AI in Non-Destructive Testing (NDT) and Inspection
Course level:Intermediate
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AI in Non-Destructive Testing (NDT) and Inspection
To enable technicians to use AI-driven image and data analysis in NDT inspections for detecting anomalies accurately and generating smart reports.
Material Includes
- Sample inspection images, AI tools (YOLOv8, OpenCV), datasets, case studies
What I will learn?
- Use AI-driven image and data analysis for NDT inspections.
- Detect defects like cracks, corrosion, and porosity accurately.
- Generate smart inspection reports using AI outputs.
Course Curriculum
Introduction to NDT Methods
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Introduction to Non-Destructive Testing (NDT) methods and their growing need for automation in modern facilities.
00:20
Computer Vision in NDT
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Role of Computer Vision in analyzing radiographic and ultrasonic inspection images using convolutional neural networks (CNNs).
00:20
Defect Classification Models
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Development of classification models to differentiate types of material defects (cracks, corrosion, porosity).
00:20
AI-Enhanced Drone Inspection
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Overview of AI-enhanced drone inspections for tanks, flare stacks, and inaccessible zones, focusing on image acquisition and object recognition.
00:20
AI Integration in NDT Devices
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Integration of AI into portable NDT devices and smart helmets for real-time anomaly detection.
00:20
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Requirements
- Minimum of 5 candidates per course
Free
Free access this course
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LevelIntermediate
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Last UpdatedApril 11, 2026
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