管道泄漏检测中的VMD算法研究
发布时间：2018-07-22 19:38
【摘要】：保障管道安全生产有诸多技术手段,其中最重要并被广泛应用的是泄漏检测技术。管道在运行维护时,需要对管道信号进行实时监测,准确判断管道运行状况,及时诊断出存在的泄漏隐患,避免安全事故的发生。天然气管道泄漏产生的次声波信号属于非平稳信号,且在管道传播过程中受到严重的外界干扰,导致泄漏的误判率高,出现错报、漏报、误报的情况。自适应时频分析方法是分析非平稳信号的重要手段,针对实验室采集的管道泄漏产生的次声波信号的特征,本文利用基于相关系数的变分模态分解(Variational Mode Decomposition,简称VMD)算法选取预设尺度K值,再通过基于互信息的VMD算法进行管道特征提取,从而进行工况识别,从而提高系统对管道泄漏判断的准确率。本文主要工作有:1、查阅有关管道泄漏检测相关论文,深入了解管道泄漏检测的相关方法,选取VMD方法应用到天然气管道泄漏检测中;对管道泄漏检测存在的故障情况进行分析,对故障情况进行分类,最终确定模式识别的目标种类;完成不同管道运行情况下的信号采集。2、针对VMD算法存在难以选取预设尺度K和分解后的有效固有模态函数(Intrinsic Mode Function,简称IMF)分量的问题,提出了一种基于相关系数的VMD方法进行参数优化,并将其用于检测管道泄漏信号。首先通过仿真信号验证基于相关系数的VMD算法的有效性;最后将基于相关系数的VMD算法应用于管道泄漏信号检测中,对算法的可行性进行验证。3、针对VMD分解的高频部分受噪声干扰导致分解的高频部分效果不理想的问题,提出了基于互信息的VMD方法。首先通过仿真信号验证基于互信息的VMD算法的有效性;最后将基于互信息的VMD算法应用于管道泄漏信号检测中,对算法的可行性进行验证。对比VMD算法,验证该方法的有效性。4、针对管道不同工况信号,利用基于相关系数的VMD算法选取预设尺度K值,再通过基于互信息的VMD算法进行管道特征提取,从而进行工况识别,通过实验结果验证该方法的准确率和可行性。
[Abstract]:There are many technical means to ensure pipeline safety, among which leak detection technology is the most important and widely used. When the pipeline is running and maintaining, it is necessary to monitor the pipeline signal in real time, accurately judge the running condition of the pipeline, diagnose the hidden trouble of leakage in time, and avoid the occurrence of safety accident. The infrasonic wave signal produced by natural gas pipeline leakage belongs to non-stationary signal and is seriously disturbed by the outside world in the course of pipeline propagation, which leads to the high misjudgment rate of leakage and the occurrence of false alarm, false alarm and false alarm. Adaptive time-frequency analysis method is an important means to analyze non-stationary signals, aiming at the characteristics of infrasonic signals generated by pipeline leakage collected in laboratory. In this paper, the variable Mode decomposition (VMD) algorithm based on the correlation coefficient is used to select the preset scale K value, and then the pipeline feature is extracted by the mutual information based VMD algorithm to identify the working conditions. In order to improve the accuracy of the system to determine pipeline leakage. The main work of this paper is as follows: 1, referring to relevant papers on pipeline leakage detection, deeply understanding the relevant methods of pipeline leakage detection, selecting VMD method to be applied to natural gas pipeline leakage detection, and analyzing the fault situation of pipeline leakage detection. Classification of fault conditions, and finally determine the target type of pattern recognition; In order to solve the problem that it is difficult to select the preset scale K and the decomposed Intrinsic Mode function (IMF) component in the VMD algorithm, the signal acquisition under different pipeline operation conditions is completed. A VMD method based on correlation coefficient is proposed for parameter optimization, and it is used to detect pipeline leakage signal. At first, the validity of the VMD algorithm based on correlation coefficient is verified by simulation signal. Finally, the VMD algorithm based on correlation coefficient is applied to the detection of pipeline leakage signal. The feasibility of the algorithm is verified. A mutual information based VMD method is proposed to solve the problem that the high frequency part of VMD decomposition is not satisfactory due to the noise interference. At first, the validity of the mutual information based VMD algorithm is verified by the simulation signal. Finally, the mutual information based VMD algorithm is applied to the pipeline leakage signal detection, and the feasibility of the algorithm is verified. Comparing with the VMD algorithm, the validity of the method is verified. According to the pipeline signal under different working conditions, the default scale K value is selected by using the VMD algorithm based on the correlation coefficient, and then the pipeline feature is extracted by the VMD algorithm based on mutual information. The accuracy and feasibility of the method are verified by the experimental results.
【学位授予单位】：东北石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE973.6
，
本文编号：2138356
[Abstract]:There are many technical means to ensure pipeline safety, among which leak detection technology is the most important and widely used. When the pipeline is running and maintaining, it is necessary to monitor the pipeline signal in real time, accurately judge the running condition of the pipeline, diagnose the hidden trouble of leakage in time, and avoid the occurrence of safety accident. The infrasonic wave signal produced by natural gas pipeline leakage belongs to non-stationary signal and is seriously disturbed by the outside world in the course of pipeline propagation, which leads to the high misjudgment rate of leakage and the occurrence of false alarm, false alarm and false alarm. Adaptive time-frequency analysis method is an important means to analyze non-stationary signals, aiming at the characteristics of infrasonic signals generated by pipeline leakage collected in laboratory. In this paper, the variable Mode decomposition (VMD) algorithm based on the correlation coefficient is used to select the preset scale K value, and then the pipeline feature is extracted by the mutual information based VMD algorithm to identify the working conditions. In order to improve the accuracy of the system to determine pipeline leakage. The main work of this paper is as follows: 1, referring to relevant papers on pipeline leakage detection, deeply understanding the relevant methods of pipeline leakage detection, selecting VMD method to be applied to natural gas pipeline leakage detection, and analyzing the fault situation of pipeline leakage detection. Classification of fault conditions, and finally determine the target type of pattern recognition; In order to solve the problem that it is difficult to select the preset scale K and the decomposed Intrinsic Mode function (IMF) component in the VMD algorithm, the signal acquisition under different pipeline operation conditions is completed. A VMD method based on correlation coefficient is proposed for parameter optimization, and it is used to detect pipeline leakage signal. At first, the validity of the VMD algorithm based on correlation coefficient is verified by simulation signal. Finally, the VMD algorithm based on correlation coefficient is applied to the detection of pipeline leakage signal. The feasibility of the algorithm is verified. A mutual information based VMD method is proposed to solve the problem that the high frequency part of VMD decomposition is not satisfactory due to the noise interference. At first, the validity of the mutual information based VMD algorithm is verified by the simulation signal. Finally, the mutual information based VMD algorithm is applied to the pipeline leakage signal detection, and the feasibility of the algorithm is verified. Comparing with the VMD algorithm, the validity of the method is verified. According to the pipeline signal under different working conditions, the default scale K value is selected by using the VMD algorithm based on the correlation coefficient, and then the pipeline feature is extracted by the VMD algorithm based on mutual information. The accuracy and feasibility of the method are verified by the experimental results.
【学位授予单位】：东北石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE973.6
，
本文编号：2138356
本文链接：https://www.wllwen.com/kejilunwen/shiyounenyuanlunwen/2138356.html
