Uncertainties encompassing predictive models of concrete bridges make it difficult to decidethe timing of management activities. A methodology has been developed by the authors that use data obtained through proactive health monitoring of systems to increase the confidence in predicted performance by reduc-ing the associated uncertainties. The extent of deterioration varies considerably at different locations due tothe spatial and temporal effects of various deterioration variables involved. This limitation can be overcome by the use of sensors at various locations. Multiple sensors can also be used to increase the robustness / re-dundancy of the monitoring system at critical areas. This paper describes the development of updating proce-dures for the two mentioned scenarios, incorporating the information from multiple sensors (at different loca-tions of a system or its members) with a view of predicting the performance of the entire monitored domain with increased confidence. The advantages and limitations of the two approaches are discussed along with the scenarios where these approaches are applicable. The results for both of the cases are presented in terms of thenumber of sensors and how they influence the statistical properties of predicted performance.
|Title of host publication||Safety and Reliability of Engineering Systems and Structures|
|Subtitle of host publication||ICOSSAR 2005|
|Editors||G Augusti, G. I. Schueller, M Ciampoli|
|Number of pages||8|
|Publication status||Published - 2005|
- Bayesian updating
- Structural health monitoring
- systems performance
- predictive models
Rafiq, M. I., Chryssanthopoulos, M., & Onoufriou, T. (2005). The role of proactive health monitoring in performance prediction: A systems approach. In G. Augusti, G. I. Schueller, & M. Ciampoli (Eds.), Safety and Reliability of Engineering Systems and Structures : ICOSSAR 2005 IOS Press.