Artificial Intelligence, Machine Learning and Smart Technologies for Nondestructive Evaluation

被引:29
作者
Taheri, Hossein [1 ]
Gonzalez Bocanegra, Maria [1 ]
Taheri, Mohammad [2 ]
机构
[1] Georgia Southern Univ, Dept Mfg Engn, Lab Adv Nondestruct Testing Insitu Monitoring & E, Statesboro, GA 30458 USA
[2] South Dakota State Univ, Dept Math & Stat, Brookings, SD 57007 USA
关键词
nondestructive evaluation (NDE); Artificial Intelligence (AI); machine learning (ML); NDE; 4; 0; digital twins; CLASSIFICATION; DEFECTS;
D O I
10.3390/s22114055
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Nondestructive evaluation (NDE) techniques are used in many industries to evaluate the properties of components and inspect for flaws and anomalies in structures without altering the part's integrity or causing damage to the component being tested. This includes monitoring materials' condition (Material State Awareness (MSA)) and health of structures (Structural Health Monitoring (SHM)). NDE techniques are highly valuable tools to help prevent potential losses and hazards arising from the failure of a component while saving time and cost by not compromising its future usage. On the other hand, Artificial Intelligence (AI) and Machine Learning (ML) techniques are useful tools which can help automating data collection and analyses, providing new insights, and potentially improving detection performance in a quick and low effort manner with great cost savings. This paper presents a survey on state of the art AI-ML techniques for NDE and the application of related smart technologies including Machine Vision (MV) and Digital Twins in NDE.
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页数:17
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