管道“诊病”有“良方”

Core Insights - Sinopec Petroleum Engineering Design Company has developed an intelligent auxiliary evaluation system for pipeline radiographic defect detection, achieving a defect identification accuracy of 96% during testing, comparable to experienced human experts [1] - This achievement signifies a significant step towards the intelligent and automated transformation of non-destructive testing in long-distance pipeline engineering, promoting the application of AI technology in engineering design [1] Technology and Innovation - The intelligent system features its own knowledge base, a radiographic defect database, and employs advanced algorithms such as adaptive threshold histogram equalization and guided filtering to enhance image clarity [1] - By integrating the YOLOv7 model with an improved feature fusion network, the system accurately identifies and locates defects such as cracks, pores, and lack of fusion in pipelines, demonstrating the practical application of AI in non-destructive testing [1] Efficiency and Application - The system has improved the efficiency of evaluation by over 10 times, transforming the traditional reliance on human labor and experience, significantly enhancing detection accuracy and reducing subjective error risks [2] - The development team is continuously optimizing the system's functionality to enhance its applicability in various complex welding scenarios and is accelerating the pilot application of the system in pipeline engineering projects [2]