Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification
Modal parameter identification is considered to be one of the most important tasks in structural health monitoring because it provides a reliable reference for structural vibration control, damage severity, and operational state. Moreover, at present, the combined deterministic-stochastic subspace a...
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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: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/8855162 |
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| _version_ | 1832546893472727040 |
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| author | Peng Wen Inamullah Khan Jie He Qiaofeng Chen |
| author_facet | Peng Wen Inamullah Khan Jie He Qiaofeng Chen |
| author_sort | Peng Wen |
| collection | DOAJ |
| description | Modal parameter identification is considered to be one of the most important tasks in structural health monitoring because it provides a reliable reference for structural vibration control, damage severity, and operational state. Moreover, at present, the combined deterministic-stochastic subspace algorithm is cogitated as one of the key algorithms in the modal parameter identification, which is why it is widely used in the modal parameter identification of bridge structures. In this paper, a novel method is proposed, which is a time-domain identification algorithm, based on sliding window-fuzzy C-means clustering algorithm-combined with deterministic-stochastic subspace identification (SC-CDSI), to achieve online intelligent tracking and identification of modal parameters for nonlinear time-varying structures. First of all, to realize the online tracking and identification process, it is necessary to divide the input and output signal of the nonlinear time-varying structure by windowing; for that, to determine the window function, window size and window step length according to the characteristics of the signal are analyzed. Secondly, in order to satisfy the intelligent identification of effective modals in stability diagram, the fuzzy C-means clustering algorithm is kept as a base, whereas frequency, damping ratio, and modal shapes serve as clustering elements, applied to fuzzy C-means clustering algorithm, and then the intelligent selection of effective modals is achieved. Finally, a shaking table test bridge is used as a modal parameter identification in lab, and its results are compared with the MIDAS finite element results. The compared results show that the proposed SC-CDSI identification algorithm can accurately achieve the intelligent identification of online tracking of the structural frequency, and the identification results are reliable to be used in real-life bridge structures. |
| format | Article |
| id | doaj-art-99a0f15f16d9434a8fa4e1cc1d8d332e |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-99a0f15f16d9434a8fa4e1cc1d8d332e2025-02-03T06:46:44ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/88551628855162Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter IdentificationPeng Wen0Inamullah Khan1Jie He2Qiaofeng Chen3Bridge Engineering Department, Southwest Jiaotong University, Chengdu, ChinaSchool of Civil Engineering, National University of Sciences and Technology, Islamabad, PakistanChina Railway Eryuan Engineering Group. Co. Ltd, Chengdu, ChinaBridge Engineering Department, Southwest Jiaotong University, Chengdu, ChinaModal parameter identification is considered to be one of the most important tasks in structural health monitoring because it provides a reliable reference for structural vibration control, damage severity, and operational state. Moreover, at present, the combined deterministic-stochastic subspace algorithm is cogitated as one of the key algorithms in the modal parameter identification, which is why it is widely used in the modal parameter identification of bridge structures. In this paper, a novel method is proposed, which is a time-domain identification algorithm, based on sliding window-fuzzy C-means clustering algorithm-combined with deterministic-stochastic subspace identification (SC-CDSI), to achieve online intelligent tracking and identification of modal parameters for nonlinear time-varying structures. First of all, to realize the online tracking and identification process, it is necessary to divide the input and output signal of the nonlinear time-varying structure by windowing; for that, to determine the window function, window size and window step length according to the characteristics of the signal are analyzed. Secondly, in order to satisfy the intelligent identification of effective modals in stability diagram, the fuzzy C-means clustering algorithm is kept as a base, whereas frequency, damping ratio, and modal shapes serve as clustering elements, applied to fuzzy C-means clustering algorithm, and then the intelligent selection of effective modals is achieved. Finally, a shaking table test bridge is used as a modal parameter identification in lab, and its results are compared with the MIDAS finite element results. The compared results show that the proposed SC-CDSI identification algorithm can accurately achieve the intelligent identification of online tracking of the structural frequency, and the identification results are reliable to be used in real-life bridge structures.http://dx.doi.org/10.1155/2021/8855162 |
| spellingShingle | Peng Wen Inamullah Khan Jie He Qiaofeng Chen Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification Shock and Vibration |
| title | Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification |
| title_full | Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification |
| title_fullStr | Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification |
| title_full_unstemmed | Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification |
| title_short | Application of Improved Combined Deterministic-Stochastic Subspace Algorithm in Bridge Modal Parameter Identification |
| title_sort | application of improved combined deterministic stochastic subspace algorithm in bridge modal parameter identification |
| url | http://dx.doi.org/10.1155/2021/8855162 |
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