AI-Assisted-Nondestructive Evaluation

Dear Colleagues,

AI-assisted Nondestructive Evaluation (AI-NDE) integrates artificial intelligence (AI) technologies with traditional nondestructive evaluation (NDE) methods, effectively addressing critical limitations in quality control and structural integrity assessment. Conventional NDE techniques—such as ultrasonic testing, terahertz inspection, and X-ray imaging—heavily rely on human expertise for data interpretation, often resulting in subjective judgments and low efficiency when handling complex defects. The rapid advancement of deep learning and machine vision has revolutionized this field: AI algorithms can automatically extract and analyze features from high-dimensional NDE data, significantly enhancing the accuracy and consistency of defect detection. Currently widely applied in aerospace, semiconductor, and automotive industries, AI-NDE enables the early identification of subtle flaws that might otherwise be overlooked.

This Special Issue, “AI-Assisted Nondestructive Evaluation”, aims to highlight advances and developments in the application of state-of-the-art machine/deep learning algorithms to material characterization and structural health monitoring. It seeks to bridge the gap between academic research and industrial practice, providing a dedicated platform for sharing innovative solutions to real-world NDE challenges.

We invite researchers, engineers, and practitioners to contribute their innovative insights, significant theoretical and experimental advancements, and specific case studies in the field of AI-assisted nondestructive evaluation. Relevant research areas include (but are not limited to) the following:

• Nondestructive evaluation methodologies;
• Material characterization techniques;
• Data/image processing for terahertz spectroscopy and imaging;
• Physics-guided deep/machine learning for NDE;
• Structural health monitoring systems.

This Special Issue aligns closely with the scope of Electronics, which serves as a premier journal for researchers and engineers to publish cutting-edge research on electronic science and its applications. We encourage contributors to submit manuscripts that address the aforementioned themes, offering innovative insights and robust solutions to fundamental research and diverse practical applications related to nondestructive characterization.

We eagerly anticipate receiving your valuable contributions.

Dr. Min Zhai
Dr. Cheng Liu
Guest Editors

Manuscript Submission Information

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