基于声波特征的管道泄漏信息融合故障诊断方法研究

发布时间：2018-06-24 07:23

本文选题：故障诊断 + 泄漏检测　；参考：《河北科技大学》2015年硕士论文

【摘要】：管道运输在石油、天然气以及其他流体输送中占有重要的地位,管道故障一旦发生,不仅影响油气的正常运输,甚至引发爆炸火灾等事故,同时也给人类的生命财产安全和国家的经济建设造成威胁。因此,研究基于声波特征的管道泄漏信息融合故障诊断方法具有重要的理论意义和实际应用价值。本文以油气管道泄漏故障声波信号为研究对象,分析管道故障特征提取方法,结合故障信号的特点,给出联合时-频域分析方法,并选择希尔伯特变换方法对故障信号进行分析。在此基础上,本文提出一种形态开-闭和闭-开的混合形态滤波方法,用于滤除声波信号中的噪声,实现信号预处理功能。针对经验模态分解中出现的模态混叠现象,本文提出一种改进经验模态分解时频分析方法,对声波信号进行时频分析,实现管道泄漏声波信号的检测。模拟实验研究表明提出的混合形态滤波方法可实现对故障信号的预处理；改进的经验模态分解方法可以有效解决经验模态分解中出现的模态混叠问题,并能准确得到音波信号的时频特征信息。由此可见,基于声波特征的管道泄漏信息融合故障诊断方法的研究,为油气管网故障诊断提供了新途径。
[Abstract]:Pipeline transportation plays an important role in the transportation of oil, natural gas and other fluids. Once the pipeline failure occurs, it will not only affect the normal transportation of oil and gas, but also cause accidents such as explosion and fire. At the same time, it also poses a threat to the safety of human life and property and the economic construction of the country. Therefore, it is of great theoretical significance and practical value to study the fault diagnosis method of pipeline leakage information fusion based on acoustic characteristics. In this paper, the acoustic wave signal of oil and gas pipeline leakage fault is taken as the research object, and the method of fault feature extraction is analyzed. Combining with the characteristics of the fault signal, a combined time-frequency domain analysis method is presented. The Hilbert transform method is chosen to analyze the fault signal. On this basis, a hybrid morphological filtering method is proposed, which is used to filter the noise in the acoustic signal and realize the signal preprocessing function. Aiming at the phenomenon of modal aliasing in empirical mode decomposition, an improved time-frequency analysis method of empirical mode decomposition is proposed in this paper, which can detect the acoustic signal of pipeline leakage by time-frequency analysis. The simulation results show that the proposed hybrid morphological filtering method can preprocess the fault signal, and the improved empirical mode decomposition method can effectively solve the modal aliasing problem in the empirical mode decomposition. The time-frequency characteristic information of acoustic signal can be obtained accurately. Therefore, the research of pipeline leakage information fusion fault diagnosis method based on acoustic characteristics provides a new way for oil and gas pipeline network fault diagnosis.
【学位授予单位】：河北科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE973.6;TN912.3

【参考文献】