Research And Development Of Drilling Database System For Carbon Fiber Composites

The design and development of drilling database system for carbon fiber composites, which is aimed at helping processing personnel on forecasting the drilling force and temperature and choosing reasonable drilling parameters quickly.The traditional method of selecting drilling parameters is hard to meet the modern production needs of the quick selection of reasonable drilling parameters, so establishing a database system to predict drilling force and drilling temperature and optimize drilling parameters is benefit to decrease the workload of processing personnel, improve the production efficiency, and eventually reduce the processing cost. The main research content of this paper is as follows:(1) According to the software engineering thought, the overall scheme of drilling database system for carbon fiber composites has been reseaarched, the demand of the database system is analyzed and the structural design of system's function module is completed under the premise of the specific requirements of drilling. The E-R model of drilling database system for carbon fiber composites is established, and the different data sheets of drilling database for carbon fiber composites is determined.(2) According to the drilling experiment in carbon fiber composite material,the influence of spindle speed and the amount of feed per revolution to drilling force and drilling temperature is summarized. Drilling force,drlling temperature and tool wear are predicted by two methods of multiple linear regression and BP neural network, and a comparative study of two methods is made. The results show that more reliable BP neural network algorithm is to be used for data forecast when linear relationship of the result on regression analysis' s data processing were not notable.(3) This thesis establishs a drilling parameter optimization model with the minimal processing time(the maximum productivity) as the objective function, the spindle speed and feed rate of per revolution as variable and the technical requirements of drilling force, drilling temperature, hole wall roughness as the constraints on the basis of the prediction model.It combines the genetic algorithm optimization theory and uses this algorithm to compute the minimum of the objective function and obtain the optimized drilling parameters.(4) Based on the above research contents, the drilling database system for carbon fiber composites is developed by applying the language of C#? SQL Server?Matlab and the system running instance has been given.