Breakthrough in pipeline defect detection technology

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Breakthrough in Pipeline Defect Detection Technology Author/Source: China News Network Date: 2022-03-16 Clicks: 17 Recently, it was reported by the Yanchang Petroleum Pipeline Transportation Company that, after 28 months of effort, the company has achieved a new breakthrough in the technology it developed for detecting defects in pipelines and storage tank bottoms. This technology enables non-invasive detection of certain pipelines and tanks, filling a gap in this field in China. For many years, the domestic oil and gas storage and transportation industry has relied on tank cleaning for defect detection and repair of tank bottoms; this approach presents problems such as interference with tank operation due to cleaning, long construction periods, and high costs. The defect detection technology for internal pipelines and tank bottoms developed by this company employs ultrasonic guided wave testing. By using the transmission and reception of sound waves at different frequencies, as well as signals related to the attenuation and reflection of these sound waves, which are then amplified, adjusted, and processed, defects in the welding process of the tank bottom can be detected from outside the tank. The detection data is sent to a data platform, allowing for an easy assessment of the corrosion status of the tank bottom. “In simple terms, it’s like performing an ‘ultrasound’ on the pipes inside the station and the bottoms of the storage tanks; it is a detection method that is practical, highly repeatable, and causes no radiation damage. ”said Wang Jiong, manager of the company’s Materials and Equipment Department. The greatest advantage of this technology is that the massive amount of stored data allows for the identification of corrosion patterns in the subject under inspection, thereby enabling the diagnosis of the true ‘cause’ of the problem. This data platform not only allows access to inspection data but also enables the display of defect types, generating lists of defects, distribution maps of defects, 3D models of defects, as well as comparisons between defects. In essence, it creates a defect database in which each defect has its own unique \"identification information,\" along with the possibility for 3D visualization. When the dimensions of the storage tank are incorrect, the intelligent algorithm will automatically fill in the missing dimension data after calibration, and use it to create a 3D visual model that provides a more intuitive, realistic, and clear representation.