http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Alessandra Achilli,Giacomo Bernagozzi,Raimondo Betti,Pier Paolo Diotallevi,Luca Landi,Said Quqa,Eleonora M. Tronci 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.2
This paper proposes a novel method suitable for vibration-based damage identification of civil structures and infrastructures under ambient excitation. The damage-sensitive feature employed in the presented algorithm consists of a vector of multivariate autoregressive parameters estimated from the vibration responses collected at different locations of the analyzed structure. Outlier analysis and statistical pattern recognition are exploited for damage detection and localization. In particular, the Mahalanobis distance between a set of reference (i.e., “healthy”) and inspection parameters is evaluated. A threshold is then selected to determine whether the inspection vectors refer to damaged or undamaged conditions. The effectiveness of the proposed approach is proved using numerical simulations and experimental data from a benchmark test. The analysis results show that the largest values of Mahalanobis distance can be found in the proximity of those sensors closest to the damaged elements. Thus, the Mahalanobis distance applied to vectors of multivariate autoregressive parameters has proven to be a robust indicator for damage detection and localization.