and SVM is effective for coal-gangue interface detection even when the number of samples is small.http://dx.doi.org/10.1155/2014/283606 |
| spellingShingle | Wei Liu Kai He Qun Gao Cheng-yin Liu Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection Journal of Applied Mathematics |
| title | Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection |
| title_full | Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection |
| title_fullStr | Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection |
| title_full_unstemmed | Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection |
| title_short | Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection |
| title_sort | application of emd based svd and svm to coal gangue interface detection |
| url | http://dx.doi.org/10.1155/2014/283606 |
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