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Cui Changcai
Che Rensheng
Ye Dong
Huang Qingcheng
Department of Automatic Measurement
and Control,
Harbin Institute of Technology,
Harbin 150001, China |
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RESEARCH ON THE MINIMUM ZONE
CYLINDRICITY EVALUATION BASED
ON GENETIC ALGORITHMS*
Abstract: A genetic algorithm (GA)-based method is proposed to solve the nonlinear optimization problem of minimum zone cylindricity evaluation. First, the background of the problem is introduced. Then the mathematical model and the fitness function are derived from the mathematical definition of dimensioning and tolerancing
principles. Thirdly with the least squares solution as the
initial values, the whole implementation process of the
algorithm is realized in which some key techniques, for example,
variables representing, population initializing and such basic
operations as selection, crossover and mutation, are discussed
in detail. Finally, examples are quoted to verify the proposed algorithm. The computation results indicate that the GA-based optimization method performs well on cylindricity evaluation. The outstanding advantages conclude high accuracy, high efficiency and capabilities of solving complicated nonlinear and large space problems.
Key words:
Genetic algorithm (GA) Cylindricity Form error Minimum zone |