供水管道泄漏检测定位中的信号分析及处理研究
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摘要
由于各种人为和自然因素,比如管道腐蚀、地质沉降和城市建设等,城市供水管网泄漏事故时有发生,不可避免,若不能及时发现泄漏故障管道和确定管道泄漏位置,将造成大量水资源浪费。目前对压力管道泄漏检测与定位的主要研究工作集中在长输油、输气管道上,研发了解决相应实际问题的漏点发现和定位方法及仪器系统。由于供水管网与长输油管道和输气管道在空间分布、构成及工作条件上存在较大的差异,供水管网具有自身特点:1)管网空间分布复杂,主副及更次级管道组成一个复杂的拓扑管网系统,分支多、节点多;2)主副及更次级管道供水负荷不同,因此,在一个管网系统中的管道条件(如管内供水压力、管道材质、管径、管壁厚度、管道间接口形式和管道埋设条件等)复杂多变,主副及更次级管道条件差异较大;3)泄漏形式多种多样,包括小孔、裂纹和管道接口破裂等。因此,通常用于输油或输气管道的泄漏检测与定位方法较难在供水管道上应用。目前,基于泄漏声信号处理的方法已广泛应用在供水管道泄漏检测与定位中,主要的研究工作集中在泄漏声信号的传播机理、各种时延估计定位算法优化和泄漏检测仪器系统构建上,对泄漏声信号产生机理、泄漏声信号特征提取及辨识,以及解决我国供水管道泄漏检测定位中所面临的实际问题做的工作或研究较少,如传统时延估计泄漏定位方法需要准确知道被测管道长度和泄漏声传播速度这两个参数,但在实际应用中,两参数存在较大误差或难以获得,常导致定位不准或错误。
针对以上问题,论文主要研究工作如下:
1.根据流体力学和计算流体动力学基本理论,分析了因泄漏引起的泄漏管段流场,认为因泄漏引起的管内空泡声、湍流声和湍流附面层脉动压力是引起泄漏处管道振动的激励源,分析了管道泄漏条件(开口大小、管内压力等)与空泡声、湍流声和湍流附面层脉动压力间的关系;应用薄壳振动理论研究了在上述激励源下的管道振动特性。进行了泄漏声产生机理实验,验证了管道泄漏条件与泄漏声信号间的关系。
2.从泄漏声产生机理出发,分析了管道泄漏处湍流拟序结构与空泡间相互作用的机理,认为在该机理作用下,泄漏声信号产生过程具有“不可重复”的特征;由于相关函数具有分析时间序列拟序结构的能力,且近似熵从统计的角度区别时间过程的复杂性,因此,提出将信号相关分析和近似熵理论相结合的方法,提取泄漏声信号“不可重复”的特征,辨识管道泄漏故障发生;在实际检测现场,由于各种管内和管外固定声源噪声(如阀门噪声、工地施工噪声等)常导致泄漏误判和漏点定位错误,重点分析了管内固定噪声源(阀门噪声和接口噪声)的产生机理和特征,为复杂干扰环境下的泄漏辨识提供理论支持。将提出的泄漏信号特征提取和辨识方法应用于实际供水管道泄漏检测中,在各种管内管外干扰源下,提出的方法与其他方法相比具有低的漏检和误检率。
3.阐述了广义互相关、自适应滤波等时延估计方法的基本原理及其在泄漏定位中的应用,分析了这些传统定位方法在实际泄漏点定位中存在的问题。
4.研究了泄漏声信号在以管道、管内流体和管道埋设介质等构成的信道中传播的特征,从而构建了新的泄漏信号传感模型;阐述了盲系统辨识基本原理,由于泄漏声信号传播信道是高阶系统,且信道间存在病态问题,因此,提出采用overlap-save和相关函数配准原理构建代价函数,解决高阶信道估计和信道间的病态问题;采用遗传算法对多目标函数进行全局最优化,避免梯度算法收敛陷入局部最小点,对泄漏声信道辨识进行优化。通过高阶信道盲辨识仿真及实际泄漏声传播信道盲辨识,验证了该方法的有效性。
5.实际泄漏检测定位环境中,不可避免存在干扰噪声,尤其是各种突发干扰噪声,分析了该类噪声对泄漏声传播信道盲辨识的影响,提出了突发干扰噪声抑制方法;借助泄漏声信道盲辨识,研究了泄漏声传播速度与管道条件间的关系,进而获得一种不依赖声传播速度的泄漏定位方法;通过从辨识的泄漏声传播信道中提取新的定位参数,获得不依赖管道长度的泄漏定位方法。盲系统辨识与传统时延估计泄漏定位方法实际应用结果表明,盲系统辨识方法具有高于传统定位方法的应用优势和定位精度。
6.应用多功能、高性能的数字混合信号处理器构成实时数据采集、预处理嵌入式系统,实现检测数据的分布采集;以性价比极高的便携式个人计算机为仪器系统主机,采用虚拟仪器技术,将泄漏声信号特征提取及辨识方法、盲系统辨识定位方法应用到该技术平台上,软硬件结合,实现了泄漏检测与定位系统的各种仪器功能。
The leakage of pipe is one of the emergency problems confronted by water supply industry. It is necessary to find and locate the leak occurrences timely, which can be beneficial to maintain the safely running of pipeline and avoid the waste of water resource. The research on the leak detection and location of pressure pipelines mainly focuses on the long-distance oil and gas pipelines. Although the techniques involved in a leakage control program of long-distance oil and gas pipelines are well developed, the techniques are almost not appropriate for using in water pipelines. The reasons are as follows: 1) Because of the size and complexity of the water distribution network, the major and minor pipes in the network form a topological structure with multi-branch and multi-node. 2) Because of the different supply arrangements between major and minor pipes, the pipe conditions in the distribution network are diverse, such as the pipe size, pipe material, the pipe wall thickness, the joints and the cover conditions. 3) Leakage occurs in different components of the distribution system: transmission pipes, distribution pipes, service connection pipes, joints, valves, and fire hydrants. Causes of leaks include corrosion, material defects, faulty installation, excessive water pressure, water hammer, ground movement due to drought or freezing, and excessive loads and vibration from road traffic. Thus, the developed methods for leak detection and location in the long-distance oil and gas pipelines are almost not suitable for application in the water pipelines.
Acoustic leak detection techniques have been shown to be effective and are widely used in the nondestructive testing of water industry. The current studies mainly focus on the leak acoustic signal propagation characteristics and the optimization of leak location methods based on time delay estimation. In this thesis, the mechanism of leak acoustic signal generation, the feature extraction and identification and a new leak location method are investigated. The main work is provided as follows:
1. Aiming at the mechanism of leak acoustic signal generation, we investigate the leak fluid field in pipe by computational fluid dynamics (CFD). The results show that the unsteady flow separation at the leak hole, cavitations, and fluctuating pressure in a turbulent boundary layer are the excitation sources of leak noise. The effects of leak type, pipe pressure on the excitation sources are investigated. The vibration characteristics of the pipe under excitation are analyzed based on the thin shell vibration principle. The experimental results show the validness of the mechanism analyses.
2. According to the generation mechanism of the leak acoustic signal, the characteristics of the leak acoustic signal are investigated. The auto correlation technology is adopted to descript the leak signal characteristics due to the ability to analyze the coherence of time series. A new procedure to identify the leak acoustic signal from the disturbed noises is proposed based on the conjunction of correlation and approximate entropy algorithm.
3. The principle and application in leak location of the correlation and the adaptive filter techniques are introduced. The problems of the traditional leak location methods are analyzed.
4. In order to establish the leak detection signal model, the leak acoustic propagation characteristics are investigated experimentally. The leak acoustic channels may be supposed to be linear time-invariant FIR systems. It is noted that a leak acoustic channel system has an impulse response with quite a long sequence. Because the overlap-save technique is a block processing where the channel coefficients being identified are updated once per block of input data, it is accurate for the identification of a long impulse response. The cross-correlation fitting technique shows superior performance when the channel is close to unidentifiable. Therefore, two cost functions are constructed based on the overlap-save and the cross-correlation fitting techniques to identify the leak acoustic channels. As genetic algorithm (GA) requires no gradient calculation and is less susceptible to local optima, we adopt GA to optimize the cost functions in blind channel identification. The practical identification results show the validness of the proposed scheme.
5. Since the collected signals are heavily blurred by bursting interferences and present non-stationary, we propose a method to discriminate and remove the burst-type noise. Actually the acquired signals contain the characteristics related to the acoustic propagation channels, thus the blind system identification strategy is applied to estimate the transmission performances of acoustic channels. Then the times due to the propagation of the leak source signal traveling from the leak point to sensors are determined. The leak noise propagation velocity is directly calculated based on the estimated propagation times and pipe length. Here the variations of propagation velocity with pipe conditions are investigated experimentally. Due to the fact that the propagation times can be estimated by leak acoustic channel identification, for leak location, even if the information of pipe conditions is not available, the leak point can be located. This way, for leak location, the detection distance or the propagation velocity is no longer a prerequisite.
6. The intelligent leak detection and location instrument system consists of a host computer, multiple data acquisition units connected to accelerometers integrated with ICs. Based on the virtual instrumentation, the hardware combined with the software implements the functionalities of information acquisition, storage, transmission, processing and presentation.
针对以上问题,论文主要研究工作如下:
1.根据流体力学和计算流体动力学基本理论,分析了因泄漏引起的泄漏管段流场,认为因泄漏引起的管内空泡声、湍流声和湍流附面层脉动压力是引起泄漏处管道振动的激励源,分析了管道泄漏条件(开口大小、管内压力等)与空泡声、湍流声和湍流附面层脉动压力间的关系;应用薄壳振动理论研究了在上述激励源下的管道振动特性。进行了泄漏声产生机理实验,验证了管道泄漏条件与泄漏声信号间的关系。
2.从泄漏声产生机理出发,分析了管道泄漏处湍流拟序结构与空泡间相互作用的机理,认为在该机理作用下,泄漏声信号产生过程具有“不可重复”的特征;由于相关函数具有分析时间序列拟序结构的能力,且近似熵从统计的角度区别时间过程的复杂性,因此,提出将信号相关分析和近似熵理论相结合的方法,提取泄漏声信号“不可重复”的特征,辨识管道泄漏故障发生;在实际检测现场,由于各种管内和管外固定声源噪声(如阀门噪声、工地施工噪声等)常导致泄漏误判和漏点定位错误,重点分析了管内固定噪声源(阀门噪声和接口噪声)的产生机理和特征,为复杂干扰环境下的泄漏辨识提供理论支持。将提出的泄漏信号特征提取和辨识方法应用于实际供水管道泄漏检测中,在各种管内管外干扰源下,提出的方法与其他方法相比具有低的漏检和误检率。
3.阐述了广义互相关、自适应滤波等时延估计方法的基本原理及其在泄漏定位中的应用,分析了这些传统定位方法在实际泄漏点定位中存在的问题。
4.研究了泄漏声信号在以管道、管内流体和管道埋设介质等构成的信道中传播的特征,从而构建了新的泄漏信号传感模型;阐述了盲系统辨识基本原理,由于泄漏声信号传播信道是高阶系统,且信道间存在病态问题,因此,提出采用overlap-save和相关函数配准原理构建代价函数,解决高阶信道估计和信道间的病态问题;采用遗传算法对多目标函数进行全局最优化,避免梯度算法收敛陷入局部最小点,对泄漏声信道辨识进行优化。通过高阶信道盲辨识仿真及实际泄漏声传播信道盲辨识,验证了该方法的有效性。
5.实际泄漏检测定位环境中,不可避免存在干扰噪声,尤其是各种突发干扰噪声,分析了该类噪声对泄漏声传播信道盲辨识的影响,提出了突发干扰噪声抑制方法;借助泄漏声信道盲辨识,研究了泄漏声传播速度与管道条件间的关系,进而获得一种不依赖声传播速度的泄漏定位方法;通过从辨识的泄漏声传播信道中提取新的定位参数,获得不依赖管道长度的泄漏定位方法。盲系统辨识与传统时延估计泄漏定位方法实际应用结果表明,盲系统辨识方法具有高于传统定位方法的应用优势和定位精度。
6.应用多功能、高性能的数字混合信号处理器构成实时数据采集、预处理嵌入式系统,实现检测数据的分布采集;以性价比极高的便携式个人计算机为仪器系统主机,采用虚拟仪器技术,将泄漏声信号特征提取及辨识方法、盲系统辨识定位方法应用到该技术平台上,软硬件结合,实现了泄漏检测与定位系统的各种仪器功能。
The leakage of pipe is one of the emergency problems confronted by water supply industry. It is necessary to find and locate the leak occurrences timely, which can be beneficial to maintain the safely running of pipeline and avoid the waste of water resource. The research on the leak detection and location of pressure pipelines mainly focuses on the long-distance oil and gas pipelines. Although the techniques involved in a leakage control program of long-distance oil and gas pipelines are well developed, the techniques are almost not appropriate for using in water pipelines. The reasons are as follows: 1) Because of the size and complexity of the water distribution network, the major and minor pipes in the network form a topological structure with multi-branch and multi-node. 2) Because of the different supply arrangements between major and minor pipes, the pipe conditions in the distribution network are diverse, such as the pipe size, pipe material, the pipe wall thickness, the joints and the cover conditions. 3) Leakage occurs in different components of the distribution system: transmission pipes, distribution pipes, service connection pipes, joints, valves, and fire hydrants. Causes of leaks include corrosion, material defects, faulty installation, excessive water pressure, water hammer, ground movement due to drought or freezing, and excessive loads and vibration from road traffic. Thus, the developed methods for leak detection and location in the long-distance oil and gas pipelines are almost not suitable for application in the water pipelines.
Acoustic leak detection techniques have been shown to be effective and are widely used in the nondestructive testing of water industry. The current studies mainly focus on the leak acoustic signal propagation characteristics and the optimization of leak location methods based on time delay estimation. In this thesis, the mechanism of leak acoustic signal generation, the feature extraction and identification and a new leak location method are investigated. The main work is provided as follows:
1. Aiming at the mechanism of leak acoustic signal generation, we investigate the leak fluid field in pipe by computational fluid dynamics (CFD). The results show that the unsteady flow separation at the leak hole, cavitations, and fluctuating pressure in a turbulent boundary layer are the excitation sources of leak noise. The effects of leak type, pipe pressure on the excitation sources are investigated. The vibration characteristics of the pipe under excitation are analyzed based on the thin shell vibration principle. The experimental results show the validness of the mechanism analyses.
2. According to the generation mechanism of the leak acoustic signal, the characteristics of the leak acoustic signal are investigated. The auto correlation technology is adopted to descript the leak signal characteristics due to the ability to analyze the coherence of time series. A new procedure to identify the leak acoustic signal from the disturbed noises is proposed based on the conjunction of correlation and approximate entropy algorithm.
3. The principle and application in leak location of the correlation and the adaptive filter techniques are introduced. The problems of the traditional leak location methods are analyzed.
4. In order to establish the leak detection signal model, the leak acoustic propagation characteristics are investigated experimentally. The leak acoustic channels may be supposed to be linear time-invariant FIR systems. It is noted that a leak acoustic channel system has an impulse response with quite a long sequence. Because the overlap-save technique is a block processing where the channel coefficients being identified are updated once per block of input data, it is accurate for the identification of a long impulse response. The cross-correlation fitting technique shows superior performance when the channel is close to unidentifiable. Therefore, two cost functions are constructed based on the overlap-save and the cross-correlation fitting techniques to identify the leak acoustic channels. As genetic algorithm (GA) requires no gradient calculation and is less susceptible to local optima, we adopt GA to optimize the cost functions in blind channel identification. The practical identification results show the validness of the proposed scheme.
5. Since the collected signals are heavily blurred by bursting interferences and present non-stationary, we propose a method to discriminate and remove the burst-type noise. Actually the acquired signals contain the characteristics related to the acoustic propagation channels, thus the blind system identification strategy is applied to estimate the transmission performances of acoustic channels. Then the times due to the propagation of the leak source signal traveling from the leak point to sensors are determined. The leak noise propagation velocity is directly calculated based on the estimated propagation times and pipe length. Here the variations of propagation velocity with pipe conditions are investigated experimentally. Due to the fact that the propagation times can be estimated by leak acoustic channel identification, for leak location, even if the information of pipe conditions is not available, the leak point can be located. This way, for leak location, the detection distance or the propagation velocity is no longer a prerequisite.
6. The intelligent leak detection and location instrument system consists of a host computer, multiple data acquisition units connected to accelerometers integrated with ICs. Based on the virtual instrumentation, the hardware combined with the software implements the functionalities of information acquisition, storage, transmission, processing and presentation.
引文
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