Applying Genetic Algorithm and BP Neural Network Model to Predict Cutting Area Temperature Distribution in the Laser-Assisted Milling

Abstract:

Laser assisted milling(LAM) can change the cutting processability of the workpiece, which is evaluated by the temperature of cutting zone. Therefore, the prediction of cutting zone temperature in LAM has an important practical meaning. There is a kind of complicated nonlinear relation between the cutting zone temperature and its adjacent temperature. Meanwhile the BP neural network (BP NN)can truly elaborate the nonlinear relation. In this paper, a new kind of algorithm combined the advantages of genetic algorithm (GA) and BP neural network is introduced to predict the temperature correctly. GA is used to train connection weights and biases of BP neural network. According to the characteristics of cutting area temperature distribution, the adjacent temperature and time are selected as the judging indexes. Then the model of predicting the cutting zone temperature is built. Practical application reveals that the model is a very efficient method.

• Periodical: Materials Science Forum (Volumes 800-801)
• Pages: 275-279
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.800-801.275
• Online since: July 2014
• Authors: Xue Feng Wu*, Teng Fei Gao, Bo Wen Zhao, He Rong Cao
• Keywords: BP Neural Network (BPNN), Genetic Algorithm (GA), Laser Assisted Milling, Temperature Distribution

References

[1] Rozzi J C, Pfefferkorn F E, Incropera F P, et al. Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: I. Comparison of predictions with measured surface temperature histories[J]. International Journal of Heat and Mass Transfer, 2000, 43(8): 1409-1424.

DOI: 10.1016/s0017-9310(99)00217-3

[2] Rozzi J C, Incropera F P, Shin Y C. Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: II. Assessment of parametric effects[J]. International Journal of Heat and mass transfer, 2000, 43(8): 1425-1437.

DOI: 10.1016/s0017-9310(99)00219-7

[3] Tian Y, Shin Y C. Thermal modeling for laser-assisted machining of silicon nitride ceramics with complex features[J]. Journal of manufacturing science and engineering, 2006, 128(2): 425-434.

DOI: 10.1115/1.2162906

[4] Tian Y, Wu B, Anderson M, et al. Laser-assisted milling of silicon nitride ceramics and Inconel 718[J]. Journal of manufacturing science and engineering, 2008, 130(3).

DOI: 10.1115/1.2927447

[5] Li Hua. Neural network based on improved genetic algorithm[D]. Tai Yuan: Taiyuan University of Technology, (2007).

[6] XIAO Hongfei, TIAN Yunli. Prediction of mine coal layer spontaneous combustion danger based on genetic algorithm and BP neural networks[J]. Procedia Engineering 2011, (26): 139-146.

DOI: 10.1016/j.proeng.2011.11.2151

[7] Shi F, Wang Xiaochuan et al. Analysis of 43 neural network cases[M]. Bei Jing: Bei Hang University Press, (2013).