| High-efficiency and high-precision cutting is the main feature of modern manufacturing automation production,which puts forward higher requirements for workpiece cutting efficiency and tool cutting state monitoring.With the increasing requirement for fuel economy and safety,vermicular graphite cast iron materials with excellent mechanical properties,thermal conductivity and casting properties are increasingly used in automotive engines,brake discs and other parts.However,due to the high strength and hardness of vermicular graphite cast iron,the cutting temperature is higher in high-speed cutting,which leads to faster tool wear and difficult to control the surface quality of the workpiece,while the lower cutting speed makes it difficult to improve the processing efficiency.In addition,tool cutting state monitoring is also one of the key technologies for efficient and advanced manufacturing technology,which is of great significance for ensuring high rhythm production,improving the quality and efficiency of workpiece processing,and protecting processing equipment.At present,there are many studies on high-efficiency cutting of aluminum alloys,titanium alloys,etc.,but few theoretical studies and technical applications for high-efficiency processing of vermicular graphite cast iron,meanwhile,the existing intelligent tool cutting state monitoring technology has complex models,large calculations and low recognition accuracy and other issues.Aiming at the problems in high efficiency cutting,cutting temperature,cutting force,surface quality and tool wear of the cutting performance of vermicular graphite cast iron are studied in this paper,thus an on-line dynamic balancing device for high speed face milling is developed;in order to improve the efficiency and reliability of on-line tool cutting state monitoring,and study tool wear and the feature vector extraction and pattern recognition of cutting chatter,a new method for on-line monitoring for tool wear and cutting chatter is proposed.The main research work is as follows:(1)The cutting temperature and temperature field of vermicular graphite cast iron during high speed milling were studied theoretically and experimentally.Base on the characteristics of face milling,in order to reduce the interference of chips on infrared temperature measurement,a scheme of infrared temperature measurement of milling temperature was designed,in which a single factor cutting experiment was used to study the influence of cutting parameters on cutting temperature.The experiment shows that the milling temperature increases with the increase of cutting speed,feed rate and cutting depth,and the increase of cutting speed results in a larger increase in cutting temperature;for the mechanical properties of high hardness and brittleness of vermicular graphite cast iron,a modeling method of high-speed cutting constitutive model was studied,and a three-dimensional simulation model of milling temperature field was established.Referring to the temperature measurement experiment,the simulation accuracy of the constitutive model was validated,and the AdvantEdge FEM software was used to study the temperature field of vermicular graphite cast iron tool edge in high speed milling.The results show that the highest temperature on the tool is near the cutting edge of the rake face,and the highest temperature on the workpiece is at the bottom area where the chip contacts the cutting edge.Due to the low thermal conductivity of vermicular graphite cast iron,the temperature gradient and Von Mises Stress at the cutting edge of the tool are the largest,and increase with the increase of the cutting speed,which result in that the bond wear and diffusion wear of the cutting edge of the tool are aggravated under the condition of high-speed cutting.(2)Through a series of milling experiments,cutting force,stability and surface quality of the high-speed cutting performance of vermicular graphite cast iron were studied,and the tool material and structural parameters were optimized,meanwhile,the cutting parameters are optimized;a surface roughness analysis model of the workpiece was established to study the influence of tool unbalance and dynamic cutting force on workpiece surface roughness in high speed face milling;based on the basic principles of control engineering and dynamics,an on-line dynamic balancing device was developed to improve the milling efficiency of vermicular graphite cast iron.The results show that the YBD152 tool with a tool cutting edge angle of 60° can achieve better results to reduce the cutting force and improve the cutting stability,while the optimum cutting parameters are obtained where cutting speed is 180 m/min to 280 m/min,feed rate is 0.05 mm/z to 0.35 mm/z,cutting depth is 0.45 mm to 1.25 mm;based on the fact that the dynamic balancing accuracy of the tool has an important influence on the surface roughness of the workpiece at higher cutting speed,an on-line dynamic balancing device for high-speed milling is developed according to the basic principles of control engineering and dynamics.The experimental results show that the on-line dynamic balancing device can better improve the milling stability and efficiency under high speed conditions.(3)Aiming at the problem of easy wear of high speed cutting tools,the tool wear experiment for face milling of vermicular graphite cast iron Rut450 material was designed to collect acoustic emission signals during tool wear.Due to the non-linearity and non-stationarity of acoustic emission signals,the variational mode decomposition(VMD)was introduced to process the cutting acoustic emission signals,and the mutual information method was used to extract the sensitive intrinsic mode components and calculate the correlation dimension to form feature vector which improves the reliability of the tool wear feature vector by optimizing the penalty factor ? and the intrinsic mode number K;on the basis of extracting the effective feature vector,the relevant vector machine(RVM)was introduced to construct the tool wear state recognition model in view of the characteristics of fewer training samples and high real-time requirement for tool state monitoring.The results show that the monitoring method can effectively extract the feature information with high correlation with tool wear,which solves the problem of small samples of experimental data well,improves the online recognition accuracy and real-time performance of tool wear,and provide a new method for tool wear state monitoring.(4)Aiming at the chatter problem of vermicular graphite cast iron under high-speed milling,the chatter experiment for face milling of vermicular graphite cast iron Rut450 material was designed.The tool cutting vibration signals were used as the monitoring object,which were subjected to the entire local mean decomposition(ELMD)processing,and the adaptive selection algorithm of K-L divergence was used to select the main PF component;based on the change rule of cutting vibration signal information during the chatter generation process,a method of constructing the feature vector using the sample entropy of the main PF component was proposed,which can effectively distinguished the three stages of stable cutting,chatter transition and chatter cutting for chatter generation;the extracted feature vector was combined with the improved SVM classifier(Boosting-SVM)to recognize the cutting chatter.The results show that the tool wear state monitoring method based on ELMD sample entropy and Boosting-SVM can effectively identify stable cutting,chatter transition and chatter cutting state,and has obvious advantages in recognition accuracy and efficiency,compared with the recognition methods supporting vector machine(SVM)and BP neural network. |
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