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Artificial Intelligence, Machine Learning and Smart Technologies for Nondestructive Evaluation.

Hossein Taheri1, Maria Gonzalez Bocanegra1, Mohammad Taheri2

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Summary

Artificial Intelligence (AI) and Machine Learning (ML) enhance Nondestructive Evaluation (NDE) by automating data analysis for improved flaw detection. This survey explores AI-ML, Machine Vision, and Digital Twins for advanced NDE applications.

Keywords:
Artificial Intelligence (AI)NDE 4.0digital twinsmachine learning (ML)nondestructive evaluation (NDE)

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Area of Science:

  • Materials Science and Engineering
  • Computer Science
  • Mechanical Engineering

Background:

  • Nondestructive Evaluation (NDE) is crucial for assessing component integrity and detecting flaws without damage.
  • NDE supports Material State Awareness (MSA) and Structural Health Monitoring (SHM), preventing failures and saving costs.
  • Traditional NDE methods can be time-consuming and labor-intensive.

Purpose of the Study:

  • To survey state-of-the-art Artificial Intelligence (AI) and Machine Learning (ML) techniques in NDE.
  • To explore the integration of smart technologies like Machine Vision (MV) and Digital Twins with AI-ML for NDE.
  • To highlight the potential of AI-ML in automating NDE data collection and analysis.

Main Methods:

  • Comprehensive literature review of AI-ML applications in NDE.
  • Analysis of current trends in smart technologies (MV, Digital Twins) within NDE.
  • Categorization of AI-ML techniques based on their role in NDE processes.

Main Results:

  • AI-ML techniques offer significant improvements in detection performance and efficiency for NDE.
  • Machine Vision and Digital Twins are emerging as key enablers for AI-ML driven NDE.
  • Automation through AI-ML leads to quicker analysis, new insights, and cost savings in NDE.

Conclusions:

  • AI-ML, MV, and Digital Twins represent the future of advanced NDE.
  • These technologies promise enhanced accuracy, speed, and cost-effectiveness in structural and material assessment.
  • Further research is needed to fully realize the potential of integrated AI-ML solutions in diverse NDE applications.