發(fā)布時間：2018-03-08 06:10

  本文選題：離心式壓縮機　切入點：機理模型　出處：《東北大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：離心式壓縮機是工業(yè)生產(chǎn)中的關(guān)鍵設(shè)備,它具有排氣壓力高、輸送流量小的優(yōu)點,在航天、能源、化工及冶金等行業(yè)中發(fā)揮著十分重要的作用。為了適應(yīng)循環(huán)經(jīng)濟發(fā)展的需要,合理利用鋼鐵冶煉過程中的富余煤氣,節(jié)約能源,同時減少煤氣放散帶來的環(huán)境污染,寶鋼投產(chǎn)建成兼具經(jīng)濟效益和社會效益的燃?xì)狻羝?lián)合循環(huán)發(fā)電工程。離心壓縮機為燃?xì)廨啓C提供高壓煤氣,是整個發(fā)電工藝流程的重要設(shè)備。針對實際生產(chǎn)過程中離心式壓縮機系統(tǒng)的性能分析和研究,建立壓縮機系統(tǒng)的機理模型是主要的技術(shù)手段,而結(jié)合系統(tǒng)的實際運行數(shù)據(jù)確定模型中的參數(shù)是一個亟待解決的問題。 本文以寶鋼聯(lián)合循環(huán)發(fā)電機組離心壓縮機為對象,研究多級離心式壓縮機模型參數(shù)辨識問題。通過分析離心壓縮機的工作機理,利用壓縮機對煤氣做功過程中的能量守恒以及煤氣質(zhì)量守恒關(guān)系,建立離心壓縮機的機理模型。結(jié)合現(xiàn)場大量實測數(shù)據(jù),采用基于sigmoid函數(shù)的自適應(yīng)遺傳算法辨識機理模型中的四個非線性參數(shù),得到離心壓縮機的準(zhǔn)確模型,并利用現(xiàn)場數(shù)據(jù)對所建立的模型與標(biāo)準(zhǔn)遺傳算法和余弦改進(jìn)型自適應(yīng)遺傳算法擬合效果進(jìn)行了對比分析驗證。仿真結(jié)果表明,基于sigmoid函數(shù)的自適應(yīng)遺傳算法收斂速度更快,穩(wěn)定性更好,適合于處理傳統(tǒng)搜索算法解決不好的復(fù)雜的和非線性問題,具有全局優(yōu)化能力,且參數(shù)辨識后的模型輸出與實際測量值的相對誤差更小。模型驗證結(jié)果表明,辨識后的參數(shù)能夠準(zhǔn)確反應(yīng)離心式壓縮機的實際工作特性,得到較高精度的模型。
[Abstract]:Centrifugal compressor is a key equipment in industrial production. It has the advantages of high exhaust pressure and low flow rate. It plays a very important role in aerospace, energy, chemical and metallurgical industries. Make rational use of the surplus gas in the process of iron and steel smelting, save energy and reduce the environmental pollution caused by the gas emission at the same time, Baosteel put into operation a gas-steam combined cycle power generation project with both economic and social benefits. Centrifugal compressors provide high pressure gas for gas turbines. It is an important equipment in the whole power generation process. In view of the performance analysis and research of centrifugal compressor system in actual production process, establishing the mechanism model of compressor system is the main technical means. It is an urgent problem to determine the parameters of the model by combining the actual operation data of the system. In this paper, taking the centrifugal compressor of Baosteel combined cycle generating set as the object, the model parameter identification of the multistage centrifugal compressor is studied, and the working mechanism of the centrifugal compressor is analyzed. The mechanism model of centrifugal compressor is established by using the conservation of energy and gas quality in the process of work done by compressor on gas. The accurate model of centrifugal compressor is obtained by using adaptive genetic algorithm based on sigmoid function to identify four nonlinear parameters in the model of mechanism. The simulation results show that the adaptive genetic algorithm based on sigmoid function converges faster than the conventional genetic algorithm and cosine modified adaptive genetic algorithm. It is more stable and suitable for solving complex and nonlinear problems which are not well solved by traditional search algorithms. It has the ability of global optimization, and the relative error between the model output and the actual measured value after parameter identification is smaller. The model verification results show that, The identified parameters can accurately reflect the actual working characteristics of centrifugal compressor and obtain a higher precision model.
【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】：2012
【分類號】：TH452;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 高學(xué)金;王普;孫崇正;易建強;張亞庭;張會清;;基于實數(shù)編碼的自適應(yīng)遺傳算法及應(yīng)用[J];北京工業(yè)大學(xué)學(xué)報;2007年02期

2 朱少華,汪芳;基于遺傳算法的模糊神經(jīng)網(wǎng)絡(luò)在動態(tài)系統(tǒng)辨識中的應(yīng)用[J];電機與控制學(xué)報;2000年03期

3 徐晶;王成山;李曉輝;張來;吳彬;肖峻;;基于自適應(yīng)遺傳算法的配電網(wǎng)改造方案優(yōu)化[J];電力系統(tǒng)自動化;2007年14期

4 李紅星;基于遺傳算法的閉環(huán)系統(tǒng)辨識方法[J];電氣傳動;2000年03期

5 任子武;傘冶;;實數(shù)遺傳算法的改進(jìn)及性能研究[J];電子學(xué)報;2007年02期

6 崔平遠(yuǎn);飛行器參數(shù)辨識方法與應(yīng)用研究[J];飛行力學(xué);1996年03期

7 徐麗娜,李琳琳;遺傳算法在非線性系統(tǒng)辨識中的應(yīng)用研究[J];哈爾濱工業(yè)大學(xué)學(xué)報;1999年02期

8 陳世哲;劉國棟;浦欣;浦昭邦;胡濤;劉宛予;;基于優(yōu)勢遺傳的自適應(yīng)遺傳算法[J];哈爾濱工業(yè)大學(xué)學(xué)報;2007年07期

9 賀素良,喻壽益;基于動態(tài)補償參數(shù)和改進(jìn)的自適應(yīng)遺傳算法的系統(tǒng)辨識方法[J];計算機工程與應(yīng)用;2003年19期

10 鄺航宇;金晶;蘇勇;;自適應(yīng)遺傳算法交叉變異算子的改進(jìn)[J];計算機工程與應(yīng)用;2006年12期

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本文編號：1582711