Design of Regenerative Chatter Stability Detection System in Machine Tool Cutting based on Computer Vision and SAR Image

The thesis starts with the analysis of the stability of the regenerative cutting chatter system. Based on the SAR image algorithm, the machine is processed in the processing steps of image denoising, image segmentation, target detection and recognition, focusing on the limit cutting width and random bed spindle speed W. The main factors affecting the stability of the machine tool cutting system are systematically analyzed, including the dynamic parameters of the main vibration system, and a SAR image segmentation method based on the global Maxflow neighborhood growth algorithm is proposed, which combines the texture and boundary information In combination, using C# as the development tool, designed a turning chatter stability limit prediction software, and systematically introduced the function realization and use method of the software.