Based On BP Neural Networks Genetic Algorithm Special Robot For Hydraulic Turbine Repair Structural Optimization

Since 1960's,with the fact that development of discipline such as computer technology, Optimization technology have got prompt development Optimization theory, computer technology and engineering technology have combined closely, forming optimum technology, which is a modern design method, and technology. When resolving the complicated engineering design problem, the application optimizing a technology can realize the design plan optimization quicker, improve efficiency and quality of design. Have come true successfully owing to improving robot structural optimization design of integration of type BP neural networks with genetic algorithm in this paper.At first, introduction analyzes the development of optimization theory and actuality of optimum design application carefully. Analysing process of development BP neural networks and introducing that Applytion of Structural optimization designed detailedly by the summary. Have analysed the shortcoming and merit of tradition optimization algorithm and modern excellent optimization algorithm. Analyze feasibility and superiority of genetic algorithm based on ANN.The main body of the paper take Ansys Workbench software as implement. Choosed several typical posture in actual job condition of Special-purpose Robot for Hydraulic Turbine Repair.Under satisfying various constraint condition, Come true the analysis of the static and dynamics of robot. It is produced that the robot stress distribution cloud chart and the work terminal biggest displacement, which provide the data sample for network function training,studying and checking function based on BP neural networks and genetic arithmetic structural optimization.Analyze and research BP network's data prepares , hide layer of node numbers , network structure design.Be aimed at to whose shortcoming , bring forward improvement way. Be that improves network convergence speed by the constant momentum, Lead into genetic algorithm having avoided appearing part minimum value. Bring forward GA-BP algorithm for opitmum design.In the algorithm, Characteristics such as the overall property having owed genetic arithmeti and the neural networks.GA provides global initial solutions, from which ANN obtains the finial solutions.Thus,the defects of slow convergence with GA and easily falling into local lutions with ANN can be overcome. Have the fairly good overall situation and convergence speed. Making use of data sample gaining in Ansys Workbech to study finally, verify feasibility and validity of that method. According to that algorithm, construct a new method about net topological frame structure and join according to MATLAB toolbox passes programming. The structural optimization realizing BP neural networks , finite element method analysis , genetic algorithm being organically combined , being in progress to the Special-purpose Robot for Hydraulic Turbine Repair structural optimization on significance designs that really.