Tool Wear Eigenvalue Acquisition Method Based on Machine Vision
In order to effectively detect the tool wear status in the production process,improve the processing efficien-cy and reduce the processing cost,a machine vision based tool wear eigenvalue acquisition method and detection device are proposed.According to the requirements of the processing situation,a in place tool image acquisition device with two states of recycling and unfolding is developed.Image processing technologies such as gray-scale processing,Gaussian blur filte-ring,two-dimensional median filtering,adaptive binarization and morphology are used to preprocess the tool image,combine GrabCut algorithm to segment the image background,use OTSU segmentation algorithm to extract the tool contour,use Can-ny operator edge detection to extract the tool wear area,and then combine the tool diameter to calculate the tool wear char-acteristic value.Through the orthogonal test of 6061 aluminum alloy aero engine blade,the measured value of tool wear characteristics is obtained,and compared with the actual value obtained by the electronic digital microscope,the results show that the error between the measured value and the actual value is kept within 0.02mm except for a small part.
万方数据
维普
