A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
The hybrid multivariate analysis method for damage detection
As the defects and superiorities of indices are mutualisms frequently, such as noise immunity and damage sensitivity, damage identification based on single damage index may hardly present the effective result all the time, so multiple indices fusion method is introduced in this paper to achieve some complementary improvements. In this paper, two kinds of no‐baseline mode shape‐based damage indices, namely, the generalized local entropy and the curvature waveform capacity fractural, are utilized to construct the basic index set for combination, and the fuzzy cluster method is introduced in order to establish fusion process. These two parts generate the hybrid multivariate analysis method finally. The multivariate analysis' superiority mainly displays on two aspects: (1) the use of no‐baseline mode shape‐based method ensures the damage detection efficiency with the absence of healthy mode shape serving as baseline and (2) the fusion conducted by cluster method provides the mutual support and complementation among indices, which can enhance the robustness of algorithm. The performances of the present method are verified via sufficient numerical examples, and then experiments are demonstrated on three typical engineering structures, namely, cantilever beam, blower wheel, and rotor, for further validations. Copyright © 2015 John Wiley & Sons, Ltd.
The hybrid multivariate analysis method for damage detection
As the defects and superiorities of indices are mutualisms frequently, such as noise immunity and damage sensitivity, damage identification based on single damage index may hardly present the effective result all the time, so multiple indices fusion method is introduced in this paper to achieve some complementary improvements. In this paper, two kinds of no‐baseline mode shape‐based damage indices, namely, the generalized local entropy and the curvature waveform capacity fractural, are utilized to construct the basic index set for combination, and the fuzzy cluster method is introduced in order to establish fusion process. These two parts generate the hybrid multivariate analysis method finally. The multivariate analysis' superiority mainly displays on two aspects: (1) the use of no‐baseline mode shape‐based method ensures the damage detection efficiency with the absence of healthy mode shape serving as baseline and (2) the fusion conducted by cluster method provides the mutual support and complementation among indices, which can enhance the robustness of algorithm. The performances of the present method are verified via sufficient numerical examples, and then experiments are demonstrated on three typical engineering structures, namely, cantilever beam, blower wheel, and rotor, for further validations. Copyright © 2015 John Wiley & Sons, Ltd.
The hybrid multivariate analysis method for damage detection
Yang, Zhi‐Bo (author) / Chen, Xue‐Feng (author) / Xie, Yong (author) / Zhang, Xing‐Wu (author)
Structural Control and Health Monitoring ; 23 ; 123-143
2016-01-01
21 pages
Article (Journal)
Electronic Resource
English
Multivariate statistical analysis for early damage detection
| Online Contents | 2013
Structural Damage Detection Using Multivariate Time Series Analysis
| British Library Conference Proceedings | 2012
Structural Damage Detection Using Multivariate Time Series Analysis
| Springer Verlag | 2012
Multivariate Statistical Approach to Structural Damage Detection
| Online Contents | 2010