| 基于流体诱发振动的非接触式湿气流流型识别(英文) |
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| 引用本文： | 华陈权,王昌明,耿艳峰,石天明.基于流体诱发振动的非接触式湿气流流型识别(英文)[J].中国化学工程学报,2010,18(5):795-803. |
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| 作者姓名： | 华陈权 王昌明 耿艳峰 石天明 |
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| 作者单位： | 1. College of Information & Control Engineering, China University of Petroleum, Dongying 257061, China;2. College of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China |
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| 基金项目： | Supported by the National Natural Science Foundation of China (60672003) |
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| 摘 要： | A novel noninvasive approach, based on flow-induced vibration, to the online flow regime identification for wet gas flow in a horizontal pipeline is proposed. Research into the flow-induced vibration response for the wet gas flow was conducted under the conditions of pipe diameter 50 mm, pressure from 0.25 MPa to 0.35 MPa, Lockhart-Martinelli parameter from 0.02 to 0.6, and gas Froude Number from 0.5 to 2.7. The flow-induced vibration signals were measured by a transducer installed on outside wall of pipe, and then the normalized energy features from different frequency bands in the vibration signals were extracted through 4-scale wavelet package transform. A “binary tree” multi-class support vector machine(MCSVM) classifier, with the normalized feature vector as inputs, and Gaussian radial basis function as kernel function, was developed to identify the three typical flow regimes in-cluding stratified wavy flow, annular mist flow, and slug flow for wet gas flow. The results show that the method can identify effec-tively flow regimes and its identification accuracy is about 93.3%. Comparing with the other classifiers, the MCSVM classifier has higher accuracy, especially under the case of small samples. The noninvasive measurement approach has great application prospect in online flow regime identification.
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| 关 键 词： | flow regime identification wet gas flow flow-induced vibration wavelet package transform support vector machine |
| 收稿时间： | 2009-9-8 |
| 修稿时间： | 2009-9-8
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Noninvasive Flow Regime Identification for Wet Gas Flow Based on Flow-induced Vibration |
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| HUA Chenquan,WANG Changming,GENG Yanfeng,SHI Tianming.Noninvasive Flow Regime Identification for Wet Gas Flow Based on Flow-induced Vibration[J].Chinese Journal of Chemical Engineering,2010,18(5):795-803. |
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| Authors: | HUA Chenquan WANG Changming GENG Yanfeng SHI Tianming |
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| Affiliation: | 1. College of Information & Control Engineering, China University of Petroleum, Dongying 257061, China;2. College of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China |
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| Abstract: | A novel noninvasive approach, based on flow-induced vibration, to the online flow regime identification for wet gas flow in a horizontal pipeline is proposed. Research into the flow-induced vibration response for the wet gas flow was conducted under the conditions of pipe diameter 50 mm, pressure from 0.25 MPa to 0.35 MPa, Lockhart-Martinelli parameter from 0.02 to 0.6, and gas Froude Number from 0.5 tO2.7. The flow-induced vibration signals were measured by a transducer installed on outside wall of pipe, and then the normalized energy features from different frequency bands in the vibration signals were extracted through 4-scale wavelet package transform. A "binary tree" multi-class support vector machine(MCSVM) classifier, with the normalized feature vector as inputs, and Gaussian radial basis function as kernel function, was developed to identify the three typical flow regimes including stratified wavy flow, annular mist flow, and slug flow for wet gas flow. The results show that the method can identify effectively flow regimes and its identification accuracy is about 93.3%. Comparing with the other classifiers, the MCSVM classifier has higher accuracy, especially under the case of small samples. The noninvasive measurement approach has great application prospect in online flow regime identification. |
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| Keywords: | flow regime identification wet gas flow flow-induced vibration wavelet package transform support vector machine |
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