燃气长直管道泄漏检测及定位方法研究
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摘要
目前，我国国民经济的持续高速发展对能源，特别是燃气资源的需求越来越迫切。随着我国西部天然气大开发和国外天然气的大量引进，燃气管道的长度越来越长，并且呈现高压力、大管径的特点。伴随着这些高压燃气管道的长度不断增加，管道泄漏事故也时有发生。因为管道内燃气压力很高，一旦发生泄漏，会造成严重的生命财产损失和环境污染。因此，及时发现泄漏并定位泄漏位置，开展应对措施，对燃气管道安全至关重要。本文采用实验和理论相结合的方法，对燃气长直管道的泄漏检测与定位做了以下的研究：
根据燃气流动基本控制方程，针对燃气管道正常工况和泄漏工况，利用特征线法分别推导了基本控制方程对应的差分方程，研究了相应的计算方法。根据燃气流动的运动方程和能量方程推导出管道沿线压力和温度分布。建立了燃气管道泄漏的储罐模型、小孔模型、大孔模型和管道模型。并利用计算算例，对模型的正确性进行了验证，实现了燃气管道泄漏量的计算。
根据实验研究目的，考虑研究对象的物理模型和实验条件，改造搭建了燃气直管道泄漏检测实验台。研究了光纤光栅应变传感器检测管道内压力变化的原理，并进行了实验测试。结合流体力学理论，对泄漏实验结果进行了分析，验证了实验研究的可行性。
为了利用基于扩展卡尔曼滤波器的方法来检测泄漏并定位泄漏位置，将滤波器估计的实时模型法的基本思想与已经建立的离散化的泄漏工况下的管道瞬态流动模型结合，假设泄漏分布在分段点上，从而建立离散化的包含多点泄漏的瞬态流动模型。将分段点上泄漏量包含到模型中，并使其成为状态变量的一个分量。利用扩展卡尔曼滤波器对状态变量进行估计，并利用等效管道的原理，研究了实际管道泄漏量和泄漏位置的计算方法。应用模拟算例和实验数据测试验证了该方法。
负压波法是目前应用最广泛的管道泄漏检测与定位的方法，但这种方法的漏报率比较高、定位精度比较低。本文将光纤传感技术与负压波法结合，提出一种改进负压波法，并研究了此方法泄漏检测及定位的原理。研究了基于小波阈值法的负压波信号降噪的方法。通过实验对比及负压波衰减规律的研究，从技术和理论上分析了改进负压波法检测效果优于负压波法的原因。
为了应用改进负压波法定位泄漏位置，首先研究了小波分析寻找信号突变点的方法，并利用此方法得到负压波传播到上下游光纤光栅应变传感器的时间差。其次，考虑管道内气体流速变化和负压波传播速度变化对泄漏定位的影响，建立了改进的燃气管道泄漏定位算法，并利用复化辛普森和二分法进行求解。最后，应用实验数据测试验证了该方法的定位效果。
为了降低误漏报率、减少人工，将模式识别的理论引入到燃气管道的泄漏检测。提取改进负压波法采集到的泄漏工况和正常工况下的波形特征作为输入特征向量，并由此建立基于最小二乘支持向量机的燃气管道泄漏检测模型，实现了燃气管道泄漏的实时智能检测。
The demand for energy, especially for natural gas resources, is becoming more urgent now. With the exploitation of natural gas in western China and the import of foreign natural gas, pipelines connecting natural gas fields to demand centers are becoming longer, of increased pressure and with larger diameter pipes. In this case, pipeline leakage accidents occur frequently, and lead to serious life and property loss and environmental pollution. Therefore, it is vital to detect and locate the leaks in time and to carry out countermeasures to prevent leaks. Therefore, this thesis presents research toward the detection and locating of leakage in long straight pipelines using both experimental and theoretical techniques.
For normal conditions and leakage conditions, differential equations of basic gas flow equations are deduced respectively using the method of characteristic line. Pressure and temperature distribution along the pipeline are obtained based on the equations of motion and the energy equation. The gas pipeline leakage models (a storage tank model, a small hole model, a large hole model and a pipe model) are establised, these four models are verified using simulation data, thus, leakage rate can be calculated.
Toward to this research object, consider the physical model and the experimental condition, a gas pipeline leakage detection test bench is built. The principle of Fiber Bragg grating (FBG) strain sensors detecting pipeline internal pressure changes is studied, and also experimental tested. Combined with hydrodynamic theory, the leakage test results were analyzed to verify the feasibility of experimental studies.
In order to use the extend kalman filter (EKF) based method to detect and locate leaks in natural gas pipeline, the basic idea of real-time model for filter and the established discrete transient pipe flow model including one point leakage are combined. In this condition, assuming the leak points are distributed on the segment, so a discrete transient flow model includes multi-point leakage are obtained. The leakage amount of segment points is included in this discrectizaion model and taken as a component of state variables. Consider the impact of system noise and measurement noise, the EKF is employed to estimate the flow of hydraulic elements, such as leakage amout et al. The leakage amount and leakage position formulas are eatablished. Simulation example and experimental data are used to test and verify this method.
The negative pressure wave (NPW) method is currently the most widely used method for pipeline leak detection and location. However, high rates of false positives and low accuracy of positioning are the main drawbacks of this method. In this thesis, the method of using FBG strain sensors to detect negative pressure waves is studied and experimental tested. From this, an improved NPW method for leak detection and location is proposed and the principle of this method is studied. Using this method, the signal from FBGs is de-noised by a wavelet threshold method. Based on the comparison of experimental results and the study of the negative pressure wave attenuation law, the reasons why an improved NPW method is superior to a conventional NPW method is technically and theoretically analyzed.
In order to locate the leakage position using the improved NPW method, firstly, wavelet analysis is employed to find the signal point mutation. Therefore, the time difference between the arrivals of the negative pressure wave propagates at the upstream and downstream FBG strain sensors can be calculated. Secondly, an improved leak location formula is proposed based on the variation in the negative pressure wave propagation velocity and the gas velocity variation, and Compound Simpson and Dichotomy Searching are employed to solve this formula. Finally, the positioning effect is verified by using experimental data.
To reduce the false alarm rate and labor, the pattern recognition theory is introduced into the leak detection field. Using this theory, the features of the normal signal and leakage signal, as captured by FBG strain sensors are extracted as input feature vectors, and thus a least squares support vector machine (LS-SVM) based gas pipeline leak detection model is built, a real-time intelligent gas pipeline leak detection system is achieved.
根据燃气流动基本控制方程，针对燃气管道正常工况和泄漏工况，利用特征线法分别推导了基本控制方程对应的差分方程，研究了相应的计算方法。根据燃气流动的运动方程和能量方程推导出管道沿线压力和温度分布。建立了燃气管道泄漏的储罐模型、小孔模型、大孔模型和管道模型。并利用计算算例，对模型的正确性进行了验证，实现了燃气管道泄漏量的计算。
根据实验研究目的，考虑研究对象的物理模型和实验条件，改造搭建了燃气直管道泄漏检测实验台。研究了光纤光栅应变传感器检测管道内压力变化的原理，并进行了实验测试。结合流体力学理论，对泄漏实验结果进行了分析，验证了实验研究的可行性。
为了利用基于扩展卡尔曼滤波器的方法来检测泄漏并定位泄漏位置，将滤波器估计的实时模型法的基本思想与已经建立的离散化的泄漏工况下的管道瞬态流动模型结合，假设泄漏分布在分段点上，从而建立离散化的包含多点泄漏的瞬态流动模型。将分段点上泄漏量包含到模型中，并使其成为状态变量的一个分量。利用扩展卡尔曼滤波器对状态变量进行估计，并利用等效管道的原理，研究了实际管道泄漏量和泄漏位置的计算方法。应用模拟算例和实验数据测试验证了该方法。
负压波法是目前应用最广泛的管道泄漏检测与定位的方法，但这种方法的漏报率比较高、定位精度比较低。本文将光纤传感技术与负压波法结合，提出一种改进负压波法，并研究了此方法泄漏检测及定位的原理。研究了基于小波阈值法的负压波信号降噪的方法。通过实验对比及负压波衰减规律的研究，从技术和理论上分析了改进负压波法检测效果优于负压波法的原因。
为了应用改进负压波法定位泄漏位置，首先研究了小波分析寻找信号突变点的方法，并利用此方法得到负压波传播到上下游光纤光栅应变传感器的时间差。其次，考虑管道内气体流速变化和负压波传播速度变化对泄漏定位的影响，建立了改进的燃气管道泄漏定位算法，并利用复化辛普森和二分法进行求解。最后，应用实验数据测试验证了该方法的定位效果。
为了降低误漏报率、减少人工，将模式识别的理论引入到燃气管道的泄漏检测。提取改进负压波法采集到的泄漏工况和正常工况下的波形特征作为输入特征向量，并由此建立基于最小二乘支持向量机的燃气管道泄漏检测模型，实现了燃气管道泄漏的实时智能检测。
The demand for energy, especially for natural gas resources, is becoming more urgent now. With the exploitation of natural gas in western China and the import of foreign natural gas, pipelines connecting natural gas fields to demand centers are becoming longer, of increased pressure and with larger diameter pipes. In this case, pipeline leakage accidents occur frequently, and lead to serious life and property loss and environmental pollution. Therefore, it is vital to detect and locate the leaks in time and to carry out countermeasures to prevent leaks. Therefore, this thesis presents research toward the detection and locating of leakage in long straight pipelines using both experimental and theoretical techniques.
For normal conditions and leakage conditions, differential equations of basic gas flow equations are deduced respectively using the method of characteristic line. Pressure and temperature distribution along the pipeline are obtained based on the equations of motion and the energy equation. The gas pipeline leakage models (a storage tank model, a small hole model, a large hole model and a pipe model) are establised, these four models are verified using simulation data, thus, leakage rate can be calculated.
Toward to this research object, consider the physical model and the experimental condition, a gas pipeline leakage detection test bench is built. The principle of Fiber Bragg grating (FBG) strain sensors detecting pipeline internal pressure changes is studied, and also experimental tested. Combined with hydrodynamic theory, the leakage test results were analyzed to verify the feasibility of experimental studies.
In order to use the extend kalman filter (EKF) based method to detect and locate leaks in natural gas pipeline, the basic idea of real-time model for filter and the established discrete transient pipe flow model including one point leakage are combined. In this condition, assuming the leak points are distributed on the segment, so a discrete transient flow model includes multi-point leakage are obtained. The leakage amount of segment points is included in this discrectizaion model and taken as a component of state variables. Consider the impact of system noise and measurement noise, the EKF is employed to estimate the flow of hydraulic elements, such as leakage amout et al. The leakage amount and leakage position formulas are eatablished. Simulation example and experimental data are used to test and verify this method.
The negative pressure wave (NPW) method is currently the most widely used method for pipeline leak detection and location. However, high rates of false positives and low accuracy of positioning are the main drawbacks of this method. In this thesis, the method of using FBG strain sensors to detect negative pressure waves is studied and experimental tested. From this, an improved NPW method for leak detection and location is proposed and the principle of this method is studied. Using this method, the signal from FBGs is de-noised by a wavelet threshold method. Based on the comparison of experimental results and the study of the negative pressure wave attenuation law, the reasons why an improved NPW method is superior to a conventional NPW method is technically and theoretically analyzed.
In order to locate the leakage position using the improved NPW method, firstly, wavelet analysis is employed to find the signal point mutation. Therefore, the time difference between the arrivals of the negative pressure wave propagates at the upstream and downstream FBG strain sensors can be calculated. Secondly, an improved leak location formula is proposed based on the variation in the negative pressure wave propagation velocity and the gas velocity variation, and Compound Simpson and Dichotomy Searching are employed to solve this formula. Finally, the positioning effect is verified by using experimental data.
To reduce the false alarm rate and labor, the pattern recognition theory is introduced into the leak detection field. Using this theory, the features of the normal signal and leakage signal, as captured by FBG strain sensors are extracted as input feature vectors, and thus a least squares support vector machine (LS-SVM) based gas pipeline leak detection model is built, a real-time intelligent gas pipeline leak detection system is achieved.
引文
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