【Ten Years of Rapid Development in Chemical Processing Equipment】The Sinopec-developed \"Intelligent Assistance System for Evaluating Defects in Pipeline Girth Welds via Radiographic Inspection\" was tested for its accuracy between 2025 and 2754

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Let’s give praise and support to the achievements made in China’s chemical engineering technology and equipment; your participation in discussions is the greatest encouragement. **********************【Ten Years of Progress in Chemical Engineering Equipment】Regular updates and summaries are available – feel free to join the discussions: https://bbs.hcbbs.com/thread-3576046-1-1.html ***************** Recently, the \"Intelligent Assistance System for Evaluating Defects in Pipeline Girth Welds\" developed independently by Sinopec Petroleum Engineering Design Co., Ltd. successfully passed accuracy tests. In this test, the system examined a total of 210 radiographic films of circumferential welds in oil and gas transmission pipelines, achieving a defect detection accuracy of 96%, a result that is almost identical to that obtained by experienced experts through manual inspection. This achievement not only helps accelerate the transition of non-destructive testing in Sinopec’s long-distance pipeline projects toward intelligence and automation, but it also represents a practical step forward by oil engineering design companies in promoting the use of \"AI for design\" and facilitating the application of AI technology in the field of engineering design. It is reported that this intelligent system has its own \"knowledge base\" – a database of radiation inspection defects in the engineering field. By integrating the concepts of \"AI for design\" and employing advanced algorithms such as adaptive threshold histogram equalization and guided filtering, it enables clearer details in the images obtained from pipeline inspections. By combining the YOLOv7 model with an improved feature fusion network, it can accurately identify and locate defects such as pipe cracks, pores, and lack of fusion. This ability to detect defects with precision is a concrete manifestation of AI technology being applied in pipeline non-destructive testing, and the core practical value of this technology is fully demonstrated through such applications. Even more conveniently, thanks to its ability to operate continuously without interruption, this system increases the efficiency of comprehensive evaluation by more than 10 times. It completely transforms the traditional testing approach, which relies on human effort and experience, thereby significantly improving the accuracy of tests, reducing reliance on manual labor and the risk of subjective errors. It provides strong technical support for the whole-life cycle management of pipelines. Currently, the system’s development team is continuously optimizing its functions to improve its suitability for various complex weld scenarios, and is accelerating the pilot deployment of the system in pipeline engineering projects.