输油管道泄漏实时监测报警系统的研究与开发
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摘要
本系统采用先进的微弱信号检测技术和现代信号处理技术，解决了低进站压力条件下泄漏负压波检测的难题，存在大量工业噪声的工况下，成功地检测出微弱的负压波信号。采用独特的信号自动分段技术和结构模式识别技术对泄漏进行判断，减少了误报率，提高了检测灵敏度。本系统基于对泄漏引发的负压波波形结构特征的深入分析，提出了三个反映压力波信号结构变化的三个主要的统计特征参数，并给出了信号进入异常段时的判定公式。
本系统将先进的小波变换技术引入负压波特征拐点的捕捉。利用小波变换的快速算法(Mallat算法)对泄漏负压波信号进行了多分辨率分析，同时得到了其低频概貌和高频细节。因此稳定地提取了负压波的拐点，提高了定位的准确性。本文应用负压波检测的方法，通过数学分析工具小波分析对采集到信号进行处理，建立原油泄漏的综合数学模型，并提出了一种新型的原油长输管道原油泄漏检测的方法。这种方法能够在较短的时间内采集到现场原油泄漏的数据，从而达到快速准确判断出原油泄露点的目的。与传统的检测方法相比，该方法的泄漏检测速度快，具有较高的定位精度、灵敏度和可靠性。
This system, in which the advanced small-signal detection and modern signal processing techniques are introduced, has resolved a problem that it is difficult to detect the negative pressure wave caused by the leak of pipeline in the case of low oil pressure at oil stations and successfully detected small negative pressure wave signals in the presence of much industrial noise. And unique signal automatic segmentation and structural pattern recognition techniques are used to judge the leaks, which makes for a decrease in the rate of false alarms and an increase in the detection sensitivity. Based on in-depth analyses of the negative pressure wave structural features, this system brings forward three primary statistic characterization parameters reflecting structural changes of pressure wave signals, and provides a determinant formula for signals within abnormal segments.
The advanced wavelet transform technique is introduced into this system to capture the Leak inflexions of the negative pressure wave. And the negative pressure wave signals are multi-resolution analyzed to obtain its low-frequency profile and high-frequency details. Therefore, the said inflexions are stably captured so as to improve the location accuracy. This paper introduces the negative pressure wave detection method and wavelet analyses, one kind of mathematic analysis tools, to process the captured signals. Then the integrative mathematic model is set up for oil leak detection and one new leak detection method is brought forward for oil pipelines, which can collect field data in connection with oil leaks in shorter time so as to achieve the goal of locating the leak points quickly and accurately. Compared with the traditional detection methods, this method is quicker in leak detection, more accurate in location, higher in sensitivity and more reliable.
本系统将先进的小波变换技术引入负压波特征拐点的捕捉。利用小波变换的快速算法(Mallat算法)对泄漏负压波信号进行了多分辨率分析，同时得到了其低频概貌和高频细节。因此稳定地提取了负压波的拐点，提高了定位的准确性。本文应用负压波检测的方法，通过数学分析工具小波分析对采集到信号进行处理，建立原油泄漏的综合数学模型，并提出了一种新型的原油长输管道原油泄漏检测的方法。这种方法能够在较短的时间内采集到现场原油泄漏的数据，从而达到快速准确判断出原油泄露点的目的。与传统的检测方法相比，该方法的泄漏检测速度快，具有较高的定位精度、灵敏度和可靠性。
This system, in which the advanced small-signal detection and modern signal processing techniques are introduced, has resolved a problem that it is difficult to detect the negative pressure wave caused by the leak of pipeline in the case of low oil pressure at oil stations and successfully detected small negative pressure wave signals in the presence of much industrial noise. And unique signal automatic segmentation and structural pattern recognition techniques are used to judge the leaks, which makes for a decrease in the rate of false alarms and an increase in the detection sensitivity. Based on in-depth analyses of the negative pressure wave structural features, this system brings forward three primary statistic characterization parameters reflecting structural changes of pressure wave signals, and provides a determinant formula for signals within abnormal segments.
The advanced wavelet transform technique is introduced into this system to capture the Leak inflexions of the negative pressure wave. And the negative pressure wave signals are multi-resolution analyzed to obtain its low-frequency profile and high-frequency details. Therefore, the said inflexions are stably captured so as to improve the location accuracy. This paper introduces the negative pressure wave detection method and wavelet analyses, one kind of mathematic analysis tools, to process the captured signals. Then the integrative mathematic model is set up for oil leak detection and one new leak detection method is brought forward for oil pipelines, which can collect field data in connection with oil leaks in shorter time so as to achieve the goal of locating the leak points quickly and accurately. Compared with the traditional detection methods, this method is quicker in leak detection, more accurate in location, higher in sensitivity and more reliable.
引文
1．靳世久等．原油管道漏点定位技术．石油学报，1998：19(3)：93-97
2．王立宁等．热输原油管道瞬态压力波泄漏点定位研究．石油学报，2000；21(4)：93-96
3．靳世久等．原油管道泄漏检测与定位仪器仪表学报，1997：18(4)：343-347
4．靳世久等．瞬态负压波结构模式识别法原油管道泄漏检测技术．电子测量与仪器报,1998；12(1)：5944
5．玉立宁．原油输送管道泄漏检测理论及其监测系统的研究．中国学位论文库,Y281960
6．王立宁．瞬态负压波原油管道泄漏检测技术及其监测系统研究．中国学位论文库，Y193615
7．唐秀家．流体输送管道泄漏检测定位的方法及装置．CN 1 184931
8．刘忠勇等．一种新型管道泄漏监测装置．泊气储运，2000：19(6)：53-54
9．王可非．基于负压波的管道泄漏诊断．信息与控制，1992：21(4)217—221
10．王洪生．GPS在长输管道测量中的应用．天然气工业,1994；14(3)56-59
11．东北输油局科研所等．长输管线泄漏实时监测系统试验成功．中国石油报，1992：10(7)2
12．唐新环等．一种用于检测流体运输管道或储存罐泄漏的方法．CN103948
13．小波分析算法与应用 程正兴．西安交通大学出版社 1997 178—204
14. Hao Ye,et al.Application of wavelet transform to leak detection 11d location in transport pipelines-Engineering Simulation-,996; 13(6):1025-1032
15. Gunarathne GP, et al .Ultrasonic feature extraction techniquesor characterisation and quantification of scales in petroleum pipelines-998IEEEUltrasqnics Symposium.1998(1):859-64
16. Koyanagi Y, et al.Method of detecting leak from liquidtransportation pipeline-JP.56160499
17. Otterlstein SAFet al. System and method for locating breaks in liquid pipeline-US 3851521
18. Zharlg Jun.Designing a cost-effective and reliable pipeline leak-detection system. Pipes and Pipelines Inter □ ational.1997;42(1):20-26
19. Savic M.Appts. For detecting and determining position of leak in under-ground pipeline-US 5416724
20. Fraser AJ,et al. Providing surveillance for pipeline fortransport of e.g. oil and gas, comprises merging satellite data of piplinewith existing data to form current map, and comparing with
previous map to detect relative changes.Wo 200018124
21．宗孔德 胡广书 数字信号处理．北京：清华大学出版社．1988
22．杨福生 小波变换的工程分析与应用．北京：科技出版社．1999
23．王建 冉启文 纪延超等 小波变换频域特性分析．电力系统自动化．1998，22(7)
24．汪润生 周师熊 数据通讯工程．北京：人民邮电出版社．1990
25．高传善．计算机网络．北京：学苑出版社．1994
26．胡道元．计算机网络工程指南．北京：电子工业出版社．1993
27．秦前清．实用小波分析．西安电子科技大学出版社．1992
28．程正兴．国外小波及应用概况．工程数学学报，1992，9(3)125
29．周继成等．人工神经网络．北京：科技普及出版社．1993
30．粱学章等．二元样条函数与小波．天津计算数学年会文集．1991
2．王立宁等．热输原油管道瞬态压力波泄漏点定位研究．石油学报，2000；21(4)：93-96
3．靳世久等．原油管道泄漏检测与定位仪器仪表学报，1997：18(4)：343-347
4．靳世久等．瞬态负压波结构模式识别法原油管道泄漏检测技术．电子测量与仪器报,1998；12(1)：5944
5．玉立宁．原油输送管道泄漏检测理论及其监测系统的研究．中国学位论文库,Y281960
6．王立宁．瞬态负压波原油管道泄漏检测技术及其监测系统研究．中国学位论文库，Y193615
7．唐秀家．流体输送管道泄漏检测定位的方法及装置．CN 1 184931
8．刘忠勇等．一种新型管道泄漏监测装置．泊气储运，2000：19(6)：53-54
9．王可非．基于负压波的管道泄漏诊断．信息与控制，1992：21(4)217—221
10．王洪生．GPS在长输管道测量中的应用．天然气工业,1994；14(3)56-59
11．东北输油局科研所等．长输管线泄漏实时监测系统试验成功．中国石油报，1992：10(7)2
12．唐新环等．一种用于检测流体运输管道或储存罐泄漏的方法．CN103948
13．小波分析算法与应用 程正兴．西安交通大学出版社 1997 178—204
14. Hao Ye,et al.Application of wavelet transform to leak detection 11d location in transport pipelines-Engineering Simulation-,996; 13(6):1025-1032
15. Gunarathne GP, et al .Ultrasonic feature extraction techniquesor characterisation and quantification of scales in petroleum pipelines-998IEEEUltrasqnics Symposium.1998(1):859-64
16. Koyanagi Y, et al.Method of detecting leak from liquidtransportation pipeline-JP.56160499
17. Otterlstein SAFet al. System and method for locating breaks in liquid pipeline-US 3851521
18. Zharlg Jun.Designing a cost-effective and reliable pipeline leak-detection system. Pipes and Pipelines Inter □ ational.1997;42(1):20-26
19. Savic M.Appts. For detecting and determining position of leak in under-ground pipeline-US 5416724
20. Fraser AJ,et al. Providing surveillance for pipeline fortransport of e.g. oil and gas, comprises merging satellite data of piplinewith existing data to form current map, and comparing with
previous map to detect relative changes.Wo 200018124
21．宗孔德 胡广书 数字信号处理．北京：清华大学出版社．1988
22．杨福生 小波变换的工程分析与应用．北京：科技出版社．1999
23．王建 冉启文 纪延超等 小波变换频域特性分析．电力系统自动化．1998，22(7)
24．汪润生 周师熊 数据通讯工程．北京：人民邮电出版社．1990
25．高传善．计算机网络．北京：学苑出版社．1994
26．胡道元．计算机网络工程指南．北京：电子工业出版社．1993
27．秦前清．实用小波分析．西安电子科技大学出版社．1992
28．程正兴．国外小波及应用概况．工程数学学报，1992，9(3)125
29．周继成等．人工神经网络．北京：科技普及出版社．1993
30．粱学章等．二元样条函数与小波．天津计算数学年会文集．1991