An Identification And Compensation Method For Identifying Static Geometric Errors Of The Optical Freeform Surfaces Machine Tool

With the development of technology and the demand of the market,the application of the optical freeform surface has become increasingly widespread.However,the domestic optical freeform surface machine tool is dependent on imports currently,which makes the cost of the optical freeform surface products extremely high.Therefore,it is of great significance to break through the key technologies of optical free-form surface processing machine tools.As the processing machine tool of the product,its processing accuracy directly affects the product quality.In order to improve the machining accuracy,in this paper,a feature-based static geometric error identification algorithm for the optical freeform surface machine is developed,and then the error compensation scheme of the fast tool system of the machine tool is designed.The precondition for machine tool error identification is to establish an appropriate model to describe the error transfer relationship.Based on the spatial structure of the machine tool,the topological relationship between the machine tool measuring system and the fast tool system is described by a multi-sequence array.In order to describe the in-depth intrinsic relationship of static errors,the reference coordinate systems of the above two systems are respectively established.Then a mathematical model of the static error of the machine tool system is established through multi-body system kinematics theory,which contains 13 independent static errors.In order to identify the static error of the system,a feature-based identification algorithm is proposed.Firstly,the geometric constraint relationships between the measurement system and the fast tool system are established respectively,and then the general constraint equations applicable to the two systems are constructed.Secondly,based on the constraint equations,a static error identification algorithm is proposed to design a matching feature sample.Finally,in order to verify the feasibility and accuracy of the error identification algorithm,MATLAB is used to simulate the system error identification process.Simulation analysis shows that the relative deviation of the 13 independent static errors identified by the algorithm is smaller than 15%.Using the static error model of the fast system as the objective function,based on the identified static error parameters,the optimal motion trajectory of the moving axis of the machine tool is obtained,realizing the compensation of the fast tool processing system.Simulation results show that the numerical iterative process converges.In order to verify the feasibility of the static error compensation algorithm,a preliminary experimental study on the measurement system and the fast system is conducted by standard plane calibration and lens processing.The measurement system is used to detect the standard plane,and then the coordinate of the sampling point of the standard plane is derived.The measurement accuracy of the measurement system is evaluated by comparing the measurement position of the sampling point with the actual position.Result shows that the measurement accuracy of the measurement system after compensation is smaller than 2μm.The lens is processed separately using the uncompensated and compensated sharp knife system,and the error compensation significantly improves the processing quality of the lens.In conclusion,experimental study shows that the static error identification algorithm and compensation algorithm proposed in this paper are feasible and effective.