Damage Detection Based on the Cross Correlation Function Amplitude Vector and its Application to the ASCE Benchmark Structure

2007 ◽  
pp. 2317-2320
Author(s):  
Zhe Feng Yu ◽  
Zhi Chun Yang
Keyword(s):  
Correlation Function ◽  
Damage Detection ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
The Cross

Damage Detection Based on the Cross Correlation Function Amplitude Vector and its Application to the ASCE Benchmark Structure

2007 ◽  
Vol 353-358 ◽  
pp. 2317-2320 ◽  
Author(s):  
Zhe Feng Yu ◽  
Zhi Chun Yang
Keyword(s):  
Correlation Function ◽  
Damage Detection ◽  
Structural Damage ◽  
Cross Correlation ◽  
Relative Difference ◽  
Random Excitation ◽  
Cross Correlation Function ◽  
Vibration Responses ◽  
Specific Frequency ◽  
The Cross

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.

Simultaneous Measurement of Temperature and Velocity Using µPIV

2006 ◽  
Author(s):  
Pramod Chamarthy ◽  
Steven T. Wereley ◽  
Suresh V. Garimella
Keyword(s):  
Brownian Motion ◽  
Correlation Function ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
Motion Information ◽  
Peak Broadening ◽  
Constant Temperature Water Bath ◽  
Gravity Driven ◽  
The Cross ◽  
Gravity Driven Flow

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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