【摘要】：隨著科技的發(fā)展，大型機械產品的設計逐漸從零件設計轉向系統(tǒng)設計，涉及的學科領域由單一學科領域變成多個學科領域，對設計系統(tǒng)的優(yōu)化從單目標優(yōu)化發(fā)展到多目標優(yōu)化。 大型水輪發(fā)電機作為一種大型機械，它的整體方案設計包含電氣、機械、水力等多個學科領域，需要不同學科領域的專家互相協(xié)作，這其中包含了多個關鍵技術：為提高效率，需要對水輪發(fā)電機方案設計中各領域的復雜模型進行近似建模；各個方案設計領域模型的解耦問題；為實現(xiàn)整體方案優(yōu)化，需要研究多目標優(yōu)化問題。 研究從水輪發(fā)電機設計案例中通過近似建模來獲取隱含的方案設計模型的方法。本文研究了兩種近似建模方法，針對變量個數(shù)少，設計空間維數(shù)低，要求精度不高的系統(tǒng)采取多項式響應面近似建模方法；針對變量個數(shù)較多，設計空間維數(shù)高，要求精度高的系統(tǒng)采取支持向量機近似建模方法。并對水輪發(fā)電機的材料成本和電磁領域分別進行了近似建模，驗證了兩種方法的適用性。 對于近似建模后獲得的設計模型中存在的耦合問題，本文研究了兩種解耦優(yōu)化方法，基于學科耦合變量最小方差的解耦方法和基于遺傳算法的多學科解耦優(yōu)化方法。對水輪發(fā)電機的定子重量耦合模型采用解耦方法進行了解耦優(yōu)化。 針對設計方案中的多目標優(yōu)化問題，提出了基于特征合成的多目標優(yōu)化方法，采用多個模型對提出的算法進行了算法驗證，并將算法運用到了水輪發(fā)電機的材料重量優(yōu)化的設計中，獲得較好的優(yōu)化結果。 基于上述研究結果，開發(fā)了水輪發(fā)電機多學科優(yōu)化系統(tǒng)，特別針對設計過程中的近似建模、解耦優(yōu)化和多目標優(yōu)化問題，開發(fā)了對應的功能模塊，可用于水電設備方案設計的多學科優(yōu)化。
[Abstract]:With the development of science and technology, the design of large-scale mechanical products is gradually changing from part design to system design, and the subject field is changed from a single discipline to a multi-disciplinary field. The optimization of design system develops from single-objective optimization to multi-objective optimization. As a kind of large machinery, the overall design of large hydrogenerator includes electrical, mechanical, hydraulic and other fields of study, which require experts from different disciplines to cooperate with each other, which includes several key technologies: to improve efficiency, It is necessary to approximate modeling the complex models in each domain of hydrogenerator scheme design; decouple the models in each scheme design domain; and study the multi-objective optimization problem in order to realize the overall scheme optimization. The method of obtaining implicit scheme design model by approximate modeling from hydrogenerator design case is studied. In this paper, two approximate modeling methods are studied. The polynomial response surface approximation modeling method is adopted for the system with less variables, low dimension of design space and low precision, and the number of variables is large, and the dimension of design space is high. Support vector machine (SVM) approximate modeling method is adopted in the system with high accuracy. The material cost and electromagnetic field of hydrogenerator are modeled approximately, and the applicability of the two methods is verified. For the coupling problem in the design model obtained by approximate modeling, this paper studies two decoupling optimization methods, one is based on the minimum variance of the subject coupling variable, the other is the multi-disciplinary decoupling optimization method based on genetic algorithm. Decoupling method is used to decouple the stator weight coupling model of hydrogenerator. Aiming at the multi-objective optimization problem in the design scheme, a multi-objective optimization method based on feature composition is proposed, and the algorithm is verified by using multiple models. The algorithm is applied to the design of material weight optimization of hydrogenerator, and better results are obtained. Based on the above research results, a multi-disciplinary optimization system for hydrogenerator is developed, especially for the approximate modeling, decoupling optimization and multi-objective optimization in the design process, and the corresponding functional modules are developed. It can be used for multi-disciplinary optimization of hydropower equipment scheme design.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM312

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本文編號：2151611