Numerical control machining error compensation technology based on three-coordinate calibration

Yihan Wang

doi:10.1117/12.2683563

26 June 2023 Numerical control machining error compensation technology based on three-coordinate calibration

Yihan Wang

Proceedings Volume 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023); 127140P (2023) https://doi.org/10.1117/12.2683563
Event: Third International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 2023, Sanya, China

Abstract

The machining error of parts is the result of the coupling action of various error sources, such as the spatial error of machine tools in the processing system. Machining error modeling is to establish the machining error relationship model according to the source of machining error or the measurement result of the machining error to compensate and improve the error. The accuracy of the machine tool itself is difficult to meet the requirements of the product process size. Therefore, it is necessary to carry out targeted process research to improve the processing accuracy and solve the problem of insufficient production capacity. In this paper, the data verification technology of CMM is adopted to preprocess point cloud, such as point cloud elimination, curvature analysis, point cloud division, regression analysis and point cloud regeneration. Firstly, the maximum allowable error position is found in the error model to carry out the subsequent compensation research. Finally, the proposed method is tested in a simulation environment to verify its effectiveness. The research tells that it plays an important role in improving the position accuracy, shape accuracy, surface integrity and consistency of machining.

Citation Download Citation

Yihan Wang "Numerical control machining error compensation technology based on three-coordinate calibration", Proc. SPIE 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 127140P (26 June 2023); https://doi.org/10.1117/12.2683563

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