3188results about "Numerical control" patented technology

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 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 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.

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 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 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 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.

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 method for grabbing an object by a robot, which comprises the following steps: acquiring surface vibration, transient deformation and three-dimensional deformation data of the object through multi-point pulse excitation, and generating stress wave characteristic mapping data; analyzing internal propagation characteristics of the object according to the stress wave characteristic mapping data, identifying a stress transmission channel, determining a material boundary position and a deformation sensitive area, and generating internal structure characteristic data; calculating a deformation risk coefficient and a stability contribution degree according to the internal structure characteristic data, selecting a grabbing position, and generating grabbing strategy data; and according to the stress wave characteristic mapping data and the grabbing strategy data, the inherent frequency and the local deformation characteristic are identified, a force loading sequence is designed, the vibration state and the deformation amount are monitored, and the force loading sequence is dynamically adjusted. According to the method, the deformation behavior of the object can be accurately predicted, the optimal grabbing strategy is determined by analyzing the internal structure characteristics of the object, dynamic force control is achieved based on frequency modulation, and the instability problem in the grabbing process of the deformed object is effectively solved.

The invention provides a surrounding type numerical control rotary table intelligent braking system based on AI predictive control, and belongs to the technical field of intelligent manufacturing and numerical control. The problems that an existing numerical control rotary table braking system is lagged in response, lacks intelligent prediction and self-adaptive capacity, and is insufficient in control precision and attenuated in long-term performance are solved. The surrounding type numerical control rotary table intelligent brake system based on AI predictive control comprises a state acquisition module, an AI predictive module, a pressure control module, a surrounding type brake execution structure and a feedback correction module, an AI predictive mechanism and a self-correction feedback loop are introduced, intelligence, self-adaption and high responsiveness of brake control are achieved, and the brake control precision is improved. The positioning precision, the braking stability and the overall energy efficiency level of the numerical control rotary table are improved, and the numerical control rotary table has the advantages that the response speed is remarkably increased, the positioning precision is high, the self-adaptive capacity is high, the braking process is stable and the intelligent degree is high.

The invention provides a honeycomb core six-axis ultrasonic cutting tool path dynamic compensation and trajectory optimization control method, which relates to the technical field of intelligent control, and comprises the following steps: obtaining honeycomb core structure parameters and cutting contour lines, establishing an interaction model based on deep reinforcement learning, and generating stress-strain prediction data; according to the method, feature regions are divided, differential initial machining parameters are set, an initial tool path track is generated, a digital twin model is established, machining data dynamic optimization parameters are collected in real time, and a tool path is compensated, so that the cutting precision and efficiency of the honeycomb core structure are improved, and machining deformation and material damage are reduced.

The invention discloses an automatic production line control system and method for stamping and welding vehicle body parts, and relates to the technical field of vehicle body part production. The system comprises a welding robot module, an integrated visual detection module, an image processing server, a control PLC, a welding parameter regulator, a defective workpiece processing module, a data tracing cloud platform, a multispectral illumination module, a deep learning acceleration card and a welding spot temperature infrared sensor. On-line full inspection of the welding spot quality is achieved, the omission ratio is extremely low, and the integrated vision module maintains the imaging definition in a splashing environment through a nanometer coated lens and a piezoelectric self-cleaning technology; the multi-spectral lighting module solves the problem of reflective interference of an aluminum vehicle body, the defect recognition accuracy is high, the real-time closed-loop response is fast, the pseudo soldering recurrence rate is low through dynamic current compensation, the pneumatic marking positioning precision is high, accurate coordinates are provided for repair, the system supports high-speed detection of welding spots, and the high-beat requirement of a vehicle body part punching and welding automatic production line is met.

The invention discloses an RFID tag production line defect real-time detection system and compensation method based on machine vision, and belongs to the technical field of intelligent manufacturing and quality control. The system comprises an image acquisition module, a defect detection module, a compensation execution module and a feedback control module, based on defect types and positions, a grading compensation strategy is triggered, the grading compensation strategy comprises real-time printing parameter adjustment, laser accurate repair of a defect area or automatic rejection of a mechanical arm, and a process parameter library is synchronously updated through an industrial Internet of Things platform. The innovation points are as follows: (1) a multi-modal defect data fusion method is provided, and the detection robustness under complex working conditions is improved; (2) a lightweight double-branch detection network is designed, and the detection speed and precision are both considered; and (3) developing a compensation instruction cooperative control algorithm to realize seamless connection between defect repair and production line rhythm. According to the scheme, the defect omission ratio can be reduced to 0.5% or below, the compensation response time is shortened to be within 200 ms, and the production line yield and the production efficiency are remarkably improved.

The invention relates to the technical field of numerical control programming, in particular to a five-axis machining path planning method and system based on data driving, and the method comprises the following steps: obtaining real-time coordinates of each axis of a machine tool, calculating linear velocity and angular velocity components to construct a Jacobian matrix, executing singular value decomposition, and calculating a conditional number ratio by using maximum and minimum singular values; and inputting a nonlinear mapping function to calculate a dynamic penalty factor, generating a rotating shaft weighted item in combination with a rotating shaft identifier, constructing a weighted damping least square objective function, calculating a five-axis motion increment, and accumulating the five-axis motion increment with a real-time coordinate to generate a target absolute position coordinate. According to the method, the pose singularity degree is quantified by monitoring the machine tool pose condition number ratio and converted into the dynamic penalty factor to apply the self-adaptive constraint to the rotating shaft, the severe sudden change of the rotating shaft in the singularity area is inhibited, the tool nose track following error is minimized, and meanwhile smooth distribution of the motion increment is achieved; and the dynamic stability and the surface quality of five-axis linkage machining are improved.

The invention discloses an intelligent mold part machining cutting tool control method and system. The method comprises the following steps that S1, a multi-source sensing information collection layer is established; s2, constructing a cutter health knowledge graph; s3, generating a dynamic decision control instruction; s4, executing a bimodal control response; and S5, realizing closed-loop control optimization. Through quadruple mechanism coupling of global coverage of a multi-mode sensing layer, dynamic deduction of a knowledge graph decision-making layer, risk isolation of a double-track execution layer and intelligent evolution of a closed-loop optimization layer, the method is realized in an industrial control domain for the first time: raising a sensing dimension, and converting a physical world fragmentation signal into a cutter full life cycle digital twinborn body; reconstructing decision logic, replacing traditional threshold judgment with topological correlation, and foreseeably inhibiting ill-conditioned failure; the system is ecological and self-consistent, and the control strategy continuously evolves in operation to form the anti-interference capability; and finally, normal form transition of tool wear control from passive remediation to active immunity is achieved.

The invention relates to the technical field of numerical control machine tool precision detection and compensation, in particular to a coordinated motion planning control method and related products in the five-axis machining process, and the method comprises the steps: building a machine tool digital twin model, and combining constraint conditions; calculating a dynamic load rate and adjusting an error weight according to the load rate; an optimal cooperative motion instruction is obtained through multi-objective optimization; obtaining a feed-forward compensation amount and a feedback compensation amount; fusing the feedforward compensation amount and the feedback compensation amount to obtain a total compensation amount, and correcting the optimal cooperative motion instruction in real time to generate a final control signal; according to the method, dynamic constraints of different dimensions of a shaft are unified, the real-time dynamic load rate of the shaft is calculated, and weight coefficients of a translation shaft error and a rotation shaft error in an objective function are dynamically adjusted and optimized according to the difference; and constructing a multi-objective optimization function, solving an optimal cooperative motion instruction according to the dynamic weight, and integrating feed-forward compensation and feedback compensation to generate a final control signal so as to realize accurate control.

The invention relates to the technical field of laser cutting, and discloses a high-power laser cutting light path system, a laser cutting head and a using method of the laser cutting head. The system comprises a dynamic cutting path accounting module, a multi-dimensional cutting difference analysis module, an abnormal region association positioning module and a self-adaptive cutting strategy generation module. The dynamic cutting path accounting module builds a model based on laser cutting historical data, and collects laser power fluctuation, light beam quality distribution and cutting speed sequence data of current cutting in real time. The multi-dimensional cutting difference analysis module receives the information and performs three-dimensional difference analysis with an actual measurement path of the optical sensor to generate a workpiece-level difference coefficient matrix; and the abnormal region association positioning module inputs the matrix into a space geometric analysis network, generates an abnormal probability thermal distribution diagram of a cutting defect propagation path, and positions an abnormal cutting region. And the adaptive cutting strategy generation module configures parameters according to the thermodynamic diagram, and applies multi-band impedance disturbance to the adjacent node cutting head with the maximum abnormal probability gradient change.

The invention discloses a ship steel plate digital cutting and typesetting optimization method and system, and the method comprises the steps: collecting the morphology data of a to-be-cut steel plate, and generating a machining region model; based on the machining area model and the specification data of the target part, a deep reinforcement learning-genetic hybrid algorithm is adopted as a solving strategy, and an optimal typesetting scheme is output; generating a numerical control cutting path and a corresponding numerical control code according to the preferable typesetting scheme, and carrying out kerf gap constraint and thermal deformation compensation on the numerical control cutting path; based on the deviation between the ideal coordinates of the reference mark points in the machining area and the real coordinates of the reference mark points projected on the to-be-cut steel plate, the to-be-cut steel plate is positioned and calibrated; and executing a cutting instruction, evaluating a cutting result, and feeding back deviation data to adjust and optimize strategy parameters. On the premise of ensuring the process feasibility, limit utilization of the steel plate is achieved, the cost is reduced, the cutting quality is improved, and the method is suitable for shipbuilding scenes with various complex parts and high cutting precision requirements.

The invention discloses a control system for improving the numerical control machining precision of a bionic unmanned aerial vehicle wing, and relates to the professional technical field of numerical control machining, and the control system specifically comprises a multi-dimensional sensing module, a digital twin model construction module and a numerical control machining precision improvement module, the multi-dimensional sensing module acquires geometric and material states and dynamic response data through a high-precision sensor cluster and realizes space-time consistency, the digital twin model building module comprises geometric modeling and physical attribute modeling, and is used for predicting the service life of a tool by combining an Archard wear model based on laser scanning point cloud and CAD (Computer Aided Design) model registration compensation pose deviation. And meanwhile, a five-axis machine tool multi-body dynamic model is established, a numerical control machining precision improving module dynamically divides sub-routes, establishes an error prediction model, corrects a machining path in real time, regulates and controls monitoring frequency according to geometric errors, thermal errors and material damage errors, triggers a cooling system to enhance or bypass a damage area, and guarantees machining precision.

The invention provides a numerical control machine tool linkage operation system which comprises a multi-axis error real-time monitoring module, an error coupling dynamic modeling module, a linkage shaft error dynamic compensation control module, a control stability optimization module and a man-machine interaction intelligent guide module. By arranging the multi-axis error real-time monitoring module and the error coupling dynamic modeling module, real-time position information of a plurality of linkage shafts is collected in the operation process of the machine tool, a linkage error dynamic model is constructed based on the information, the linkage coupling influence relation between the shafts is introduced, and the linkage error dynamic modeling is realized. The space superposition state of errors in the multi-axis linkage process is more accurately reflected, the compensation control module is combined to convert the real-time errors predicted by the model into instruction level control correction, and therefore dynamic closed-loop adjustment of linkage shaft displacement is achieved, and the problem of track deviation caused by error coupling between linkage shafts is effectively solved.

The invention relates to the technical field of path control, in particular to a combined path and laser processing planning method based on machine vision, which comprises the following steps: acquiring an image by an industrial camera to extract contour measurement parameters to identify defective materials, setting path start-stop optimization connection smooth obstacle avoidance based on a feature table, and detecting a dynamic adjustment range of a hot area. And according to the adaptive group setting threshold evaluation capability, the delay prediction adjustment power speed is calibrated, an instruction set is called to compensate, predict and correct error dynamic matching, and an optimal processing path and a synchronous processing setting table are output. According to the method, the workpiece image is obtained in real time, the machining features are analyzed, the machining precision and efficiency are improved, fine control in the machining process is achieved, effective cooperation of path planning and machining parameters is ensured, the problem of mismatching of path planning is avoided, the response precision and stability in the machining process are improved, and the machining precision and efficiency are improved. The processing quality and time management are remarkably improved, and low efficiency and quality fluctuation caused by manual adjustment in the prior art are avoided.

The invention provides a numerical control machining control method and device, a numerical control machine tool, a medium and a program product, and relates to the technical field of numerical control machining. The numerical control machining control method comprises the steps that in response to a received first setting instruction of a self-adaptive learning state, a main shaft of a numerical control machine tool is controlled to machine a part based on a fixed feeding rate under a preset machining condition, and a corresponding main shaft power curve is generated; performing adaptive learning based on the main shaft power curve and the configured power range to obtain a processing model; and in response to a received second setting instruction of the self-adaptive control state, in the machining process of the part, the sensed load of the main shaft is input into the machining model, so that the machining model outputs the feeding rate of the main shaft based on the self-adaptive adjustment operation, and the main shaft operates based on the changing feeding rate. According to the technical scheme, the machining model is used for adjusting the feeding rate of the machine tool spindle in real time based on the detected real-time load, and the machining efficiency is higher.