Analysis Of Thrust Force And Research On Adaptive Controller In CFRP Drilling Process

The carbon fiber reinforced polymers (CFRP) are highly promising materials for the application in aeronautical and aerospace industries due to its series of excellent performances such as high specific strength, high specific stiffness, corrosion resistant, heat fatigue resistance and high design freedom. On the other hand, CFRP has its own weakness and the domestic production-manufacturing level is low, so the drilling efficiency and drilling quality of CFRP are direct restrictions to the development of this new material.Taking the drilling process of CFRP as the research object in this paper, the factors caused poor quality were analyzed by utilizing a software named ABAQUS. Then technologies and theories such as BP neural network, adaptive control and MATLAB were used to design an adaptive controller based on neural network which can be adopted to control the drilling process of CFRP. The detailed work is as following:1. By searching information about CFRP to learn the current situation, the performance of HT3/5224that is the workpiece in this paper and the reasons why hole defects appear. The main factor leading to hole defects is drilling force, especially the overload thrust force.2. Based on the above situation, a3D finite element (FE) model of drilling CFRP is developed in this article. The thrust force in drilling process under different machining parameters was simulated by utilizing ABAQUS. Good agreement was obtained between the experimental and numerical simulation results of the thrust force under the same machining parameters, which demonstrated that the3D FE model is reasonable and it can predict the thrust force effectively. Using ABAQUS to do a numerical simulation study on drilling process of CFRP provides a new research approach to replace the traditional experiment and convenience to optimize technical parameters as well. This new method can induce the experiment cost significantly also.3. Because the drilling efficiency of CFRP is low and the main factor leading to hole defects is drilling force, this paper combined the neural network and adaptive control technology, which are developed rapidly in recent years, to the drilling process of CFRP. And an adoptive controller based on BP neural network aimed to control the thrust force was designed. Then the software MATLAB was used to train and test the adoptive controller. The well trained adoptive controller could be applied to the drilling process of CFRP to adjust the feeding speed timely, so the thrust force could be controlled effectively, the hole defect could be reduced and the drilling efficiency of CFRP could be improved also. At the end, the application prospect of this kind of adaptive controller is put forward.