| 基于双槽式孔板组合和神经网络技术的凝析天然气流量计开发 |
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| 引用本文： | 耿艳峰,郑金吾,石天明,石岗. 基于双槽式孔板组合和神经网络技术的凝析天然气流量计开发[J]. 中国化学工程学报, 2007, 15(2): 281-285. DOI: 10.1016/S1004-9541(07)60071-8 |
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| 作者姓名： | 耿艳峰 郑金吾 石天明 石岗 |
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| 作者单位： | I）epartment of A~omation, ＂China University of Petroleum, Dongying 257061, China |
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| 基金项目： | Supported by the National Natural Science Foundation of China （No.60672003） and Shandong Key Technology R＆D Program （2004GG2205016）. |
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| 摘 要： | A slotted orifice has many superiorities over a standard orifice. For single-phase flow measurement, its flow coefficient is insensitive to the upstream velocity profile. For two phase flow measurement, various characteristics of its differential pressure （DP） are stable and closely correlated with the mass flow rate of gas and liquid. The complex relationships between the signal features and the two-phase flow rate are established through the use of a back propagation （BP） neural network. Experiments were carried out in the horizontal tubes with 50ram inner diameter, ooerated with water flow rate in the range of 0.2m^3·h^-1 to 4m3·h^-1, gas flow rate in the range of 100m^3·h^-1 to 1000m^3·h^-1, and pressure at 400kPa and 850kPa respectively, where the temperature is ambient temperature. This article includes the principle of wet gas meter development, the experimental matrix, the signal processing techniques and the achieved results. On the basis of the results it is suggested that the slotted orifice couple with a trained neural network may provide a simple but efficient solution to the wet gas meter development.
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| 关 键 词： | 槽式孔板 神经网络技术 湿气流量计 研制 凝析天然气 |
| 收稿时间： | 2006-03-08 |
| 修稿时间： | 2006-03-082006-09-15 |
Wet gas meter development based on slotted orifice couple and neural network techniques |
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| GENGYanfeng,ZHENGJinwu,SHITianming,SHIGang. Wet gas meter development based on slotted orifice couple and neural network techniques[J]. Chinese Journal of Chemical Engineering, 2007, 15(2): 281-285. DOI: 10.1016/S1004-9541(07)60071-8 |
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| Authors: | GENGYanfeng ZHENGJinwu SHITianming SHIGang |
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| Affiliation: | Department of Automation,China University of Petroleum,Dongying 257061,China;Department of Automation,China University of Petroleum,Dongying 257061,China;Department of Automation,China University of Petroleum,Dongying 257061,China;Department of Automation,China University of Petroleum,Dongying 257061,China |
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| Abstract: | A slotted orifice has many superiorities over a standard orifice.For single-phase flow measurement,its flow coefficient is insensitive to the upstream velocity profile.For two phase flow measurement,various characteristics of its differential pressure (DP) are stable and closely correlated with the mass flow rate of gas and liquid.The complex relationships between the signal features and the two-phase flow rate are established through the use of a back propagation (BP) neural network.Experiments were carried out in the horizontal tubes with 50mm inner diameter,operated with water flow rate in the range of 0.2m3·h-1 to 4m3·h 1,gas flow rate in the range of 100m3·h-1 to 1000m3·h-1,and pressure at 400kPa and 850kPa respectively,where the temperature is ambient temperature, This article includes the principle of wet gas meter development,the experimental matrix,the signal processing techniques and the achieved results.On the basis of the results it is suggested that the slotted orifice couple with a trained neural network may provide a simple but efficient solution to the wet gas meter development. |
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| Keywords: | wet gas meter two-phase flow slotted orifice neural network wavelet analysis principal component analysis |
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