【摘要】：水泵應(yīng)用于國民經(jīng)濟(jì)和社會(huì)發(fā)展的各個(gè)領(lǐng)域,其技術(shù)性能的好壞影響著應(yīng)用效果的可靠性,故獲得水泵的各種性能參數(shù)是很有必要的。在一般含泵裝置的工程應(yīng)用中,通過水泵的性能曲線來研究水泵的運(yùn)行情況,但在泵系統(tǒng)的水力過渡過程(如水錘的計(jì)算及分析)的研究中,就需要用能反映在任意可能運(yùn)行條件下的泵運(yùn)行特性的全特性曲線。雖然有很多研究人員做過對水泵全特性曲線的預(yù)測工作,但結(jié)果還不夠精確,不能滿足某些實(shí)際工程應(yīng)用的需要,且沒有較實(shí)用的泵全特性預(yù)測軟件。所以對水泵全特性曲線資料的預(yù)測在理論研究和實(shí)際工程應(yīng)用價(jià)值方面均具有重要意義。本文的研究內(nèi)容和成果有： 1、對水泵全特性曲線的幾種表現(xiàn)方法進(jìn)行研究分析后,發(fā)現(xiàn)x-WH及x-WM坐標(biāo)水泵全面特性曲線在運(yùn)用中廣泛使用。對比幾種神經(jīng)網(wǎng)絡(luò)模型和算法,提出遺傳算法和徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)相結(jié)合的GARBF神經(jīng)網(wǎng)絡(luò)模型。 2、運(yùn)用GARBF神經(jīng)網(wǎng)絡(luò)模型,開發(fā)出以MATLAB為設(shè)計(jì)平臺(tái)的預(yù)測水泵全特性曲線的工程軟件。以已知的幾個(gè)比轉(zhuǎn)數(shù)的水泵全特性曲線資料做為樣本,進(jìn)行訓(xùn)練預(yù)測,可以得到任意比轉(zhuǎn)數(shù)泵的全特性曲線資料(以x-WH及x-WM曲線資料為表現(xiàn)方法)。 3、提出比較水泵全特性曲線的幾種預(yù)測方法的評價(jià)系統(tǒng),并運(yùn)用相關(guān)系數(shù)等評價(jià)指標(biāo)對用GARBF神經(jīng)網(wǎng)絡(luò)法的預(yù)測結(jié)果與已知樣本資料進(jìn)行擬合度判斷。結(jié)果顯示該方法的預(yù)測效果較好。并利用該評價(jià)系統(tǒng)對用GARBF網(wǎng)絡(luò)法與四項(xiàng)式擬合,及BP神經(jīng)網(wǎng)絡(luò)法預(yù)測的水泵全特性曲線資料進(jìn)行擬合度判斷,結(jié)果表明在預(yù)測水泵全特性曲線資料(尤其對離心泵)方面,GARBF網(wǎng)絡(luò)法比其他預(yù)測法準(zhǔn)確度高。
[Abstract]:Water pump is applied in various fields of national economy and social development, and its technical performance affects the reliability of application effect, so it is necessary to obtain various performance parameters of water pump. In the general engineering application of pump equipment, the performance curve of pump is used to study the running condition of pump, but in the hydraulic transition process of pump system (such as the calculation and analysis of water hammer), It is necessary to use a full characteristic curve that can reflect the pump operating characteristics under any possible operating conditions. Although many researchers have done the prediction of the full characteristic curve of the pump, the results are not accurate enough to meet the needs of some practical engineering applications, and there is no practical software for predicting the full characteristics of the pump. Therefore, the prediction of the full characteristic curve of water pump is of great significance in both theoretical research and practical engineering application value. The main contents and achievements of this paper are as follows: 1. After studying and analyzing several performance methods of water pump's full characteristic curve, it is found that the x-WH and x-WM coordinate water pump's overall characteristic curve is widely used in application. By comparing several neural network models and algorithms, a GARBF neural network model combining genetic algorithm and radial basis function neural network is proposed. 2. Using the GARBF neural network model, the engineering software of predicting the full characteristic curve of water pump based on MATLAB is developed. Based on the known total characteristic curves of pumps with specific rotation number as samples and training prediction, the full characteristic curve data of arbitrary specific rotation pumps can be obtained (represented by x-WH and x-WM curves). 3. The evaluation system of several forecasting methods for comparing the full characteristic curve of water pump is put forward, and the fitting degree between the prediction result of GARBF neural network method and the known sample data is judged by using correlation coefficient and other evaluation indexes. The results show that this method has good prediction effect. The evaluation system is used to judge the fitting degree of the whole characteristic curve of water pump predicted by GARBF network method and quaternion method and BP neural network method. The result shows that the whole characteristic curve data of pump (especially for centrifugal pump) are predicted. The accuracy of GARBF network method is higher than that of other prediction methods.
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH38;TP319

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王文海,冀四梅;水泵性能曲線的數(shù)學(xué)化處理方法[J];北京建筑工程學(xué)院學(xué)報(bào);2003年02期

2 黃席樾,劉菡萏,石為人;基于遺傳算法的 RBF 神經(jīng)網(wǎng)絡(luò)設(shè)計(jì)[J];重慶大學(xué)學(xué)報(bào)(自然科學(xué)版);1998年02期

3 李一波,黃小原;基于改進(jìn)排序遺傳算法的徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)色譜峰解析[J];分析化學(xué);2001年03期

4 張玉瑞,陳劍波;基于RBF神經(jīng)網(wǎng)絡(luò)的時(shí)間序列預(yù)測[J];計(jì)算機(jī)工程與應(yīng)用;2005年11期

5 陳達(dá)衛(wèi);水泵全特性曲線的神經(jīng)網(wǎng)絡(luò)預(yù)測模型的研究[J];煉油技術(shù)與工程;2004年12期

6 鄭銘,陳池,袁壽其;水錘數(shù)值計(jì)算的全特性曲線法[J];農(nóng)業(yè)機(jī)械學(xué)報(bào);2000年05期

7 周龍才,丘傳忻;水泵性能曲線的正交多項(xiàng)式擬合[J];排灌機(jī)械;2001年04期

8 談明高;劉厚林;吳賢芳;;基于FLUENT的離心泵水力性能預(yù)測技術(shù)[J];排灌機(jī)械;2008年03期

9 聶書彬,關(guān)醒凡,劉厚林;利用人工神經(jīng)網(wǎng)絡(luò)預(yù)測離心泵性能的探索[J];水泵技術(shù);2002年05期

10 劉光臨,郭滿華;水泵全性能曲線的計(jì)算機(jī)仿真[J];水利學(xué)報(bào);1998年08期

相關(guān)博士學(xué)位論文 前1條

1 侯霞;小波神經(jīng)網(wǎng)絡(luò)若干關(guān)鍵問題研究[D];南京航空航天大學(xué);2006年

相關(guān)碩士學(xué)位論文 前4條

1 蔣鴻;多級離心泵的全面性能預(yù)測[D];華中科技大學(xué);2005年

2 談明高;離心泵性能預(yù)測理論及其軟件開發(fā)[D];江蘇大學(xué);2006年

3 張健偉;離心泵葉輪參數(shù)化建模及葉片加工仿真的研究[D];西華大學(xué);2007年

4 王秀勇;離心泵流動(dòng)特征的數(shù)值分析[D];浙江大學(xué);2007年

，

本文編號(hào)：2334543