| 基于实验研究的油气钻采水平两相流管道泄漏声发射检测 |
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| 引用本文： | 张源,杜莎莎,顾纯巍,夏强,刘鹏谦,徐长航. 基于实验研究的油气钻采水平两相流管道泄漏声发射检测[J]. 中国海上油气, 2021, 0(1): 158-165 |
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| 作者姓名： | 张源 杜莎莎 顾纯巍 夏强 刘鹏谦 徐长航 |
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| 作者单位： | 中国石油大学（华东）机电工程学院;中海石油（中国）有限公司钻完井办公室 |
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| 基金项目： | 国家重点研发计划“海洋油气开采工艺设施安全及完整性检测、监测技术及装备(编号:2017YFC0804503)”部分研究成果。 |
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| 摘 要： | 气液两相流管道在油气钻采、运输中应用广泛,但对其泄漏检测的研究较少.本文通过搭建水平气液两相流泄漏实验系统,利用声发射(AE)检测原理对气体压力、流型、泄漏孔径、泄漏位置等因素对泄漏声发射信号的影响进行了实验研究,提出通过经验模态分解(EMD)去噪并用小波包分解(WPD)提取声发射信号特征输入BP神经网络进行泄漏存在性...
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| 关 键 词： | 气液两相流 管道泄漏 声发射 无损检测 BP神经网络 |
Acoustic emission detection of horizontal gas-liquid two-phase flow pipeline leakage based on experimental research |
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| ZHANG Yuan,DU Shasha,GU Chunwei,XIA Qiang,LIU Pengqian,XU Changhang. Acoustic emission detection of horizontal gas-liquid two-phase flow pipeline leakage based on experimental research[J]. China Offshore Oil and Gas, 2021, 0(1): 158-165 |
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| Authors: | ZHANG Yuan DU Shasha GU Chunwei XIA Qiang LIU Pengqian XU Changhang |
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| Affiliation: | (College of Mechanical and Electrical Engineering,China University of Petroleum,Qingdao,Shandong 266580,China;Drilling&Completion Office,CNOOC China Limited,Beijing 100010,China) |
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| Abstract: | Gas-liquid two-phase flow pipeline is widely used in oil&gas drilling,production and transportation,but there are few researches on its leakage detection.In this paper,through establishing a horizontal gas-liquid two-phase flow leakage experimental system,the influence of gas pressure,flow pattern,leak aperture,leak position and other factors on leaking acoustic emission(AE)signal was studied by using acoustic emission detection principle.Then,empirical mode decomposition(EMD)is used to denoise and wavelet packet decomposition(WPD)is adopted to extract the features of acoustic emission signal,which is input into BP neural network to identify the existence and flow pattern of leakage.The results show that the leakage detection method proposed in this paper improves the accuracy of BP neural network in detecting the leakage pattern of gas-liquid two-phase flow and realizes the effective detection of two-phase flow pipeline,which has a good reference significance. |
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| Keywords: | gas-liquid two-phase flow pipeline leakage acoustic emission non-destructive testing BP neural network |
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