Intelligence Selection System for Honing Parameter Based on Genetics and Artificial Neural Networks

Abstract:

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Appropriate selecting of process parameters influences the machining quality greatly. For honing, the main factors are product precision, material components and productivity. In view of this situation, a intelligence selection model for honing parameter based on genetics and artificial neural networks was built by using excellent robustness, fault-tolerance of artificial neural networks optimization process and excellent self-optimum of genetic algorithm. It can simulate the decision making progress of experienced operators, abstract the relationship from process data and machining incidence, realize the purpose of intelligence selection honing parameter through copying, exchanging, aberrance, replacement strategy and neural networks training. Besides, experiment was performed and the results helped optimize the theories model. Both the theory and experiment show the updated level and feasibility of this system.

Info:

Periodical:

Advanced Materials Research (Volumes 102-104)

Edited by:

Guozhong Chai, Congda Lu and Donghui Wen

Pages:

846-850

DOI:

10.4028/www.scientific.net/AMR.102-104.846

Citation:

W. Y. Pu et al., "Intelligence Selection System for Honing Parameter Based on Genetics and Artificial Neural Networks", Advanced Materials Research, Vols. 102-104, pp. 846-850, 2010

Online since:

March 2010

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Price:

$35.00

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