Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation
A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown struct...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/9301876 |
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| _version_ | 1832550144851050496 |
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| author | Huili Xue Kun Lin Yin Luo Hongjun Liu |
| author_facet | Huili Xue Kun Lin Yin Luo Hongjun Liu |
| author_sort | Huili Xue |
| collection | DOAJ |
| description | A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. It can be found from the identification results that the proposed method can identify the wind load from limited measurement of acceleration responses with good accuracy and stability, indicating that it is an effective approach for estimating wind load on building structures. |
| format | Article |
| id | doaj-art-71d08016ec0442778aec0ab6be0c99a4 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-71d08016ec0442778aec0ab6be0c99a42025-02-03T06:07:32ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/93018769301876Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased EstimationHuili Xue0Kun Lin1Yin Luo2Hongjun Liu3Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, ChinaShenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, ChinaShenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, ChinaShenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, ChinaA minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. It can be found from the identification results that the proposed method can identify the wind load from limited measurement of acceleration responses with good accuracy and stability, indicating that it is an effective approach for estimating wind load on building structures.http://dx.doi.org/10.1155/2017/9301876 |
| spellingShingle | Huili Xue Kun Lin Yin Luo Hongjun Liu Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation Shock and Vibration |
| title | Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation |
| title_full | Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation |
| title_fullStr | Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation |
| title_full_unstemmed | Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation |
| title_short | Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation |
| title_sort | time varying wind load identification based on minimum variance unbiased estimation |
| url | http://dx.doi.org/10.1155/2017/9301876 |
| work_keys_str_mv | AT huilixue timevaryingwindloadidentificationbasedonminimumvarianceunbiasedestimation AT kunlin timevaryingwindloadidentificationbasedonminimumvarianceunbiasedestimation AT yinluo timevaryingwindloadidentificationbasedonminimumvarianceunbiasedestimation AT hongjunliu timevaryingwindloadidentificationbasedonminimumvarianceunbiasedestimation |