1890results about "Numerical control" patented technology

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 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 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 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 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 track board drilling parameter intelligent optimization method and system based on deep learning, and relates to the technical field of deep learning, and the method comprises the steps: recognizing a feature region in three-dimensional scanning data through a deep learning semantic segmentation network, building a local coordinate system, calculating hole site deviation, constructing a pose correction field, and achieving the intelligent correction of drilling process parameters. And an optimal drilling track is generated by using a state space search algorithm. The method can adapt to actual geometric errors of the track plate, the drilling precision and efficiency are improved, the drilling failure rate is reduced, and the manufacturing quality of the track plate is improved.

The invention relates to the technical field of intelligent control of numerical control machine tools, in particular to a numerical control machine tool machining parameter self-optimization system based on cross-frequency interference coupling regulation and control, which comprises a cross-frequency interference event judgment unit and a dynamic coupling regulation and control unit, a cross-frequency interference event judgment unit calculates cross-frequency interference intensity factors in continuous M control periods by comparing a blade frequency band characteristic value rising amplitude with a cutter frequency band characteristic value falling amplitude, a cooperative regulation and control instruction is generated, a dynamic coupling regulation and control unit executes step down-regulation of the feeding amount after receiving the instruction, and the frequency band characteristic value of the blade is adjusted. And a main shaft torque compensation current is synchronously calculated and injected to stabilize the rotating speed, meanwhile, transient jitter is sampled through the rotating speed micro-oscillation suppression sub-module, reversed-phase pulse counteracting is generated, and when a blade frequency band characteristic value fluctuates, a cutter frequency band regression reference and an interference intensity factor reach a safe area, regulation and control are terminated, and the machining precision is improved.

The invention provides a multi-axis linkage engraving equipment control algorithm optimization method, which belongs to the technical field of engraving equipment, and comprises the following steps of: decomposing a model into a plurality of curved surface segmentation segments according to a curvature change rate, and performing NURBS curve parameterization processing on each segment to generate control point coordinates and weight coefficient data; a dynamic weight adjustment model is adopted to dynamically calculate a path planning weight coefficient according to a tool cutting force value, a surface roughness demand value and a machining efficiency index value, a minimum spanning tree path algorithm is utilized to carry out path connection sequence planning, and a layered interpolation operation framework combining preprocessing interpolation calculation and real-time interpolation compensation is established. And the optimized interpolation coordinate data is converted into an axis control instruction sequence containing a position instruction, a speed instruction and an acceleration instruction, and the technical problem that the interpolation calculation precision and the real-time performance are difficult to balance when the multi-axis linkage carving equipment is used for machining a complex curved surface is solved.

The invention discloses a five-axis machining tool path planning method for a complex curved surface, and relates to the technical field of numerical control machining. Subregions are divided based on the Gaussian curvature of a curved surface model, and a region equation is fitted; projecting the sub-regions and screening to obtain a boundary point set, fitting a curved surface equation by adopting cubic NURBS, and performing normal vector and curvature constraint optimization to splice an optimal curved surface equation; setting a section plane, calculating a section curve, calculating an arc length based on a Simpson formula, and planning a track point coordinate sequence according to the curvature; constructing a spiral equation of adjacent section planes, calculating a spiral step length based on a Simpson formula according to a position and tangent continuous constraint solving coefficient, and generating a cross-plane track point sequence; in the section plane, based on lossless and cutting direction constraints, an optimal angle sequence is obtained through optimization of a genetic algorithm, and a cross-plane angle sequence is obtained through cosine interpolation; and a machining pose sequence is generated through integration, and high-precision machining of the complex curved surface is achieved.

The invention relates to the technical field of machine tool control, and provides a machine tool machining control method and system.The method comprises the steps that in the machine tool machining process, microenvironment parameters of a cutting area are obtained and monitored; obtaining a cutter type, a workpiece material attribute and a preset cutting parameter corresponding to the machine tool; based on the tool type, the workpiece material attributes and the preset cutting parameters, an initial judgment basis of the tool wear speed is established; according to the deviation between the microenvironment parameters and a preset standard value, the initial judgment basis is corrected, and the corrected tool wear speed is obtained; according to the actual tool abrasion loss, the rule for subsequently correcting the initial judgment basis is optimized; and based on the corrected tool wear speed, the tool remaining life is updated, and when tool wear reaches a preset threshold value, a compensation strategy of the cutting parameters or the tool path is decided and executed in combination with the value of the machined workpiece and the remaining machining task. The method has the effect of improving the prediction accuracy of the tool wear speed.

The invention relates to the technical field of machining control, in particular to an intelligent planning system and method for a multi-axis linkage numerical control machining path, and the system comprises a data collection unit which is used for obtaining the form attribute parameter information of a machined workpiece and the axial motion attribute parameter information of a multi-axis machining unit; and the initial division unit is used for performing initial division on a workpiece machining range according to the morphological attribute parameter information and the axial motion attribute parameter information to obtain an initial segmentation result and an initial trajectory planning result of the machining range, and the initial trajectory planning result comprises coordinate information of each trajectory segment. The collision condition between the motion path of the cutting tool and the feature range of the workpiece can be checked in real time through the collision checking unit, and the path is automatically adjusted through the collision avoidance unit, so that possible machining errors and equipment damage are avoided, and the machining safety and stability are greatly improved through intelligent collision avoidance.

The invention belongs to the technical field of intelligent manufacturing, relates to the directions of numerical control machining, industrial robot trajectory control, complex curved surface path planning and the like, and provides a topology maintenance type curved surface trajectory optimization algorithm fusing surface curvature induction and multi-domain coupling optimization. The method comprises the steps of curved surface preprocessing, initial path construction, multi-domain coupling optimization, topology maintenance, trajectory output and the like. The method comprises the following steps: extracting local curvature characteristics of a free-form surface, adaptively arranging path points, constructing a multi-target optimization model containing indexes such as path uniformity, normal consistency and track fairness, and ensuring that the path direction is consistent with the normal height of the surface through an optimization process. The algorithm adopts an evolutionary optimization strategy to globally adjust the path, and introduces a topology maintenance mechanism to ensure that the original curved surface structure is not damaged in the optimization process. The method is suitable for CNC machining, industrial robot trajectory control and three-dimensional modeling, and has the advantages of being reasonable in path distribution, high in geometric consistency, stable in optimization effect and the like.

The invention provides a machining cutter feeding speed control method and system.The method comprises the steps that a three-dimensional stress field, a temperature field and cutter micro-vibration characteristics of a cutter cutting area are collected through a preset sensor array, and real-time plastic deformation parameters of a workpiece material and machine tool spindle power fluctuation data are combined; forming a corresponding processing state sensing matrix; obtaining a machining constraint condition of the tool, and optimizing the initial particle swarm algorithm through the machining state sensing matrix and the constraint condition to generate a corresponding target particle swarm algorithm; a speed reference curve matched with the cutter is generated in real time through a target particle swarm algorithm, and cutting noise spectrum features are collected through a high-frequency sonic sensor; and performing conversion processing on the speed reference curve and the cutting noise spectrum characteristics to generate a feeding speed matched with the cutter in real time. The feeding speed can be accurately controlled, and the production efficiency is correspondingly improved.

The invention relates to the technical field of turning machining, and discloses an ultra-precision turning machining control method and system and a storage medium. The method comprises the steps that a laser contourgraph detects geometric parameters and abrasion data of a turning tool, and a tool health degree index is calculated; performing error compensation based on the health degree index to obtain a feeding control parameter; cutting force signals are collected, and technological parameters are optimized through a multi-target genetic algorithm; arranging a temperature sensor array, and adjusting cooling control according to process parameters; and generating a track control point and performing interpolation processing to obtain a motion control sequence. According to the method, the problem that the machining precision is unstable due to the fact that the cutter state cannot be quantitatively evaluated in real time in traditional turning is solved, and the precision control capability and machining quality consistency of ultra-precision turning are improved.

The invention discloses a deviation correction method, system and equipment based on a tool bit, and relates to the technical field of tool bit correction.The method comprises the steps that after a tool bit replacement correction request sent by a user side is received, the system executes first-time destination cutting, generates a destination cutting groove virtual model, extracts cutting parameters and compares the cutting parameters with preset parameters, and destination cutting deviation data is obtained; the system compensates the tool bit track and then executes second-time return cutting, a return cutting groove virtual model is generated, cutting parameters are extracted, and return cutting deviation data are obtained; the residual deviation is compared with a preset residual deviation threshold value, and whether the tool bit is corrected or not is judged; and if the correction is not completed, calculating a correctable value, and judging whether the return cutting deviation data can be continuously used for subsequent compensation or not. According to the method, whether the tool bit deviation can be compensated or not can be dynamically judged according to actual conditions, system oscillation caused by blind correction is avoided, rapid detection, effective compensation and intelligent decision making of the tool bit deviation are achieved, and the cutting precision and the system stability are improved.

The invention discloses a gear machining multi-source thermal error compensation system based on tensor compression edge deployment, which fuses physically guided multi-source error modeling, tensor-based model compression, edge deployment and bandwidth sensing signal scheduling to realize low-delay and high-precision error compensation. The method comprises the following steps: firstly, establishing a three-layer system architecture comprising a cloud layer, an edge layer and a sensing layer, supporting distributed model training, edge reasoning and error compensation so as to support closed-loop operation for realizing adaptive scheduling with extremely low delay, and mainly comprising: (1) a multi-source error model, thermal and geometric errors are fused into coupling high-order representation for capturing space-time interaction through an analytical method; and (2) establishing a sensitivity analysis model based on a physical guidance tensor mode decomposition method (PG-TMDM), identifying a key error source through a three-order tensor structure, and calculating a physical perception contribution rate to retain physical interpretability. And in order to realize real-time deployment, deploying to the edge layer through model compression, model packaging and an edge deployment strategy.

The invention relates to the technical field of numerical control machine tool monitoring, and discloses a numerical control machine tool intelligent monitoring system based on digital twinning. A digital twin modeling module of the system obtains geometric parameters, physical attributes and historical operation data of a numerical control machine tool in real time, and constructs a dynamically updated virtual machine tool model; the working condition sensing module collects vibration, temperature and current data through a multi-source sensor, and generates a running state feature set through time sequence alignment processing. The exception response module is used for matching an exception mode library according to the feature set and outputting an exception type identifier and an influence range parameter; the decision optimization module generates an optimization instruction set containing maintenance priority ranking based on the parameters; and the strategy iteration module monitors an instruction execution result, calculates a deviation value between an actual effect and a virtual model prediction effect, and dynamically updates the abnormal mode library. According to the system, accurate sensing of the operation state of the numerical control machine tool, quick response to abnormity and dynamic optimization of a maintenance strategy are realized, and the intelligent level of monitoring is improved.

The invention discloses a machine tool energy consumption monitoring and energy-saving optimization control system and method, and belongs to the technical field of industrial automation control, and the method comprises the steps: S1, collecting the instantaneous power of a machine tool through an energy consumption data real-time monitoring module; s2, on the basis of the instantaneous power, the change rate of the instantaneous power and the like, a predictive dynamic anomaly index is calculated; s3, in response to the fact that the dynamic abnormality index is larger than a preset dynamic abnormality activation threshold value, applying a correction item positively correlated with the dynamic abnormality index, and generating a dynamically corrected control parameter; s4, outputting the dynamically corrected control parameters to a numerical control system of the machine tool; and S5, based on the dynamically corrected control parameters and the instantaneous power, adjusting and presetting model parameters of the machine tool energy consumption monitoring and energy-saving optimization control system through a closed-loop feedback and model self-correction module. Intervention is performed through the dynamically corrected control parameters, the feed rate is properly reduced, cutter failure is delayed, and workpiece scrapping is avoided.

The invention discloses a mill collaborative optimization control method and system based on digital twinning, belongs to the technical field of intelligent manufacturing, and is used for solving the technical problems that an existing mill control system has obvious defects in the aspects of perception of complex working conditions in a mill, self-adaptive control, collaborative optimization of upstream and downstream equipment and the like. The method comprises the following steps: constructing a digital twinborn model of a target mill; collecting multi-source operation data of the target mill in real time through a sensor group arranged on the target mill; performing data fusion on the multi-source operation data to obtain multi-source fusion data; transmitting the multi-source fusion data to a digital twin model, and simulating the running state of the mill; generating a control strategy of the target mill based on mill load parameters of the digital twin model in the mill running state simulation process; and the control strategy is sent to a control module of the target mill, so that the running state of the target mill is adjusted in real time.

The invention discloses an AGV-six-degree-of-freedom mechanical arm operating system and method based on double-vision fusion, the system comprises a control system and a six-degree-of-freedom mechanical arm, and the control system comprises a master control unit, a slave control unit and a dynamic error compensation module; the method comprises the steps of AGV autonomous navigation and material transfer, cross-station accurate docking and dynamic error compensation, high-precision biological medicine operation under double-vision fusion guidance, and material recovery and circulation. According to the invention, through dual-vision dynamic fusion of eyes outside the hand and eyes on the hand, adaptive switching from global coarse positioning to local fine positioning is realized; due to the integrated design of the AGV and the six-degree-of-freedom mechanical arm, the operation flexibility is greatly improved; an extended Kalman filtering dynamic error compensation algorithm is innovatively adopted, so that the comprehensive error of the AGV, the mechanical arm and the visual system can be corrected in real time; and by combining with a double-layer distributed control architecture, the system realizes multi-task intelligent scheduling and modular collaboration.

The invention discloses a five-axis numerical control machining track fairing optimization method and a five-axis numerical control machining system.The five-axis numerical control machining track fairing optimization method comprises the steps that according to a plurality of target poses designated by a numerical control tool in the space, space broken line paths formed by tool nose points of a tool shaft of the numerical control tool in the space are determined respectively, and a spherical arc path formed by a cutter axis direction vector of the numerical control cutter in the space. Transition curves are added to the space broken line path and the spherical arc path respectively, and a broken line updating path of the space broken line path and an arc updating path of the spherical arc path are obtained; and a machining control instruction for the numerical control tool is determined according to the broken line updating path and the arc updating path. According to the method, the space broken line path and the spherical arc path are constructed and are respectively subjected to fairing treatment, so that the limitation of the prior art in the aspects of transition curve insertion strategy and direction vector continuity control is broken through, and the problems of machining errors and unstable movement are effectively relieved while the track fairing is improved.

The invention relates to the field of precise motion control, in particular to a precise motion control method and system for a multi-axis linkage direct-drive-force tool tower crane. Comprising the following steps: acquiring a processing track, dispersing the processing track into a plurality of spatial motion units, and determining a target displacement for each motion axis; receiving a completion signal; and after determining that the motion axis participating in the current space motion unit completes the corresponding target displacement according to the completion signal, obtaining the completion time of each motion axis, and issuing the target displacement corresponding to the next space motion unit to each motion axis by taking the completion time of the motion axis with the longest completion time as a time reference. Therefore, each motion shaft is started to move the next space motion unit. The technical problems that the machining precision is reduced and the product quality is unqualified due to clock frequency drift and movement shaft synchronization deviation accumulation caused by gradual change of microcosmic physical characteristics in a system of a multi-shaft linkage direct-driving-force tool tower crane are solved.

The invention provides a precision machining and 3D printing mixed manufacturing execution system, and relates to the technical field of data processing, and the system is used for dividing a three-dimensional model into a configuration area and a finishing area, generating a layer-by-layer closed contour path, obtaining configuration path data, extracting a boundary segment close to the finishing area, and obtaining a configuration path data set; calculating a space projection vector on a finishing target surface to obtain primary finishing path data; calculating a boundary torsion value; superposing interference offset in a historical sample path to a primary finishing path; calculating an interference amplitude index; the fitting path data and the configuration path data are subjected to path connection and unified processing according to the manufacturing sequence, and a mixed execution path instruction is obtained. Precise machining and 3D printing are integrated, and path overlapping, empty cutting or unnecessary machining is avoided.

The invention relates to the field of equipment control, and provides a numerical control machine tool cutting parameter optimization method and system based on neural learning. The method comprises the steps that the cutting process of the numerical control machine tool is monitored in real time, cutting process signals are collected, and multi-dimensional time sequence data are obtained; establishing cutting performance evaluation indexes according to the multi-dimensional time sequence data; taking cutting parameters and process parameters as input feature vectors, taking the cutting performance evaluation indexes as output variables, and training a neural learning model to obtain a cutting performance prediction model; a multi-objective optimization mathematical model is constructed based on the cutting performance prediction model, global optimization is carried out in a parameter space through a multi-objective particle swarm optimization algorithm, multiple groups of non-dominated cutting parameter solutions are obtained through calculation, and an optimal solution set is formed; and based on the cutting performance prediction model and the optimal solution set, establishing a cutting parameter decision model, and outputting corrected cutting parameters. Intelligent optimization of cutting parameters can be achieved, and the machining efficiency and quality are improved.

The invention discloses a machine tool cutter cutting control method and system, and relates to the technical field of high-precision manufacturing, and the method comprises the steps: obtaining a first vibration signal, temperature data and a cutting force signal of a main shaft bearing; generating a spindle bearing health score according to the first vibration signal and the temperature data; according to the cutting force signal, the tool abrasion loss is calculated; according to the health score of the main shaft bearing, the tool abrasion loss is corrected; determining a cutter replacement threshold value according to the health score of the main shaft bearing; and if the corrected tool abrasion loss is larger than the tool replacement threshold value, a tool replacement instruction is generated, and cutting is carried out after tool replacement. The cutter can be replaced by combining the health score of the spindle bearing and the abrasion loss of the cutter, so that the cutting control of the cutter is realized, the reliability is improved, and the resource consumption is reduced.

The invention discloses a grabbing and placing task-oriented robot trajectory planning method and device, and the method comprises the steps: obtaining a natural language task instruction, carrying out the path decomposition based on a large language model, and generating a stage sequence containing pre-grabbing, grabbing, lifting, pre-placing, placing and withdrawing, and each stage target and / or constraint; receiving the optimal grabbing pose and / or placing pose provided by the upstream module, and replacing or correcting stage targets related to grabbing and / or placing; generating a trajectory segment according to the corrected stage target and constraint, and carrying out smoothing processing to obtain a trajectory sequence; performing collision detection on the track sequence, and if collision occurs, outputting collision information and executing local repair or replanning until the collision detection is passed or a preset replanning condition is met; and outputting the executable track sequence of the robot controller. According to the scheme, stage decomposition and key pose landing are achieved, and a collision feedback closed loop is formed to obtain an executable track.

The invention relates to the technical field of friction stir repair, and discloses a multi-dimensional defect friction stir solid-phase repair planning system and a defect repair method. The system comprises a defect acquisition unit for acquiring multi-dimensional defect data of a workpiece and generating a time-space correlation data set covering defect depth distribution, a material heat affected zone range, a friction tool wear state and environment temperature and humidity parameters; the feature reconstruction unit decomposes the data set and separates core and abnormal feature tensors; the repair planning unit generates a multi-region cooperation scheme containing a tool path, a pressure sequence and a rotating speed strategy in combination with the core features and the process constraints; the dynamic adjusting and optimizing unit monitors abnormal characteristics and adjusts the scheme when conditions are met; the collaborative strategy unit responds to cross-regional defect linkage abnormity, allocates a standby tool and updates a track offset; and the feature fusion unit fuses the multi-scale monitoring features to generate a repair quality evaluation feature set. The system enhances the comprehensiveness and adaptability of complex defect repair.

The invention relates to the technical field of numerical control machining, and discloses a milling cutter path optimization method of a numerical control milling machine, which comprises the following steps: acquiring an initial milling cutter path, and identifying corner points between adjacent straight line segments; obtaining a corner angle, the length of a relatively short straight line segment and a matrix M of a tool-spindle system; constructing a vibration suppression objective function, and solving the transition arc radius of the corner point; calculating a basic transition feeding speed; calculating a weighted influence factor of each corner point in the N continuous corner point sequences, performing summation to obtain a comprehensive influence coefficient, and calculating a correction transition feeding speed; planning a speed transition area; constructing an S-shaped acceleration and deceleration speed curve; and according to the S-shaped acceleration and deceleration speed curve, the speed transition area and the feeding speed on the transition arc are determined, and an optimized milling cutter path is generated. According to the method, comprehensive and unified speed planning can be carried out on a complex path comprising a plurality of continuous corners, and the surface machining quality and machining efficiency of the workpiece are improved.