Abstract
Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRUs) in composite material samples via pulsed thermography (PT). Finite Element Method (FEM) modeling provides the economic examination of the response pulsed thermography. In this work, Carbon Fiber Reinforced Polymer (CFRP) specimens embedded with flat bottom holes are stimulated by a FEM modeling (COMSOL) with precisely controlled depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the stimulated CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.
Highlights
Non-destructive evaluation (NDE) has emerged as an important method for the evaluation of the properties of components or systems without damaging their structure
In pulsed thermography (PT), a high-power exponential heating impulse is applied to the samples, and a thermal response is measured during a period of time
The methodology proposed here employed a Gated Recurrent Units (GRUs) model combined with pulsed thermography to analyze the depth of defects
Summary
Non-destructive evaluation (NDE) has emerged as an important method for the evaluation of the properties of components or systems without damaging their structure. Several state of the arts methodologies such as Pulsed Phase Thermography (PPT) [1], Principal Component Thermography (PCT) [2], Differential of Absolute Contrast (DAC) [3], Thermographic Signal Reconstruction (TSR) [4], as well as Candid Covariance Free Incremental Principal Component Thermography [5], have been implemented to process thermographic sequences and improve the defect visibility These techniques can be beneficial for qualitative analysis of composite materials. Method [6] estimated the depth based on the characteristic time from peak contrast. This is the first time that the thermal temporal characteristic model (GRU; RNN; LSTM etc.) is used to qualify the depth of defects.
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