1216 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 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.

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 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 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 relates to the technical field of unmanned helicopters, in particular to a carbon fiber reinforced rotor wing connecting piece numerical control lathe vibration suppression clamp which comprises a claw disc, a vibration suppression mechanism and an inner supporting mechanism. The clamping blocks make contact with the ends of the carbon fiber rotor wing connecting pieces. The vibration suppression mechanism comprises a clamping adjusting assembly penetrating through the top of the damping rod, the clamping adjusting assembly is in pressure communication with the pneumatic rail, the damping rod provides buffering and vibration suppression, and the inner supporting mechanism and the claw disc are coaxially fixed. The clamping pressure is adjusted in real time through the linkage design of the pneumatic track and the vibration suppression mechanism, the cutting force difference during asymmetric machining is effectively balanced and high-frequency vibration of a carbon fiber material is suppressed in combination with a multi-point supporting structure of the inner supporting mechanism, so that the dimensional precision and the surface quality of a workpiece are guaranteed, and the machining efficiency is improved. The device has the advantages of dynamically adjusting clamping pressure, balancing cutting stress, restraining high-frequency vibration and improving machining precision.

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 utility model relates to the technical field of cold-bending strip steel production, and discloses a cold-bending strip steel edge processing device which comprises a rack, a winding roller is rotationally installed on the inner surface of the rack, a cold-bending strip steel body is arranged on the outer surface of the winding roller, and a winding frame is arranged at the other end, away from the rack, of the cold-bending strip steel body. Deburring mounting frames are arranged on the two sides of the cold-bending strip steel body. According to the processing device for the edge of the cold-bent strip steel, the cutter can be rapidly pushed to cut a cold-bent strip steel body through the design of the air cylinder, and the cutting force is controlled by adjusting air pressure so as to adapt to strip steel of different thicknesses and materials. The structural strength of the deburring treatment assembly is enhanced through attachment of a reinforcing base, a first fixing plate and a fixing rod, a longitudinal moving motor drives a second two-way lead screw to rotate, the longitudinal position of a burr treatment motor is accurately controlled, a grinding roller can be longitudinally and flexibly adjusted, it is ensured that strip steel with different thicknesses and burr distribution is deburred, and the deburring efficiency is improved. And the adaptability of the equipment to different products and the use diversity of the device 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 relates to the technical field of porcelain production, and discloses a fettling device for ceramic production, which comprises a base, a rotating table is rotatably arranged on the base, and the rotating table is used for placing a green body; a fettling mechanism, a first transmission mechanism and a driving mechanism are further arranged on the base, the fettling mechanism comprises a first sliding seat and a turning tool, and the turning tool is elastically connected with the first sliding seat through a spring damper; the driving mechanism comprises a rotating seat rotationally arranged in the base, and a rotating disc is arranged on the rotating seat and connected with the rotating table. According to the fettling device for ceramic production, a mechanical device is adopted for automatic fettling, the production efficiency is improved, the position and angle of a turning tool can be freely adjusted to replace manual holding of the turning tool, the stability of rotary cutting fettling is improved, the position of the turning tool can be automatically adjusted along with the thickness change of a contacted green body, and the rotating speed of the rotating table can also be automatically adjusted; the method of rough trimming and then fine trimming during manual fettling is simulated, and the situation that a blank is damaged due to the fact that initial rotary cutting force is too large is avoided.

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 a numerical control machine tool spindle predictive maintenance system, and belongs to the technical field of mechanical equipment health management and intelligent manufacturing. The main shaft driving motor real-time power processing module is used for processing the main shaft driving motor real-time power to estimate and obtain a real-time cutting torque sequence and a real-time main shaft total power sequence, and processing the multiple paths of temperature signals to obtain multiple paths of real-time temperature sequences, and the basic degradation state evaluation module is used for calculating mechanical accumulated damage quantitative indexes based on the real-time cutting torque sequence. And calculating a cumulative thermally induced damage index based on the multi-path real-time temperature sequence, and fusing the mechanical cumulative damage quantitative index and the cumulative thermally induced damage index to generate a basic degradation index. And the robustness and operability of a prediction result in a real industrial environment are remarkably improved.

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 invention provides a deep hole drilling numerical control correction method and system based on force sense feedback, and relates to the technical field of machining numerical control, and the method comprises the steps: monitoring the vibration amplitude and frequency spectrum features of the surface of a drill rod, comparing the vibration amplitude and frequency spectrum features with a cutting vibration feature library, and extracting a chip attachment signal strength index; fusing the index with a resultant force time domain signal to generate a data pair, and separating an additional load time domain sequence from a pure cutting force time domain sequence by using an interference stripping algorithm; if the additional load time domain sequence exceeds the threshold value, a cleaning signal is issued, and cuttings are discharged; comparing the pure cutting force time domain sequence with a corresponding reference, calculating a force deviation, and generating a compensation instruction according to a feed compensation strategy; the instruction is executed, machining continues, the hole diameter and guiding deviation are fed back, the correction effect is verified, and parameters are adjusted till the machining precision is met, so that chip accumulation can be accurately recognized, cleaning is triggered, the real cutting force and the additional interference load are effectively separated, the feeding parameters are dynamically compensated, and the deep hole machining precision and stability are remarkably improved.

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.