【摘要】：石油泵站單套機(jī)組由一部電機(jī)和一臺(tái)離心泵構(gòu)成,是石油集輸生產(chǎn)過程的核心設(shè)備。為了避免因設(shè)備故障而導(dǎo)致安全生產(chǎn)事故,建立輸油泵機(jī)組工作狀態(tài)實(shí)時(shí)監(jiān)測(cè)與故障診斷系統(tǒng)具有非常重要的意義。輸油泵機(jī)組在運(yùn)行狀態(tài)下伴有振動(dòng)和噪聲,而這種特定的運(yùn)行噪聲含有豐富的設(shè)備狀態(tài)信息,可以作為客觀評(píng)估設(shè)備運(yùn)行狀態(tài)及故障診斷的依據(jù)。目前應(yīng)用聲學(xué)診斷技術(shù)進(jìn)行設(shè)備故障診斷已經(jīng)成為領(lǐng)域新的研究熱點(diǎn),盡管人們對(duì)于電機(jī)和離心泵各自運(yùn)行噪聲產(chǎn)生機(jī)理、典型故障成因及其引發(fā)噪聲異變機(jī)理基本明晰,但是如何從整體運(yùn)行噪聲中準(zhǔn)確的辨識(shí)各類典型故障尚需進(jìn)一步研究。本課題提出基于噪聲分析法的石油泵站機(jī)組故障自動(dòng)監(jiān)測(cè)技術(shù)研究,期待從技術(shù)層面提高輸油泵機(jī)組運(yùn)行狀態(tài)評(píng)估的可靠性及故障判斷的精準(zhǔn)性。本課題融合虛擬儀器技術(shù)、聲學(xué)檢測(cè)與分析技術(shù),以輸油泵機(jī)組的組成結(jié)構(gòu)及噪聲特性參數(shù)為依據(jù),以從石油泵站現(xiàn)場(chǎng)采集的機(jī)組運(yùn)行噪聲為分析樣本,通過理論和試驗(yàn)相結(jié)合的方式進(jìn)行系統(tǒng)研究。本文重點(diǎn)探索汽蝕故障所引發(fā)的噪聲頻譜異變,從而進(jìn)一步確定汽蝕故障的檢測(cè)方法與汽蝕發(fā)生初期判別算法。具體試驗(yàn)研究過程中針對(duì)輸油泵故障在線實(shí)時(shí)監(jiān)測(cè)過程中實(shí)現(xiàn)汽蝕故障初期狀態(tài)的精準(zhǔn)判別,需要依據(jù)具體機(jī)組汽蝕噪聲特征確定汽蝕故障初期噪聲比對(duì)分析樣本。為此,提出基于特征頻率分析的輸油泵汽蝕故障初期噪聲樣本合成方法。本課題依據(jù)輸油泵汽蝕故障噪聲異變機(jī)理,在石油集輸生產(chǎn)現(xiàn)場(chǎng)采集FS100-65-200機(jī)組運(yùn)行噪聲樣本中捕捉汽蝕故障初期噪聲頻譜,按幅值遞減方式從中提取N個(gè)單頻信號(hào),以此為基準(zhǔn)基于LabVIEW實(shí)現(xiàn)汽蝕故障初期噪聲樣本合成。具體實(shí)現(xiàn)分三步:特征頻率選擇與標(biāo)定、對(duì)應(yīng)幅值設(shè)定、汽蝕故障初期特征噪聲多頻信息樣本合成。試驗(yàn)證明,合成頻率給定值調(diào)整步長(zhǎng)為1Hz,給定頻率與基準(zhǔn)頻率最大偏差0.32Hz,對(duì)應(yīng)合成信號(hào)與基準(zhǔn)信號(hào)幅值占比相對(duì)誤差最大值1.90%,該方法針對(duì)不同型號(hào)輸油泵機(jī)組具有可重復(fù)性和現(xiàn)實(shí)可操作性。
[Abstract]:The single unit of petroleum pumping station is composed of a motor and a centrifugal pump, which is the core equipment of petroleum gathering and transportation production process. In order to avoid accidents caused by equipment failure, it is of great significance to establish a real-time monitoring and fault diagnosis system for oil pump units. Oil pump unit is accompanied with vibration and noise in operation state, and this particular operating noise contains abundant information of equipment state, which can be used as the basis for objectively evaluating the equipment running state and fault diagnosis. At present, the application of acoustic diagnosis technology in equipment fault diagnosis has become a new research hotspot in the field, although the mechanism of noise generation, the cause of typical faults and the mechanism of noise aberration caused by motor and centrifugal pump are basically clear. However, how to identify the typical faults accurately from the whole running noise still needs further study. In this paper, the automatic fault monitoring technology of oil pumping station based on noise analysis method is proposed. It is expected to improve the reliability of operation state evaluation and the accuracy of fault judgment of oil pump unit from the technical level. The subject combines virtual instrument technology, acoustic detection and analysis technology, based on the structure of the oil pump unit and noise characteristic parameters, and takes the unit running noise collected from the oil pumping station as the analysis sample. Systematic research is carried out by combining theory with experiment. In this paper, the noise spectrum variation caused by cavitation fault is discussed, and the detection method of cavitation fault and the discrimination algorithm in the initial stage of cavitation are further determined. In the process of specific test and research, it is necessary to determine the initial noise comparison analysis sample according to the cavitation noise characteristics of specific units in order to accurately distinguish the initial state of cavitation failure in the process of on-line real-time monitoring of oil pump faults. Based on the characteristic frequency analysis, an initial noise sample synthesis method for oil pump cavitation fault is proposed. According to the noise variation mechanism of oil pump cavitation fault, the noise spectrum of the initial cavitation fault is captured in the sample of operating noise of FS100-65-200 unit collected from oil gathering and transportation production site, and N single frequency signals are extracted according to the mode of amplitude decrement. Based on LabVIEW, the initial noise sample synthesis of cavitation fault is realized. The realization is divided into three steps: characteristic frequency selection and calibration, corresponding amplitude setting, and multi-frequency sample synthesis of characteristic noise in the initial stage of cavitation failure. Experiments have proved that, The adjustment step of the synthetic frequency is 1 Hz, the maximum deviation between the given frequency and the reference frequency is 0.32 Hz, and the maximum relative error ratio of the synthetic signal to the reference signal is 1.90. This method has repeatability for different types of oil pump units. And practical maneuverability.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TE977

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本文編號(hào)：2233318