Modeling of CMM dynamic error based on optimization of neural network using genetic algorithm

Qu Ying; Luo Zai; Lu Yi

doi:10.1117/12.885603

31 December 2010 Modeling of CMM dynamic error based on optimization of neural network using genetic algorithm

Qu Ying, Luo Zai, Lu Yi

Proceedings Volume 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation; 75445Q (2010) https://doi.org/10.1117/12.885603
Event: Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 2010, Hangzhou, China

Abstract

By analyzing the dynamic error of CMM, a model is established using BP neural network for CMM .The most important 5 input parameters which affect the dynamic error of CMM are approximate rate, length of rod, diameter of probe, coordinate values of X and coordinate values of Y. But the training of BP neural network can be easily trapped in local minimums and its training speed is slow. In order to overcome these disadvantages, genetic algorithm (GA) is introduced for optimization. So the model of GA-BP network is built up. In order to verify the model, experiments are done on the CMM of type 9158. Experimental results indicate that the entire optimizing capability of genetic algorithm is perfect. Compared with traditional BP network, the GA-BP network has better accuracy and adaptability and the training time is halved using GA-BP network. The average dynamic error can be reduced from 3.5μm to 0.7μm. So the precision is improved by 76%.

Citation Download Citation

Qu Ying, Luo Zai, and Lu Yi "Modeling of CMM dynamic error based on optimization of neural network using genetic algorithm", Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 75445Q (31 December 2010); https://doi.org/10.1117/12.885603

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available