【摘要】：水泵廣泛使用在國民經濟的各個部門，而隨著國民經濟的發(fā)展，對水泵及其輸運系統(tǒng)的運行安全性要求越來越高。然而對于水泵的研究還遠遠不能滿足實際需要，尤其是水泵全特性參數(shù)的研究。水泵全特性參數(shù)能夠表示水泵—水輪機的各種工況，對于水泵及其輸運系統(tǒng)的水力過渡過程的計算和分析至關重要，而水力過渡過程的計算直接影響水泵輸運系統(tǒng)的設計與建成后的運行安全。雖然在水泵全特性數(shù)據的獲取與預測方面，中外的學者們做了大量工作，但是截止目前實測數(shù)據稀少，預測工作的精度仍有待提高，因此尋找更好的模型對水泵全特性參數(shù)進行預測具有重要的實際意義。 本文的主要研究內容和成果有： 1、詳細介紹了水泵的相關理論，分析了水泵全特性曲線的應用，并對水泵全特性數(shù)據的獲取及預測方法進行了總結。 2、對神經網絡的神經元模型、學習算法、分類及常用模型進行了介紹，分析對比了幾種神經網絡的特點。對粒子群算法原理及其發(fā)展進行了介紹。構建了采用自適應慣性權重的粒子群算法來優(yōu)化RBF神經網絡的預測模型。 3、在MATLAB R2012b平臺上，利用MATLAB提供的神經網絡工具箱和GUI工具箱，基于提出的預測模型，，開發(fā)出水泵全特性曲線參數(shù)預測軟件。依據現(xiàn)有數(shù)據對未知水泵的全特性參數(shù)進行預測，采用合理方法對預測結果進行評價分析，并與其它方法進行對比，體現(xiàn)出本文方法的優(yōu)勢。 4、將開發(fā)的預測軟件應用于實際工程中，優(yōu)化了水力過渡過程的計算分析，對于水泵輸運系統(tǒng)中可能發(fā)生的問題，提出合理的防護措施。
[Abstract]:Pumps are widely used in various sectors of the national economy, but with the development of the national economy, the operational safety requirements of pumps and their transport systems are becoming more and more high. However, the research on the pump is far from meeting the actual needs, especially the study of the full characteristic parameters of the pump. The full characteristic parameters of the pump can express the various working conditions of the pump and turbine, which is very important for the calculation and analysis of the hydraulic transition process of the pump and its transportation system. The calculation of hydraulic transition process directly affects the design and operation safety of pump transportation system. Although scholars at home and abroad have done a great deal of work in obtaining and predicting the full characteristic data of pumps, the precision of prediction work needs to be improved because of the scarcity of measured data so far. Therefore, it is of great practical significance to find a better model to predict the full characteristic parameters of the pump. The main contents and achievements of this paper are as follows: 1. The related theory of water pump is introduced in detail, the application of the full characteristic curve of water pump is analyzed, and the method of obtaining and predicting the data of the whole characteristic of water pump is summarized. 2. The neuron model, learning algorithm, classification and common models of neural network are introduced, and the characteristics of several neural networks are analyzed and compared. The principle and development of particle swarm optimization (PSO) are introduced. An adaptive particle swarm optimization (PSO) algorithm is proposed to optimize the prediction model of RBF neural network. 3. On the platform of MATLAB R2012b, using the neural network toolbox and GUI toolbox provided by MATLAB, based on the proposed prediction model, the software for predicting the parameters of the full characteristic curve of water pump is developed. Based on the existing data, the full characteristic parameters of the unknown pump are forecasted. The reasonable method is used to evaluate and analyze the prediction results, and compared with other methods, the advantages of this method are reflected. 4. The developed prediction software is applied to practical engineering, the calculation and analysis of hydraulic transition process are optimized, and reasonable protective measures are put forward for the problems that may occur in the pump transportation system.
【學位授予單位】：長安大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TV136.2;TH38

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本文編號：2329033