【Ten Years of Rapid Development in Chemical Engineering Equipment】The intelligent pipeline inspection large model for petroleum and petrochemical pipelines in China, developed from 2025 to 2035, has been successfully created and put into use

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Let’s give praise and encouragement to the achievements made in China’s chemical engineering technology and equipment; your participation in discussions is the greatest encouragement. **********************【Ten Years of Great Development in Chemical Engineering Equipment】Continuous updates and summaries are available; feel free to join the discussions: https://bbs.hcbbs.com/thread-3576046-1-1.html ***************** An intelligent model for the inspection of pipelines has been successfully developed and put into use. Workers’ Daily, May 30, 2025. On May 28th, at the launch event for China National Petroleum Corporation’s “300 Billion Kunlun Model,” an intelligent model for the quality inspection of energy transmission pipelines, developed by the technical team of CNPC Baoshishun (Qinhuangdao) Steel Pipe Co., Ltd., was demonstrated on site. Its ability to automatically and accurately identify X-ray images of welds was truly impressive. The successful development and application of this model mark a new era of intelligent inspection for oil pipeline inspection technology in China. It is understood that this technology project is the first AI-based intelligent inspection project implemented by CNPC Gem Tube Co., Ltd. – the parent company of CNPC Baoshishun Company – in the pipeline sector. The development of the model took 12 months, with over 20 technical personnel from all member companies of Gemstone Tube Industry participating in data collection and algorithm optimization. The project team achieved end-to-end integration of AI engineering, including the collection of millions of industrial image datasets and the detailed annotation of over 100,000 core samples ； From the deep adaptation of the Pangu Vision large model architecture to the parameter tuning through millions of iterations of training. Every aspect of the project embodies the wisdom of collaborative innovation in the industry. Industrial applications: The core advantage of this model lies in its ability to create an integrated system that combines \"visual AI\" with industrial quality inspection. By leveraging the strong feature-extraction capabilities of the Pangu visual large model, along with a database of expertise related to the inspection of welds in conveyor pipes, it is possible to carry out intelligent diagnosis of typical defects such as cracks, pores, and lack of fusion within milliseconds. Compared to traditional inspection methods, it can not only accurately detect minute defects on a millimeter scale, but also reduce the inspection time for a single image to one-third of that required by manual methods through automated processes, providing an excellent tool for ensuring quality control throughout the entire production process of high-pressure pipelines. Verified in industrial settings, the steel pipe weld defect detection system integrated into this model achieves a defect detection rate of over 96% and a 40% improvement in operational efficiency, effectively overcoming the limitations in accuracy and speed associated with traditional manual inspection methods. Currently, this model has entered the stage of industrial application, with pilot operations first being carried out at the pipe manufacturing plant of CNPC Baoshishun Company. In line with the goal of \"continuous iteration and comprehensive empowerment,\" the project team will, on the one hand, expand the functional capabilities of the model by incorporating more diverse types of detection data ； On the other hand, it will work together with ecosystem partners such as Huawei Cloud to optimize the algorithm architecture, striving to raise the defect detection rate to over 98% within 3 years, with the goal of creating an industry-level AI quality inspection platform that integrates \"intelligent detection, quality tracking, and process optimization\".