Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
AbstractDifferent types of sensors in a structural health monitoring (SHM) system installed in a structure enable various types of structural responses to be measured. However, their distinct properties and limitations considerably complicate multisensing structural condition assessment. As a result, the information from these sensors is often used separately, and the potential advantage of multisensing information has not been used effectively. This paper first proposes a covariance-based multisensing (CBMS) damage detection method in the time domain in terms of a CBMS vector as a new damage index and a sensitivity study for damage detection. The proposed method has the merit of assimilating heterogeneous data and reducing the adverse effect of measurement noise. The CBMS damage detection method is then used in two stages for detecting damage location and severity consecutively. Numerical studies are finally performed to investigate the feasibility and accuracy of the proposed framework using an overhanging beam with two damage scenarios. The results show that the two-stage CBMS damage detection method improves the accuracy of damage detection and that the proposed method can be effectively used to combine multisensing information for better damage detection.
AbstractDifferent types of sensors in a structural health monitoring (SHM) system installed in a structure enable various types of structural responses to be measured. However, their distinct properties and limitations considerably complicate multisensing structural condition assessment. As a result, the information from these sensors is often used separately, and the potential advantage of multisensing information has not been used effectively. This paper first proposes a covariance-based multisensing (CBMS) damage detection method in the time domain in terms of a CBMS vector as a new damage index and a sensitivity study for damage detection. The proposed method has the merit of assimilating heterogeneous data and reducing the adverse effect of measurement noise. The CBMS damage detection method is then used in two stages for detecting damage location and severity consecutively. Numerical studies are finally performed to investigate the feasibility and accuracy of the proposed framework using an overhanging beam with two damage scenarios. The results show that the two-stage CBMS damage detection method improves the accuracy of damage detection and that the proposed method can be effectively used to combine multisensing information for better damage detection.
Two-Stage Covariance-Based Multisensing Damage Detection Method
2017
Aufsatz (Zeitschrift)
Englisch
Two-Stage Covariance-Based Multisensing Damage Detection Method
Online Contents | 2016
|Development of a Multisensing Detector
British Library Conference Proceedings | 1998
|Response covariance-based sensor placement for structural damage detection
Taylor & Francis Verlag | 2018
|Subspace-based Mahalanobis damage detection robust to changes in excitation covariance
BASE | 2021
|