A Visual Question Answering Model to Automate Nondestructive Evaluation Image Analysis

Abstract

This study introduces a Visual Question Answering (VQA) model designed specifically for nondestructive evaluation (NDE) applications. VQA models allow inspectors to interactively query NDE images—asking targeted questions like "Is there a crack?" or "Where is the defect located?"—and receive precise answers from the model. Leveraging deep learning and natural language processing, the developed system integrates image feature extraction (via a ResNet-50 model) and language generation capabilities (via GPT-2) to provide accurate, informative feedback. By enabling direct question-and-answer interactions, this VQA model significantly improves inspection efficiency, reduces potential errors, and enhances usability in practical field scenarios.