10 results about "Cutting force model" patented technology

The application discloses a kind of cutting force vector regulation and control methods based on micro-element blade method, it is related to metal processing field.The main implementation method includes: first, milling coefficient is solved, fixed tool parameters and the rest milling parameters except every tooth feed rate, carries out multiple sets of orthogonal experiments and records the average milling force value of each group of experiments and corresponding every tooth feed rate, and obtains milling coefficient by linear regression of least square method;Then based on micro-element blade method, first, milling cutter is divided into multiple discrete micro-elements along the axial direction, then the actual spiral contact angle of each micro-element is calculated and whether it is actually involved in milling is judged, then the milling force model of each micro-element is established, every blade of milling cutter is integrated along the axial direction, then the milling force of each blade is summed to obtain the magnitude of the cutting force of the whole milling cutter;Finally, milling parameters are optimized by NSGA-II algorithm, aiming at studying the influence of every tooth feed rate and axial depth of cut on cutting force, the constructed milling force model is used as objective function, the input value is axial depth of cut and every tooth feed rate, the target is the average axial milling force of a period, the maximum axial milling force and material one rate, a group of optimized Pareto solution is obtained by multiple crossover mutation.The method can quickly obtain a group of more optimal milling parameters according to the cutting force model and optimization algorithm, and can effectively regulate and control the size of cutting force vector and the part relief deformation, to provide guidance for optimizing processing parameters.

The present invention provides a fault detection method and system based on an adapter tool shank and relates to the technical field of fault diagnosis of mechanical equipment. The method includes: obtaining a displacement signal of the adapter tool shank; based on the displacement signal, determining a feed rate; based on the feed rate, building a cutting force model; based on the cutting force model, building a disturbance model; building an observer model; based on the disturbance model and the observer model, determining a cutting force error; based on the observer model, determining a wear rate of the adapter tool shank; combining the cutting force error and the wear rate to perform fault detection; and based on a fault detection result, judging whether the adapter tool shank is faulted. The present invention improves the efficiency of fault diagnosis, reduces the maintenance cost, and improves the production efficiency.

The application provides a micro-milling machining parameter identification method considering the influence of random tool wear, comprising the following steps: establishing a cutting force model under the influence of tool wear by considering tool runout and chip separation mechanism; updating the tool rotation radius according to the influence of runout and wear on the tool edge radius value, and obtaining the tool tip trajectory equation; collecting tool wear data in the actual machining process, training the neural network model, and optimizing the hyperparameters in the neural network model by using a bidirectional long short-term memory network; identifying the machining parameter values in the neural network model by using a particle filtering algorithm; simulating and calculating the cutting force and wear values under different working conditions by using the neural network model, comparing the experimental results, and evaluating the accuracy of the machining parameter identification. In the modeling process, the randomness of tool wear is fully considered, the prediction accuracy is significantly improved, and the application value is stronger.

The application discloses a method and system for optimizing the arrangement of cutters of a slurry shield cutter head, and relates to the technical field of shield cutter heads.A method for optimizing the arrangement of cutters on the front face of a slurry shield cutter head is provided.The method comprises the following steps: obtaining the structural parameters of the front face cutters and working conditions to determine the cutter arrangement parameters;establishing a soil breaking amount model based on the cutting process of the cutters and the cutter arrangement parameters;establishing a cutting force model according to the Rankine passive earth pressure theory, in combination with the cutting resistance model of the tillage cutters and the synergistic effect and cutting mechanism of the cutters;then, establishing a cutting efficiency model based on the soil breaking amount model and the cutting force model;finally, evaluating the cutting efficiency under different cutter combination arrangement parameters through the cutting efficiency model, and selecting the cutter arrangement parameters with the highest cutting efficiency as the optimal arrangement scheme.The application can improve the accuracy of the cutter arrangement parameters of the slurry shield cutter head, and thus improve the tunneling efficiency of the slurry shield cutter head.

The invention discloses a numerical control agent execution device driven by a large model, which belongs to the technical field of intelligent manufacturing and numerical control and comprises an agent subsystem, a real-time actuator subsystem, a virtual machine tool subsystem and a physical machine tool. The agent subsystem generates a verified instruction sequence through simulation interaction with the virtual machine tool subsystem; the real-time actuator subsystem is responsible for analyzing and executing the instruction generated by the intelligent agent and driving the physical machine tool to move; the virtual machine tool subsystem is used for verifying and optimizing instructions of the intelligent agent subsystem and providing simulation verification support; and the physical machine tool is driven by the real-time actuator subsystem to execute final machining operation. According to the numerical control agent execution device driven by the large model, intelligent optimization of a machine tool machining process is achieved through driving of the cutting force model, the control model and the error model in the agent, and the machining efficiency and the machining quality are improved under the condition that the machining dynamic precision is guaranteed.

The present application relates to a kind of time-varying chatter prediction methods in thin-walled part milling process, comprising: at initial time, un-milled thin-walled part is divided into multiple units, each unit is the same eight-node hexahedron of length-width-height;At the t time, the unit node information of each unit in the machined, to-be-cut and target machining forming part of thin-walled part is obtained, and the stiffness matrix of each unit is obtained according to the unit node information of each unit and the unit stiffness matrix of eight-node hexahedron;The stiffness matrix of each unit is assembled, and the time-varying stiffness matrix of thin-walled part is obtained;And the time-varying stiffness matrix of thin-walled part is corrected;Cutting force model in thin-walled part milling process is constructed;According to cutting force model and the time-varying deformation of corrected time-varying stiffness matrix, the time-varying deformation of thin-walled part is calculated;Finally, the time-varying chatter of thin-walled part is predicted according to time-varying deformation.This method can significantly improve the efficiency and accuracy of thin-walled part machining stability prediction.

The invention discloses a non-iteration thin-wall part side milling error compensation method considering chip thickness updating, and belongs to the technical field of thin-wall part machining deformation. The method comprises the steps that firstly, an infinitesimal cutting force model is established and used for deformation solving of a rigidity equation; then realizing stiffness equation reduction based on a node classification method, and realizing stiffness updating by using a time-varying stiffness matrix; the radial cutting depth and cutting thickness are updated by introducing a multi-element coupling effect, and an iterative deformation calculation model is established; thirdly, reconstructing the cutting force model to obtain a deformation closed-form solution, and constructing a non-iteration deformation prediction model; based on the deformation prediction model, establishing a non-iterative error compensation model by using a mirror image compensation principle; and finally, proving the effectiveness of the non-iterative compensation model through simulation and experiments. The method has good prediction precision and calculation efficiency, can be widely applied to the high-precision machining process of thin-walled parts in aerospace and the like, and provides theoretical and technical support for improving the machining precision.

The present application relates to the technical field of milling force prediction, and provides a variable helix angle milling cutter milling force model calibration method based on force pocket area maximization, which comprises the following steps: according to the principle of cutting mechanics, a linear average milling force model can be established; a loss function of minimizing the simulation cutting force F S and the experimental cutting force F M error is obtained, and each group of cutting force coefficients of the variable helix angle milling cutter is obtained. The tool radial runout effect is integrated, the accuracy of the variable helix angle cutter cutting force model is improved, the cutting-in phase matching of the experimental force and the simulation force is completed based on the force pocket area maximization principle, the cutting force coefficient identification accuracy is improved, in addition, the L2 regularization parameter is introduced to further ensure the stability and reasonableness of the cutting force coefficients, and the occurrence of the ill-conditioned solution is avoided. The present application is used for accurately identifying the multiple groups of cutting force coefficients and the tool runout parameters of the variable helix angle milling cutter, so as to improve the cutting force prediction accuracy of the variable helix angle milling cutter, and provides a basis for accurately judging the stability of the machining process.

The invention belongs to the technical field of intelligent manufacturing twin modeling, and discloses a five-axis numerical control machine tool energy consumption modeling method and system based on energy flow footprint, and the method comprises the steps: building a five-axis numerical control machine tool three-dimensional geometric model, and obtaining part parameters; an electromechanical coupling dynamic model of the five-axis numerical control machine tool is built based on an SVPWM algorithm, and a machine tool machining process energy consumption model is built according to the electromechanical coupling dynamic model; a theoretical cutting force model is established based on an Altintas mechanical model, cutting loads of all axes are obtained according to a kinematical equation of the five-axis numerical control machine tool and applied to the load end of the machine tool machining process energy consumption model, and machine tool machining process energy consumption modeling is completed. According to the method, the cutting load model of each shaft of the machine tool is established, the cutting load can be estimated before actual machining, proper machining parameters are selected to meet the performance requirements of the machine tool, the energy consumption of the machine tool is reduced, and the problem that a method for obtaining the machine tool energy consumption model according to experimental measurement data is not applicable due to equipment change is solved.

This invention discloses a dynamic control method and system for cutting force in CNC machine tools for machining integral bladed disks, comprising: a geometric mapping module between the tool and the blade surface, which considers the complex surface features of the blade and solves in real time the contact point position and surface normal of the tool and the blade surface; a cutting force model construction module, which constructs a theoretical model of infinitesimal cutting force using the infinitesimal method and calculates the total cutting force of the CNC machine tool using integral summation; and a dynamic closed-loop control module for cutting force, which projects the elastic displacement of the blade and the vibration displacement of the tool tip onto the normal of the surface contact point to form a chip thickness correction amount, thereby correcting the undeformed chip thickness in the next time step and realizing the dynamic correction of the theoretical calculation model of cutting force. This invention effectively reduces the prediction error of chip thickness in the machining of thin-walled blades with complex surfaces by introducing the surface contact point normal vector, dynamic coupling, and closed-loop correction mechanism, thus improving the machining stability of CNC machine tools.