本文選題：故障診斷 + 泄漏檢測��； 參考：《河北科技大學》2015年碩士論文

【摘要】：管道運輸在石油、天然氣以及其他流體輸送中占有重要的地位,管道故障一旦發(fā)生,不僅影響油氣的正常運輸,甚至引發(fā)爆炸火災等事故,同時也給人類的生命財產(chǎn)安全和國家的經(jīng)濟建設造成威脅。因此,研究基于聲波特征的管道泄漏信息融合故障診斷方法具有重要的理論意義和實際應用價值。本文以油氣管道泄漏故障聲波信號為研究對象,分析管道故障特征提取方法,結(jié)合故障信號的特點,給出聯(lián)合時-頻域分析方法,并選擇希爾伯特變換方法對故障信號進行分析。在此基礎(chǔ)上,本文提出一種形態(tài)開-閉和閉-開的混合形態(tài)濾波方法,用于濾除聲波信號中的噪聲,實現(xiàn)信號預處理功能。針對經(jīng)驗模態(tài)分解中出現(xiàn)的模態(tài)混疊現(xiàn)象,本文提出一種改進經(jīng)驗模態(tài)分解時頻分析方法,對聲波信號進行時頻分析,實現(xiàn)管道泄漏聲波信號的檢測。模擬實驗研究表明提出的混合形態(tài)濾波方法可實現(xiàn)對故障信號的預處理；改進的經(jīng)驗模態(tài)分解方法可以有效解決經(jīng)驗模態(tài)分解中出現(xiàn)的模態(tài)混疊問題,并能準確得到音波信號的時頻特征信息。由此可見,基于聲波特征的管道泄漏信息融合故障診斷方法的研究,為油氣管網(wǎng)故障診斷提供了新途徑。
[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.
【學位授予單位】：河北科技大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TE973.6;TN912.3

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本文編號：2060584