Research On Key Technologies Of HSM Based On SPA

With the global economic recovery, the demand of manufacturing industries graduallyincreasing. High-speed cutting as one of the main mode of production in modernmanufacturing industries, which has become an important trend. However, there are stillmany problems in High-speed cutting field. Firstly, researches on cutting are most focus onspecial process conditions, which lead to the conclusion of the research cannot be widelyused. Secondly, High-speed cutting is a complex physical-chemical process, at the sametime the research on the mechanism of physical-chemical has reached a bottleneck. Finally,control processing quality and costs is always the target of High-speed cutting, however,previous studies are main rely on check and recheck to find error, which is inefficient anduneconomic. Besides, during recheck, a lot of resources are wasted on defective products. Inorder to solve these problems, main research contents of this thesis are as follows:(1) Feasible experimental program is designed based on the characteristic of issue.Obtained experimental data at the maximum, while minimizing the number of tests. A dataacquisition experimental program based on uniform design and orthogonal design isproposed, which effectively control the experiment cost.(2) Combine with Mathematical model processing function of Matlab, a dataprocessing program is designed. Several Mathematical models processing, fitting andforecasting the collected data at the same time. In order to obtain the optimal model,compare the consistency of all the models by setting certain parameters indicators, whichsolve the mathematical model cannot be used widely in previous studies.(3) Based on the optimal model obtained above, SPC theory is applied to high-speedmachining process monitoring. The idea of online monitoring for high-speed machiningprocess is proposed. Firstly, analysis control charts are used to determine whether theprocess can be controlled or not. Then conducts a process capability evaluation. Finally,control charts are used to monitoring cutting process, judgments will be made if there areexceptions. This method solve the problem mentioned above, and put the cutting process ina precaution status.(4) Based on SPC control mentioned above, Neural Networks is used to diagnose theexceptions judged by SPC, which realized SPA. By simplifying fault type of high-speedmachining process and choosing reasonable fault type and system input characteristics to build up probabilistic neural network to train and classify data, which well diagnose thecomplex fault type.(5) Matlab software is chosen as the develop platform and its matrix processingfunction is used to processing experimental data, then SPC control charts are completed, andfinally neural network mode is used to develop fault diagnosis.Based on the research mentioned above, the problem that mathematical model cannotbe used widely is effectively solved. At the same time, use statistical data processing toavoid inaccuracy of physical-chemical. On the other hands, the application of statisticalprocess control and neural network fault diagnosis improves passive checks after cutting.