Paradigm Shift in Non-Destructive Testing: IRIS
IRIS (Internal Rotary Inspection System) is a non-destructive testing method that uses ultrasound to accurately diagnose corrosion, cracks, and wear in metallic equipment. It is particularly effective in precisely analyzing the condition of critical equipment, such as heat exchanger and steam generator tubes, maximizing their safety and value. This enables the extension of equipment lifespan, prevention of unexpected failures, and efficient facility management.
Vision
Creating the Future of IRIS Inspection with AI Technology
Our goal is to maximize equipment safety and revolutionize inspection efficiency through IRIS technology. By integrating AI and data analytics, we aim to overcome the limitations of traditional inspection methods and deliver more reliable results that customers can trust. Through continuous research and development, we are expanding the precision and application scope of IRIS technology, leading the future of non-destructive testing.
R&D
AI-Based Automatic Defect Detection
By utilizing AI algorithms, reliable automatic defect detection and classification are achieved from ultrasonic signals.
Key Research Areas
1. Development of a Deep Learning-Based Defect Classification Model
• Accurate Defect Type Classification Through Learning of Various Defect Patterns
• Implementation of Real-Time Defect Detection and Location Tracking Algorithms
• Improved Accuracy in Measuring Defect Size and Depth
2. Advancement of Signal Processing Algorithms
• Noise Reduction and Abnormal Collection Section Processing
• Signal Quality Improvement Based on Frequency Signals
3. Development of an Automated Inspection Report Generation System
Tube Wall Thinning Analysis
Through AI inference, it analyzes tube wall thinning information and provides a residual life prediction feature.
Key Research Areas
1. Development of an AI-Based Residual Life Prediction Model
• Design of an AI Prediction Model Utilizing Tube Wall Thinning Information
• Estimating Lifetime Degradation Patterns by Learning Thinning History Data
2. Generation of Customized Predictive Reports by Equipment
• Providing Residual Life Prediction Results Reflecting Equipment Characteristics
• Facilitating User Understanding and Supporting Decision-Making Through Customized Reports
Achievements
SK Energy PoC
Using AI algorithms, we have developed technology that accurately detects and classifies defects from ultrasonic signals, earning the SK Performance Certification.
Acquired a total of three certifications.
We have obtained a total of three certifications: TTA Artificial Intelligence Reliability Verification and Certification, TTA Artificial Intelligence Productivity Verification and Certification, and the TTA Certified Test Report.