The Simulation And Forecast Of Varying Parameter's Vibration Drilling Based On Wavelet Neural Network

Multi-element varying-parameters vibration drilling is an optimal machining method supported for adapting the appearance of new-type material, optimizing the cutting process and improving the quality of hole machining. In the different section of drilling process, the method needs adopt the optimal vibration parameters and cutting parameters. But for the limitation of experiment equipments and other external factors, it is impossible for continually changing the parameters very extensively. So it is necessary to analyze and simulate cutting process roundly by using computers. It demands us to use cutting theory, vibration theory, control theory to describe the system visually, structure the simulation model of vibration drilling and implement the dynamic simulation of vibration drilling. All the work must be based on system identification.The multi-element orthogonal polynomial regression is used for traditional optimization technique of parametric optimum design, and the experimental research is done by some experiential formula. This research need describe the system visually by using cutting theory, vibration theory, control theory etc, then the simulation model can be structured. It must deal with data greatly, and the non-linear relationship between capability guideline and factors is very complex and difficulty to describe accurately. In recent years, with the development of Neural Network techniques, there are some examples of Neural Network models to simulate the vibration drilling process and optimize the parameters of brass materials, and the estimated results is very right.Wavelet Transform theory has been put forward by Grossman and Morlet, two France scientists in 1970's, when they analyzed the signs of the earthquake. They founded the inversion formulas based on practical demand and experiment. The Wavelet Transform is a part change of the time and the frequency. So the signs can be picked up effectively. The signs and the functions can be also multi-scale analyzed by the operational function such as flexing and parallel moving. And many difficult questions that Fourier cannot be figured out have been solved now. The Wavelet Transform is famous as the mathematical microscope. It is a sign as a landmark for the analysis phylogeny.The Wavelet neural network is a result combined by the wavelet analysis and the neural network. If we think it from a form of the network, it is a combination of Wavelet analysis and the feed front type. Usually, the sigmoid function of the concealed nodes, which is in theneural network of the formal single concealed layer, is replaced by Wavelet function. The corresponding weight, which is from input layer to concealed layer, and concealed layer threshold value are replaced by yardstick of Wavelet function and parallel moving parameters.This dissertation puts forward a method that unites the neural network and the Wavelet function, and then applies it to the drilling process' simulation and parametric optimum. The method has broadened the application field of computer intelligence. And the good result has been obtained.The whole dissertation consists of six parts.The first chapter introduces the origin and development of the neural network and the wavelet theory, and discusses the current situation and develop trend with regard to the computer intelligent technology on mechanism machining and vibration drilling field. And then ascertain the studying content and direction of this article.Chapter 2 introduces the basic knowledge and applying field and develop trend of the neural network and the Wavelet theory.Chapter 3 introduces the neural network model which is in the process of varying parameter's vibration drilling. And the correlative concepts have been also presented. Varying parameter's vibration drilling is the best optimum methods of process. In the varying drilling section, the optimum parameters of vibration and drilling need to be adopted. It must obtain the best optimum parameters of the every layer material for the beginning drilling and the midd...