Design and experimental research of internal leakage detection device of buried pipeline ball valve based on valve cavity pressure detection. (March 2022)

• Record Type: Journal Article
• Authors: Shi, Mingjiang; Ye, Ting; Zhou, Bo; Pu, Hengli; Jiang, Chuan
• Is Part Of: Flow measurement and instrumentation. Volume 83(2022)
• Publication Date: 2022-03
• Subjects: Ball valve -- Buried pipeline -- Valve cavity pressure -- Internal leakage -- Opening inversion; Fluid dynamic measurements -- Periodicals; Flow meters -- Periodicals; Fluides, Dynamique des -- Mesure -- Périodiques; Débitmètres -- Périodiques; 681.2805
• DOI: 10.1016/j.flowmeasinst.2021.102112
• Languages: English
• ISSNs: 0955-5986

Abstract

Abstract: Valve is a key control component in the oil and gas long-distance pipelines, and the internal leakage detection of the valve has important research significance and application value. In this paper, a new method for detecting internal leakage of the buried pipeline ball valve based on the pressure change of the valve cavity was proposed. Firstly, a simplified internal leakage model of ball valve was established, and the change law of valve cavity pressure under different openings was obtained by finite element simulation. Secondly, a set of detection device was designed based on the internal leakage principle of buried ball valve and an experimental platform of ball valve internal leakage was built. Then, the pressure signal of the ball valve cavity under different openings and different pressures was collected by the pressure sensor, and the relationship between the power source pressure, the opening and the time required for the valve cavity pressure to reach equilibrium was established. Finally, the internal leakage degree of ball valve was simulated by ball valve opening and the Back Propagation (BP) neural network was selected to invert the ball valve opening. The inversion results showed that the maximum relative error of the liquid and gas experiment were 13.4% and 19.1%, respectively. The inversion results also verified the feasibility of BP neural network in the inversion calculation of the internal leakage degree of the ball valve, which provides guidance for the study of the classification of the internal leakage degree. The experiment and inversion results show that the proposed method can realize the detection of the internal leakage of the buried ball valve, which provides application reference in practice. Highlights: The detection principle of internal leakage of the buried ball valve is proposed. The internal leakage detection device is designed and its applicability is validated by experiment. The prediction of the internal leakage degree of the ball valve is realized by BP neural network.