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Structural Health Monitoring
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Determination of structural and damage detection system influencing parameters on the value of information

Authors: Lijia Long; Michael Döhler; Sebastian Thöns;

Determination of structural and damage detection system influencing parameters on the value of information

Abstract

A method to determine the influencing parameters of a structural and Damage Detection System (DDS) is proposed based on the Value of Information (VoI) analysis. The VoI analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of DDS for the structural integrity management during service life. First the influencing parameters of the structural system, such as deterioration type and rate are introduced for the performance of the prior probabilistic system model. Then the influencing parameters on the DDS performance, including number of sensors, sensor locations, measurement noise and the Type I error are investigated. The pre-posterior probabilistic model is computed utilizing the Bayes' theorem to update the prior system model with the damage indication information. Finally, the value of DDS is quantified as the difference between the maximum utility obtained in pre-posterior and prior analysis based on the decision tree analysis, comprising structural probabilistic models, consequences, as well as benefit and costs analysis associated with and without monitoring. With the developed approach, a case study on a statically determinate Pratt truss bridge girder is carried out to validate the method. The analysis shows that the deterioration rate is the most sensitive parameter on the effect of relative VoI over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative VoI; only specific sensor locations near the highest utilized components lead to a high relative VoI; measurement noise and the Type I error should be controlled and be as small as possible. An optimal sensor employment with highest relative VoI is found. Moreover, it is found that the proposed method can be a powerful tool to develop optimal service life maintenance strategies-before implementation-for similar bridges and to optimize the DDS settings and sensor configuration for minimum expected costs and risks.

International audience

Countries
France, Denmark, France
Subjects by Vocabulary

Microsoft Academic Graph classification: Computer science Decision theory Structural system Decision tree computer.software_genre Value of information System model Probabilistic logic Statistical model Data mining computer Type I and type II errors

Keywords

Value of information, Biophysics, Decision theory, Probability of damage indication, Damage detection systems, decision theory, Deteriorating structures, [STAT.AP]Statistics [stat]/Applications [stat.AP], Mechanical Engineering, probability of damage indication, deteriorating structures, value of information, [SPI.GCIV.DV]Engineering Sciences [physics]/Civil Engineering/Dynamique, vibrations

15 references, page 1 of 2

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Pozzi M and Kiureghian AD. Assessing the Value of Information for Long-Term Structural Health Monitoring. Health monitoring of structural and biological systems 2011. San Diego, California, United States2011.

Thö ns S and Faber MH. Assessing the value of structural health monitoring. Safety, Reliability, Risk and Life-cycle Performance of Structures and Infrastructures 2013.

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    16
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
16
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187
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