人工智能、机器学习和智能技术在无损检测中的创新应用

Kuldeep Sharma
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引用次数: 0

摘要

一些行业使用无损检测(NDT)方法来检查零件和结构的性能是否存在缺陷和异常,而不会影响零件的稳定性或对被检查的零件造成损坏。它涉及到监视。材料状态感知(MSA)和结构健康监测(SHM)。使用无损检测程序可以帮助消除与组件故障相关的潜在损失和风险,同时在不牺牲可靠性和即将到来的利用率的情况下减少资金和时间。另一方面,机器学习(ML)和人工智能(AI)技术是实用的工具,可以帮助自动数据收集和分析,提供新的见解,并可能以高成本快速轻松地提高检测效率。本研究概述了现代AI-ML无损检测算法及其与智能技术相关的应用,如数字双胞胎和机器视觉(MV)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative Applications of AI, Machine Learning, and Smart Technologies in Non destructive Testing (NDT)
Several industries use non-destructive testing (NDT) methods to check the properties of parts and structures for flaws and oddities without affecting the part's stability or causing damage to the part being checked. It involves surveillance. Situation of the materials (Material State Awareness (MSA)) and the structural health monitoring (SHM). Using NDT procedures can help eliminate potential losses and risks associated with component failures while reducing both money and time by not sacrificing its reliability and upcoming utilization. On the other hand, machine learning (ML) and artificial intelligence (AI) techniques are practical instruments that can aid in automated data collection and analysis, offering fresh insights and perhaps enhancing detection efficiency at a high cost quickly and easily. The present research provides an overview of modern AI-ML NDT algorithms and their applications of associated with smart technologies, such as digital twins and machine vision (MV).
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