Prediction and optimization algorithm of process parameters for laser dressing grinding wheels
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1.
Laser Research Institute, Hunan University, Changsha 410082, China;
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2.
State Key Laboratory of Advanced Design and Manufacturer for Vehicle Body, Hunan University, Changsha 410082, China
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Received Date:
2014-04-21
Accepted Date:
2014-05-04
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Abstract
In order to find a method of prediction and optimization of laser dressing grinding wheel, an optimization model of process parameters for laser dressing grinding wheels was established based on the neural network and particle swarm optimization. Firstly, the neural network model mapping the relationship between the process parameters and the specimen surface roughness was constructed . Then, the process parameters were optimized by means of the particle swarm optimization algorithm based on the predication model. Finally, laser dressing experiments were carried out based on 5 groups of parameters optimized by the particle swarm algorithm. Experimental results show that the relative error between the sample value and output value from neural network is less than 3% and the relative error between the test value and the expected value is lower than 6%. In conclusion, the model has good ability of optimization.
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