Cost-based optimization of the performance of a damage detection system
2019 (English)In: Life-Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision - Proceedings of the 6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018, CRC Press/Balkema , 2019, p. 2103-2112Conference paper, Published paper (Refereed)
Abstract [en]
Situations such as the collapse of civil engineering structures can be avoided if Structural Health Monitoring (SHM) systems can detect early potential failures and timely withdraw the structure from service ahead of a likely disaster. Structural safety is the leading reason for the implementation of SHM but also noteworthy is the cost reduction associated with routine maintenance and inspection. One of the remaining obstacles to fully implement SHM systems in our infrastructure deals with justifying their economic advantage. This paper proposes a rational framework for the use of SHM in the decision making process regarding the maintenance of civil engineering structures, based on the optimal setup of the damage detection system that yields the minimum associated deployment cost. Concepts such as Bayesian Theorem, Damage Index and Receiver Operating Characteristic curve are used in the proposed framework.
Place, publisher, year, edition, pages
CRC Press/Balkema , 2019. p. 2103-2112
Keywords [en]
Cost reduction, Damage detection, Decision making, Life cycle, Structural health monitoring, Structures (built objects), Civil engineering structures, Cost-based optimization, Damage detection systems, Decision making process, Economic advantages, Receiver operating characteristic curves, Routine maintenance, Structural health monitoring (SHM), Cost engineering
National Category
Construction Management
Identifiers
URN: urn:nbn:se:kth:diva-252102ISI: 000471120402048Scopus ID: 2-s2.0-85063957299OAI: oai:DiVA.org:kth-252102DiVA, id: diva2:1340154
Conference
6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018, 28 October 2018 through 31 October 2018
Note
QC 20190802
2019-08-022019-08-022022-06-26Bibliographically approved