1598 results about "Cutting force" patented technology

The invention provides a numerical control machine tool wear automatic detection and compensation method based on artificial intelligence, and the method comprises the steps: collecting the cutting force data of a high-curvature region in real time through multi-sensor fusion, and obtaining the cutting force fluctuation characteristics; cutting temperature data of the high-curvature area are monitored and obtained, the cutting temperature change rate is extracted, whether the temperature exceeds a preset threshold value or not is judged, and if yes, an alarm mechanism is triggered, and cutting parameters are adjusted; predicting the tool wear rate in combination with the co-evolution relationship between wear and temperature, the online monitoring data and the processed time, and generating a wear prediction curve in a preset time period; and performing trend analysis and feature extraction on the wear prediction curve to obtain wear parameter changes of the cutter in a preset time, and if the prediction curve shows that the wear parameter changes at a certain time point in the future exceed a preset critical value, adjusting the cutting parameters and generating a target cutting parameter combination.

The invention relates to a digital twinning-based bogie numerical control machining error compensation method and system, and the method comprises the steps: constructing an initial digital twinning model comprising material characteristics and geometric constraints through fusing the historical machining data of a bogie and the structural characteristics of a workpiece; according to the real-time cutting force and temperature data dynamic correction model, time-varying stiffness parameters are updated, and a deformation prediction result is generated; identifying an error exceeding area based on the precision requirement of the bearing seat assembly surface; and the feed rate compensation amount is calculated according to the thin-wall area deformation gradient, and a pre-compensation parameter scheme used for adjusting the cutting path is generated. The method overcomes the industrial problems that a traditional compensation technology cannot dynamically suppress instantaneous deformation, multi-source error coupling is difficult to decouple, and parameter adjustment depends on trial cutting verification, and the machining precision and efficiency of the bogie are remarkably improved.

The invention relates to the technical field of program control, in particular to a servo position control method and system applied to an engraving and milling machine. The method comprises the following steps that real-time temperature data and real-time load data of lead screws of all shafts in the engraving and milling machine are obtained; collecting multi-node temperature distribution data of the engraving and milling machine; obtaining cutting force data and resonant frequency characteristic values in the engraving and milling machine; constructing a screw rod reverse clearance prediction model based on the real-time temperature data and the real-time load data of the screw rod, and generating a clearance compensation value; performing pre-compensation control before the servo position direction of each axis is changed based on the clearance compensation value to obtain a correction position instruction; and performing thermal deformation simulation on the engraving and milling machine based on the multi-node temperature distribution data to generate thermal deformation compensation amounts of all shafts. Through multi-source data fusion and intelligent control, comprehensive optimization of the servo position system of the engraving and milling machine is achieved, the machining precision, dynamic response and stability are effectively improved, and efficient and reliable operation of high-speed and high-precision machining is guaranteed.

The invention discloses a numerical control machining path control system based on artificial intelligence, particularly relates to the field of numerical control machining, is used for solving the problems of continuity and stability of a curvature mutation area in cutter path planning, and accurately captures global and local geometric characteristics of a curved surface through a curvature constraint feature matrix and a curvature adaptive convolutional network. A machining track meeting the differential geometric continuity is generated, and the problem of path breakage of a curvature sudden change area is effectively avoided; meanwhile, energy scale criteria and curvature manifold constraints are introduced, the machining track is dynamically repaired, geometric repair and physical stability are balanced, cutting force sudden change and stress concentration are reduced, and therefore the machining reliability is enhanced; in addition, through finite element simulation of the digital twin platform and synchronous updating of servo system parameters, dynamic closed-loop matching of a control instruction and a machining state is achieved, and the control efficiency and the surface quality are further optimized. And therefore, high-precision, high-stability and high-efficiency collaborative optimization is realized in complex curved surface processing.

The invention provides a mobile phone middle frame CNC machining optimization method based on artificial intelligence. The mobile phone middle frame CNC machining optimization method comprises the steps that the surface of a mobile phone middle frame workpiece is scanned in real time, initial data of material hardness distribution are obtained, a hardness distribution mapping graph is formed, and a hardness change region division result is obtained; the hardness grade distribution and the cutting force sudden change amplitude of the cutting force sudden change specific position are recognized, adjustment parameters of the cutter feeding speed are obtained through calculation according to the hardness grade distribution and the cutting force sudden change amplitude, and a speed adjustment instruction is generated according to the adjustment parameters; and dynamically matching the cutting depth parameters according to the speed adjusting instruction, determining target cutting depth configuration, and matching the cutting path deviation monitoring value, the vibration amplitude index and the machining precision deviation value in real time through the target cutting depth configuration.

The invention relates to the technical field of numerical control machine tool operation, in particular to a machining data acquisition method and system applied to a numerical control machine tool, and the method comprises the steps: obtaining a machining precision error value according to the difference between cutting parameters of different dimensions and initial cutting parameters; according to the difference change condition of the cutting parameter and the initial cutting parameter, a tool wear characteristic value is obtained; obtaining a tool wear influence value according to the tool wear characteristic value and the cutting force change influence value; obtaining a machining precision error influence value according to the tool wear influence value and the machining precision error value; acquiring an acquisition frequency regulation factor at the current moment according to the variation trend of the processing precision error influence values of different target error historical time periods; and acquiring the boring and milling data acquisition frequency at the current moment based on the acquisition frequency regulation factor. The boring and milling precision of the numerical control machine tool is improved.

The invention discloses a hard and brittle material ultra-precision turning damage monitoring method based on multi-sensor fusion, and relates to the technical field of precision / ultra-precision machining state monitoring, a multi-sensor signal acquisition device is built on an ultra-precision turning machine tool to capture different types of sensor signals generated in the turning process in real time; performing signal preprocessing operation of minimum entropy deconvolution filtering on the acquired sensor signal; feature extraction is carried out on the signals subjected to minimum entropy deconvolution filtering, and 95 time domain and frequency domain statistical features reflecting turning damage are extracted; by integrating data from different sensors, the precision and reliability of monitoring are remarkably improved, more comprehensive and more accurate information can be obtained by capturing and fusing acoustic characteristics, cutting force and mechanical vibration information in the machining process, so that the abrasion degree of a tool and the damage condition of a workpiece are judged more accurately, and the machining accuracy is improved. And false alarm and missing alarm can be reduced, and the monitoring reliability can be improved.

The invention discloses a discrete point-based cutting force prediction method supporting any cutting edge shape, and relates to the technical field of milling machining.The discrete point-based cutting force prediction method comprises the steps that firstly, a workpiece and a tool are both expressed in a discrete model, a milling track is defined as a series of linear segments through NC codes, and a tool and cutting edge model and a Tri-Dexel workpiece model are built; secondly, a tool swept volume is obtained, and material removal is calculated; then subdividing the tool motion into smaller analysis steps to obtain the cutting condition of each turn, determining the cutting meshing area of each analysis step and blade elements participating in cutting, and calculating the nominal instantaneous undeformed chip thickness of each blade element based on the actual feeding direction, the normal vector and the compensation coefficient; then, discretizing the cutting condition into a plurality of orthogonal cutting units, and predicting the cutting force of each participating blade element by adopting a neural network trained based on simulation data; and finally, integrating the cutting forces of all participating blade elements to obtain a synthetic cutting force field of each analysis step. According to the method provided by the invention, the force field prediction capability in a variable geometry processing scene is effectively improved.

The invention relates to the technical field of cycloidal gear machining control, in particular to a speed reducer cycloidal gear efficient machining method and device based on a machining machine tool, and the method comprises the steps that machining data in the cycloidal gear machining process are obtained and preprocessed; preliminarily judging whether a flutter phenomenon occurs or not by analyzing the periodic change of the cutting depth and the periodic fluctuation of the cutting force under different temperature changes; vibration, current and cutting force data are combined to evaluate the chatter occurrence possibility; classifying the processing data through clustering analysis by utilizing the chatter occurrence possibility so as to screen out high-quality processing data and flaw processing data; and a dragonfly optimization algorithm is adopted, initial position distribution of the algorithm is optimized through the high-quality machining data and the defect machining data, and the optimal cutting speed is solved to serve as the cutting speed in the current cycloidal gear machining process. According to the method, the flutter phenomenon is comprehensively analyzed through the multi-dimensional machining data, so that the overall machining efficiency in the current cycloidal gear machining process is improved.

The invention provides a robot milling surface roughness prediction method and system based on parallel convolution and coordinate attention mechanism feature fusion. According to the method, firstly, multi-source heterogeneous high-frequency signals in the milling process of a robot are synchronously collected, empty slice segments are eliminated and environmental noise is filtered out by utilizing a self-adaptive threshold value and a robust statistical method, and a standardized time sequence sample set is constructed; secondly, establishing a multi-source heterogeneous feature fusion roughness prediction model, and independently extracting deep features of cutting force and vibration signals by adopting a double-branch parallel convolution architecture; a coordinate attention mechanism is introduced, heterogeneous modal features are mapped into a virtual two-dimensional topological structure, the dynamic relative contribution degree of cutting force and vibration signals changing along with the machining state is captured through pooling aggregation along the modal dimension, and an attention weight map is generated to conduct dynamic weighting on the features. And finally, outputting a surface roughness predicted value through a regression network. According to the method, the problem that an existing fusion method neglects the dynamic dependency relationship between physical quantities is effectively solved, the anti-interference capability of the robot in the weak rigidity machining process is enhanced, and the precision and robustness of surface roughness prediction are remarkably improved. The method can be widely applied to robot complex component machining quality analysis and intelligent optimization, and has high efficiency and reliability.

The invention discloses a three-dimensional jitter compensation method and device for laser cutting and a storage medium, and relates to the technical field of lasers, and the method comprises the steps that fast Fourier transform is carried out based on a vibration signal of a to-be-machined thin plate in the Z-axis direction, and a frequency spectrum feature is obtained; according to the frequency spectrum characteristics, combining a preset jitter filtering parameter set to carry out frequency domain filtering processing, and generating a filtering signal; reconstructing the filtering signal into a time domain compensation amount through inverse Fourier transform; based on the time domain compensation quantity, performing weighted fusion by combining the cutting acceleration and the cutting displacement deviation in the current cutting direction, and generating a three-dimensional compensation vector; and superposing the three-dimensional compensation vector to an original cutting path coordinate through a motion controller so as to correct the following state of the cutting head. The technical problem that the thin plate shakes due to nonlinear cutting force caused by interaction between high-speed movement of the cutting head and laser and materials is solved, and the stability of the thin plate during laser cutting is improved.

The invention relates to the technical field of spline machining, in particular to a spline machining device and method for an eccentric shaft of a speed reducer, and the method comprises the steps that the amplitude-frequency difference between all cutting force data and all vibration data in a frequency domain and the correlation between all cutting force data and all temperature data within a preset duration before all moments are analyzed; determining a cutting risk value; comprehensively analyzing a cutting risk value, an energy ratio, a dominant frequency amplitude difference between all vibration data and all cutting force data in a frequency domain and a change relation of a cutting related index along with the machining quality in a preset period before the current moment, predicting a machining quality score to determine a machining instability index, and combining the energy ratio and the machining quality score to determine the machining instability index. And determining a main shaft rotating speed correction value and a cutter feeding amount. The problem of compensation failure of traditional PID control is solved, the spline machining quality is improved, and the service life of a workpiece is prolonged.

The invention relates to the technical field of precision machining, in particular to a cutting force signal synchronous calibration method based on multi-sensor data fusion, which comprises the following steps of: 1, dynamically preprocessing acquired signals; step 2, constructing a reference time axis based on the spindle current signal, and realizing time domain alignment of multichannel signals by adopting a dynamic time warping algorithm; 3, establishing a feature incidence matrix containing a force-vibration-temperature coupling relation, and generating a fusion cutting force feature vector through frequency domain energy weight distribution; 4, a dynamic transfer function model is constructed, model parameters are updated in real time, and the fusion feature vector is mapped into a calibration cutting force signal; and 5, carrying out dynamic compensation on the calibration signal by adopting a nonlinear inverse compensation and residual modal screening strategy. According to the method, the accuracy of cutting force signals can be remarkably improved, errors and uncertainty in the machining process are reduced, and the production quality and efficiency are optimized.

The utility model discloses a cleaning rolling brush, cleaning equipment and a cleaning system, and belongs to the technical field of electrical equipment. The cleaning rolling brush comprises a shell, a cleaning strip, a first cutting piece and a second cutting piece, and the first cutting piece and the second cutting piece extend on the outer surface of the shell; the cleaning strip protrudes out of the outer surface of the shell; wherein a cleaning strip is arranged in a gap between the first cutting piece and the second cutting piece, so that the cutting force on entanglements wound on the cleaning strip can be improved, the entanglements can be cut off, the entanglements are prevented from being wound on the shell as much as possible, the influence of the entanglements on the cleaning rolling brush is reduced, and the working effect of the cleaning rolling brush is improved; and the service life of the cleaning rolling brush is prolonged.

The invention provides a dynamic cooperative speed regulation control system and method for a machine tool spindle and a feed shaft, and the method comprises the steps: building a spindle energy transmission model and a feed shaft load-motion model, and constructing a strong correlation coupling relation between the two through cutting power; collecting main shaft power, torque and rotating speed and feed shaft cutting force, acceleration and displacement data in real time, and fusing to generate a combined state vector; calculating spindle margin and time correction based on spindle actual power and torque, and identifying working condition abrupt change according to the joint state vector; the feeding speed and the cutting depth are dynamically adjusted with the spindle margin sum as the constraint condition, and a cooperative adjustment strategy is generated; and converting the cooperative adjustment strategy into a feed shaft motion instruction and executing the feed shaft motion instruction. By constructing a real-time coupling closed loop of'spindle power-torque-rotating speed 'and'feed shaft speed-acceleration-position', the spindle is always locked to operate in a maximum power-torque envelope efficient area, the speed of the feed shaft is dynamically adjusted according to the spindle margin, locked rotor is completely eradicated, and no-load is eliminated.

The invention relates to the technical field of numerical control system fault pre-diagnosis, and particularly discloses a fault monitoring method and system for a numerical control machine tool. The method comprises the steps that a spindle vibration signal, a cutting force signal and a spindle current signal are collected; outputting an alignment signal set; respectively executing adaptive filtering processing according to the alignment signal set; constructing a multi-dimensional feature vector; constructing a health index under the processing behavior period; then accumulated trend deviation analysis is executed through a CUSUM algorithm; and judging whether the tool wear trend is abnormal. The technical problem that in the prior art, static threshold judgment is carried out based on a single signal source, and especially in a numerical control machining scene with signal noise interference, accurate early warning of the early wear trend of a tool cannot be achieved is solved. Due to the fact that a period calibration mechanism fusing spindle vibration, cutting force and current signals, feature vector entropy weight optimization and a CUSUM trend detection mechanism are adopted, the pre-diagnosis level of the numerical control machine tool on cutter state changes is improved.

The invention relates to the technical field of fastener process production, in particular to a process parameter control method and system applied to fastener production. The method comprises the following steps: acquiring three-dimensional cutting force of a tool-workpiece contact area in a fastener thread machining process in real time, and generating cutting force dynamic fluctuation characteristic data; the real-time abnormal situation of the current machining process is recognized according to the cutting force dynamic fluctuation characteristic data, a tool wear mode is judged, thread ring machining deviation prediction is conducted, and a predicted thread geometric deviation value is generated; and adjusting multiple machining control parameter values according to the predicted thread geometric deviation value, and carrying out real-time machining feedback monitoring so as to realize fastener production self-adaptive control. According to the method, intelligent recognition of the tool wear mode and accurate prediction of the machining deviation are achieved through cutting force sensing, and it is ensured that the thread machining precision of the fastener is stable and controllable through multi-parameter cooperative self-adaptive regulation and control.

The invention provides a lead screw precision milling closed-loop optimization and real-time control process based on multi-axis linkage, which comprises the following steps of: acquiring geometric parameters of a workpiece, material attributes and kinetic parameters of a machine tool, designing a cutter and clamp scheme, and setting initial processing parameters based on a cutting database; constructing a lead screw spiral groove high-precision curved surface model by using an NURBS curve, and optimizing a path through curvature adaptive discretization and quintic spline interpolation; an idle stroke path is iteratively optimized by adopting a real number coding genetic algorithm, and the total time of the path and the reversing frequency are shortened; multi-axis synchronous control is achieved through inverse kinematics solution, and the cutter inclination angle is dynamically adjusted in real time based on the contact angle; and virtual simulation and finite element analysis are utilized to predict cutting force, thermal deformation and interference risks. According to the method, the continuous and smooth multi-axis synchronization instruction is generated, the positioning error of each axis is effectively reduced, meanwhile, the cutter inclination angle is dynamically corrected through force feedback of the contact angle, cutting force fluctuation is effectively restrained, and it is ensured that the tooth surface roughness of the spiral groove meets the requirement.

Methods and systems are provided that calculate data representing an estimate of formation strength while drilling. The methods and systems employ a drill bit that is instrumented with a first sensor and a second sensor. A processor is configured to i) determine and store first data representing cutting forces acting on a cutting element of the drill bit while drilling based on measurements of the first sensor while drilling, ii) determine and store second data representing depth of cut of the drill bit while drilling based on measurements of the second sensor while drilling, and iii) process the first data and second data to generate and store data representing contact stress against the formation while drilling. This resultant data can be used as an estimate of formation strength. This estimate of formation strength is similar to UCS and can be used in oilfield operations / planning, such as formation characterization while drilling, or drilling efficiency analysis while drilling.

The invention relates to the technical field of tool control, in particular to a tooth cutting tool parameter control system based on bevel angle cutting, which comprises a tool parameter acquisition module used for acquiring the rotating speed, the axial feeding amount and the cutting depth of a tool in real time; the force-heat prediction model is used for outputting predicted cutting force and predicted cutting tool temperature; the multi-target parameter optimization model is used for receiving constraint conditions set by a user, optimizing the rotating speed, the axial feeding amount and the cutting depth of the cutter by taking the lowest cutting force, the lowest temperature of the cutting cutter and the highest machining efficiency as targets in the constraint conditions, and integrating and outputting a regulation and control strategy; and the cutter parameter control module is used for regulating and controlling the rotating speed, the axial feeding amount and the cutting depth of the cutter based on a regulation and control strategy when the predicted cutting force and the predicted temperature of the cutting cutter exceed threshold values. According to the method, by accurately regulating and controlling the parameters of the tooth cutting tool, the machining efficiency of the tooth cutting tool can be ensured, and meanwhile the abrasion speed of the tooth cutting tool is reduced.

The invention relates to the technical field of automobile film roll dividing and edge cutting, in particular to a slitting device for improving color changing film slitting precision and flatness, which comprises a mounting seat, two supporting plates are arranged at the top of the mounting seat, an auxiliary mechanism, a conveying mechanism and a mounting strip are sequentially arranged between the two supporting plates, and a sliding groove is formed in the bottom side of the mounting strip. A transmission lead screw is rotationally arranged in the sliding groove, a sliding block is in threaded engagement with the transmission lead screw, a cutting knife is arranged on the top side of the sliding block through a reciprocating assembly, a receding strip hole communicating with the sliding groove is formed in the top side of the mounting strip, a servo motor is arranged on the side wall of the supporting plate, and an output shaft of the servo motor rotationally penetrates into the sliding groove. The servo motor drives the transmission lead screw to rotate to be meshed with the sliding block and drives the cutting knife to move horizontally, and under the cooperation of the reciprocating assembly, the cutting knife moves vertically in a reciprocating mode and is matched with the cutting force of the cutting knife to cut the color changing film.

The present invention discloses a bionic swallowtail-shaped micro-textured tool and a preparation method thereof, belonging to the technical field of metal cutting tools. The preparation method is based on a cemented carbide tool substrate, and combines the structural advantages of the swallowtail structure in reducing frictional resistance and accelerating the flow of gas and liquid. On this basis, a corresponding functional tool is prepared by machining a bionic swallowtail-shaped groove and surface texture. The designed tool groove is used to discharge chips and store and convey cutting fluid; the surface texture is used to reduce the frictional force between the chip and the tool during cutting and promote the discharge of chips, thereby reducing the cutting force, improving the tool life and processing efficiency. Compared with the prior art, based on the bionic principle, the present invention combines the tool groove and the surface texture to design and prepare a functional tool, achieving the functional requirements of improving the heat resistance and wear resistance of the tool, prolonging the tool life, reducing the production and processing cost, and realizing green processing, and meeting the production and processing needs.

The invention relates to the technical field of ultrasonic cutting, in particular to a sawtooth-shaped circular knife ultrasonic cutting acoustic system which comprises a main shaft, an ultrasonic vibrator and an ultrasonic cutting tool, the ultrasonic vibrator is connected with the main shaft, the ultrasonic cutting tool is installed on the side, away from the main shaft, of the ultrasonic vibrator, and a plurality of sawtooth grooves are formed in the peripheral face of the ultrasonic cutting tool. The sawtooth grooves are annularly distributed at equal intervals, and sawteeth are formed between every two adjacent sawtooth grooves. According to the ultrasonic cutting tool, the sawtooth grooves are formed in the peripheral surface of the ultrasonic cutting tool, so that the machining mode of the workpiece is intermittent cutting, the contact time of the ultrasonic cutting tool and the workpiece is shortened, and then friction resistance generated by contact between the ultrasonic cutting tool and the workpiece is reduced; heat generated between an ultrasonic cutting tool and a workpiece in the workpiece machining process can be greatly reduced, heat is released through non-contact gaps, and cutting force is reduced by reducing friction resistance.

The invention discloses a tool wear real-time prediction method fusing wear and jumping mechanism-three-dimensional vibration data, and belongs to the field of machine tool state monitoring and intelligent manufacturing. According to the method, a three-dimensional acceleration sensor is arranged near a main shaft or a cutter handle, three-dimensional vibration signals in the machining process are obtained, and a cutting force mechanism model is established in combination with cutting parameters and geometric features of the cutter; and tool wear correction and bounce disturbance items are introduced into the mechanism model, and prediction calculation of the three-way cutting force is carried out. And then, a cutting force prediction result and vibration signal features are fused, a comprehensive feature vector is constructed, and real-time prediction of the tool abrasion loss is realized based on a deep learning regression model. According to the method, physical rule constraints of mechanism modeling and data driving advantages of vibration signals are fully utilized, the accuracy and real-time performance of tool wear prediction are effectively improved, and important engineering application value is provided for improving the machining quality, prolonging the service life of a tool and achieving intelligent production.

The invention discloses a soil-rock composite formation hob fracture avoidance method based on FEM-DEM coupling, and relates to the technical field of tunnel and underground engineering, and the method comprises the steps: building a hob cutting model based on a finite element-discrete element coupling method; generating a soil rock calibration parameter according with the input of the hob cutting model; calculating a cutting force curve of hob impact under any working condition by using the hob cutting model, and extracting the maximum value of the cutting force curve as a load peak value; extracting a cutter ring stress peak value corresponding to the moment of the load peak value; and calculating the current comprehensive equivalent stress of the hobbing cutter ring based on the limit stress, comparing the comprehensive equivalent stress with the dynamically matched yield strength threshold, and judging the risk level of the hobbing cutter ring. According to the method, refined simulation of the whole rock breaking process of the hobbing cutter in the soil-rock composite stratum is achieved, the transient impact load peak value and the induced cutter ring limit stress distribution are captured, and the fracture risk identification precision is remarkably improved.

The invention provides a piston machining drilling clamp and belongs to the technical field of piston machining, the piston machining drilling clamp comprises a machine tool and a machining table arranged on the machine tool, a piston is placed on the machining table, a clamping assembly used for fixing the piston is arranged on the machining table, and a supporting mechanism is arranged at the bottom of the piston. The supporting mechanism comprises two sets of supporting plates arranged at the bottom of the machining table, guide plates are slidably arranged on the supporting plates, and supporting cylinders are rotatably mounted on the guide plates; by arranging the supporting mechanism, precise positioning of the piston pin hole can be achieved, a stable machining reference is established, stable supporting of the pin hole is achieved through the synergistic effect of the multiple sets of supporting blocks, deformation of the pin hole due to different cutting forces is prevented, the supporting assembly can gradually retreat along with drilling, the supporting blocks always keep stable clamping force, and the machining precision of the piston pin hole is improved. And it is ensured that the hole wall is stressed in a balanced mode in the whole drilling process, and temporary deformation is avoided.

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 utility model relates to the technical field of machine tool equipment, and discloses a self-centering tool rest which comprises a sliding plate and a tool mounting table arranged on the sliding plate and used for mounting a tool, and the sliding plate is provided with a cutting position directly facing the tool and a rolling jacking mechanism used for counteracting cutting force of the tool. The rolling jacking mechanism comprises a jacking part, a rolling jacking part and a first driving assembly, wherein the jacking part is arranged on the sliding plate and moves in the radial direction of the workpiece at the position right opposite to the cutter installing table, the rolling jacking part is arranged on the end face, right opposite to the cutter installing table, of the jacking part, can be close to the workpiece and is right opposite to the cutter to abut against the workpiece, and the first driving assembly drives the jacking part to be close to or away from the workpiece. According to the self-centering tool rest in the scheme, when a tool cuts a workpiece, the axis of the workpiece can be effectively prevented from deviating.

The invention provides a flexible adjustable mixed line machine tool spindle cooling system and method, and belongs to the technical field of machine manufacturing. The system comprises a main shaft cooling unit, a dry type air cooling unit, a circulating cooling water unit and a cutting fluid cooling unit, integrates four cooling modes of traditional cutting fluid, minimal quantity lubrication, dry type air cooling and circulating water cooling, and is provided with temperature, flow, cutting force and liquid level monitoring instruments as well as a regulating valve, a switching valve, power equipment and the like which are correspondingly interlocked. By monitoring machine tool machining states such as spindle temperature and cutting force in real time and dynamically optimizing a cooling strategy, flexible switching among four modes and parameter regulation and control are achieved, so that machining heat damage is reduced, the service life of a tool is prolonged, the machining efficiency is improved, meanwhile, cooling medium consumption is reduced, and the efficient, low-cost, low-carbon and safe machining process is achieved.

The invention relates to the technical field of internal spline machining, in particular to an internal spline high-precision machining method and device suitable for a planetary gear, and the method comprises the steps that periodicity measurement and a trend line function are obtained; obtaining a cutting force fluctuation coefficient and a cutting influence coefficient of each time of internal spline machining; and on the basis of the cutting influence coefficient, obtaining the particle weight of each particle in the particle swarm optimization algorithm and the updated inertia weight of each iteration, and performing high-precision machining on the internal spline of the planetary gear. The machining precision of the internal spline of the planetary gear is improved.