马氏距离
结构健康监测
主成分分析
结构工程
自相关
桥(图论)
振动
计算机科学
模式识别(心理学)
工程类
可靠性工程
人工智能
统计
数学
声学
医学
物理
内科学
作者
Jesus J. Yanez-Borjas,José M. Machorro-López,David Camarena-Martinez,Martín Valtierra-Rodríguez,Juan P. Amezquita-Sanchez,Francisco J. Carrion-Viramontes,Juan A. Quintana-Rodriguez
标识
DOI:10.1142/s0219455421501273
摘要
Cable-stayed bridges are widely used all around the world. Unfortunately, during their service life, they are exposed to adverse conditions that may cause their deterioration and, consequently, their collapse. Vibration-based structural health monitoring techniques have become the most promising alternatives for efficiently detecting and locating damage into civil structures. In this regard, this paper presents a new methodology based on statistical features, Principal component analysis (PCA), and Mahalanobis distance (MD) for detecting and locating a cable loss in the Río Papaloapan bridge (RPB) using vibration signals. It is based on the extraction of a set of statistical time features (STFs) from vibration signals, which are analyzed using the autocorrelation function (ACF) to denoise and strengthen the features found in them. Then PCA-based models are computed by using the STFs to enhance the damage location process. Then a new damage index based on MD is proposed to indicate if a damage exists and its location.
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