TY - JOUR A1 - Thöns, Sebastian A1 - Döhler, M. A1 - Long, Lijia T1 - On Damage Detection System Information for Structural Systems N2 - Damage detection systems (DDS) provide information of the structural system integrity in contrast to e.g. local information by inspections or non-destructive testing techniques. In this paper, an approach is developed and demonstrated to utilize DDS information to update the structural system reliability and to integrate this information in structural system risk and utility analyses. For this aim, a novel performance modelling of DDS building upon their system characteristics and non-destructive testing reliability is introduced. The DDS performance modelling accounts for a measurement system in combination with a damage detection algorithm attached to a structural system in the reference and damage states and is modelled with the probability of indication accounting for type I and II errors. In this way, the basis for DDS performance comparison and assessment is provided accounting for the dependencies between the damage states in a structure. For updating of the structural system reliability, an approach is developed based on Bayesian updating facilitating the use of DDS information on structural system level and thus for a structural system risk analysis. The structural system risk analysis encompasses the static, dynamic, deterioration, reliability and consequence models, which provide the basis for the system model for calculating the direct risks due to component failure and the indirect risks due to system failure. Two case studies with the developed approach demonstrate a high Value of DDS Information due to risk and expected cost reduction. KW - Damage detection KW - Value of Information KW - Structural systems KW - Damage detection uncertainty PY - 2018 U6 - https://doi.org/10.1080/10168664.2018.1459222 VL - 28 IS - 3 SP - 255 EP - 268 PB - Taylor & Francis AN - OPUS4-46964 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Thöns, Sebastian A1 - Döhler, M. ED - Del Grosso, A.E. ED - Basso, P. T1 - Structural reliability updating with stochastic subspace damage detection information T2 - EACS 2012 - Smart structures - 5th European conference on structural control CY - Genoa, Italy DA - 2012-06-18 KW - Stochastic subspace KW - Structural reliability KW - Bayesian updating KW - Probability od detection PY - 2012 SN - 978-88-95023-13-7 IS - Paper #008 SP - 1 EP - 12 PB - Erredi Grafiche Editoriali AN - OPUS4-26181 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Long, Lijia A1 - Thöns, Sebastian A1 - Döhler, M. T1 - Damage Detection and Deteriorating Structural Systems N2 - This paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented. The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural integrity and facilitating to describe the structural system performance and its functionality throughout the service life. The structural system performance is described with its functionality, its deterioration and its behavior under extreme loading. The structural system reliability given the damage detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated as the difference between the expected benefits and risks utilizing the damage detection information or not. With an application example of the developed approach based on a deteriorating Pratt truss system, the value of damage detection information is determined,demonstrating the potential of risk reduction and expected cost reduction. T2 - International Workshop on Structural Health Monitoring CY - Stanford, CA, USA DA - 12.09.2017 KW - Reliability updating KW - Structural reliability and risks KW - Damage detection KW - Value of information PY - 2017 SN - 978-1-60595-330-4 SP - 1276 EP - 1284 AN - OPUS4-43624 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Long, Lijia A1 - Thöns, Sebastian A1 - Döhler, M. T1 - The effects of SHM system parameters on the value of damage detection information N2 - This paper addresses how the value of damage detection Information depends on key Parameters of the Structural Health Monitoring (SHM) system including number of sensors and sensor locations. The Damage Detection System (DDS) provides the information by comparing ambient vibration measurements of a (healthy) reference state with measurements of the current structural system. The performance of DDS method depends on the physical measurement properties such as the number of sensors, sensor positions, measuring length and sensor type, measurement noise, ambient excitation and sampling frequency, as well as on the data processing algorithm including the chosen type I error for the indication threshold. The quantification of the value of Information (VoI) is an expected utility based Bayesian decision analysis method for quantifying the difference of the expected economic benefits with and without information. The (pre-)posterior probability is computed utilizing the Bayesian updating theorem for all possible indications. If changing any key parameters of DDS, the updated probability of system failure given damage detection information will be varied due to different indication of probability of damage, which will result in changes of value of damage detection information. The DDS system is applied in a statically determinate Pratt truss bridge girder. Through the analysis of the value of information with different SHM system characteristics, the settings of DDS can be optimized for minimum expected costs and risks before implementation. T2 - 9th European Workshop on Structural Health Monitoring CY - Manchester, UK DA - 10.07.2018 KW - SHM KW - Damage detection system KW - Value of information PY - 2018 SP - 375 EP - 384 AN - OPUS4-46190 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Long, Lijia A1 - Döhler, M. A1 - Thöns, Sebastian T1 - Determination of structural and damage detection system influencing parameters on the value of information N2 - A method to determine the influencing parameters of a structural and damage detection system is proposed based on the value of Information analysis. The value of information analysis utilizes the Bayesian pre-posterior decision theory to quantify the value of damage detection system 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 damage detection system performance, including number of sensors, sensor locations, measurement noise, and the Type-I error are investigated. The preposterior probabilistic model is computed utilizing the Bayes’ theorem to update the prior system model with the damage indication information. Finally, the value of damage detection system 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 value of information over the whole service life. Furthermore, it shows that more sensors do not necessarily lead to a higher relative value of information; only specific sensor locations near the highest utilized components lead to a high relative value of information; measurement noise and the Type-I error should be controlled and be as small as possible. An optimal sensor employment with highest relative value of information 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 damage detection system settings and sensor configuration for minimum expected Costs and risks. KW - Damage detection systems KW - Value of information KW - Deteriorating structures KW - Probability of damage indication KW - Decision theory PY - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-508083 SN - 1475-9217 SN - 1741-3168 VL - 21 IS - 1 SP - 19 EP - 36 PB - Sage Publications CY - Thousand Oaks, Calif. AN - OPUS4-50808 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -