Talking about the Modeling Process of CNC Machine Tools
At present, most of the research on intelligent CNC machining is limited to the direct measurement of cutting force level, but there are many problems: the bottom area of ​​the machined workpiece is strictly limited by the effective area of ​​the force measuring platform, and the depth of the dynamometer Change is not sensitive and expensive. These defects make the technology difficult to put into practical use.
To change the research perspective, the AC servo motor current used in modern CNC machine tools has a certain nonlinear relationship with the cutting load. If a self-organizing fuzzy neural network can be used to establish the strong robust nonlinearity between the two. The relational model is used for indirect measurements, and the problems with the dynamometer can be solved.
The modeling experiment uses MIMO self-organizing fuzzy neural network (3×3×15×125×125×3×3), and the total number of nodes of the network is: 3+3+15+125+125+3+3=277; The total connection weight is: 3+15+125×3+125×3+3=771, where: each fuzzy set of the member function layer is divided into five fuzzy subsets (NS, NB, ZE, PS, PB), rules The layer contains C15C15C15=125 nodes. The parameters of the measured current signal and the cutting force signal are respectively, and are scaled and finally normalized. The number of data samples of the network model is 1024×5=5120, and finally the network approximation model can be obtained.
(Finish)
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