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The Research Of Calculating Form Error Based On Genetic Algorithms

Posted on:2003-08-28Degree:DoctorType:Dissertation
Country:ChinaCandidate:P LiaoFull Text:PDF
GTID:1101360125958129Subject:Mechanical design and theory
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This dissertation mainly discussed the research on the theory of Genetic algorithms based on real encoding, the application of Genetic algorithms at function optimization, and the computation of simply form error, flat curve form error, complex surface form error. Follow are mainly study contents in this paper.1.Study and discussion of Genetic algorithms theory.This dissertation put up systemic and embedded research for genetic algorithms with real number encoding, Proposed Normalization Real number encoding, then discussed and studied the mechanism of the pattern theory, the definition of fitting function, analyzed and researched copy arithmetic, cross arithmetic and mutation arithmetic with normalization Real number encoding, studied the relation both length of normalization real number encoding and optimization precision, analyzed the convergence of genetic algorithms based on normalization real number encoding with Markov chain, discussed the calculating efficiency and performance of genetic algorithms based on normalization real number encoding. Aimed at mult-dimension optimization problem, proposed the mult-dimension combine genetic algorithms, and particularly studied its copy arithmetic, cross arithmetic and mutation arithmetic.2. Research of the function optimization technology with genetic algorithms based on normalization real number encoding.Following study works has been developed in this dissertation at function optimization problem:l)Studied the optimization problem of single dimension function with genetic algorithms based on normalization real number encoding, discussed the selection of control parameters, genetic arithmetic and fitting function, analyzed its convergence speed, at last test and analyzed the performance by use of a series of typical function.2) Studied the optimization problem of mult-dimension function with genetic algorithms based on normalization real number encoding, discussed the selection of control parameters, genetic arithmetic and fitting function, analyzed its convergence speed. With the test of a series of typical functions, The author probed that this method can accelerate convergence speed of global optimization solution.3) Discussed solved the constraint optimization problem by use of combined with genetic algorithms based on normalization real number encoding, penalty function method and simulated annealing algorithm. With The test of a series of typical functions, The author probed that this method has better convergence.3. Research of the calculating of basic form errors with genetic algorithms.This dissertation in turn set up the mathematic model of describing circularity error, flat straightness error, space straightness error, flatness error, cylindricity error, taper error and sphere error, it resolved the calculating problems of simplex form error for satisfying minimal zone law.This dissertation applied the research result of genetic algorithms based on normalization real number encoding to calculating complex form error, it can precision obtain the resolve of simplex form error and be realized easily with computer. This method inaugurated a new route for the data process of simplex form error.4. Research of calculating flat curve form error with genetic algorithms.According to minimal zone law, This dissertation set up the mathematic models of describingflat standard function curve form error, established the mathematic model of describing flat complex curve form error with B-sample function, in turn establish their fitting functions, then calculate form error with mult-dimension parallel genetic algorithms based on normalization real number encoding. The solution satisfy minimal zone law.5.Calculating of surface form error with genetic algorithms.According to minimal zone law, This dissertation set up the mathematic models of describing standard parameter surface form error, established the mathematic model of describing complex surface form error with B-sample function, in turn establish their fitting functions, then calculate...
Keywords/Search Tags:genetic algorithms, real number encoding, function optimization, form error, curve form error, surface form error
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