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A Variation Model Method for Real Time System Identification in Bridge Health Monitoring

A Variation Model Method for Real Time System Identification in Bridge Health Monitoring
Author(s): , , , ,
Presented at IABSE Conference: Engineering the Past, to Meet the Needs of the Future, Copenhagen, Denmark, 25-27 June 2018, published in , pp. 360-366
DOI: 10.2749/copenhagen.2018.360
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The Structural Health Monitoring of bridge structures is becoming increasingly important. Due to new developments in the field of sensor and data processing technology, a new method will be introduc...
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Bibliographic Details

Author(s): (Institute of Construction Informatics, TU Dresden, Germany)
(Institute of Construction Informatics, TU Dresden, Germany)
(Institute of Construction Informatics, TU Dresden, Germany)
(Institute of Construction Informatics, TU Dresden, Germany)
(Institute of Construction Informatics, TU Dresden, Germany)
(Leonard, Andrä und Partner Consult, Germany)
Medium: conference paper
Language(s): English
Conference: IABSE Conference: Engineering the Past, to Meet the Needs of the Future, Copenhagen, Denmark, 25-27 June 2018
Published in:
Page(s): 360-366 Total no. of pages: 7
Page(s): 360-366
Total no. of pages: 7
DOI: 10.2749/copenhagen.2018.360
Abstract: The Structural Health Monitoring of bridge structures is becoming increasingly important. Due to new developments in the field of sensor and data processing technology, a new method will be introduced, which enables prognosis of the bridge lifespan through system identification based on the monitoring process. Therefore, the damages of the bridge, which are modelled in an appropriate damage model, will be linked with its BIM Model. The damage data will then be variated by using a separate Variation Model. Using this method results in the automatized creation of numerous input models for mass simulation. This forms the basis for a multi‐stage procedure, which identifies the structural bridge state by using the simulation results for a numerical best‐fit method. Thereby engineers can utilize the evaluated models to make more precise decisions and improve the Structural Health Monitoring of bridge structures.
Keywords:
Building Information Modeling bridge health monitoring system identification Multi Model