5961results about "Measurement/indication equipments" patented technology

A stop for use with an electric drill bit, the stop having at least one threaded sleeve for positioning the stop relative to a surface into which the drill bit will extend. The stop may have both an inner and an outer sleeve. The sleeves are mounted coaxially, one inside the other about the drill bit. One of the sleeves, preferably the inner sleeve, provides coarse adjustment of the position of the shoulder relative to the tip of the bit, while the other, preferably the outer sleeve, provides fine adjustment of the position of the shoulder relative to the top of the bit.

The present invention provides a tool wear state monitoring method and system based on multiple types of signals, and relates to the technical field of data processing. The method includes: obtaining data of a cutting force, an acoustic emission signal and a vibration signal, and extracting a plurality of statistical features from data of the cutting force and the acoustic emission signal; extracting a singularity feature from the vibration signal by combining a singularity analysis with a wavelet transform; building a tool wear state monitoring model based on a random forest, using an obtained feature to perform preliminary training, and outputting a wear prediction result; and based on the real-time data of the cutting force, the acoustic emission signal and the vibration signal, monitoring the wear state of the tool through the refined model.

The invention belongs to the field of machining, and relates to a machining process quality online monitoring and feedback adjusting system and method. The system comprises a multi-modal data acquisition module used for acquiring a mechanical vibration signal and a high-frequency micro-damage signal; the feature preprocessing and cross-modal fusion module is used for carrying out time domain, frequency domain and time-frequency domain feature extraction on the collected mechanical vibration signals and high-frequency micro-damage signals, carrying out edge, texture and shape feature extraction on workpiece machining surface image signals, and introducing a cross-modal attention mechanism to achieve weighted fusion of heterogeneous signals. And finally generating a fusion feature vector with high discrimination. The machine tool / cutter state and workpiece quality intelligent analysis module is used for constructing an intelligent analysis model for the equipment operation state and the workpiece machining quality; inputting the fusion feature vector into an intelligent analysis model to obtain a quality evaluation result; and the quality judgment and feedback adjustment module is used for adopting a dynamic threshold adjustment mechanism to realize adaptive comparison with a process standard according to a quality evaluation result.

The invention discloses a control method and equipment suitable for a rotary turn-over clamp of a numerical control milling center, and relates to the technical field of numerical control machining. The clamping force is optimized through the multi-source sensing and digital twinning technology, and workpiece deformation is prevented; thermal compensation and an error transfer chain model are integrated, the turnover angle is accurately corrected, and error accumulation is restrained; real-time comparison, traceability and self-adaptive adjustment in the machining process are achieved through digital twin pre-verification and multi-sensor closed-loop monitoring; the problems of out-of-tolerance of precision and batch consistency caused by unstable clamping, thermal deformation and error transmission in multi-surface milling of high-precision parts are solved, and the precision, reliability and process adaptability of complex part machining are remarkably improved.

The invention relates to a cutting path generation system based on visual positioning, cutting equipment and a cutting method. The system comprises a scanning camera control module, an image acquisition and recognition module, an image processing module, a cutting path planning module and a cutting control module. According to the system, by combining a Laplace algorithm and an LBP and GLCM texture extraction technology, the boundary recognition problem under the condition that a pattern and a background are in the same color or low contrast is solved; the path smoothness and the cutting quality are improved by adopting contour optimization and curvature compensation algorithms, the cutting sequence is optimized by combining weighting functions of the area, complexity and overlapping degree, and material deformation is reduced. And motor driving is dynamically adjusted through PID control, and stable control over the speed of the tool bit is achieved. The method has the advantages of being high in recognition precision, high in adaptability, intelligent in path planning and stable in cutting process, the automatic cutting efficiency and the finished product quality of complex patterns or same-color materials are remarkably improved, and the overall cutting precision fluctuation is controlled within + / -2%.

The invention discloses a visual precise plastic mold surface milling system and method, and the method comprises the steps: obtaining and analyzing the surface topography data of a milling region and a tool displacement track in real time through an optical sensor, and extracting wear-related micro-deformation features through multi-band filtering processing; generating a deviation vector matrix through three-dimensional mapping of the deviation vector matrix and a reference curved surface, and realizing dynamic calculation and path correction of the cutter offset; the high efficiency and stability of the compensation cutting process are ensured by combining the self-adaptive adjustment of the rotating speed and the feeding rate of the main shaft; meanwhile, the compensation effect is projected to a visual interface in real time to form a comparison layer, hardware acceleration is started to maintain the system response speed when the frame rate fluctuates, and finally the material removal volume is evaluated according to the deviation vector matrix to intelligently control the machining cycle termination time. Therefore, the problem of microtopography deviation caused by tool abrasion in the milling process of the complex curved surface mold is effectively solved, and the machining precision and efficiency as well as the robustness and the automation level of the system are remarkably improved.

The invention provides a titanium alloy thin-wall part high-precision milling method and system based on dynamic compensation, and the method comprises the following steps: constructing a multi-physics field coupling model based on the constitutive relation and milling process parameters of a titanium alloy material; according to the method, a multi-physical field coupling model represented by dynamic parameters is constructed, structural feature recognition and coupling weight dynamic allocation are combined, and the model is iteratively optimized through a detection result after processing, so that the problem that a traditional prediction model is disjointed from an actual working condition is solved; by building a real-time monitoring and feedback system and combining a dynamic compensation closed-loop mechanism, non-interruption linkage of monitoring-adjustment in the machining process is achieved, and the problem that the hysteresis of a traditional compensation method is remarkable is solved; the initial compensation amount is optimized through a multi-objective genetic algorithm, a self-adaptive processing path strategy is adopted, dynamic parameter adjustment of structure adaptation is combined, a traditional single compensation strategy is replaced, and the problem of dynamic rigidity change in the complex curved surface and material removal process can be flexibly solved.

The invention relates to the technical field of machine tool fault diagnosis and maintenance, and discloses a machine tool fault predictive maintenance method based on vibration analysis, which comprises the following steps: collecting vibration, temperature and acoustic emission signals and machine tool working condition parameters through a multi-modal sensor, extracting multi-domain features after preprocessing the vibration signals, and combining the working condition parameters through feature fusion and dimension reduction to obtain a machine tool fault predictive maintenance result. And establishing a fault classification model by using transfer learning, and performing hierarchical optimization. Model parameters are updated in real time based on an online learning mechanism, a fault early warning agent model is constructed to predict fault probability distribution, a dynamic threshold strategy is designed to avoid false report and missing report, and finally, related models and strategies are integrated to edge computing equipment. According to the method, multi-source data are integrated, multiple advanced algorithms are applied, machine tool faults can be accurately predicted, real-time monitoring and maintenance decision output are achieved, the machine tool operation reliability is improved, and the maintenance cost is reduced.

The invention relates to the technical field of planet carrier boring machining, in particular to a planet carrier boring machining device and a boring machining method.The method comprises the steps that deviation characteristic values are determined on the basis of the difference between each machining parameter and a preset rated value and abnormal distribution of each machining parameter at all moments before all deviation to-be-corrected moments; on the basis of the correlation between each machining parameter at all moments before each deviation to-be-corrected moment and the cutting temperature and the vibration frequency, a characteristic coefficient is determined, and the deviation value of each machining parameter is determined by combining the difference between each machining parameter at each deviation to-be-corrected moment and a preset rated value and the deviation characteristic value; and each machining parameter at each deviation to-be-corrected moment in the boring machining process is regulated and controlled. The machining deviation is actively compensated by fusing the cutting temperature and the vibration frequency in real time, and the machining precision of planet carrier boring is improved.

The invention relates to the technical field of machining, and discloses a lathe tool wear self-inspection alarm system which comprises a multi-source sensing module, an intelligent analysis module, a dynamic response module, an interactive display module and a self-adaptive energy supply module. The multi-source sensing module synchronously acquires the surface abrasion loss, the vibration spectrum and the acoustic emission signal of the cutter through an optical sensor, a capacitive sensor and an MEMS triaxial accelerometer, and outputs the surface abrasion loss, the vibration spectrum and the acoustic emission signal to the intelligent analysis module; and the intelligent analysis module performs fusion analysis on the multi-source data by adopting a mixed feature extraction and double-model decision mechanism. High-precision monitoring and dynamic evaluation of lathe tool wear are realized through optical, vibration and acoustic emission sensors of the multi-source sensing module in combination with mixed feature extraction and a double-model decision mechanism of the intelligent analysis module. By means of the mode of combining multi-dimensional monitoring and intelligent analysis, machining defects and equipment failure risks caused by tool abrasion can be reduced.

The invention belongs to the technical field of production monitoring systems, and discloses a numerical control machine tool dynamic fault diagnosis method and system. The method comprises the following steps: generating a global time reference signal through a main shaft encoder and a clock synchronization protocol; the method comprises the following steps: collecting vibration data of a main shaft bearing in each unit time, current data of an electric cabinet and process parameters, and generating a preprocessed data sequence through transmission delay compensation and multi-rate frequency raising processing; inputting the vibration data and the current data into a preset mechanical-electrical transfer function model, and calculating a time delay parameter; performing phase alignment on the preprocessed data sequence based on the time delay parameter to generate an aligned data sequence; inputting the aligned data sequence into a time sequence neural network, and outputting a fusion feature vector; calculating a cross correlation coefficient of the fusion feature vector, and generating a fault diagnosis result based on a preset cross correlation threshold value; the problem of failure of fault feature extraction caused by data asynchronization in the prior art is solved.

The invention discloses an automatic machine tool cooling liquid supplementing device based on a liquid level sensor, which is applied to the technical field of automatic machine tool cooling liquid supplementing and comprises a liquid supplementing mechanism and a liquid level detection mechanism, the liquid level detection mechanism is arranged on one side of the liquid supplementing mechanism, and the liquid level detection mechanism is in pipeline connection with the liquid supplementing mechanism; the liquid supplementing mechanism comprises a machine body, a control cabinet and a four-way pipe, and the control cabinet is in signal connection with a liquid supplementing system; the liquid level detection mechanism comprises a circulating box, a fifth liquid supplementing pump, a liquid level sensor, a buffering assembly and a cleaning assembly, the buffering assembly and the cleaning assembly are both located in the fine filtrate area, and a concentration sensor is fixedly connected to the interior of the circulating box; the buffer assembly comprises two sets of limiting blocks and a plurality of fan wheels, the cleaning assembly comprises an air cylinder, a cleaning rod and a motor, the bottom of the cleaning rod is arranged to be in a semicircular shape matched with the radius of a floating ball of the liquid level sensor, and automatic and accurate control over cooling liquid can be achieved.

The invention relates to the technical field of numerical control lathe machining, in particular to a numerical control lathe cutting parameter optimization method and system. The method comprises the following steps: receiving a processing task for batch workpieces, dividing processing batches in the processing task, and determining a detection processing step; in the detection machining step, cutting process signals and machine tool machining parameters of a machine tool are collected and detected in real time; based on the cutting process signals and the corresponding machine tool machining parameters, an expected stable signal interval is dynamically established, and transient impact events are recognized and quantified; performing statistics and normalization processing on the transient impact events to generate risk assessment information; sharing risk assessment information with other machine tools in a machining batch range; and according to the risk assessment information, cutting parameters of the subsequent machining steps are adjusted in advance, and after the pre-adjustment is completed, machining of the batch of workpieces is executed. The problem that production efficiency and stability are reduced due to the fact that information of an existing numerical control lathe is not shared in a multi-machine-tool cooperative machining scene is solved.

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 machine vision-based numerical control machine tool cutter wear identification method and system, and relates to the technical field of machine vision. A numerical control machine tool cutter two-dimensional image sequence is collected, high-precision point clouds are obtained through three-dimensional reconstruction and calibration, and high-precision cutter reference three-dimensional point clouds are obtained; constructing a functional region division rule, segmenting the high-precision tool reference three-dimensional point cloud to obtain a tool functional region, and generating tool region structured reference data through geometric shape quantitative description algorithm analysis; collecting regional structured data of the cutter in different machining periods, and obtaining a shape evolution track of the cutter through space-time registration; constructing a tool wear recognition model based on the time sequence convolutional network, inputting a tool morphology evolution trajectory, and outputting a tool wear type; and collecting tool historical case data to construct a wear mechanism knowledge base, performing matching mapping on a tool wear type and the knowledge base, and generating a tool wear identification result. And based on the wear identification result, realizing the identification of the wear of the numerical control machine tool cutter.

The invention discloses a horizontal five-axis turning and milling composite center with a self-adaptive matching system. The horizontal five-axis turning and milling composite center comprises a tool turret, a boring tool mechanism, a tool changing area and a control system. A radio frequency identification reading device is arranged in a tool changing area of the tool turret and the boring tool mechanism, and an RFID chip tag is attached to the outer surface of each tool and used for storing tool serial numbers, specifications and length compensation parameters. And the control system realizes self-adaptive matching and sequential error correction of the cutter and the working procedure through radio frequency identification. The tool changing area is provided with a visual monitoring assembly which comprises a plurality of sets of industrial cameras, an adjustable light source and a structured light stripe illumination module and is used for detecting the clamping posture, the abrasion state and the type of a tool. The system has self-learning and digital twinning simulation functions, and can simulate the motion trail of the cutter and predict the interference risk before the cutter is changed. According to the method, integrated control over automatic tool recognition, posture correction, abrasion detection and path prediction is achieved, and the tool changing precision, the operation stability and the automation level of the horizontal five-axis turning and milling composite center are remarkably improved.

The invention relates to the technical field of machining automation control, and discloses an intelligent tool changing decision-making method based on tool wear perception, which comprises the following steps: acquiring real-time state data of a tool through vibration, acoustic emission, force and temperature sensors, and fusing features of a multi-modal graph neural network to obtain tool wear feature data. And inputting the parameters into a Bayesian decision network, optimizing a tool changing strategy by using a dynamic probabilistic reasoning structure, and generating decision optimization parameters. And a multi-target tool changing optimization model with the highest machining efficiency and the longest service life of the tool as targets is constructed, and an optimal tool changing strategy is determined by adopting an improved particle swarm algorithm. Based on this, a hierarchical decision control model is established and comprises a global evaluation layer, a dynamic adjustment layer and an execution control layer, and intelligent control of tool changing action is realized. In addition, a self-healing control module is embedded in the system to deal with abnormal wear of the cutter. The machining efficiency is improved, the service life of the cutter is prolonged, the machining quality is guaranteed, and intelligent development of machining is promoted.

The invention is suitable for the technical field of copper pipe cutting, and provides a copper pipe cutting device and method for refrigeration air conditioner machining, the copper pipe cutting device for refrigeration air conditioner machining comprises a workbench, a limiting seat is arranged on the workbench, and clamping mechanisms used for fixing a copper pipe are arranged on the two sides of the limiting seat; the workbench is fixedly connected with a supporting frame, the supporting frame is fixedly connected with an electric telescopic rod, the telescopic end of the electric telescopic rod is fixedly connected with a fixing frame, the fixing frame is connected with a limiting mechanism, and the limiting mechanism can vertically limit a copper pipe; buffering assemblies are fixedly connected to the two ends of the electric telescopic rod correspondingly, and a cutting assembly is horizontally limited between the two buffering assemblies. According to the method, the regulation and control analysis model fuses vibratology, thermodynamics and the material processing principle, real-time quantitative prediction of'cutting precision 'which cannot be directly observed is achieved through measurable parameters, and a theoretical core is provided for intelligent manufacturing.

The invention provides a communication and interaction method of a digital twinning system in a compressor blisk machining process, and relates to the technical field of digital twinning and aeronautical manufacturing, and the method comprises the steps: collecting vibration, temperature and acoustic emission data in the compressor blisk machining process in real time, analyzing machine tool machining data, carrying out the alignment and noise reduction of the collected data, and obtaining a digital twinning result; then time-frequency domain mixed feature extraction is carried out, and time-frequency domain mixed feature data are optimized and uploaded in a graded mode; a deterministic transmission network is constructed, data transmission priorities of 5G communication and LoRa dual channels are dynamically adjusted according to a network load, and intelligent switching between 5G communication and a LoRa protocol is realized based on a switching decision model; analyzing normal processing data of the whole stage of the processing process, and establishing a processing data thread; and predicting the abnormal processing risk in the processing process, and updating the model parameters. According to the method, the communication and interaction efficiency of the digital twin system in the machining process of the compressor blisk in the aero-engine can be improved.

The invention provides a cutting tool wear state identification and residual life prediction method based on a digital twinning technology, and relates to the technical field of intelligent tool health. The method comprises the following steps: constructing a cutting process physical model consistent with a machine tool-tool-workpiece system and process parameters, generating a virtual monitoring signal and a virtual degradation track, and comparing the virtual monitoring signal and the virtual degradation track with actually measured data of a multi-source sensor to form virtual-real synchronous monitoring residual features; constructing a likelihood function based on the residual error, and jointly calibrating cutter individual and material parameters through Bayesian updating to obtain an updated digital twinborn model accurately matched with the current working condition; on this basis, a corrected state discrimination model is constructed, stable recognition of the tool wear state is achieved, a random degradation process model is adopted for quantitative prediction of wear evolution and residual life, and the accuracy and robustness of tool health monitoring and life prediction are effectively improved.

The invention discloses a horizontal eight-axis five-linkage turning and milling composite machine tool based on a hybrid robot, and belongs to the technical field of high-end equipment manufacturing. According to the technical scheme, the horizontal eight-axis five-linkage turning and milling composite machine tool based on the hybrid robot comprises a machine tool body, and a tool turret mechanism, a workpiece fixing mechanism and a hybrid robot mechanism are sequentially arranged on the side of the machine tool body from bottom to top; the tool turret mechanism comprises a left lower tool turret assembly and a right lower tool turret assembly which are symmetrically arranged on the two sides of the machine tool body. Eight-axis five-linkage machining is achieved through cooperative movement of the symmetrical tool turret assembly and the lifting control mechanism, the self-adaptive supporting assembly and the hybrid robot mechanism are combined, and the problems that a traditional machine tool is insufficient in linkage capacity, poor in workpiece supporting stability and low in automatic cooperative efficiency are solved; the multi-axis linkage machining center has the advantages of being high in machining efficiency, high in supporting stability, excellent in multi-axis linkage precision and outstanding in automatic cooperation capacity.

The invention relates to the technical field of gang drills, in particular to a numerical control gang drill device which comprises a machine tool body, a telescopic assembly is arranged in the machine tool body, the output end of the telescopic assembly faces downwards and is connected with an extrusion block, and a storage plate is arranged at the position, below the telescopic assembly, in the machine tool body. One side of the machine tool body is connected with a gang drill plate through an air cylinder, and the side, facing the machine tool body, of the gang drill plate is evenly connected with a plurality of through drill seats. According to the device, a second clamping block and a first laser distance measuring sensor are arranged, the first laser distance measuring sensor can detect the distance value between a drill bit and an extension block at different positions of the drill bit, and the distance value between the drill bit and the extension block can be detected in the mode that the drill bit rotates; the detected distance value is uploaded to a background control system to be compared with a standard data value, and if the detected data value exceeds a standard data value interval, it is indicated that the drill bit deforms.

The invention relates to the technical field of image processing, in particular to an intelligent detection method and system for support turning. The method comprises the steps that sensor signals of the support in the turning machining process are obtained in real time; constructing a sensor topological graph; extracting real-time time sequence process features reflecting the dynamic response of the tool-workpiece-machine tool system in the sensor topological graph; inputting the real-time time sequence process features into a trained multi-task prediction model, and outputting prediction deviation values of a plurality of geometric dimensions of the support and a prediction surface defect mask pattern; and if all the predicted deviation values are within the corresponding tolerance threshold values and the ratio of the defect area of the predicted surface defect mask pattern to the total area of the bracket is smaller than a set area threshold value, judging that the expected quality state of the bracket is qualified. According to the scheme, the expected quality state of the support product can be comprehensively judged in real time.

A cutting tool for turning includes a cutting insert having a cutting edge, a holder for holding the cutting insert, a wireless communication unit for transmitting information based on a measurement result of a sensor attached to the cutting tool, an acceleration sensor installed in the holder, and a control unit for performing first control for controlling activation of the wireless communication unit based on the measurement result of the acceleration sensor.

The invention discloses an intelligent sidesway safety protection method and device for a magnetic drill press based on multi-parameter monitoring, and relates to the technical field of magnetic drill press control. The intelligent sidesway safety protection method and device for the magnetic drill press based on multi-parameter monitoring comprise the steps that S1, operation sensing data of the magnetic drill press are collected, and preprocessing of the operation sensing data of the magnetic drill press is completed; s2, executing magnetic drill press operation state combined judgment, completing magnetic drill press operation disturbance evaluation, judging whether a structure disturbance behavior exists or not, and generating an operation disturbance data set; s3, constructing a lateral displacement analysis basic data set, executing structure displacement trend identification, judging whether a structure lateral displacement behavior exists or not, and completing shutdown control and displacement state marking; and S4, drill bit abrasion tendency evaluation is completed, the execution unit is controlled to switch the operation state of the magnetic drill press in a linkage mode according to the evaluation result, and closed-loop intelligent maintenance control is achieved. The problems of structure lateral displacement and follow-up operation risks caused by the fact that tiny angle deviation is difficult to recognize in time after equipment stalling are solved.

The invention discloses a milling process vibration state monitoring method and system for a machine tool milling cutter, and belongs to the technical field of intelligent monitoring. The method comprises the following steps: acquiring a vibration signal of a milling cutter under a reference processing condition, and establishing a reference template containing normal vibration characteristics; dynamically adjusting an alarm threshold value, and starting fault diagnosis analysis; performing envelope spectrum analysis on the vibration signal triggering diagnosis; preliminarily judging the affiliation fault type of the abnormal vibration through a preset fault classification model; and carrying out association verification by combining the attribution fault type and the spatial position information when the abnormality occurs, confirming the root cause of the fault, and outputting a targeted classification alarm instruction. According to the invention, the cutter handle single sensor is linked with phase slicing and dynamic threshold and coordinate verification, so that the faults of the cutter, the cutter rest and the workpiece are accurately distinguished and directionally alarmed, and the problems that a fault source cannot be distinguished by a single channel and the false alarm rate is high in the prior art are solved.

The invention discloses a modular visual guidance robot feeding and discharging device, and relates to the technical field of robot-assisted feeding and discharging equipment, and the modular visual guidance robot feeding and discharging device comprises a visual module which is installed on a production line and is used for identifying the position of a workpiece and outputting coordinate information; the manipulator module is mounted on the production line, and a clamp connecting mechanism and an end effector are arranged at the tail end of the manipulator module; the clamp module is installed at the tail end of the mechanical arm module through a clamp connecting mechanism, and the clamp module is electrically connected with the tail end executor and used for grabbing a workpiece; and the control system module is electrically connected with the vision module, the manipulator module and the end effector and is used for controlling the manipulator module to act according to the coordinate information output by the vision module and controlling the clamp module to act through the end effector. The production requirements of diversified products on different production lines can be met, and the universality and adaptability of equipment are improved.

The invention discloses a rapid positioning and punching device and method for a precision die, and relates to the technical field of precision die and die casting machining equipment. The device comprises a workbench and an air floatation-vibration suppression and vacuum pre-fixing integrated platform at the bottom of a positioning groove of the workbench, and the air floatation-vibration suppression and vacuum pre-fixing integrated platform can be switched between a vacuum adsorption pre-fixing mode and an air floatation vibration suppression mode. Y-axis modules are arranged on the two sides of the workbench and drive the X-axis module and the Z-axis lifting mechanism to move. The intelligent drilling unit adopts an inner cooling type drill bit with a built-in phase change microcapsule, and the position error is compensated in real time through a laser interferometer. The method integrates the devices and sequentially comprises the steps of workpiece vacuum pre-fixing, air floatation vibration suppression, self-adaptive balanced clamping, vision and laser composite positioning, drilling and phase change self-cooling, laser dynamic error compensation and the like. The problems of positioning drifting, short service life of a drill bit and clamping unbalance during drilling of high-hardness die steel and large die castings (such as electric control boxes of new energy automobiles) are effectively solved.

The invention belongs to the technical field of inner star wheel clamps, and particularly relates to an inner star wheel quick-change high-precision clamp which comprises a clamping shell, a clamping component is arranged in the clamping shell, the clamping component comprises a quick-change clamping block, and the quick-change clamping block clamps an inner star wheel. According to the quick-change high-precision clamp for the inner star wheel, the clamping component and the driving component are arranged, a chute is in inclined sliding fit with an inclined rod, and a pushing taper sleeve drives the conical surface of a roller on an inserting rod, so that the single axial movement of a driving hydraulic cylinder is creatively changed into the single axial movement of the driving hydraulic cylinder; according to the three-jaw chuck, the three clamping jaws are synchronously decomposed and converted into the composite motion of radial shrinkage and axial compression of the three clamping jaws, and the structure enables the clamp to actively and reliably restrain the axial degree of freedom of a workpiece while clamping the outer circle of the workpiece, so that the defect that the axial constraint of a traditional three-jaw chuck is weak is overcome. The method has the following direct effects: firstly, a machine tool is allowed to process by adopting larger cutting depth and feed rate, so that the processing efficiency is obviously improved, and the service life of a cutter is prolonged;

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.