9206results 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 invention provides a numerical control machine tool wear automatic detection and compensation method based on artificial intelligence, and the method comprises the steps: collecting the cutting force data of a high-curvature region in real time through multi-sensor fusion, and obtaining the cutting force fluctuation characteristics; cutting temperature data of the high-curvature area are monitored and obtained, the cutting temperature change rate is extracted, whether the temperature exceeds a preset threshold value or not is judged, and if yes, an alarm mechanism is triggered, and cutting parameters are adjusted; predicting the tool wear rate in combination with the co-evolution relationship between wear and temperature, the online monitoring data and the processed time, and generating a wear prediction curve in a preset time period; and performing trend analysis and feature extraction on the wear prediction curve to obtain wear parameter changes of the cutter in a preset time, and if the prediction curve shows that the wear parameter changes at a certain time point in the future exceed a preset critical value, adjusting the cutting parameters and generating a target cutting parameter combination.

The invention provides an intelligent fault diagnosis method for a numerical control machine tool, which is applied to a control system of the numerical control machine tool. The method comprises the steps of collecting multi-source sensor data in the operation process of the numerical control machine tool, wherein the multi-source sensor data comprises at least two of a vibration signal, a temperature signal, a current signal and a sound signal; performing preprocessing and feature extraction on the multi-source sensor data to obtain preprocessed data; based on the preprocessed data, constructing and training a machine tool dynamic model to obtain a target machine tool dynamic model; when abnormal operation of the numerical control machine tool is detected, fault state estimation is carried out based on the target machine tool dynamic model and a model prediction control method, and a fault estimation result is obtained; and based on the fault estimation result, constructing a fault evolution path by adopting a Monte Carlo tree search algorithm, and outputting a fault diagnosis result. The accuracy and efficiency of fault diagnosis of the numerical control machine tool can be improved.

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 discloses a control method and system of a vertical multi-axis numerical control mortise broaching machine and a storage medium, and relates to the technical field of broaching machines. The control method comprises the following steps that S1, a three-dimensional model of a workpiece is imported, and a mortise machining area is recognized based on geometric features of the model; s2, according to the material attribute, the tool type and the machining precision requirement, the feeding speed, the cutting depth and the main shaft rotating speed parameter of a machining path are set; s3, generating a multi-axis linkage tool path plan, and decomposing a tool path into a control instruction of multi-axis cooperative motion through a numerical control system; s4, the deviation between the actual position and the theoretical position of each shaft is monitored in real time in the machining process, and the output torque and the rotating speed of the servo motor are dynamically adjusted; s5, collecting cutting force data in real time; s6, the distance between the cutter and the surface of the workpiece is measured in real time through a laser displacement sensor, and a displacement feedback signal is generated; and if the cutting force data and the displacement feedback signal exceed preset threshold values, a dynamic compensation mechanism is triggered. The broaching machine control method has the effect of improving broaching machine control accuracy.

The invention relates to the technical field of motion control, in particular to a CNC machine tool motion control system which comprises a cutting force feedback monitoring module, a multi-axis load coordination module, a spindle vibration suppression module and a dynamic path optimization module. According to the method, the cutting force fluctuation of each axle can be accurately mastered by monitoring the axle cutting force in real time and analyzing the load change, the load and the feeding speed of the axle are adjusted according to real-time feedback, machining errors caused by uneven loads are reduced, and the vibration amplitude and frequency can be calculated and the rotating speed of the main shaft can be adjusted by monitoring the vibration data of the main shaft in real time. The resonance phenomenon is effectively restrained, the machining stability is improved, meanwhile, dynamic path optimization is conducted, the dynamic response problem caused by improper path setting is avoided by evaluating the dynamic response of a machine tool and adjusting the machining path, the cutting direction and the feeding speed in real time, the machining precision and stability are remarkably improved, and the machining efficiency is improved. And the complex machining environment adaptability of the machine tool is improved.

The invention discloses a tool wear loss prediction method based on physical information self-supervised learning under the condition of few marks, and belongs to the technical field of numerical control machining center tool wear state prediction. Comprising the steps of collecting monitoring signals such as cutting force, vibration and acoustic emission in the machining process; carrying out preprocessing operation of interception and Z score standardization on each sample; a mixed residual convolutional neural network tool wear monitoring model is designed, and information fusion and high-dimensional representation extraction are carried out on multi-source sensor signals; pre-training the tool wear monitoring model by using the auxiliary task I, and guiding the model to extract the invariance feature of the signal; according to the method, under the condition of scarce marked data, high-precision prediction and excellent generalization ability of tool wear are realized, the fluctuation amplitude of prediction errors can be effectively reduced, and the stability of a prediction result is kept. According to the method, a small amount of mark data is effectively utilized in model training, the stability and reliability of tool wear monitoring are ensured, and the requirements for monitoring precision and adaptability in actual production are met.

The invention discloses a numerical control lathe tool wear monitoring method and system. The method comprises the steps that numerical control lathe tool operation process data are monitored in real time; a corresponding preset operation parameter threshold value is matched according to the operation process data, and when it is monitored that the preset operation parameter threshold value is exceeded, the operation process data of the numerical control lathe tool is transmitted to an edge computing node; matching a corresponding preset operation parameter combination and finishing operation parameter screening according to the operation process data by utilizing the edge computing node; based on the screened operation parameters, key features are selected and extracted by using a feature selection algorithm, and an optimal feature set is acquired and uploaded to a cloud platform; and matching a corresponding tool wear prediction model according to the operation process data at the cloud platform, inputting the optimal feature set into the matched tool wear prediction model, obtaining a wear value, a wear degree and a life prediction result, and performing early warning decision and early warning prompt. According to the invention, efficient, accurate and real-time tool wear monitoring under complex working conditions is realized.

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 relates to the field of tool wear in the numerical control machining process, in particular to a tool wear monitoring and predicting method which comprises the steps of signal collection, multi-domain feature extraction, multi-modal feature fusion, tool wear prediction model construction, real-time monitoring and wear prediction. And a multi-signal fusion monitoring and prediction model is constructed, so that the precision of tool wear monitoring and the reliability of prediction are remarkably improved, and the defects of a traditional method are effectively overcome.

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 the field of machining, in particular to the field of tool face abrasion prediction, and particularly discloses a tool face abrasion loss prediction method and system and a digital twin system. Inputting the preprocessed real-time machine tool spindle current data into the trained blunt state classification model to obtain a blunt state classification result; if the blunt state classification result is a non-blunt state, inputting the preprocessed real-time machine tool spindle current data into a trained first tool face abrasion loss prediction model to obtain a tool face abrasion loss prediction value; and if the blunt state classification result is a blunt state, inputting the preprocessed real-time machine tool spindle current data into the trained second tool face abrasion loss prediction model to obtain a tool face abrasion loss prediction value. According to the method, the tool wear states are classified, wear loss prediction models are trained for different wear states, wear state information is fully utilized, and higher prediction precision is achieved.

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

The invention 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 an equipment environment detection method and system based on a fiber grating sensor, and relates to the technical field of equipment environment detection methods, and the comprehensive environment of equipment is determined based on the internal production environment of the equipment, the production image of the equipment and the external environment of the equipment. The internal production environment of the equipment, the production image of the equipment and the external environment of the equipment are integrally controlled, accurate detection of the comprehensive environment of the equipment is achieved, and the accuracy of the comprehensive environment of the equipment is improved. Therefore, the production grade of the equipment is determined according to the comprehensive environment of the equipment and the detection of the real-time image of the material produced by the equipment; and if the production grade of the equipment is lower than the preset production grade threshold value, determining the abnormal part in the equipment based on the abnormal detection of the equipment, and triggering the autonomous regulation and control of the abnormal part, thereby realizing the autonomous regulation and control of the abnormal part, and fully considering the production grade of the equipment.

The invention relates to the technical field of tool state detection, in particular to a tool state indicating method and device for variable-pitch screw multi-tool machining. Determining a vibration fluctuation coefficient according to the vibration data of each cutter in any direction and the difference of all vibration data of each cutter in any direction between each time period and the adjacent previous time period; for a vertical direction in all directions of each cutter, determining a frequency domain fluctuation coefficient according to a difference and a distribution condition of frequency domain fluctuation conditions of all vibration data between each time period and the first time period; and based on the correlation between the vibration fluctuation coefficient and the frequency domain fluctuation coefficient of each tool in all time periods, determining the weight of the tool, and monitoring the state of the tool in combination with the vibration data. The fluctuation conditions of the vibration data in the time domain and the frequency domain are comprehensively analyzed, and the accuracy of cutter state detection is improved.

The invention relates to the technical field of image processing, and discloses a visual positioning system and method for a complex box five-axis numerical control comprehensive processing machine. The system comprises a calibration module for collecting multi-angle images and utilizing mark point calibration coordinates to obtain a parameter mapping table, an extraction module for carrying out edge detection and contour extraction splicing features to obtain a three-dimensional data set, a marking module for calculating the actual position of a box and marking inner cavity machining areas, a recording module for analyzing and determining cutting parameters and deformation of all the areas, and a display module for displaying the cutting parameters and the deformation of all the areas. The processing module generates an obstacle avoidance cutter path and a thin-wall area machining strategy, and the comparison module monitors and compares actual effects to dynamically adjust parameters to obtain compensation data. According to the five-axis numerical control comprehensive processing machine, high-precision visual positioning and intelligent processing parameter optimization of the complex box on the five-axis numerical control comprehensive processing machine are realized, and the processing precision, efficiency and reliability of the complex box are improved.

The invention belongs to the related technical field of numerical control machining, and discloses a tool wear real-time monitoring and prediction method and system based on multi-sensor information fusion, and the method comprises the steps: S1, collecting a monitoring signal and a tool wear image in a machining experiment process; s2, carrying out wear region segmentation on the tool wear image by adopting a wear region segmentation model, and calculating to obtain a real wear value; s3, establishing a monitoring training sample set by using the monitoring signal and the real wear value, and training the wear monitoring model; establishing a prediction training sample set by using the sequence of the real wear values, and training a wear prediction model; s4, the real-time monitoring signal and the wear monitoring model are used for monitoring the wear value of the tool in real time; and performing online prediction on the wear value of the cutter by using the wear prediction model. According to the invention, the wear value of the cutter can be monitored in real time according to the real-time monitoring signal, online wear value prediction can be realized, and the production efficiency can be greatly improved.

The invention relates to the technical field of numerical control machine tool cutter state monitoring, and discloses an intermittent turning cutter service life monitoring and evaluating system based on multi-sensor fusion. The detection and evaluation system is composed of a data acquisition module, a noise data preprocessing module, a noise feature analysis and mode recognition module, a tool life prediction module and a multi-source data fusion module. According to the method, noise, vibration and temperature data are integrated, a weighted average algorithm is adopted, noise interference of a single sensor is reduced, the accuracy of cutter state evaluation is improved, filtering, smoothing and signal enhancement technologies are used, high-frequency noise is removed, data fluctuation is smoothed, useful signals are enhanced, data quality is improved, and data of all the sensors are standardized; the weight is calculated according to the reliability and the precision, weighted average fusion is carried out, fused high-quality data is generated, and the beneficial effect that errors caused by interference caused by noise in service life monitoring during cutting of the cutter are avoided is achieved.

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

The invention discloses a shaping robot, a shaping system and a grain processing method thereof. An integrated moving and transferring device is used as a chassis for bearing all modules; the shaping industrial robot is used for driving a cutter on the mechanical arm to conduct shaping machining. The medicine scrap sucking and cleaning device is used for cleaning scraps generated by processing; the tool changing magazine is used for placing and managing tools and comprises a quick-changing tool rest, and a detection sensor used for detecting whether the tools exist or not is arranged on the quick-changing tool rest; the control system comprises a coordinate system management module, a tool path planning module, a robot kinematics module, a collision detection module, a motion simulation module and a robot program generation module. Automatic machining positioning, automatic machining path planning and automatic cutting tool switching and management can be achieved; the automation degree of grain cutting machining is effectively improved; in the shaping process, temperature and contact force detection sensors are used for detection, and early warning protection in the machining process is achieved.

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 belongs to the technical field of clamping, and provides a self-adaptive shape follow-up centering clamp and an automatic clamping method. The self-adaptive shape follow-up centering clamp comprises an end cover, an outer circular ring, a floating shape follow-up positioning cylinder, a driving clamping cylinder, an inner circular ring, a hanging ring, a rib plate and a PLC control system. The automatic clamping method can replace a traditional process ring clamping method, self-adaptive shape follow-up positioning and clamping of the barrel workpiece are achieved, the process ring turning procedure is omitted, and material consumption is reduced. After the outer circular ring, the cylindrical roller bearing and the axis of the lathe spindle in the self-adaptive shape follow-up centering clamp are mounted consistently, it can be guaranteed that the middle barrel section coincides with the axis of the lathe spindle. Shape-following positioning of a blank barrel workpiece is achieved through the floating shape-following positioning cylinder, the barrel workpiece is clamped through the driving clamping cylinder, and it is guaranteed that stress is uniform while the axis of the barrel workpiece does not deviate. The device is achieved based on a PLC control system, the clamping force is quantitatively controlled through feedback adjustment of the oil pressure gauge and the proportional valve, and clamping deformation is reduced.

The invention relates to the technical field of tool switching, and discloses a tool switching method of a CNC tool magazine. The method comprises the following steps: performing three-dimensional laser scanning on the surface of a cutter in a CNC machine tool to obtain a wear tiny heterogeneity index; performing association mapping on the geometric features of the workpiece and the tool wear mode to obtain feature data of a cutting boundary layer; executing cutter state evaluation calculation to obtain cutter health state indexes and inter-cutter collaborative wear relation data; switching evaluation function calculation is executed in the tool state space, and a first switching time sequence decision sequence is obtained; and the first switching time sequence decision sequence is input into a CNC tool magazine management system, and automatic tool switching operation is executed by controlling a tool replacement mechanical arm according to the calculated optimal intervention angle. The cutter switching time is greatly shortened, the machining efficiency is improved, and meanwhile the consistency and stability of the machining quality are ensured.

The invention discloses a safety detection system for a tool magazine of a gantry machine tool, relates to the technical field of gantry machine tools, and solves the problems that an object entering a blind area cannot be quickly recognized to belong to a human body, and the comprehensiveness of recognition needs to be improved. By means of two-dimensional coordinate system analysis, central point overlapping and zooming operation, calculating an overlapping area proportion so as to judge whether the area is a human body area or not; the scientific judgment mode improves the accuracy and reliability of recognition, reduces the false alarm rate, ensures the accurate transmission of early warning information, and can quickly send out an early warning signal through the early warning end to remind an operator to take measures in time to avoid danger once the system judges that a change area belongs to a human body area; the real-time response mechanism can effectively reduce the probability of accidents and kill potential risks in the bud.

The invention discloses a low-temperature minimal quantity lubrication cooling method in aluminum alloy precision machining, and relates to the field of aluminum alloy precision machining. Machining parameters such as the cutting speed and the feeding amount are determined according to the aluminum alloy material, the machining requirement and the tool performance, and finite element simulation optimization is carried out; high-purity vegetable oil-based lubricating oil is selected, a nano anti-wear agent and an antioxidant are added, and cooling liquid is prepared by mixing compressed air through vortex tube refrigeration; spraying to a processing area through a special multi-channel nozzle, and dynamically adjusting the flow; multiple sensors are used for monitoring the temperature, the tool abrasion and the surface quality, and adjustment is conducted when threshold values are exceeded; and the cooling liquid is recycled after being subjected to centrifugation and membrane filtration treatment, and the metal filing is classified, recycled and reused. The cooling and lubricating effects are good, cutting heat and tool abrasion are reduced, the machining precision is improved, and the tool service life is prolonged; environment-friendly lubricating oil is recycled, so that pollution and cost are reduced; real-time monitoring and adjustment guarantee stable machining quality, machining efficiency is improved, and high-end manufacturing requirements are met.

An automatic sample cutting method for shoe sole detection relates to the field of shoe sole detection equipment, and comprises a machine table, a shoe sole clamping mechanism, a numerical control milling cutter mechanism, a manipulator and a visual system, the shoe sole clamping mechanism comprises a shoe tree, a clamping cylinder and a clamping plate, and the shoe tree is inversely arranged on a working platform; the clamping cylinder pushes the clamping plate to move and clamps the shoe on the shoe tree; the numerical control milling cutter mechanism is arranged on the machine table and can cut shoe soles. The manipulator is arranged in the machine table to clamp the cut sample; the visual system comprises a visual camera and a controller, the visual camera is arranged at the end of the mechanical arm and can move along with the mechanical arm to collect marks on the shoe sole and feed back images to the controller, the controller controls the numerical control milling cutter mechanism to switch cutters and cut the shoe sole, and cutting and sampling of shoe sole samples can be rapidly completed. According to the shoe sole cutting device, only a small number of persons are needed to install and observe shoe soles beside the device, labor force is saved, some shoe soles made of firm materials can be rapidly cut, and working efficiency is improved.