粒子群优化向量积条件下的复杂机械结构 安全性分析
首发时间:2010-07-19
摘要:由于复杂结构受载条件很复杂,在采用有限元法进行力学加载分析时,建模烦琐,网格剖分也很困难,因此具有很大的局限性。用粒子群算法优化支持向量机的参数,避免了人为选择参数的盲目性,克服了传统非确定性方法过学习问题,提高了模型的训练速度和预测推广能力。本文在对复杂机械结构安全性分析深入研究的基础上提出了一种新的安全性分析方法,即通过对结构进行有限元分析,得到多组荷载效应,然后建立基于PSO-SVM的复杂机械结构安全性分析模型,以有限元分析结果为训练样本集,利用此模型可直接进行结构的安全性分析。本文最后应用该方法进行了实例分析,结果证明该法避免了有限元分析的复杂加载和长时间运算,有效地简化了复杂结构的安全性分析问题,通过分析得到的结果与实际结果的进行对比肯定了该方法的有效性。
关键词: 粒子群优化向量积 复杂结构 安全性分析 有限元分析 荷载效应
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The Security Analysis of Complicated Mechanical Structure Based on PSO-SVM
Abstract:The loading condition of complicated structure is very sophisticated. The finite element method in doing mechanical loading analysis possesses certain limits because of the difficulty in modeling and mesh generation. The use of particle swarm optimization to improve the parameters of vector machine can avoid the blindness caused by men in selecting parameters, thus solving the problem produced by traditional and uncertain methods and promoting the training speed and the ability to predict and popularize of the model. Based on in depth research, this paper comes up with a new security analysis. The new method adopts finite element method and gets various groups of loading effects, then establishes the security analysis of complicated mechanical structure based on PSO-SVM. So the structural security analysis can be directly conducted by taking the results of the infinite element analysis as the training sample sets. Lastly, this paper does example analysis by adopting this method. By doing so, the security analysis of complicated structure is greatly simplified. The effectiveness of this method is proved through the comparison of analysis results and the actual ones.
Keywords: PSO-SVM complicated structure security analysis infinite element analysis loading effect
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No.4378934486960127****
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