Prediction Method of Large-Diameter Ball Valve Internal Leakage Rate Based on CNN-GA-DBN

Large-diameter ball valves are primarily applied in oil and gas long-distance pipelines for emergency shutdown. Due to the problems of friction between the transmission medium and the valve cavity, as well as corrosion and aging, the ball valves are prone to internal leakage, failing emergency shutd...

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Bibliographic Details
Published in:IEEE sensors journal 2023-09, Vol.23 (17), p.20321-20329
Main Authors: Wan, Jize, Shi, Mingjiang, Liang, Yanbing, Qin, Liansheng, Deng, Liyuan
Format: Article
Language:English
Subjects:
Acoustic emission
Artificial neural networks
Ball valves
Belief networks
Correlation coefficients
Gas pipelines
Genetic algorithms
Leakage
Machine learning
Natural gas
Optimization
Petroleum pipelines
Prediction models
Root-mean-square errors
Shutdowns
Valves
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Summary:Large-diameter ball valves are primarily applied in oil and gas long-distance pipelines for emergency shutdown. Due to the problems of friction between the transmission medium and the valve cavity, as well as corrosion and aging, the ball valves are prone to internal leakage, failing emergency shutdown. Therefore, it is essential to accurately detect whether the internal leak occurs in the valve. This work adopts the acoustic emission (AE) technology to detect the leaking ball valve and proposes a novel method for leakage rate prediction, which uses a convolutional neural network (CNN) combined with a deep belief network (DBN) for feature learning and a genetic algorithm (GA) to optimize DBN, building a prediction model based on CNN-GA-DBN for internal leakage rate. Combined with the built experimental platform, the internal leakage signals of ball valves under different conditions were acquired, and the experimental verification was operated. The results show that the optimal values of mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and correlation coefficient (CORR) obtained using CNN-GA-DBN are 0.8668, 14.2879, 1.0681, and 0.9963, respectively. It indicates that the proposed method can provide powerful support for the internal leakage rate prediction of ball valves.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3295362