This research investigates the performance of an existing structural damage detection method (SDIM) when only experimentally-obtained measurement information can be used to calculate the frequency response functions used to detect damage. The development of a SDIM that can accurately identify damage while processing measurements containing realistic noise levels and overcoming experimental modeling errors would provide a robust method for identifying damage in the larger, more complex structures found in practice. The existing SDIM program, GaDamDet, uses an advanced genetic algorithm, along with a two-dimensional finite element model of the structure, to identify the location and the severity of damage using the linear vibration information contained in frequency response functions (FRF) as response signatures. Datagen is a Matlab program that simulates the three-dimensional dynamic response of the four-story, two-bay by two-bay UBC test structure built at the University of British Columbia. The dynamic response of the structure can be obtained for a range of preset damage cases or for any user-defined damage case. Datagen can be used to provide the FRF measurement information for the three-dimensional test structure. Therefore, using the FRF measurements obtained from the UBC test structure allows for a more realistic evaluation of the performance of the SDIM provided by GaDamDet as the impact on performance of more realistic noise and model errors can be investigated. Previous studies evaluated the performance of the SDIM using only simulated FRF measurements obtained from a two-dimensional structural model. In addition, the disparity between the two-dimensional model used by the SDIM used to identify damage and the measurements obtained from the three-dimensional test structure is analyzed. The research results indicate that the SDIM is able to accurately detect structural damage to individually damaged members or to within a damaged floor, with few false damages identified. The SDIM provides an easy to use, visual, and accurate algorithm and its performance compares favorably to performance of the various damage detection algorithms that have been proposed by researchers to detect damage in the three-dimensional structural benchmark problem.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/3129 |
| Date | 12 April 2006 |
| Creators | Dincal, Selcuk |
| Contributors | Raich, Anne M., Anand, N.K., Jones, L. Harry |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis, text |
| Format | 3226084 bytes, electronic, application/pdf, born digital |
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