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 JF - Structural health monitoring 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 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-508083 DO - https://doi.org/10.1177/1475921719900918 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 - TY - GEN A1 - Farhan, Muhammad A1 - Schneider, Ronald A1 - Thöns, Sebastian T1 - Corrigendum to Predictive information and maintenance optimization based on decision theory: a case study considering a welded joint in an offshore wind turbine support structure T2 - Structural health monitoring N2 - This article has been revised and republished due to substantial changes to the text of the original article, as published Online First on January 31, 2021. Most of the change were minor grammatical changes. The following changes are more significant and will be highlighted below. KW - Integrity management KW - Decision theory KW - Value of information KW - Structural reliability KW - Fracture mechanics KW - Fatigue KW - Predictive maintenance KW - Wind turbine support structure PY - 2022 DO - https://doi.org/10.1177/14759217211040385 SN - 1475-9217 VL - 21 IS - 4 SP - 1956 EP - 1956 PB - Sage Publications CY - London AN - OPUS4-55165 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -