智能音波测漏系统在长输天然气管道上的实践
Practice of Intelligent Sound Wave Leak Detection System in Long Distance Natural Gas Pipeline
DOI: 10.12677/JSTA.2020.83011, PDF,   
作者: 周 巍, 罗 润, 侯 丹, 何 波：中海广东天然气有限责任公司，广东 珠海；胡 勇：北京寰宇声望智能科技有限公司，北京
关键词: 智能音波；长输天然气管道；试验；应用； Intelligent Sound Wave； Long-Distance Natural Gas Pipeline； Test； Application
摘要: 本文介绍了智能音波测漏系统的机制、组成及功能，并详细介绍了该系统在珠海–中山天然气管道项目的安装、测试等应用情况。结果表明：智能音波测漏系统在长输天然气管道上测试准确、有效，系统鲁棒性高、响应快速，定位精确，具有现实意义。
Abstract: Pipeline leakage monitoring is of great significance to ensure the safe operation of natural gas long-distanced pipeline. This paper introduces the mechanism, composition and function of the intelligent sound wave leak detection system, and introduces the application of the system in Zhuhai Zhongshan Natural Gas Pipeline Project in detail. The results show that the intelligent acoustic wave leak detection system is accurate and effective in the long-distance natural gas pipeline testing, with high system robustness, quickly response, accurate positioning, and has practical significance.
文章引用：周巍, 罗润, 侯丹, 何波, 胡勇. 智能音波测漏系统在长输天然气管道上的实践[J]. 传感器技术与应用, 2020, 8(3): 96-106. https://doi.org/10.12677/JSTA.2020.83011

参考文献

[1] 中国国家统计局. 2015年中国统计年鉴[M]. 北京: 中国国家统计局, 2015: 8-11.
[2] 靳世久, 孙家, 姜弘彦, 等. 强环境噪声下地下管道泄漏检测[J]. 天津大学学报: 自然科学与工程技术版, 1994(6): 782-787.
[3] 王海伟. 音波测漏系统在输气管道的应用[J]. 管道技术与设备, 2014(2): 22-24.
[4] Yang, G., Liu, Y., Wang, Y., et al. (2015) EMD Interval Thresholding Denoising Based on Similarity Measure to Select Relevant Modes. Signal Processing, 109, 95-109. [Google Scholar] [CrossRef] 
[5] Wade, W.R. and Rachford, H.H. (1988) Detecting Leaks in Pipe Lines in Pipe Lines Using SCADA Information. Pipe Line Industry, 68, 64-66.
[6] Wang, Z., Chang, J., Zhang, S., et al. (2015) An Improved Denoising Method in RDTS Based on Wavelet Transform Modulus Maxima. IEEE Sen-sors Journal, 15, 1061-1067. [Google Scholar] [CrossRef] 
[7] Li, S., Wen, Y., Li, P., et al. (2014) Modal Analysis of Leakage-Induced Acoustic Vibrations in Different Directions for Leak Detection and Location in Flu-id-Filled Pipelines. IEEE International Ultrasonics Symposium, Chicago, IL, 3-6 September 2014, 1412-1415. [Google Scholar] [CrossRef] 
[8] 郭静波, 蔡雄, 胡铁华, 张志文. 油气管道中智能机器人跟踪定位关键技术综述[J]. 仪器仪表学报, 2015(36): 481-498.
[9] 魏明生, 童敏明, 訾斌, 唐守锋. 基于粒子群-拟牛顿混合算法的管道机器人定位[J]. 仪器仪表学报, 2012(33): 2594-2600.
[10] 郭晨城, 文玉梅, 李平, 等. 采用EMD的管道泄漏声信号增强[J]. 仪器仪表学报, 2015, 36(6): 1397-1405.
[11] Demirci, S., Yigit, E., Eskidemir, I.H., et al. (2012) Ground Penetrating Radar Imaging of Water Leaks from Buried Pipes Based on Back-Projection Method. Ndt & E International, 47, 35-42. [Google Scholar] [CrossRef] 
[12] 孙洁娣, 肖启阳, 温江涛, 等. 局域均值分解分析的管道泄漏孔径识别及定位[J]. 仪器仪表学报, 2014, 35(12): 2835-2842.
[13] 曹欣雨. 自我健康监护仪软件系统设计及实现[D]: [硕士学位论文]. 长春: 长春理工大学, 2019.

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