Department: Structural Engineering
Faculty Advisor(s): Francesco Lanza Di Scalea | Margherita Capriotti

Primary Student
Name: Margherita Capriotti
Email: mcapriot@ucsd.edu
Phone: 858-822-4730
Grad Year: 2019

Student Collaborators
Simone Sternini, ssternin@eng.ucsd.edu

In the field of non-destructive evaluation, defect detection and visualization can be performed exploiting different techniques relying either on an active or a passive approach. In the following paper the passive technique is investigated due to its numerous advantages and its application to thermography is explored. In previous works, it has been shown that it is possible to reconstruct the Green?s function between any pair of points of a sensing grid by using noise originated from diffuse fields in acoustic environments. The extraction of the Green?s function can be achieved by cross-correlating these random recorded waves. Averaging, filtering and length of the measured signals play an important role in this process. This concept is here applied in an NDE perspective utilizing thermal fluctuations present on structural materials. Temperature variations interacting with thermal properties of the specimen allow for the characterization of the material and its health condition. The exploitation of the thermographic image resolution as a dense grid of sensors constitutes the basic idea underlying passive thermography. Particular attention will be placed on the creation of a proper diffuse thermal field, studying the number, placement and excitation signal of heat sources. Simulations and experimental tests will be presented to assess the capabilities and performances of the passive thermal technique devoted to defect detection and imaging of structural components.

Industry Application Area(s)
Aerospace, Defense, Security | Civil/Structural Engineering | Materials

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