On the cross correlation function amplitude vector and its application to structural damage detection

2007 ◽  
Vol 21 (7) ◽  
pp. 2918-2932 ◽  
Author(s):  
Zhichun Yang ◽  
Zhefeng Yu ◽  
Hao Sun
2007 ◽  
Vol 353-358 ◽  
pp. 2317-2320 ◽  
Author(s):  
Zhe Feng Yu ◽  
Zhi Chun Yang

A new method for structural damage detection based on the Cross Correlation Function Amplitude Vector (CorV) of the measured vibration responses is presented. Under a stationary random excitation with a specific frequency spectrum, the CorV of the structure only depends on the frequency response function matrix of the structure, so the normalized CorV has a specific shape. Thus the damage can be detected and located with the correlativity and the relative difference between CorVs of the intact and damaged structures. With the benchmark problem sponsored by ASCE Task Group on Structural Health Monitoring, the CorV is proved an effective approach to detecting the damage in structures subject to random excitations.


2018 ◽  
Vol 39 (3) ◽  
pp. 631-649
Author(s):  
Miao Li ◽  
Wei-Xin Ren ◽  
Tian-Li Huang ◽  
Ning-Bo Wang

This article focuses on the experimental investigations on the cross-correlation function amplitude vector of the dynamic strain (CorV_S) under varying environmental temperature for structural damage detection. It is verified that under white noise excitation, CorV_S is only related to the natural frequencies, mode shapes, and damping ratios of structures. The normalized CorV_S of the undamaged structure maintains a uniform shape. A laboratory experimental investigation based on an end-fixed steel beam shows that CorV_S can be used for structural damage detection. However, CorV_S constructed by the dynamic strain of in-situ test varies with time, and the CorV_S curves do not have the same shape. When the environmental temperature fluctuates significantly, high correlation exists between the dynamic strain and environmental temperature. By analyzing the power spectral density of the signals measured from active and inactive strain gauges, it is found that the signals induced by temperature stress, which do not reflect the dynamic performance of the bridge, exist in the very low-frequency band. To avoid the interference to CorV_S, the temperature effect component is separated from the dynamic strain by analytical mode decomposition method. Then, each CorV_S curve maintains a uniform shape. The results demonstrate that it is prone to get a misjudgment for the condition of a structure if temperature effect on CorV_S is ignored. It is necessary to eliminate the environmental temperature effect on CorV_S for the damage detection of a structure in service.


2011 ◽  
Vol 368-373 ◽  
pp. 2442-2446
Author(s):  
Yan Fang Hou ◽  
Wei Bing Hu

Cross Correlation Function Amplitude Vector(CorV) is a method of damage detection which is based on random vibration .In this paper, CorV is introduced in the damage detection of historic timber structure according to the characteristics of structure and damage.Meanwhile,the research has been done. CorV of structural damage before and after the change has been expressed that is based on Cross Correlation function amplitude Vector Criterion(CVAC) .Results show that there is a remarkable decrease of CVAC among the CorVs between damaged and intact structures.Damage locations can be determined through the relative change of CorVs which is before or after the damage of the structure . A basis can be provided for the damage of buildings and the ancient structure protection through this paper.


Author(s):  
Pramod Chamarthy ◽  
Steven T. Wereley ◽  
Suresh V. Garimella

In μPIV, for a uniform velocity field the displacement of the cross-correlation function gives the velocity of the fluid and the broadening of the peak-width represents the amount of Brownian motion present. In the presence of a linear or a parabolic shear, the shape of the cross-correlation function would have both the Brownian motion information as well as the velocity distribution information. In the present work, the broadening of the cross-correlation function caused by the velocity gradient was subtracted from the total peak broadening in order to isolate the Brownian motion information and thus infer temperature. To the authors' knowledge, this technique has not been applied to measure the temperature of a moving fluid. The experiments were conducted in a gravity driven flow through a tube surrounded by a constant temperature water bath.


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