Research On Volumetric Accuracy Measuring Points Planning Of 5-axis Machine Tool Based On Laser Tracker

Five-axis CNC machine tools are widely used in the machining of complex curved parts,and play a decisive role in aerospace,automotive,marine and other manufacturing fields.As a key indicator to measure the performance of machine tools,machining accuracy is the focus of current research in the field of machine tools.volumetric error is a direct manifestation of the machine tool error sources in the machining space.How to quickly and accurately detect and compensate volumetric errors is an effective way to improve the machining accuracy of the machine tools,and it is also an urgent problem to be solved.This paper takes the five-axis CNC machine tool as the research object,takes the improvement of the space precision of the machine tool as the main goal,and studies the detection,modeling and error identification methods of the machine tool's volumetric error.Among them,the emphasis is placed on the in-depth study of planning the measuring points in machine tool volumetric error detection.The specific content of this article is as follows:(1)The volumetric error of the machine tool is studied to establish a volumetric error model of the machine tool.The volumetric error is divided into volumetric position error and volumetric pose error,and the volumetric error representation method is defined.The error sources of the machine tool are analyzed,and the multi-body theory and the homogeneous coordinate transformation are used to model the volumetric error of the machine tool.For the needs of rapid and accurate detection of machine tool errors,the laser tracker is selected as the detection instrument,and its detection principle and volumetric position location principle are studied.(2)The identification performance of the machine tool volumetric error model is studied and an error identification model is established.The matrix vector of the identification matrix is compared to the base vector of the identification space.Through the analysis of the identification space,the identification index of the identification matrix is used to evaluate the identification of the identification matrix.Singular value decomposition is used to perform singular value decomposition of the error transfer matrix,and the influence of singular value on identification performance of the identification matrix is discussed.The core of the identification effect that affects the identification matrix is the singular value of the matrix.(3)Detection point planning for machine tool space error detection.In view of the deficiencies of the commonly used machine tool space error detection point arrangement,the establishment of the detection point planning is based on the criterion that the combination function of the singular value of the recognition matrix is the observable degree.The optimization strategy of detection points was established.The operation of adding and deleting measurement points from the generated measurement point database was performed on the initial measurement point.The genetic algorithm was used to optimize the screening measurement point process,and the final optimization measurement point was obtained.(4)The error parameters of the machine tool at different measuring points were identified and the simulation analysis was completed.According to the characteristics of the machine tool error parameters,the third-order Chebyshev polynomial is used to fit the error parameters.For the coupling problem of the error parameter,the ridge estimation algorithm and the truncated singular value identification algorithm are used to identify the error parameters of the machine tool.Finally,through simulation,the accuracy of three different sets of measuring points for machine tool error detection was compared and the effectiveness of the optimized measuring points was verified.