传统声波衰减定位模型在实现定位前需要进行管道运行参数的确定以便计算衰减模型中涉及的参数。针对该问题提出一种新的传感器布置方式,即在泄漏点上下游均放置两个传感器,通过上(下)游两传感器之间实验信号幅值比值获取衰减参数。通过变分模态分解(variational mode decomposition,VMD)这一信号处理方法对实验信号进行降噪,研究不同泄漏口径(3,6,8,10,12,15,20和27 mm)以及不同探测距离对泄漏信号的影响,最终借助极大似然估计(maximum likelihood estimation, MLE)法在衰减模型基础上进行泄漏定位。结果表明在不同泄漏口径以及不同传感器探测位置下,该方法可对泄漏进行有效定位,定位效果好于时差法且误差在15%以内。此外,敲击实验定位误差小于7%,佐证了该方法的有效性。
Abstract
The traditional acoustic attenuation positioning model needs determining pipeline operation parameters before positioning so as to calculate parameters involved in the attenuation model. Here, to solve this problem, a new sensor arrangement scheme was proposed, i.e., two sensors being placed in upstream and downstream of leakage point, and attenuation parameters being obtained with ratio values of experimental signal amplitudes between upstream and downstream sensors. The signal processing method of variational mode decomposition (VMD) was used to denoise experimental signals, and effects of different leakage diameters of 3, 6, 8, 10, 12, 15, 20, 27 mm and different detection distances on leakage signals were studied. Finally, MLE was used to do leakage positioning based on the attenuation model. The results showed that the proposed method can effectively locate leakages under conditions of different leakage calibers and different sensor positions; its positioning effect is better than that of the time difference method, and its error is within the range of 0~15%; the positioning error of knocking experiments is less than 7% to prove the effectiveness of the proposed method.
关键词
液体管道 /
声波衰减模型 /
极大似然估计(MLE) /
泄漏定位
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Key words
liquid pipeline /
acoustic attenuation model /
maximum likelihood estimation (MLE) /
leakage positioning
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参考文献
[1]文静,张敏姿. 90°弯管存在下的供水管道泄漏定位研究[J]. 振动与冲击, 2018, 37(6): 92-98.
WEN Jing, ZHANG Minzi. Water supply pipeline leakage location in the presence of 90°bend [J]. Journal of Vibration and Shock, 2018, 37(6): 92-98.
[2]MUGGLETON J M, YAN J. Wavenumber prediction and measurement of axisymmetric waves in buried fluid-filled pipes: Inclusion of shear coupling at a lubricated pipe/soil interface[J]. Journal of Sound and Vibration, 2013, 332(5): 1216-1230.
[3]LI Z L, ZHANG H F, TAN D J, et al. A novel acoustic emission detection module for leakage recognition in a gas pipeline valve[J]. Process Safety and Environmental Protection, 2017, 105: 32-40.
[4]LI S Y, WEN Y M, LI P, et al. Leak location in gas pipelines using cross-time-frequency spectrum of leakage-induced acoustic vibrations[J]. Journal of Sound and Vibration, 2014, 333(17): 3889-3903.
[5]LIU C W, LI Y X, YAN Y K, et al. A new leak location method based on leakage acoustic waves for oil and gas pipelines[J]. Journal of Loss Prevention in the Process Industries, 2015, 35: 236-246.
[6]SUN J D, XIAO Q Y, WEN J T, et al. Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis[J]. Measurement, 2016, 79: 147-157.
[7]LIU C W, LI Y X, FANG L P, et al. Experimental study on a de-noising system for gas and oil pipelines based on an acoustic leak detection and location method[J]. International Journal of Pressure Vessels and Piping, 2017, 151: 20-34.
[8]LIU C W, WANG Y Z, LI Y X, et al. Experimental study on new leak location methods for natural gas pipelines based on dynamic pressure waves[J]. Journal of Natural Gas Science and Engineering, 2018, 54: 83-91.
[9]刘翠伟, 敬华飞, 方丽萍, 等. 输气管道泄漏声波衰减模型的理论研究[J]. 振动与冲击, 2018, 37(20): 109-114.
LIU Cuiwei,JING Huafei, FANG Liping,et al. A theoretical study on the attenuation model of leakage acoustic waves for natural gas pipelines[J]. Journal of Vibration and Shock, 2018, 37(20): 109-114.
[10]QU Z G, WANG H Y, AN Y, et al. Online monitoring method of hydrate agglomeration in natural gas pipelines based on acoustic active excitation[J]. Measurement, 2016, 92: 11-18.
[11]WANG X, GHIDAOUI M S. Identification of multiple leaks in pipeline: linearized model, maximum likelihood, and super-resolution localization[J]. Mechanical Systems and Signal Processing, 2018, 107: 529-548.
[12]LIANG W, ZHANG L B, XU Q Q, et al. Gas pipeline leakage detection based on acoustic technology
[J]. Engineering Failure Analysis, 2013, 31: 1-7.
[13]潘凌云, 赵岩, 高丙坤. 一种基于VMD和小波去噪的管道泄漏检测算法[J]. 自动化技术与应用, 2017, 36(9): 1-5.
PAN Lingyun, ZHAO Yan, GAO Bingkun. A pipeline leak detection algorithm based on VMD and wavelet denoising[J]. Control Theory and Applications, 2017, 36(9): 1-5.
[14]WANG X, GHIDAOUI M S. Pipeline leak detection using the matched-field processing method[J]. Journal of Hydraulic Engineering, 2018, 144(6): 04018030.
[15]曹源. 气固耦合管路振动机理研究[D]. 秦皇岛: 燕山大学, 2016.
[16]孙立瑛, 李一博, 靳世久, 等. 充液管道中声发射波的传播及衰减特性研究[J]. 压电与声光, 2008, 30(4):20-22.
SUN Liying, LI Yibo, JIN Shijiu, et al. Study on propagation and attenuation characteristics of acoustic emission wave propagation along fluid loaded pipeline[J]. Piezoel Ectectrics & Acoustooptics, 2008, 30(4):20-22.
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