Measurement And Evaluation Of Micro Diamond Cutting Tool

Microstructured surfaces are widely used in military and aerospace fields for their superior wear reduction,optical,and superhydrophobic properties,etc.To achieve the desired performance of microstructured surfaces,high shape accuracy and ultra-smooth surfaces need to be machined.At present,surface microstructure processing methods include milling and turning,among which turning method using micro-arc diamond tools has become an important processing technology due to its simple principle and excellent effect.In order to process high precision and high quality microstructure surface,the quality of the tool itself must also be extremely strict.As the sharpening quality of current micro-arc diamond tools is getting better and better,their requirements for quality inspection means are also more stringent.Therefore,it is of great practical value to study a high precision and high efficiency quality inspection and evaluation method for micro-arc diamond tools.Based on this objective,the following theoretical and experimental studies are carried out in this paper.Firstly,this paper acquires the relevant images suitable for tool tip arc evaluation by using ultra-high resolution CCD camera,and by comparing and analyzing the image edge pixel point extraction methods,a more accurate edge extraction scheme is derived.At the same time,this paper adopts the spatial transformation theory to fit the tool tip arc,and compares the evaluation results with the DTRC radius wave amplitude measurement instrument,and the results show that the spatial transformation tool tip arc fitting method has excellent fitting accuracy.On this basis,this paper also proposes the contour curvature separation strategy to accurately separate the arc part contour,and obtains the tool tip arc contour error curve by making difference with the fitted arc,and selects the appropriate spatial cutoff filter wavelength to obtain the arc ripple evaluation results by using Gaussian filtering.In addition,this paper proposes to use AFM measurement to obtain the grinding mark data of the rear tool face near the edge part of the tool,which can provide reference for further optimization of the tool sharpening process.Secondly,the inspection of the edge profile of micro-arc diamond tools was carried out by using AFM with a special fixture,and a new error compensation method was proposed to solve the profile skew error and the AFM probe profile coupling error,respectively.Finally,a stepwise least-squares fitting method was used to evaluate the blunt radius of the cutting edge,while the detection,classification and evaluation of micro-defects of the edge for the actual cutting part were carried out based on a large number of measurement experiments.Finally,a comprehensive evaluation model for micro-arc diamond tools was constructed based on neural networks,and a larger number of training sets were collected by ultra-precision cutting experiments,and better model results were obtained by continuous training combined with genetic algorithms.Meanwhile,based on the research results in the above sections,this paper further designs and writes the integrated processing software,which greatly improves the measurement convenience and measurement efficiency.