23 results about "Cutting tool wear" patented technology

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 belongs to the technical field of combination of biomedical engineering and intelligent monitoring, and discloses a vibration cutting tool wear state monitoring method suitable for biological soft tissue, which comprises the following steps: S1, executing vibration cutting on the biological soft tissue, and obtaining a three-channel cutting force original signal; s2, inputting the three-channel cutting force original signal into a one-dimensional residual network, and expanding the three-channel cutting force original signal into a multi-feature channel; s3, a channel attention mechanism is applied, and first enhancement is achieved for some feature channels with wear sensitivity; s4, continuing to apply the time attention mechanism, and focusing for the key time interval; s5, regression is carried out to obtain a corresponding cutter flank abrasion loss prediction value; and S6, the real-time state of the cutter is judged. Compared with the prior art, the method has the advantages that the monitoring precision and robustness in a soft tissue cutting application scene can be remarkably improved, and the high quality of subsequent microscopic optical section tomography combined with cutting, the continuity of three-dimensional modeling and the data reliability are correspondingly and effectively guaranteed.

The invention relates to the technical field of automatic tunneling equipment, and provides a cutting tool wear online monitoring method and system based on visual AI in order to solve the problems of low efficiency, high cost, poor safety and the like caused by dependence on manual detection in the prior art. Wear identification and grading are carried out on the acquired image by using a deep learning model based on Faster R-CNN; and comprehensive judgment is carried out according to the abrasion grade proportion, and an alarm is automatically given when serious abrasion is achieved. According to the invention, on-line, automatic and accurate monitoring of the wear of the cutting tool is realized, the detection efficiency and reliability are obviously improved, the labor cost and the safety risk are reduced, and a key technical support is provided for intelligent mine construction.

The present application belongs to the field of furniture production and manufacturing, and provides a wood material cutting tool wear and machining precision online monitoring method, which comprises: sharpness determination and wear amount calculation and analysis of handle milling cutter and drill bit; preparing test materials and tools, determining numerical control milling machine and measuring instrument equipment; based on the tool edge retreat amount on the tool wedge angle diagonal, as the cutting tool edge wear evaluation value; tool wear test; multi-source signal synchronous acquisition and signal preprocessing and noise reduction; multi-domain feature extraction and fusion; optimization algorithm suitable for tool wear prediction model establishment: constructing LF-SMA-RELM tool state monitoring and prediction hybrid model for predicting tool edge retreat amount; online monitoring and intelligent early warning; the present application realizes full-process monitoring and prediction of cutting tool wear state and machining precision change.

The application discloses a metal cutting tool wear monitoring method and system, and relates to the technical field of wear monitoring.The method comprises the following steps: real-time monitoring of a metal cutting tool is performed to obtain a multi-source sensing sequence; a tool cutting monitoring matrix is constructed; the tool cutting monitoring matrix is input into a tool wear detection channel to obtain a tool wear first coefficient; differential detection is performed on the tool wear first coefficient according to a predetermined cutting scheme to output a wear differential signal; image perception correction is performed on the tool wear first coefficient to obtain a tool wear second coefficient; a historical tool wear coefficient set of the metal cutting tool is obtained, wear trend prediction is performed in combination with the tool wear second coefficient, a tool wear trend graph is constructed, and health management is performed on the metal cutting tool according to the tool wear trend graph.The technical problem of low tool wear monitoring precision in the prior art is solved, and the technical effect of improving tool wear monitoring precision is achieved.

Method and apparatus for centralized compliance, operation and setup of automated cutting tool machines. A system (100) and method for cutting at least one feature (118) in a workpiece (116) with at least one cutting tool (114) of a plurality of cutting tools (114) controlled by at least one cutting tool machine (104) of a plurality of cutting tool machines (104) is disclosed. The method receives process information from a cutting tool machine (104) describing cutting parameters, retrieves predictive cutting tool wear information relating predicted cutting tool wear values to the cutting parameters, retrieves cutting tool information including measured cutting tool wear information for the one cutting tool (114) of the plurality of cutting tools (114), calculates a predicted cutting tool wear value for the one cutting tool (114) of the plurality of cutting tools (114) from the measured cutting tool wear information, and cuts the at least one feature (118) according to the calculated predicted cutting tool wear value.

The present invention provides a method for studying the multi-scale wear behavior of diamond-coated cutting tools, which belongs to the technical field of diamond-coated cutting tool wear research. First, in the field of microscopic finite element simulation, a microscopic geometric model is established, and parameters such as material properties and grid size are set for the microscopic geometric model. According to the simulation results, the stress and strain distribution law of the cutting tool is analyzed to obtain the microscopic mechanical wear behavior within the crystals, between the crystals, and between the coating substrates of the polycrystalline coating at the microscale. At the same time, in the field of molecular dynamics, a nanoscopic geometric model is established, reaction potential functions are set, and parameters such as atomic layers and temperature controllers are set. According to the simulation results, the bond formation and breaking between atoms are analyzed to obtain the atomic-level chemical wear behavior of single-crystal diamond at the nanoscale. Finally, the microscopic mechanical wear behavior and the atomic-level chemical wear behavior of single-crystal diamond are combined to obtain the multi-scale wear behavior of the diamond-coated cutting tool.

The invention provides a metal slitting machine cutter group backlash automatic adjustment method, which comprises the following steps of: acquiring a metal coiled material surface image through optical scanning equipment, performing high-resolution imaging processing aiming at texture direction distribution, extracting surface texture direction distribution characteristics, and combining preset cutting direction setting to obtain initial included angle data; according to the preliminary included angle data, analyzing and judging the correlation between the texture strength difference and the relative angle deviation, and determining a preliminary backlash adjustment amplitude; aiming at the initial backlash adjustment amplitude, combining material anisotropy and material thickness influence, and integrating cutting stress influence and parallel and vertical scene resistance to obtain adjusted backlash dynamic compensation parameters; and if the edge defect associated area does not accord with the defect rate monitoring index, key points are extracted from stress distribution, cutting tool wear data are combined, backlash dynamic compensation parameters are adjusted, and an optimized backlash configuration value is obtained.

This utility model discloses a crystallization and unblocking device for wet zinc smelting electrolyte, which includes a lifting support, a motor, a connecting rod assembly, a cutting tool, and a guiding device. A pulley is provided at the bottom of the lifting support, and a motor is fixed at the top of the lifting support. A first screw is fixed to the output shaft of the motor, and the first screw is connected to the cutting tool through the connecting rod assembly. A guiding device is sleeved on the outer wall of the connecting rod assembly. The guiding device includes a guide ring, a positioning ring, and a pipe clamp. The inner ring of the guide ring is clearance-fitted with the outer wall of the connecting rod assembly through a bearing. A positioning ring matching the inner wall of the conveying pipe is fixed to the side wall of the guide ring. The outer diameter of the guide ring is consistent with the outer diameter of the conveying pipe, and a pipe clamp is provided on the outer wall of the guide ring. Advantages: With the cooperation of the cutting tool and the guiding device, during the movement of the cutting tool in the conveying pipe, the axis of the connecting rod assembly always remains parallel to the axis of the conveying pipe and is placed in the same vertical plane, reducing the problem of the cutting tool wearing down the inner wall of the conveying pipe.

The invention relates to the technical field of numerical simulation and ultra-precision machining, and particularly discloses a laser-assisted cutting tool wear simulation test method and device, and the method comprises the following steps: S1, building a tool material model through an LAMMPS language; s2, setting system boundary conditions, ensuring unification of physical quantity units and the boundary conditions, and ensuring simulation accuracy and comparability; s2, establishing an ionic group model right above the tool material model established in S1, setting an interaction potential function between atoms, and ensuring that a simulation result accords with an actual physical process; s3, layering the initial model set in the S1, setting an integral time step length and total relaxation time, and enabling the relaxation system model to reach a stable state through a conjugate gradient method and an isothermal isometric system; and S4, setting an incident angle and a speed of the ionic group, outputting an atomic parameter, a thermodynamic parameter and a visual image in the process of bombarding the tool material by the ionic group, and carrying out subsequent analysis and result verification.

The utility model discloses a kind of gas expansion axle connecting structures of cutting table, including bottom plate, protective strip and axle body;The surface of the axle body is slidably connected with top rod, the end of the top rod is fixedly connected with gas expansion strip, the number of the gas expansion strip is four, the surface of each gas expansion strip is provided with a plurality of clamping grooves, the inside of the protective strip is provided with clamping groove, the end of the clamping groove is equipped with limit plate, the clamping groove is connected with clamping strip snap connection.The utility model sets detachable protective strip on the surface of gas expansion strip, when cutting roll, it can avoid cutting tool wear, gas expansion axle both ends in the utility model can be supported, to avoid protective film to shake when rotating, improve cutting surface flatness, the utility model can first carry out the fixation of gas expansion axle, then gas expansion axle is connected with cutting table, to improve the concentricity of film roll and gas expansion axle.

The invention belongs to the technical field of combination of biomedical engineering and intelligent monitoring, and discloses a multi-modal signal fused biological tissue horizontal pushing cutting tool wear monitoring method. The method comprises the following steps: acquiring multi-modal data including three-way cutting force, three-way vibration, cutting sound and a temperature signal, and pairing the multi-modal data with an imaging result to form a'multi-modal signal-image 'data pair; generating a multi-channel feature tensor through time-frequency analysis, enhancing the multi-channel feature tensor through a channel attention mechanism, inputting the multi-channel feature tensor into a convolutional neural network model, and performing training by taking the abrasion loss of the rear cutter surface of the cutter as a label; and determining a wear threshold by combining the area of an image missing region in an imaging result, and realizing wear state prediction and early warning. The metal horizontal pushing cutter can be alternately used at different cutting positions, and after all the positions reach the threshold value, polishing maintenance is conducted so that the service life can be prolonged. According to the invention, high-precision identification and early warning of tool wear can be realized, and continuity and reliability of cutting imaging are guaranteed.

The utility model discloses a die design cutting device which comprises a machining table, a cutting knife groove is formed in the machining table, a motor is arranged above the machining table, a polygonal clamping block is fixedly connected to an output shaft of the motor, a knife disc is connected to the polygonal clamping block in a clamped mode, a clamping groove matched with the polygonal clamping block is formed in the knife disc, and the polygonal clamping block is fixedly connected with the machining table. The cutting fluid spraying head is located above the machining table and used for cooling and lubricating the cutter head, and the cutting fluid spraying head is communicated with a fluid inlet pipe. The utility model belongs to the technical field of mold manufacturing, and effectively solves the problems that when a mold design cutting device is used, a cutter is abraded to influence the cutting effect, and the efficiency of detaching and replacing the cutter is low.

The present invention relates to a method for dynamically predicting cutting tool wear based on multi-model fusion, which belongs to the field of lean manufacturing technology. It solves the technical problems of poor accuracy and poor practicality in current prediction of cutting tool wear. The method of the present invention includes selecting a method for collecting machine tool working condition data during the cutting process, conducting a tool wear processing test and collecting tool wear degradation data and corresponding cutting process working condition data, pre-processing the wear degradation data, establishing a wear increment prediction model, establishing a wear amount prediction model, constructing a hybrid prediction model and predicting tool wear. The method of the present invention uses a hybrid prediction model based on cutting process working condition data to derive degradation increments in multiple time periods, and predicts the degree of degradation based on the accumulation of degradation increments, thereby achieving dynamic prediction of tool wear for cutting tools in the future, and the model is closer to the actual situation. The implementation of the method of the present invention does not require the addition of external sensors or additional wiring, and is more economical, practical and feasible.

The utility model discloses a feeding frame structure of a cold header, belongs to the technical field of cold headers, and solves the problems that after a bar is cut for a long time, a cutter of a cutting unit is inevitably damaged, so that the bar is gradually difficult to be completely cut off at the beginning, or obvious hindrance is generated during cutting off, and the cutting efficiency of the bar is reduced. In this way, the problem that the quality of fastener products finally produced by the cold header is obviously reduced can be caused. Comprising a supporting arm, a connecting rod rotationally connected to the top of the supporting arm, and a fixing base arranged on a lathe bed. When the bar cutting-off device works, the rotating rod drives the sliding plate to slide, the guide column rotates and drives the guide connecting block to move in the moving through groove, then the top shaft and the tool apron move in a reciprocating mode, and bar cutting-off is achieved. When the cutter is worn, an operator holds the handle, presses the top shaft downwards, compresses the spring and rotates the handle to enable the limiting block to leave the connecting rod, the cutter is replaced and installed, the connecting rod drives the cutter to reset, the limiting block is limited again, the operator is prevented from stretching hands into the lathe bed, and safety is guaranteed.

The utility model belongs to the technical field of diamond micro-cutting knives, and particularly relates to a diamond micro-cutting knife supplementary tooth convenient to replace, which comprises an L-shaped support and a diamond micro-cutting knife, the diamond micro-cutting knife comprises a knife rest, the knife rest is detachably connected with a plurality of knife teeth through a connecting assembly, and the knife teeth are arranged on the L-shaped support. The L-shaped support is provided with a supporting assembly used for bearing the tool rest, and the top end of the L-shaped support is provided with a disassembling and assembling assembly used for disassembling and assembling the connecting assembly. The cutter teeth are detachably connected to the cutter rest through the connecting assembly, the cutter rest is arranged on the L-shaped support through the supporting assembly, and the connecting assembly is disassembled and assembled through the disassembling and assembling assembly, so that when the cutter teeth on the diamond micro-cutting cutter are abraded, the cutter teeth can be automatically replaced, tooth complementing is achieved, and the cutting efficiency is improved. And the whole diamond micro-cutting knife does not need to be replaced, so that the cost investment is reduced to a certain extent.

The application relates to a cutting tool wear prediction method based on an MDRSNet, which comprises the following steps: collecting a cutting force signal and a moment signal of a cutting tool in a milling process; inputting the cutting force signal and the moment signal into a preset MDRSNet tool wear prediction model to output a predicted wear amount of the cutting tool, wherein the MDRSNet tool wear prediction model is obtained by training based on a tool wear dataset, the tool wear dataset comprises cutting force signals and moment signals of X, Y and Z three axes of different cutting tools in the milling process and a wear amount of a tool flank surface of the cutting tool after each tool feed, and the MDRSNet tool wear prediction model is constructed by introducing a multi-branch structure into a deep residual shrinkage network (DRSN). The application enhances the expression ability and learning ability of the model by combining the residual shrinkage unit with the multi-branch structure, so that the model is light-weighted while the excellent prediction precision of the model is ensured.

The present application belongs to the technical field of mechanical cutting tool wear detection, and specifically discloses a milling tool wear detection method based on a double self-attention mechanism, comprising the following steps: sensor arrangement and experimental parameter setting, signal acquisition sample selection, model training, milling tool wear detection, and milling tool wear detection. The detection method effectively extracts features and reduces data dimensions of various sensor signals in the tool machining process, better utilizes the information extraction capability of deep learning technology to achieve higher precision tool wear prediction, and reduces the complexity of the model through more sophisticated model optimization design, so that the model requires less hardware adaptation, making it possible to truly realize tool wear detection, thereby effectively improving system reliability and reducing the risk of accidents, thus ensuring the safe operation of the machine tool. Not only does it overcome the limitations of traditional detection methods, but it also brings more efficient monitoring means to the milling industry.

The application relates to the technical fields of numerical simulation and ultra-precision machining, and particularly discloses a simulation test method and device for laser-assisted cutting tool wear, which comprises the following steps: S1: a tool material model is established through LAMMPS language; S2: system boundary conditions are set to ensure that physical quantity units and boundary conditions are unified, simulation accuracy and comparability are ensured; an ion group model is established directly above the tool material model established in S1, an interaction potential function between atoms is set, and it is ensured that simulation results are in line with actual physical processes; S3: the initial model set in S1 is layered, an integral time step and total relaxation time are set, a conjugate gradient method and an isothermal isochoric system relaxation system model are used, and the system model is made to reach a stable state; S4: the incident angle and speed of the ion group are set, atomic parameters, thermodynamic parameters and visualized images in the process that the ion group bombards the tool material are output, and subsequent analysis and result verification are carried out.

The utility model provides a kind of cutting and cooling integration device of flame-retardant particle, including extrusion main body, fixed plate, hinged plate, fixing frame, cutting assembly, cutting hole, screw hole, notch and locking bolt;When the phenomenon of cutting tool wear, collapse or shift occurs, only need to loosen locking bolt, then rotate hinged plate, so that cutting assembly is turned away from extrusion end, then cutting tool can be repaired or replaced;Therefore, the utility model can realize the repair or replacement of cutting tool without completely removing hinged plate and fixing frame, eliminate the problem that the distance between cutting tool and extrusion port is small, which makes it inconvenient to replace cutting tool, and if the entire fixing frame is removed, it is too troublesome and the overall weight of fixing frame and cutting assembly is relatively large, so it is also relatively laborious to disassemble.

The utility model discloses a numerical control lathe cutting tool wear adjusting device in the field of lathe cutting tool wear detection, which comprises a bottom plate, a mounting box and a support table, the top of the bottom plate is fixedly connected with the mounting box, the left part of the top of the mounting box is fixedly connected with the support table, and the top of the support table is fixedly connected with an industrial camera. According to the numerical control lathe cutting tool abrasion adjusting device, by means of the arrangement of the mounting block, a rotating rod and a rotating mechanism, a rotating disc is rotated, a threaded rod is driven to rotate, a limiting rod is used for limiting a moving block, and therefore the moving block moves; and through the movement of the rack, the gear is driven to rotate, so that the rotating rod drives the three-jaw chuck to rotate, the cutter is rotated, dynamic monitoring on the cutter is facilitated, the position of the cutter is convenient to adjust, and the detection precision is improved.

The present application relates to a kind of cutting tool wear monitoring methods, comprising: acquisition tool cutting process in multiple directions signal, the signal includes cutting force, vibration and sound signal;Acquisition tool wear after cutting is completed, signal and wear are spliced, obtain state matrix x and wear target value vector c;Using sliding window, data interception is carried out to state matrix x, obtain M data section;The time domain characteristics of the data section are calculated to obtain;Interpolation is carried out to target value vector c, and the wear of each data section corresponding is obtained;Using, training neural network and constructing tool wear monitoring model.The present application only needs to input current cutting data and the prior distribution parameter of wear, can carry out tool wear monitoring, and using codec structure improves the explainability of model.

The invention relates to the technical field of slitting machines, and provides a non-oriented silicon steel cutter and a slitting machine, the non-oriented silicon steel cutter comprises a cutter body, a silicon steel cutter ring, a pressing ring and a locking nut, one end of the cutter body is provided with an embedding groove, and the embedding groove is communicated to the peripheral side of the cutter body; the silicon steel cutter ring is inserted into the embedding groove, and the blade wall of the silicon steel cutter ring extends out of the embedding groove. According to the non-oriented silicon steel cutter, the silicon steel cutter ring serves as the cutting edge part of the non-oriented silicon steel cutter and is inserted and clamped into the inner side of the embedding groove, the silicon steel cutter ring is limited through the pressing ring, and therefore connection treatment between the silicon steel cutter ring and the cutter body is completed. When the cutting edge of the non-oriented silicon steel cutter is abraded, only the locking nut needs to be detached, the pressing ring needs to be taken down, the silicon steel cutter ring is taken out from the side, away from the embedding groove, of the silicon steel cutter ring, and the cutting edge part of the non-oriented silicon steel cutter can be rapidly replaced by replacing the silicon steel cutter ring, so that the non-oriented silicon steel cutter is convenient to use.