A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification
According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2016/7328969 |
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| _version_ | 1832558176250101760 |
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| author | Wei Gao Kaiping Yu Ying Wu |
| author_facet | Wei Gao Kaiping Yu Ying Wu |
| author_sort | Wei Gao |
| collection | DOAJ |
| description | According to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV) method and the L-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load. |
| format | Article |
| id | doaj-art-5b6fc2fb0c28451ebe6ab39d9fa9e39c |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-5b6fc2fb0c28451ebe6ab39d9fa9e39c2025-02-03T01:33:01ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/73289697328969A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load IdentificationWei Gao0Kaiping Yu1Ying Wu2Department of Astronautic Science and Mechanics, Harbin Institute of Technology (HIT), P.O. Box 304, No. 92 West Dazhi Street, Harbin 150001, ChinaDepartment of Astronautic Science and Mechanics, Harbin Institute of Technology (HIT), P.O. Box 304, No. 92 West Dazhi Street, Harbin 150001, ChinaDepartment of Astronautic Science and Mechanics, Harbin Institute of Technology (HIT), P.O. Box 304, No. 92 West Dazhi Street, Harbin 150001, ChinaAccording to the regularization method in the inverse problem of load identification, a new method for determining the optimal regularization parameter is proposed. Firstly, quotient function (QF) is defined by utilizing the regularization parameter as a variable based on the least squares solution of the minimization problem. Secondly, the quotient function method (QFM) is proposed to select the optimal regularization parameter based on the quadratic programming theory. For employing the QFM, the characteristics of the values of QF with respect to the different regularization parameters are taken into consideration. Finally, numerical and experimental examples are utilized to validate the performance of the QFM. Furthermore, the Generalized Cross-Validation (GCV) method and the L-curve method are taken as the comparison methods. The results indicate that the proposed QFM is adaptive to different measuring points, noise levels, and types of dynamic load.http://dx.doi.org/10.1155/2016/7328969 |
| spellingShingle | Wei Gao Kaiping Yu Ying Wu A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification Shock and Vibration |
| title | A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification |
| title_full | A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification |
| title_fullStr | A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification |
| title_full_unstemmed | A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification |
| title_short | A New Method for Optimal Regularization Parameter Determination in the Inverse Problem of Load Identification |
| title_sort | new method for optimal regularization parameter determination in the inverse problem of load identification |
| url | http://dx.doi.org/10.1155/2016/7328969 |
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