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Quantification experiment and prediction model construction for liquid/gas high‑pressure gate valve internal leakage
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Bolun LI1, Hui PENG1, Yue XI1, Dengwei FU1, Fushou QIU1, Jianbo WU2, Xiaomei XIANG2
Fluid Machinery | 2026, 54(3) : 10 - 20
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Fluid Machinery | 2026, 54(3): 10-20
Quantification experiment and prediction model construction for liquid/gas high‑pressure gate valve internal leakage
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Bolun LI1, Hui PENG1, Yue XI1, Dengwei FU1, Fushou QIU1, Jianbo WU2, Xiaomei XIANG2
Affiliations
  • 1Oil Production Technology Research Institute,PetroChina Xinjiang Oilfield Company,Karamay 834000,China
  • 2School of Mechanical Engineering,Sichuan University,Chengdu 610065,China
Published: 2026-03-30 doi: 10.3969/j.issn.1005-0329.2026.03.002
Outline
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To address the threats of internal leakage in high‑pressure gate valves to equipment safety and system energy efficiency optimization,research on quantitative detection and condition diagnosis of internal leakage was carried out.An internal leakage test platform for high‑pressure gate valves was established,and ultrasonic testing technology was used to conduct internal leakage tests under various combined conditions involving two media (liquid/gas),inlet pressure from 10~70 MPa,defect sizes from 0.1~0.3 mm,and valve diameters from DN65~DN130.The results show that as inlet pressure and defect size increase,both the internal leakage flow rate and the ultrasonic signal of liquid/gate valves show an increasing trend;as valve diameter increases,both decrease,a phenomenon mainly influenced by wall thickness.Under the same conditions,the gas internal leakage flow rate is approximately 10~431 times that of liquid.The gas ultrasonic signal is generally stronger than that of liquid,with signal amplitude approximately 1.4~3.2 times that of liquid;during internal leakage in liquid/gas gate valves,the outlet ultrasonic signal is generally stronger than the inlet signal,with an average difference maintained at 7.2 dBμV RMS.Based on the Gaussian process regression (GPR) method,using the Matern 5/2 kernel function (length scale of 1,signal variance of 0.707 1),an internal leakage flow rate prediction model was constructed,achieving a prediction accuracy of 93.55%.The obtained laws and the model have good universality,providing reliable application basis and theoretical support for the quantitative assessment and operating condition diagnosis of internal leakage in high‑pressure gate valves under different working conditions.

high‑pressure gate valve  /  internal leakage quantification  /  ultrasonic testing  /  quantification model
李博伦, 彭辉, 席岳, 傅登伟, 邱福寿, 伍剑波, 向晓梅. 液/气高压闸阀内漏量化试验及预测模型构建研究. 流体机械, 2026 , 54 (3) : 10 -20 . DOI: 10.3969/j.issn.1005-0329.2026.03.002
Bolun LI, Hui PENG, Yue XI, Dengwei FU, Fushou QIU, Jianbo WU, Xiaomei XIANG. Quantification experiment and prediction model construction for liquid/gas high‑pressure gate valve internal leakage[J]. Fluid Machinery, 2026 , 54 (3) : 10 -20 . DOI: 10.3969/j.issn.1005-0329.2026.03.002
Year 2026 volume 54 Issue 3
118
47
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Article Info
doi: 10.3969/j.issn.1005-0329.2026.03.002
  • Receive Date:2025-10-09
  • Online Date:2026-10-22
  • Published:2026-03-30
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  • Received:2025-10-09
  • Revised:2026-02-15
Affiliations
    1Oil Production Technology Research Institute,PetroChina Xinjiang Oilfield Company,Karamay 834000,China
    2School of Mechanical Engineering,Sichuan University,Chengdu 610065,China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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