本文選題：煤氣系統(tǒng) + 離心式壓縮機　； 參考：《東北大學(xué)》2011年碩士論文

【摘要】：隨著工業(yè)規(guī)模的不斷擴大和工業(yè)過程復(fù)雜性的日益增加,離心壓縮機被廣泛應(yīng)用于冶金、石油、化工、天然氣輸送以及制冷等工業(yè)部門。離心壓縮機雖有很多優(yōu)點,但也有其本身難以消除的缺點,如不適用于氣量小的場合、穩(wěn)定工況區(qū)較窄、易喘振等等。喘振是離心壓縮機的固有特性,出現(xiàn)喘振是很危險的,嚴(yán)重時會危及壓縮機的安全,為了保證離心壓縮機穩(wěn)定、長周期運行,必須快速判斷使其脫離喘振工況。 本文以寶鋼集團的燃氣—蒸汽聯(lián)合循環(huán)發(fā)電機組的煤氣系統(tǒng)為研究對象。針對上述出現(xiàn)的一些問題,從系統(tǒng)實際運行的角度出發(fā),通過數(shù)據(jù)建模和混合建模的方法建立煤氣系統(tǒng)中離心壓縮機的數(shù)學(xué)模型。由于系統(tǒng)具有多變量、非線性的特性,傳統(tǒng)的數(shù)據(jù)建模方法在處理非線性問題上精度不高。本文采用基于核函數(shù)的偏最小二乘(KPLS)方法,利用核函數(shù)將低維空間的非線性回歸轉(zhuǎn)化為高維空間的線性回歸,KPLS方法可以克服實際生產(chǎn)工藝中非線性因素對模型的不利影響。 本文利用現(xiàn)場的數(shù)據(jù),以煤氣成分、質(zhì)量流量、入口壓力、入口溫度等作為輸入變量,建立基于KPLS方法的離心壓縮機模型。針對機理模型誤差較大、精度不高的問題,建立了離心壓縮機混合模型�；旌夏Ｐ褪怯蓹C理模型和誤差補償器兩部分并聯(lián)組成,采用基于KPLS方法訓(xùn)練誤差補償器。仿真分析表明基于KPLS方法的壓縮機模型準(zhǔn)確可靠、精度較高。
[Abstract]:With the continuous expansion of industrial scale and the increasing complexity of industrial processes, centrifugal compressors are widely used in metallurgy, petroleum, chemical, natural gas transportation and refrigeration industries. Although centrifugal compressor has many advantages, it also has some disadvantages, such as it is not suitable for the situation of small volume of gas, the stable working condition is narrow, the surge is easy, and so on. Surge is the inherent characteristic of centrifugal compressor. Surge is very dangerous and will endanger the safety of compressor. In order to ensure the stability and long period operation of centrifugal compressor, it must be judged quickly to get rid of surge condition. In this paper, the gas system of the gas-steam combined cycle generator set of Baosteel Group is taken as the research object. In view of the problems mentioned above, the mathematical model of centrifugal compressor in gas system is established by the method of data modeling and mixed modeling from the point of view of the actual operation of the system. Because the system is multivariable and nonlinear, the traditional data modeling method is not accurate in dealing with nonlinear problems. In this paper, the kernel function based partial least squares (KPLS) method is used to transform the nonlinear regression in low dimensional space into linear regression in high dimensional space. The KPLS method can overcome the adverse effects of nonlinear factors on the model in practical production process. In this paper, the centrifugal compressor model based on KPLS method is established with gas composition, mass flow rate, inlet pressure and inlet temperature as input variables. In order to solve the problem that the error of mechanism model is large and the precision is not high, the mixed model of centrifugal compressor is established. The hybrid model is composed of mechanism model and error compensator in parallel. The error compensator is trained based on KPLS method. Simulation results show that the compressor model based on KPLS method is accurate and accurate.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號】：TH452

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