Simulating thermally induced error in CNC machine tools

被引：0
|
作者：
Mehdi, Q [1 ]
Dixon, W [1 ]
Gough, N [1 ]
Pitchford, J [1 ]
机构：
[1] Wolverhampton Univ, Sch Comp & Informat Technol, Wolverhampton WV1 1SB, England
来源：
SIMULATION IN INDUSTRY'2000 | 2000年
关键词：
industrial engineering; neural network; model design; model evaluation;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The simulation of thermally induced volumetric errors in CNC machines using Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and multiple linear regressions (MLR) have been described in our previous work. It is intended to use the models to reduce these errors and improve performance during machining. This paper applies generalised regression neural networks to the problem of simulating non-linear volumetric errors for a specific CNC machine. The models produced are then compared with those produced using MLR and ANFIS.
引用
收藏
页码：215 / 219
页数：5
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