1022 results about "Cutting force" patented technology

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 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 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 invention relates to the technical field of gear machining, and discloses adjustable precision gear turning equipment which comprises a device body, and the device body comprises a hob and a workbench; and the dynamic following type supporting unit comprises a rotating disc connected to the centering connecting column through a bearing, multiple sets of supporting rods are annularly arranged on the rotating disc, a supporting plate is installed at the ends, away from the rotating disc, of the supporting rods, and multiple sets of edge supporting assemblies are arranged on the supporting plate. By arranging the dynamic following type supporting unit, the supporting plate and the edge supporting assembly of the dynamic following type supporting unit can provide active upward supporting force for the bottom face of the gear to be machined, and during hobbing, the supporting force can actively offset downward cutting force generated by a hobbing cutter to form balance, so that bending deformation of a workpiece is directly prevented, and the service life of the gear to be machined is prolonged. Errors such as tooth shape concave and tooth direction inclination of the machined gear are avoided, and the machining precision and the surface quality of the gear are remarkably improved.

The invention provides an industrial guide rail drilling method and system. The method comprises the following steps of material pretreatment and positioning reference generation; guide rail hydraulic self-locking clamping; a reference hole laser positioning and drill bit path planning step; self-adaptive drill bit spacing adjustment is carried out; double-sided synchronous drilling and vibration suppression are achieved; integrating online burr detection and burr removal; a cutting force closed-loop control step; cooling, lubricating and self-adaptive spraying; a step of continuously discharging and automatically sorting; and predicting the service life of the cutter and replacing the cutter. The scheme has the following advantages that through the V-shaped clamping mechanism and the hydraulic compensation system, synchronous clamping of the four guide rails is achieved, and the clamping time is shortened to 2 minutes per batch; drilling units are symmetrically arranged on the guide rail up and down, double-face hole group machining is completed at a time, and 0.08 mm average positioning deviation caused by the overturning procedure is eliminated; the integrated acoustic emission sensor monitors the abrasion state of the drill bit in real time, when the cutting force fluctuation is larger than 15%, the feeding amount is automatically compensated, and the rejection rate is reduced to 1.5% from 12%.

The invention discloses an active vibration suppression and deformation compensation device for high-precision thin-walled part machining, and relates to the technical field of machining equipment. The device comprises a base module, a clamping positioning module, a multi-source sensing monitoring module, a cooperative actuation vibration suppression module, a multi-point flexible compensation module, an intelligent control module and a machine tool cooperative interface module. The multi-source sensing monitoring module synchronously collects vibration, deformation, cutting force and temperature signals in the machining process. The intelligent control module processes signals and drives the cooperative actuation vibration suppression module (including a piezoelectric actuator group and a voice coil motor follow-up supporting unit) to perform broadband vibration suppression, and meanwhile drives the multi-point flexible compensation module (including a flexible supporting matrix and a path compensation interface) to perform local and overall deformation compensation. Synchronous monitoring and active cooperative control of vibration and deformation are achieved through closed-loop control, the machining precision, the surface quality and the machining efficiency of the thin-wall part are remarkably improved, compatibility is good, and the adaptive range is wide.

The invention relates to the technical field of machining equipment, and discloses a disc-shaped part milling machine tool and a machining method.The disc-shaped part milling machine tool comprises a machine tool base, a workbench arranged on the machine tool base, a Z-axis guide rail arranged on the workbench, a connecting arm ascending and descending along the Z-axis guide rail and a motor installed at the end of the connecting arm; the output end of the motor is fixedly connected with a driving column, and a milling cutter is mounted at the bottom end of the driving column; a hydraulic cylinder is arranged below the workbench; the device further comprises a lower self-adaptive clamping assembly and an upper follow-up vibration suppression assembly. The lower self-adaptive clamping assembly comprises a connecting disc, a center cylinder, a movable cylinder, a second spring and a supporting column. Through the synergistic effect of the lower self-adaptive clamping assembly and the upper follow-up vibration suppression assembly, the machining rigidity of the disc-shaped thin-wall part is remarkably improved, the lower supporting column provides rigid support for the originally suspended center of the part after being locked, and sinking deformation caused by axial cutting force is prevented.

The invention discloses a spindle cutting force prediction method and device based on a multi-channel deep learning model and electronic equipment, and the method comprises the steps: building multi-channel time sequence input through collecting three-direction vibration signals of a machine tool spindle and three-phase current signals of a spindle motor, and inputting the signals into a multi-scale convolutional neural network module to extract local features; modeling a time dependency relationship through a bidirectional long-short-term memory network, and introducing a multi-head attention mechanism to enhance the modeling capability for a key time slice; fused features are sent into three independent output sub-networks, and cutting force components in the X direction, the Y direction and the Z direction are predicted respectively. In order to improve the overall prediction precision and the dynamic response capability of the model, a weighted composite loss function combining a mean square error, a time sequence smooth item and a peak value weighted item is designed. Compared with a traditional prediction method based on a physical model or a single signal source, the method does not need additional force measurement hardware, and is high in adaptability, high in prediction precision and fast in response to cutting force sudden change.

The invention belongs to the technical field of numerical control machine tool machining, and particularly relates to a numerical control boring and milling tool cutting force intelligent monitoring method and system, and the method comprises the steps: obtaining a real-time main force, a real-time transverse force, a real-time longitudinal force sequence, a real-time main shaft rotating speed, a signal sampling frequency and a basic statistical threshold value in a machining task of numerical control boring and milling equipment; obtaining characteristic force; calculating a historical mean value at the current moment, and recording the historical mean value as a historical mean value; calculating a current historical deviation, and determining the width of a sliding window; calculating an instantaneous deviation; obtaining the change amplitude of the characteristic force at the current moment, the severity of the change trend deviating from the historical normal state, and the maximum value of the change amplitude and the severity to obtain a risk index; and comparing whether the risk index is abnormal or not according to the basic statistical threshold, and generating a processing process digital file. The technical problems of high false alarm rate and poor reliability caused by incapability of adapting to normal wear of the cutter in the prior art are solved.

The invention discloses a vibration suppression and surface quality control method for part cutting of a numerical control machining center, which relates to the technical field of numerical control machining and comprises the following steps: multi-modal sensor fusion monitoring: mounting multi-modal sensors on key parts such as a main shaft, a cutter and a workbench of the numerical control machining center, comprising an acceleration sensor, a strain sensor and an acoustic emission sensor and monitors a vibration signal, a cutting force signal and an acoustic emission signal in the machining process in real time; self-adaptive machining parameter optimization is carried out, and machining parameters are preset according to machining task requirements; dynamic adjustment and intelligent feedback control of machining parameters are realized by adopting a vibration prediction model based on deep learning and an adaptive optimization algorithm; according to the technology, the automation level of the machining process is improved, machining errors and surface quality defects caused by vibration are effectively reduced, and the surface roughness and size precision of the workpiece are remarkably 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 self-adaptive compensation system based on cutter wear of a numerical control machine tool, and particularly relates to the field of machining precision control of the numerical control machine tool, and the self-adaptive compensation system comprises a multi-dimensional data acquisition module, a progressive data processing module, a hierarchical analysis module, a multi-stage compensation output module, a data storage module and a self-diagnosis module. The multi-dimensional data acquisition module synchronously acquires cutting force, spindle dynamic state and vibration parameters; the progressive data processing module performs preprocessing, feature extraction and data fusion on the acquired parameters; the hierarchical analysis module is used for realizing wear grade evaluation through single-mode identification, multi-mode association verification and fuzzy comprehensive evaluation; the multi-stage compensation output module outputs a state snapshot and a graded compensation instruction and predicts the service life of the cutter; the data storage module adopts local and cloud dual backup to store full-process data; and the self-diagnosis module detects the state of each module and pushes a diagnosis report when the state is abnormal. According to the system, the wear evaluation precision and real-time performance are improved, the misjudgment rate is reduced, and the machining stability is guaranteed.

The invention relates to the technical field of numerical control machining and automatic control, in particular to a numerical control machining self-adaptive control system and method based on multi-source data, and the method comprises the steps that FPGA hardware synchronously collects main shaft current, servo current of each feed shaft, cutting vibration and grating ruler pulse, and time bases are aligned and packaged into a machining multi-dimensional state matrix; the multi-physical field error is decoupled through a three-layer cascade machine tool dynamics model, a tool nose contour deviation vector is solved, and servo lag and cutting force deformation factors are fused to construct a dynamic constraint boundary. When the deviation amplitude exceeds the limit, generating a speed feed-forward gain compensation instruction based on an inverse control model to perform instant suppression; when it is monitored that oscillation is eliminated and returns to a steady state, full-time-domain data stream interception logic is triggered, and a process optimization instruction is generated through backtracking. According to the method, the problems of nonlinear time-varying error decoupling and real-time compensation lag under multi-physics field coupling are solved, and the dynamic precision and process stability of numerical control machining under complex working conditions are remarkably improved.

A water-guided laser assembly and a precision machining assembly are fixed to the same side of a sliding plate of a vertical five-axis machine tool, an ultrasonic vibration platform is installed on a C-axis workbench of the vertical five-axis machine tool, and the water-guided laser assembly, the ultrasonic vibration platform and the precision machining assembly are controlled by an industrial personal computer to cooperate with each other; a positioning measuring head is adopted to realize relative compensation of the water jet and the cutter; the water jet cooling effect is utilized in water-guided laser processing to reduce the heat affected area and improve the processing quality; ultrasonic vibration auxiliary machining effectively reduces cutting force, inhibits the surface water return phenomenon, improves machining efficiency and prolongs the service life of a cutter; and precise machining (milling, grinding and drilling) is carried out, so that the machining size precision is accurately corrected, and the residual laser-induced damage layer is removed. Through multi-energy-field in-situ combined machining, collaborative optimization of technological parameters and coordinate compensation, the problems of insufficient precision, low efficiency, thermal damage and the like during machining of complex geometrical shapes and difficult-to-machine materials in a single machining technology are solved.

The invention provides a cutting force prediction method and device based on a multi-target frost ice algorithm optimization model, and relates to the technical field of mechanical cutting machining. The method comprises the following steps: acquiring sensor signal data including cutting force data and vibration signals, extracting target features which are highly related to the cutting force from the vibration signals, constructing target feature vectors, constructing a cutting force prediction model based on SVR, and determining an SVR hyper-parameter range through initialization; the target feature vector is used as an input sample, the cutting force data is used as an output target value, the SVR hyper-parameter range is used as a constraint condition, a multi-target frost ice algorithm and a multi-target optimization mechanism are combined to optimize the SVR hyper-parameter, finally, the SVR is trained based on the optimized hyper-parameter to obtain a prediction model, and the cutting force of the numerical control machine tool is predicted. Efficient and high-precision cutting force prediction can be achieved without a large number of data samples, and the model has good generalization and feature interpretability.

The invention relates to the technical field of data processing, in particular to an AI large model multivariate data fusion method and system based on multiple modalities, and the method comprises the steps: collecting multi-source data; performing classification abnormity judgment; abnormal type identification; calculating severity; switching fusion modes; and outputting an alarm. According to the method, parameters such as the spindle temperature, the rotating speed fluctuation rate, the vibration acceleration, the current load, the acoustic emission energy spectrum peak value, the cutting force variance and the cooling liquid metal particle concentration are acquired and fused step by step in multiple dimensions in the machining process of the numerical control machine tool, so that the running state of the machine tool is dynamically sensed from multiple angles; furthermore, the physical essence of tool wear and material peeling is revealed through the coupling relationship between the cutting force variance and the metal particle concentration, and meanwhile, the dynamic stability change of the machine tool structure is captured by combining the spindle rotating speed fluctuation ratio; the problem that state monitoring is not accurate in the numerical control machining process due to data isolation and fusion strategy staticization is effectively solved.

The application discloses a cutting force self-sensing turning tool system and method, which comprises a tool shank tail, a groove, a tool head, a blade and a blade groove; the tool shank tail is connected with the tool head through a tool shank, the tool shank is an elastic square beam, the tool head is partially provided with the blade groove, the blade is arranged in the blade groove, four surfaces of the tool shank close to the tool head are provided with four grooves which are completely identical in structure, the grooves are sensing parts of the cutting force self-sensing turning tool system, and a self-sensing component is fixedly integrated on the four surfaces of the grooves. The application has simple structure, only needs to arrange the grooves on the tool shank close to the tool head, integrates the self-sensing component on the surfaces of the grooves, has low manufacturing cost and high measurement precision.

The invention provides a design method for balancing cutting force between cutting edges of a symmetrical gradually-changing end mill, and relates to the technical field of shape characteristics of milling cutters, through the design of the gradually-changing cutting edges, a truncated edge is evolved into a sharp shape, and multifunctionality from rough machining to finish machining is achieved; the gradual change characteristic remarkably improves the chip breaking effect in the cutting process, tool adhesion is effectively prevented, meanwhile, cutting chip breaking is promoted by thinning cutting chips and reducing the bending rigidity of the cutting chips, in addition, due to the symmetrical design of the odd number of cutting edges and the even number of cutting edges, cutting force is balanced, cutting loads are reduced, abrasion is reduced, and the service life of the tool is prolonged. Further, the machining stability is enhanced, and high-quality surface quality and machining precision are ensured; through deep analysis of cutting force and distribution thereof, vibration is effectively reduced through the design, the stability of the cutter is further improved, the service life of the cutter is further prolonged, meanwhile, the fracture state of cuttings is optimized, and the machining efficiency is improved.

Some implementations include a method which comprises determining a drilling efficiency of a drill bit at a first depth in a wellbore formed in a subsurface formation based, at least in part, on a bit wear level of the drill bit, determining a cutting force mechanical specific energy of the drill bit at the first depth, and determining a rock strength of the subsurface formation at the first depth based on the drilling efficiency and the cutting force mechanical specific energy of the drill bit.

This invention discloses a robotic grinding auxiliary device with a follow-up lattice circulation mechanism for thin-walled parts, comprising: a grinding robot mechanism, a thin-walled part, and a follow-up lattice magnetorheological support mechanism. The follow-up lattice magnetorheological support mechanism is positioned directly in front of the grinding robot mechanism. A left positioner and a right positioner are located on either side of the follow-up lattice magnetorheological support mechanism. The left and right positioners are configured to clamp the thin-walled part from both sides, allowing the thin-walled part to be synchronously moved with the left and right positioners. The thin-walled part is positioned vertically above the follow-up lattice magnetorheological support mechanism, and the working end of the grinding robot mechanism is positioned above the thin-walled part. This invention effectively counteracts the cutting force applied by the grinding robot by providing active and adaptive support from below, greatly suppressing workpiece vibration and deformation, and ensuring machining accuracy and surface quality.

The utility model discloses a stud processing clamp with a stable clamping mechanism, which belongs to the technical field of stud processing, and comprises a support table, the top of the support table is fixedly connected with a clamping mechanism, and the bottom of the clamping mechanism is fixedly connected with an anti-deviation mechanism. The clamping mechanism can quickly and accurately position and clamp the cylindrical part of the stud, is particularly suitable for a round stud, greatly improves the clamping efficiency, reduces the time cost of manual adjustment and positioning, can effectively improve the overall machining efficiency for the condition of batch machining of studs, and reduces the labor intensity of workers. The anti-deviation mechanism can limit the stud from the bottom of the stud and effectively restrain possible deviation of the stud in the machining process, particularly when the stud is affected by lateral component force of cutting force, machine tool vibration and the like in the machining process, it can be guaranteed that the stud is always kept at the correct machining position, and the axial precision and straightness of stud machining are improved.

The invention discloses a light-weight cabin efficient self-adaption machining method based on cutting parameter learning, solves the cutting parameter self-adaption problem in light-weight cabin machining, and belongs to the technical field of spacecraft structural part manufacturing or numerical control self-adaption machining. The method aims at improving the machining quality and the machining efficiency, minimizing the cutting force and maximizing the material removal rate, a mathematical model of two targets and cutting parameters is established, an orthogonal process test is designed to analyze the response characteristics of the two targets to the cutting parameters, the influence of the cutting parameters to the cutting force in the actual cutting process is analyzed, and the machining precision is improved. Optimized operation data and a tool database are formed; and learning of adaptive parameters is realized by applying an ACM adaptive optimization technology, and adaptive processing is carried out.

The invention discloses a remote monitoring system for a numerical control bearing processing machine tool, belongs to the technical field of machine tools, and solves the problems that during finish turning of a GCr15 thin-wall ferrule, a main shaft pretightening force is attenuated to cause inherent frequency drift, servo parameters just fall on an excitation band, cutting force induces high-frequency flutter, fish scale vibration marks are generated, the service life and noise of a bearing exceed the standard, batch reworking is carried out, and machining efficiency is high. And the precision of a machine tool is permanently damaged. Comprising a multi-source information sensing module, a causal discovery and decision center, a dynamic stiffness field regulation and control module and a real-time simulation verification module, wherein a fiber bragg grating demodulator of the multi-source information sensing module is connected to a main shaft bearing seat in a machine tool through a sensing interface; a laser Doppler vibration meter of the multi-source information sensing module is in butt joint with a tool-workpiece machining area in a machine tool through an optical probe. Pre-tightening-servo-cutting coupling is sensed in real time, the magneto-rheological rigidity is actively adjusted, resonance is avoided, flutter is restrained and eliminated, high-frequency flutter is immune in advance, chatter marks and batch accidents are eradicated, and a cutter machine tool is protected.

The utility model relates to a ceramic tile cutting machine head for a track ceramic tile cutting machine, which comprises a ceramic tile cutting machine head, and the ceramic tile cutting machine head consists of a machine head sliding body, a cutter wheel lifting connecting seat and a cutter wheel; the upper portion of the machine head sliding body is a sliding rail guide sleeve, the lower portion of the machine head sliding body is in lifting fixed fit with the cutter wheel lifting connecting base, and the cutter wheel is installed on the cutter wheel lifting connecting base. The cutting wheel has the advantages that firstly, the defect of lateral stress during ceramic tile cutting is overcome, vertical stress of the center of the cutting wheel is realized, and the glaze surface of the ceramic tile can be well scratched to ensure effective cutting; secondly, the auxiliary wheel and the cutter wheel are synchronously adjusted, so that the ceramic tile cutting machine is suitable for guiding and cutting ceramic tiles with different thicknesses, and also plays a good auxiliary guiding role on the cutter wheel; and thirdly, due to the compression amount design of the auxiliary wheel, rigid impact with the cutter wheel is avoided, the cutting force of the cutter wheel is limited, the direct action of excessive force on the cutter wheel is dispersed, and the phenomenon that the cut ceramic tile is damaged due to excessive force during cutting is avoided.

The invention relates to the field of MPP pipe machining equipment, in particular to a fixed-length cutting device and method.The fixed-length cutting device comprises a base, a mounting plate is fixedly arranged at the upper end of the base, the fixed-length cutting device further comprises a rotating plate, one end of the rotating plate is fixedly connected with an annular frame through a sliding rod, the annular frame is rotatably mounted on the side wall of the mounting plate, and a cutting frame is slidably mounted on the sliding rod; a moving motor is fixedly arranged on the side wall of the rotating plate, the output end of the moving motor is connected with a screw, the screw penetrates through the cutting frame in a threaded mode, cutting assemblies are oppositely arranged at the upper end and the lower end of the side wall of the cutting frame, spinning assemblies are oppositely arranged at the left end and the right end of the side wall of the cutting frame, and a radial driving structure is arranged on the cutting frame. The pipe is rotationally cut through the cutting assembly, and meanwhile, the spinning assembly rotates around the pipe in the cutting process and always extrudes the two sides of the pipe, so that the pipe can be rectified and positioned in the cutting process, and deformation of the pipe due to cutting acting force is avoided.

The invention relates to the technical field of numerical control machine tool machining, and discloses a dynamic optimization method for metal joint machining parameters of a numerical control machine tool. The method comprises the following steps: acquiring initial characteristic data of a metal joint blank in a numerical control machine tool processing area in real time, wherein the initial characteristic data comprises surface topology distribution data, material hardness gradient data and thermal expansion coefficient data; according to the stage identification code of the current machining procedure, a dynamic constraint rule set bound with the stage identification code is called, and the dynamic constraint rule set comprises an axial cutting force threshold value, a radial deformation tolerance range and a temperature drift compensation coefficient; and finally, based on the initial feature data and the dynamic constraint rule set, an initial machining parameter vector corresponding to a multi-objective optimization function is generated, and the initial machining parameter vector comprises a main shaft rotating speed reference value, a feeding rate weighting factor and a cooling liquid flow proportionality coefficient.