Hybrid Approach to Predict and Optimize Flaw Detection Capabilities using Laser Shearography

Yair Elbaz
Work towards MSc degree under the supervision of Associate Professor Haim Abramovich (Technion)
Department of Aerospace Engineering
Technion – Israel Institute of Technology

In recent years, there is significant integration of composite elements in the aviation world due to their unique benefits. However, these elements also have disadvantages – the sensitivity to production process and limitations of
non-destructive testing (NDT) methods. NDT of composite structures is a global challenge. One of the main methods, which has been gaining momentum in recent years, is the Laser Shearography Testing (LST). Today, due to dependence on several parameters, LST detection capabilities for composite structures, are not known in advance. The manner in which the NDT procedures are currently being developed is based on accumulated experience, trial and error, and a number of “rules of thumb”. In the present study, we present a theoretical, analytical and experimental study of the engineering prediction of shearography fringe pattern. We had developed a methodology which was implemented as a simulation that can evaluate the LST fringe pattern in advance. The simulation was tested by comparing its results to representative cases from the literature and by conducting a practical experiment by LST system yielding a good match. Subsequently, “Detection Capability Envelopes” were constructed for the LST which makes it possible to assess the flaws detection capability in advance depending on a variety of parameters. These, can be used as a guide and as a reference point for all those involved in the testing process using the LST method, developers and technicians alike, for the more efficient and accurate flaws detection in aviation structures – which will lead to improved  flight safety.

Zoom Meeting

The talk will be given in Hebrew

Wed, 05-01-2022, 13:30 (Gathering at 13:30)

Classroom 165, ground floor, Library, Aerospace Eng. & https://technion.zoom.us/j/91091112215

Light refreshments will be served after the lecture at the lounge


Hybrid Approach to Predict and Optimize Flaw Detection Capabilities using Laser Shearography