Dissertation > Industrial Technology > Metallurgy and Metal Craft > Cutting tools, abrasives,abrasive tools,fixtures,molds and hand tools > Tool > Cutter

Analysis of the study and simulation of the neural network model form cutter

Author ChenChao
Tutor HuangJianLong
School Lanzhou University of Technology
Course Mechanical Manufacturing and Automation
Keywords Neural Network Milling cutter Tool Condition Analysis Model Simulation MATLAB
Type Master's thesis
Year 2004
Downloads 116
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With the continuous improvement of the degree of automation in the manufacturing sector brought about many new problems to be addressed in the manufacturing , including tool wear and breakage . In the early mechanical processing , depends on the operating personnel observe the tool , the replacement of the tool , but in modern , automated continuous production system , the breakage of the tool will not only lead to failure of the function of the machine , but also constitutes a failure of the entire system . Therefore, the prediction tool wear and breakage generation , it is extremely urgent. Form cutter analysis neural network model . First cutter state classification, describes the characteristics of the various states , and the influencing factors were analyzed in detail . Second, for the typical four categories of state common form cutter , select the tool status is closely related to the characteristics of physical quantities as a neural network learning samples , acoustic emission signals , the cutting force signal power signal . Neural network nonlinear approximation ability , generalization of cutter wear for analysis. Neural network through a series of learning the training sample so that it has a diagnostic feature . Neural network model, and the model of a full analysis . Due to the scalability of the neural network structure , this model can be used in the other MILLS state analysis . The help of MATLAB neural network toolbox trained network simulation obtained sensitive characteristic parameters of the form cutter state of the simulation curve . The project provided for forming cutter state analysis model to prove the use of neural network model to form cutter diagnosis is entirely feasible . Due to the scalability of the neural network structure , the state diagnostic tool is also made ??possible , studies have shown that the model can effectively improve the quality and efficiency of processing .

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