本文選題：壓縮機附屬管線振動 + 狀態(tài)監(jiān)測��； 參考：《華東理工大學(xué)》2017年碩士論文

【摘要】：在化工企業(yè)長期存在著“重設(shè)備輕管道”的思想,壓縮機組作為化工裝置的核心設(shè)備,與其相關(guān)的狀態(tài)監(jiān)測與故障診斷的研究較多。管道振動也是石化企業(yè)的安全隱患之一,然而對于壓縮機附屬管線的振動狀態(tài)監(jiān)測的研究卻非常少,在企業(yè)中,管道振動狀態(tài)的評估仍然停留在感官判斷上。綜上所述,本文就壓縮機附屬管線的振動進(jìn)行深入研究。首先,介紹了壓縮機及其附屬管線基礎(chǔ)的振動理論,包括壓縮機分類和三類壓縮機工作原理,以及往復(fù)式與螺桿式壓縮機的附屬管線的振動機理。其次,比較了API標(biāo)準(zhǔn)、ASME標(biāo)準(zhǔn)與ISO標(biāo)準(zhǔn)三種壓縮機附屬管線振動狀態(tài)評估方法,并選取API系列標(biāo)準(zhǔn)作為振動狀態(tài)的評價依據(jù)。結(jié)合石化公司項目實例,得到了需要重點監(jiān)測以及需要整改的管線。由于灰色-馬爾可夫鏈模型適用于小樣本數(shù)據(jù)的短期預(yù)測,而本研究需要根據(jù)少量點檢數(shù)據(jù)預(yù)測管道振動狀態(tài),因此采用灰色-馬爾可夫鏈模型預(yù)測管道未來的振動狀態(tài)�；疑�-馬爾可夫鏈模型以灰色GM(1,1)模型預(yù)測短期的管線振動數(shù)據(jù),并根據(jù)預(yù)測數(shù)列以馬爾可夫鏈模型預(yù)測未來管線振動的最大概率狀態(tài)。最后,采用Labview開發(fā)了管道振動數(shù)據(jù)的時域分析、頻域分析和趨勢圖分析功能,初步形成了用于管道振動狀態(tài)監(jiān)測和性能預(yù)測的軟件。
[Abstract]:The idea of "heavy equipment and light pipeline" exists in chemical enterprises for a long time. As the core equipment of chemical plant, the research on condition monitoring and fault diagnosis related to compressor unit is much more.Pipeline vibration is also one of the hidden safety problems in petrochemical enterprises. However, there is little research on monitoring the vibration state of the pipeline attached to the compressor. In the enterprise, the evaluation of pipeline vibration status is still focused on sensory judgment.To sum up, the vibration of the pipeline attached to the compressor is studied in this paper.Firstly, the vibration theory of compressor and its subsidiary pipeline foundation is introduced, including the classification of compressor and the working principle of three kinds of compressors, as well as the vibration mechanism of auxiliary pipelines of reciprocating and screw compressors.Secondly, three methods for evaluating the vibration state of the pipeline attached to the compressor are compared between the API standard and the ISO standard, and the API series standards are selected as the basis for the evaluation of the vibration state.Combined with the project example of petrochemical company, the pipeline needs to be monitored and rectified.The grey-Markov chain model is suitable for the short-term prediction of small sample data, but this study needs to predict the pipeline vibration state based on a small amount of spot check data, so the grey-Markov chain model is used to predict the future vibration state of the pipeline.Gray Markov chain model is used to predict short-term pipeline vibration data and Markov chain model is used to predict the maximum probability state of pipeline vibration in the future.Finally, the functions of time-domain analysis, frequency-domain analysis and trend chart analysis of pipeline vibration data are developed by using Labview, and a software for pipeline vibration state monitoring and performance prediction is preliminarily formed.
【學(xué)位授予單位】：華東理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TQ051.21

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