The field of non-destructive testing (NDT) is undergoing a transformation with the emergence of artificial intelligence (AI). The ability of AI to automate tasks and identify patterns is being increasingly harnessed to improve the efficiency and accuracy of the inspection process.
This article explores the applications and limitations of AI in NDT, as well as the role of Picture Archiving and Communication System (PACS) in supporting AI-based inspection.
Applications of AI in NDT
One of the main applications of AI in NDT is the automatic recognition of components and the assignment to an inspection instruction. The software can recognize the inspection part based on the images and automatically place a matching template over the image, which shows exactly where measurements must be taken. The generated inspection data is then fed back into the Inspection Data Management System (IDMS).
This automated inspection can also be carried out retroactively for inspections that have already been performed, for example, for quality assurance purposes. AI can analyze past inspection data and identify patterns and trends that can help improve future inspections. By leveraging historical data, AI can help identify areas that require more attention and detect potential issues before they become major problems.Another application of AI in inspection is the automated detection of erosion, corrosion, and deposits on the test images.
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