5436results about "Numerical control" patented technology

The invention relates to the technical field of multi-axis linkage machining, and discloses a multi-axis linkage machining path generation method, device and equipment and a storage medium, and the method comprises the steps that modeling is conducted on a multi-axis machine tool and a workpiece, and a machine tool kinematics model and a workpiece obstacle avoidance scene mathematical model are obtained; a state space and an action space are constructed, and a machining path double-delay depth deterministic strategy gradient model is obtained; performing time deviation calibration to obtain a time synchronization sensing data set; performing path generation to obtain an initial processing path; the initial machining path is optimized, and an optimized machining path is obtained; according to the method, a directed acyclic graph is constructed, and task division and parallel optimization are performed to obtain a multi-axis linkage machining path, so that multi-objective optimization of machining time, cutting force fluctuation and tool wear is realized, and the machining efficiency and the machining quality are improved.

The invention provides a multi-axis linkage numerical control machining control method and device, equipment and a storage medium, and the method comprises the steps: carrying out the modeling analysis of the kinematic characteristics and static stiffness characteristics of a multi-axis numerical control machine tool, and generating a kinematic model and a static stiffness analysis model; and performing multi-objective optimization on the attitude of the target workpiece based on the models to obtain an optimal workpiece attitude parameter, and re-planning an original tool path of the machine tool according to the optimal workpiece attitude parameter to generate an optimized tool path. And according to the static stiffness analysis model and the optimized path, a static deformation compensation strategy in the machining process is formulated, and a self-adaptive stiffness compensation scheme is obtained. And real-time control and self-adaptive adjustment are performed on the machining process of the machine tool by optimizing a path and a self-adaptive rigidity compensation scheme, so that closed-loop control is realized. According to the method, the kinematics characteristic and the static rigidity characteristic of the machine tool are considered, the workpiece posture and the tool path are optimized, static deformation in the machining process is compensated in real time, and therefore efficient and high-precision numerical control machining is achieved.

The invention discloses a machine tool control method and system based on mechatronics, and the method comprises the steps: outputting an optimal cutting track sequence according to the three-dimensional model features and material attribute parameters of a machined workpiece; based on the optimal cutting track sequence, motion interference among shafts of the machine tool is eliminated through dynamic weight distribution, and an anti-interference optimization machining instruction is generated; constructing a nonlinear vibration wave propagation model according to the coupling relation between the spindle rotating speed and the feeding speed, and generating a steady speed regulation and control signal; generating an energy efficiency optimal parameter set including motor torque, cooling power and lubricating frequency based on the energy consumption efficiency constraint condition and the steady speed regulation and control signal; and outputting a closed-loop control signal and synchronously updating the three-dimensional machining precision thermodynamic diagram according to the real-time data in the machining process and the predicted deviation of the digital twin model. According to the embodiment of the invention, global optimization, dynamic adaptation and efficient operation of the machine tool can be realized, and technical support is provided for intelligent upgrading of the modern manufacturing industry.

The invention relates to the technical field of machining precision control, in particular to a laser carving precision control method and system.The laser carving precision control system comprises a feature collecting unit, a model building and analyzing unit, a dynamic threshold value adjusting unit and an online incremental learning unit, and the feature collecting unit collects vibration, current and temperature data through a multi-source sensor array; the model construction analysis unit realizes dynamic prediction of processing parameters by combining a bidirectional long-short-term memory network with an attention mechanism, and the dynamic threshold adjustment unit dynamically updates parameters of a numerical control system based on a material hardness real-time detection and thermal coupling model. The online incremental learning unit automatically generates training samples through error data, continuously optimizes model parameters and constructs a'data acquisition-intelligent modeling-dynamic compensation-model evolution 'closed loop, so that accurate prediction and adaptive adjustment of machining parameters are realized, and the adaptability of the manufacturing process to multi-variety and small-batch working conditions is remarkably improved.

The invention belongs to the technical field of numerical control machine tool machining, and particularly discloses a numerical control machine tool machining reference point correction method and system, a terminal and a medium. Based on the three-dimensional coordinate information, the actual position of a preset reference point on the machine tool is extracted and compared with a preset theoretical reference point, and a deviation value is calculated; executing coordinate deviation aggregation analysis according to the deviation value, and determining coordinate system correction parameters including a translation vector and a rotation matrix; the corrected parameters are issued to a numerical control machine tool control system, and a current workpiece coordinate system is updated; and after the coordinate system is updated, the machining task continues to be executed, the machining state is monitored in real time, and if it is detected that the deviation exceeds a threshold value, the measurement and correction process is automatically triggered again. Automatic correction of the reference point and real-time compensation of the workpiece coordinate system can be achieved, the machining precision is improved, manual intervention is reduced, and the method is suitable for high-precision numerical control machining scenes.

The invention relates to the technical field of intelligent manufacturing and numerical control machining control, and discloses a machine tool dynamic characteristic sensing and intelligent machining control method and system based on a knowledge graph and a large model, and the method comprises the following steps: extracting frequency domain parameters through a vibration sensor, obtaining vibration displacement in combination with laser displacement, and comparing the vibration displacement with modal data to construct a graph; processing parameters and displacement are synchronously sampled, time sequence characteristics are extracted to generate tensors, dynamic characteristics are predicted and corrected, and frequency response adjustment rotating speed is matched to generate optimized track control parameters which are converted into G code instructions. According to the method, a dynamic characteristic map is constructed by fusing vibration signals and displacement, a sliding window synchronizes processing parameters and vibration data, LSTM extracts joint characteristics, GRU predicts rigidity and damping ratio, an attention mechanism dynamically corrects weight, characteristic coupling analysis and prediction precision is improved, nonlinear modeling captures dominant frequency offset and harmonic distribution, response speed is enhanced, and the method has the advantages of being high in precision and high in precision. Cutting vibration is inhibited, and the process stability is guaranteed.

The invention relates to a shaft linkage curved surface component machining path real-time control method, system and device, and the method comprises the steps: obtaining geometric data and machining process parameters of a shaft linkage curved surface component, and carrying out the shaft linkage decomposition to obtain a multi-shaft linkage machining path; real-time operation parameters of machining equipment and tool workpiece contact data are obtained, deviation matching is conducted on the multi-axis linkage machining path, and a real-time axis control instruction set and an axis position compensation trend curve are obtained; performing path optimization on the shaft position compensation trend curve according to the real-time shaft control instruction group to obtain an initial shaft linkage adjustment scheme; performing curved surface precision evaluation on the tool workpiece contact data, and performing curved surface prediction in combination with the axis position compensation trend curve to obtain a curved surface quality prediction area; and performing coordinated optimization on the initial axis linkage adjustment scheme according to the curved surface quality prediction area to obtain an axis linkage optimization processing strategy. It can be guaranteed that efficient operation can be achieved in different machining states, and path deviation in the machining process is reduced.

The invention discloses a control method and system of a vertical multi-axis numerical control mortise broaching machine and a storage medium, and relates to the technical field of broaching machines. The control method comprises the following steps that S1, a three-dimensional model of a workpiece is imported, and a mortise machining area is recognized based on geometric features of the model; s2, according to the material attribute, the tool type and the machining precision requirement, the feeding speed, the cutting depth and the main shaft rotating speed parameter of a machining path are set; s3, generating a multi-axis linkage tool path plan, and decomposing a tool path into a control instruction of multi-axis cooperative motion through a numerical control system; s4, the deviation between the actual position and the theoretical position of each shaft is monitored in real time in the machining process, and the output torque and the rotating speed of the servo motor are dynamically adjusted; s5, collecting cutting force data in real time; s6, the distance between the cutter and the surface of the workpiece is measured in real time through a laser displacement sensor, and a displacement feedback signal is generated; and if the cutting force data and the displacement feedback signal exceed preset threshold values, a dynamic compensation mechanism is triggered. The broaching machine control method has the effect of improving broaching machine control accuracy.

The invention discloses an intelligent machining control method and control system for a CNC lathe, and relates to the technical field of lathe machining control, and further realizes real-time correction of a speed regulation control plan by collecting a spindle load feedback value in real time for a regulation target track section and comparing the spindle load feedback value with a spindle load dynamic prediction model, so that the machining accuracy of the lathe is improved. The problems of system response lag and load prediction deviation are effectively solved, meanwhile, after a machining task is finished, an inertia index, a main shaft load curve, speed regulation feedback data and final machining quality parameters are archived and used for updating main shaft historical operation data, a main shaft load dynamic prediction model and a track direction change rate response model can be continuously optimized, and the machining efficiency is improved. The learning ability evolved along with data accumulation is enhanced, the speed regulation control precision and machining stability of the numerical control lathe in complex path machining are fundamentally improved, and the core problems of speed regulation control delay, frequent path impact, track error accumulation and the like in the prior art are solved.

The invention relates to the technical field of machine tool calibration, and discloses a calibration method and device for precisely manufacturing a multi-axis linkage machine tool, and the method comprises the steps: collecting machine tool operation data and multi-modal sensor data of the multi-axis linkage machine tool, and carrying out the error prediction, and obtaining the error prediction data; the positions of all shafts of the machine tool are measured, and nanoscale resolution ratio position data are obtained; real-time state representation of the machine tool is obtained through the multi-branch deep neural network; constructing a multi-level hypergraph based on the real-time state representation of the machine tool, and carrying out feature processing to obtain a fault feature vector; reinforcement learning is carried out through a deep Q network to obtain an adaptive compensation strategy; linkage compensation values of all axes are generated on the basis of the self-adaptive compensation strategy, real-time adjustment and fault prevention analysis are conducted on the multi-axis linkage machine tool, a fault prevention control scheme is generated, the precision maintaining capacity and operation reliability of the multi-axis linkage machine tool are improved, and the method can be suitable for different types of multi-axis linkage machine tools.

The invention relates to the field of numerical control machining, discloses a numerical control machining method and system integrating thermal expansion dynamic compensation, and aims to solve the problem that precision is out of control due to thermal deformation in high-speed cutting of motorcycle light alloy castings. The method comprises the steps that distributed temperature and displacement sensors are arranged in a key area of a workpiece, and a temperature field and thermal expansion amount are collected in real time; constructing a local thermal deformation prediction model based on a material expansion coefficient and a geometric structure, and correcting a tool path in real time through a coordinate system dynamic offset algorithm; and an on-line measurement feedback mechanism is introduced, and model parameters are adaptively optimized, so that closed-loop compensation is realized. The system comprises a sensing module, a thermal deformation modeling and compensation calculation module, a coordinate dynamic correction module, an online measurement feedback module and a parameter adaptive updating module. Through millisecond-level dynamic compensation and closed-loop self-optimization, the size precision and form and position stability of the complex thin-wall part under the high-temperature working condition are remarkably improved, the rejection rate and cooling energy consumption are reduced, and the method is suitable for a high-precision batch machining scene.

A system for performing interactions within a physical environment including: a robot base that undergoes movement relative to the environment; a robot arm mounted to the robot base, the robot arm including an end effector mounted thereon; a first tracking system that measures a robot base position; a second tracking system that measures movement of the robot base; and, a control system that uses a robot base position to at least partially control the robot arm to move the end effector along an end effector path, wherein the control system: determines the robot base position at least in part using signals from the first tracking system; and, in the event of failure of the first tracking system: determines a robot base position using signals from the second tracking system; and, controls the robot arm to move the end effector along the end effector path at a reduced end effector speed.

The invention relates to the technical field of intelligent control, in particular to a numerical control lathe cutting precision optimization method and system for metal part machining, and the method comprises the steps: constructing a multi-mode key feature set with aligned timestamps; the initial compensation amount in the cutting feeding direction is obtained from the tool compensation lookup table; searching a corresponding historical cutting state from the processing state matrix, and inputting the key temperature distribution gradient of the cutter side, the key vibration absolute peak value of the lathe spindle and the corresponding historical cutting state into a weight coefficient model to obtain a temperature compensation weight and a vibration compensation weight of the current cutting state; calculating a dynamic correction factor, and correcting the initial compensation amount in the cutting feeding direction through the dynamic correction factor to obtain a cutting feeding direction compensation amount with a timestamp; the compensation rate of the cutting feeding direction compensation amount and the target feeding displacement under the same timestamp is calculated; and the cutting precision is optimized according to the comparison result of the compensation rate and the cutting key feeding relative deviation rate. And the requirements of high precision, low cost and fast response are met.

The invention relates to the technical field of CNC machining control, and discloses an intelligent CNC machining system and method, and the method comprises the steps: carrying out the comprehensive modeling of the machining quality, efficiency and energy consumption of CNC, and obtaining a machining quality-efficiency-energy consumption function model; obtaining the multi-dimensional time sequence state data set for feature extraction to obtain a feature data set; constructing a processing state real-time identification model; carrying out five-axis linkage CNC machining simulation to obtain a machining simulation state data set, and carrying out machining state classification identification through the machining state real-time identification model to obtain a machining state simulation identification result; and performing deep reinforcement learning, generating a machining parameter dynamic adjustment strategy and performing global parameter optimization to obtain a target CNC machining control parameter set, and the method can adaptively optimize the machining parameters to cope with different machining tasks and environment changes, thereby improving the machining precision, efficiency and energy utilization rate.

Method for intelligent monitoring of CNC processing based on industrial IoT, implemented by industrial IoT management platform, including: determining a CNC processing parameter and simulated processing data corresponding to the CNC processing parameter by performing a CNC process simulation based on the information to be processed; controlling a CNC processing device to perform the task to be processed based on the CNC processing parameter; collecting actual processing data during a performance of the task to be processed according to a monitoring frequency by a monitoring device; performing a deviation determination on the actual processing data and the simulated processing data; when a result of the deviation determination satisfies a preset alert condition, generating a processing alert instruction and sending the processing alert instruction to an alert device of a user platform; and controlling the CNC processing device to adjust the tool feed step length based on the actual processing data.

The invention relates to a metal cutting machining path planning system, and aims to optimize the efficiency and precision of a metal machining process through advanced technical means. The system comprises a plurality of functional modules: an image acquisition module captures a multi-angle high-resolution image of a to-be-processed metal workpiece; the three-dimensional reconstruction module reconstructs a three-dimensional model by using the images; the cutting simulation module simulates the three-dimensional model in a virtual environment and records stress and heat distribution conditions in the cutting process in real time; the intelligent segmentation module divides the machining process into a plurality of stages according to the stress and heat data; the comprehensive optimization module is combined with a genetic algorithm and a simulated annealing algorithm to optimize the cutting path, depth and feeding speed of each machining stage; the feedback adjusting module monitors stress and heat changes in actual machining, and when the stress and heat changes exceed threshold values, cutting parameters are automatically adjusted or machining is paused. According to the system, through comprehensive application of image processing, analog simulation and optimization algorithms, the cutting efficiency and the product quality are remarkably improved.

The invention relates to a numerical control equipment cooperative scheduling method and system based on a heterogeneous computing architecture, and aims to solve the core problems of multi-brand numerical control equipment protocol isomerism, weak digital twin generalization ability, low multi-objective optimization efficiency, quantum era communication security and the like in the industrial internet. Real-time analysis and unified format conversion of 18 industrial protocols are realized through a PDSA-Chip hardware-level protocol conversion module; in combination with a transfer learning digital twinning technology, cross-brand equipment parameter self-calibration is completed within 72 hours; a quantum annealing and NSGA-III collaborative optimization algorithm is adopted, the machining parameter optimization period is shortened to 1 / 3 of that of a traditional method, energy consumption, precision and the service life of a tool are dynamically balanced, and the service life of the tool is prolonged by 37% in a high-load scene; an NTRU lattice encryption and chaos confusion fused anti-quantum security communication system is constructed, the G code confusion degree is larger than 98%, and SL3-level quantum attacks are defended.

The invention relates to the technical field of laser welding control, and discloses a laser welding head integrated with a push-pull wire and a control system of the laser welding head. The system comprises a push-pull wire action monitoring module, a laser energy modulation module, a welding seam trajectory tracking module, a welding quality feedback module, a parameter collaborative optimization module and a dynamic deviation correction execution module. Wherein the push-pull wire action monitoring module collects motion parameters in real time and generates a cooperative state index; the laser energy modulation module analyzes the laser power requirement according to the workpiece parameters and outputs a regulation and control instruction; the welding seam trajectory tracking module identifies welding seam characteristics and offset through a multispectral sensor and generates a dynamic tracking path; the welding quality feedback module evaluates defects and generates an abnormal index set; the parameter collaborative optimization module generates an optimization control parameter set based on the abnormal index set and the tracking path adjustment parameters; and the dynamic deviation correction execution module is used for correcting the track and generating a closed-loop control signal according to the matching action and the energy output time sequence.

The invention discloses a control method and equipment suitable for a rotary turn-over clamp of a numerical control milling center, and relates to the technical field of numerical control machining. The clamping force is optimized through the multi-source sensing and digital twinning technology, and workpiece deformation is prevented; thermal compensation and an error transfer chain model are integrated, the turnover angle is accurately corrected, and error accumulation is restrained; real-time comparison, traceability and self-adaptive adjustment in the machining process are achieved through digital twin pre-verification and multi-sensor closed-loop monitoring; the problems of out-of-tolerance of precision and batch consistency caused by unstable clamping, thermal deformation and error transmission in multi-surface milling of high-precision parts are solved, and the precision, reliability and process adaptability of complex part machining are remarkably improved.

The invention relates to the technical field of high-quality machining, in particular to a valve body high-quality machining method based on a numerical control machining center, and the method comprises the steps that power data, cutting force data, feeding speed data and rotating speed data are collected in real time when a numerical control machine tool machines a valve body; determining an operation matching index of the cutting force and the rotating speed at any acquisition moment; obtaining a machine tool operation matching index of the numerical control machine tool at any acquisition moment by combining the cutting force and the operation matching index of the rotating speed at any acquisition moment; determining a feeding speed abnormal factor of the numerical control machine tool at any acquisition moment; and on the basis of the feed speed abnormal factor at the current acquisition moment, adjusting the linear speed in the main shaft linear speed control instruction at the current acquisition moment. The feeding speed in the valve body machining process is adjusted, the surface roughness and tool abrasion are reduced, and therefore high-quality machining of the valve body is achieved.

The invention discloses a free-form surface three-axis ball-end cutter equal approximation error finish machining tool path generation method which comprises the following steps: firstly, importing a free-form surface model to be machined, and setting data such as the radius, the line spacing, the approximation error maximum allowable value and the precision of a ball-end cutter; secondly, a group of section planes are planned according to the row spacing to intersect with the curved surface, the intersecting line serves as a cutter contact curve, and an equal-bow-height-error cutter contact iterative search method for driving cutter contact adjustment through the geometric distance is provided for the cutter contact curve on the section planes; the maximum distance between a cutter cutting envelope surface and a cutter contact track line is used as an approximation error, and an adaptive discrete method is adopted to carry out approximation error calculation; and finally, the cutter location points of the equal-bow-height-error cutter contact points serve as initial values, an equal-error cutter location point calculation method of step length self-adaptive adjustment iteration is provided, approximation errors between the cutter location points are all within an allowable range, and therefore the free-form surface three-axis ball-end cutter equal approximation error finish machining cutter path is obtained.

The invention relates to the technical field of machine tool part machining, in particular to an engine shaft part machining method utilizing a numerical control machine tool. The method comprises the steps that vibration data and rotating speed data of a cutter of the numerical control machine tool at all moments during cutting each time are obtained; determining the contact impact strength, the vibration offset, the vibration fluctuation degree and the abrasion influence coefficient of each cutting; and determining a synchronous change coefficient, a cutting state abnormity degree and an adjustment factor of the current adjustment period, determining a steep degree parameter of an acceleration equation in the S-shaped acceleration and deceleration algorithm of the next adjustment period, and planning the feeding speed of the cutter in the numerical control machine tool. The feeding speed of the cutter is smoothed according to different cutting states, smooth acceleration and deceleration are achieved, the stability and efficiency in the numerical control machining process are improved, and the machining precision of engine shaft parts is improved.

The invention discloses a three-dimensional cutting dynamic parameter adjusting system and method based on deep learning, and relates to the technical field of application of three-dimensional five-axis fiber laser cutting machines in the automobile manufacturing industry, and the three-dimensional cutting dynamic parameter adjusting system comprises a multi-mode sensor cluster, an edge calculation unit, a closed-loop control module and an AI model library, the multi-mode sensor cluster collects cutting data, the edge calculation unit receives the multi-mode sensor data and outputs dynamic adjustment parameters, and the closed-loop control module transmits the dynamic parameters to the laser generator and the five-axis motion controller through a high-speed communication bus to form a'sensing-decision-execution 'closed loop. The cutting state and risk are sensed in real time by designing a multi-mode sensor for collaborative decision, the problems that manual experience depends on and dynamic response lags are solved, the reject ratio is reduced, and the response speed is increased.

The invention relates to the technical field of high-frequency signal transmission, and discloses a high-frequency signal transmission optimization method for a radio frequency coaxial connector. The method comprises the following steps: acquiring an original electromagnetic parameter sequence when a high-frequency signal is transmitted in a target working frequency band in real time, wherein the original electromagnetic parameter sequence comprises an impedance change value, a dielectric loss factor and a conductor skin depth measurement value; layered feature analysis is carried out on the data, features of a basic transmission layer, an interface reflection layer and a medium coupling layer are separated out, and a layered electromagnetic feature set is generated; identifying a key performance influence section according to the set, constructing a non-uniform frequency domain analysis grid, dividing a reflection sensitive area by using a fine frequency band, and dividing a transmission stable area by using a wide frequency band; performing time-frequency joint simulation based on the grid, and extracting a full-band dynamic transmission response spectrum; and combining with the material electromagnetic property database to optimize the structure parameter configuration scheme, generating an optimization instruction set, and loading the optimization instruction set to a processing control system to execute physical structure dynamic adjustment operation.

A hot working path determination method and apparatus, and a device and a storage medium, which relate to the technical field of hot working. The method comprises: acquiring an area to be subjected to processing of a workpiece plate material and parameter information of a workpiece; establishing a dot matrix in said area, and determining a plurality of processing line segments of the workpiece in said area according to the parameter information of the workpiece; traversing all processing line segments once, so as to determine a plurality of hot working paths corresponding to the workpiece, wherein each hot working path further comprises an empty moving line segment other than the processing line segments; then, determining a thermal avoidance area during hot working in each hot working path; and finally, screening out an optimal hot working path which meets a thermal avoidance condition, wherein the thermal avoidance condition is determined at least according to a length ratio of a total line segment length of all processing line segments corresponding to the hot working paths that are located in the thermal avoidance area to a corresponding total length of the hot working paths. Therefore, it is possible to avoid secondary cutting of an overheating area within a short period of time, thereby improving the product quality of a workpiece.

A method includes initiating a connection with a semiconductor manufacturing system. The method further includes generating a set of tool data items associated with the semiconductor manufacturing system. The method further includes providing a graphical user interface (GUI) presenting the set of tool data items associated with the semiconductor manufacturing system and receiving and via the GUI, user input selecting one or more of the tool data items. The method further includes adding configuration data associated with one or more of the tool data items to a data collection plan. The method further includes validating the configuration data by locating, in the manufacturing system, a configuration data file associated with the configuration data. The method further includes executing one or more data collection operations based on the data collection plan.

The invention discloses a numerical control machine tool efficient cutting method based on real-time surface roughness prediction. Firstly, acquisition and storage of internal information of an external sensor and a numerical control system machine tool are realized through data acquisition software developed by a numerical control machine tool type; the surface roughness of the part is predicted through data preprocessing, multi-source data feature extraction and fusion and a prediction model; and in the part machining process, data are collected and input into the model for real-time prediction and machining parameter adjustment, so that the cutting efficiency is improved on the premise of ensuring certain quality of the part, and the optimal parameters are stored in the knowledge base. The defects that the quality is uncertain in the part production process of the numerical control machine tool and manpower needs to be consumed for surface roughness detection after production is completed are effectively overcome, the knowledge base can provide optimal cutting parameters for production of various parts, and the method has great benefits on improving the production efficiency on the premise of ensuring certain quality of the parts.

The invention relates to the technical field of control adjustment, in particular to an intelligent multi-head welding synchronous control system which comprises a data processing module, a modular cooperative control module, a load sensing module, a data transmission module, a self-adaptive pose execution module and a fault-tolerant module. The data processing module extracts three-dimensional geometrical characteristics of a workpiece through laser scanning, PID control parameters are migrated across working conditions in combination with a dynamic time warping algorithm, the inverse kinematics process is optimized, and the self-adaptive pose execution module drives phase synchronization of multiple welding heads based on a global reference trajectory and predicts and compensates thermal deformation errors through a thermal expansion coefficient. And the fault-tolerant module adopts a wavelet packet decomposition identification fault mode, and updates a historical parameter library in combination with an elastic weight algorithm. According to the method, three-dimensional space pose error accumulation caused by mechanical load fluctuation and signal asynchronization is inhibited through cooperation of multiple modules, and the welding process uniformity and the system dynamic stability are improved.

The invention discloses a milling path automatic generation method based on reinforcement learning, and relates to the technical field of machine tool machining, and the milling path automatic generation method comprises the following steps: step 1, defining action output; step 2, defining state input including a cutter state, a global observation space and a local observation space; 3, defining a reward function; value feedback given to the intelligent agent by the environment according to the current state and action is determined through the reward function; 4, setting deep neural networks including a feature extractor, a strategy network and a value network; 5, constructing a process autonomous generation model and a machining process world model; step 6, strategy training; step 7, outputting a strategy, and autonomously completing a machining process flow; by means of the method, the problems that in the prior art, manual experience dependence is too heavy, local optimization limitation is remarkable, and physical simulation efficiency is insufficient are solved.

The invention discloses a numerical control machine tool machining path optimization method based on artificial intelligence. The method comprises the steps that S1, a complete input data set needed by an optimization model is generated; s2, according to the complete input data set, constructing a multi-objective optimization model for numerical control machine tool processing path optimization; s3, forming a fuzzy decision basis of the optimization target; s4, determining an initial processing path optimization solution set; s5, generating an improved optimal solution set of the processing path; and S6, checking the improved optimal solution set of the machining path, checking whether the machining path meets the kinematics limitation of the numerical control machine tool, the precision requirement of the machined workpiece and the process constraint of the dynamic machining environment or not, and generating a machining path instruction of the numerical control machine tool after the machining path is checked to be qualified. According to the method, the integration of checking and instruction generation is realized, and the reliability and accuracy of path execution are effectively improved.