1300 results about "Tool wear" patented technology

The invention discloses a water-based cutting fluid used in slice machining of a hard brittle crystal material, comprising the following compositions: base oil, organic amine, organic acid, synthetic ester, emulsifier, rust and corrosion inhibitor, dispersion flocculation and hard-water resisting agent, antiseptic bactericide, antifoaming agent, coupling agent, adjuvant and a proper amount of water. Aiming at the machining techniques of inner circle slicing and outer circle slicing, the water-based cutting fluid has good generality, lubricity, strong antirust property and a long service life; when the cutting fluid is used, the machining situation can be observed easily, the cooling property is good, the cleaning and the permeability are strong, cuttings subside easily, and the machining problems of machining error, crack and the like caused by cutter blocking, abrasion and the like are solved; according to the invention, the problems that cuttings are easy to adhere and suspend, a cutter is seriously abraded, a machined product cracks easily, the accuracy is not high, the machining efficiency is low, the later period cleaning is complex and the like existing in the current slice machining of the hard brittle crystal material are solved, and further, a machine bed is protected, and the cost is reduced.

The invention discloses a tool wear monitoring system capable of realizing self-learning in a numerical control machining state. The structure of the system is that: a tool wear rule learning library stores learned tool wear rules; a data acquisition and judgment module provides a servo drive current digital signal for a data processing module to perform format conversion and store the signal as a monitoring current signal; a characteristic extraction and selection module selects signal characteristics strongly correlated with tool wear; a fitted predicted trend curve module establishes a signal characteristic-tool machining service life relationship curve; a tool wear rule module obtains the learned tool wear rules from the tool wear rule learning library, and substitutes the trend signal characteristics into the learned tool wear rules to obtain a tool wear extent; and a tool wear compensation and tool replacement module makes a tool wear compensation and tool replacement decision according to the tool wear extent, and provides the tool wear compensation and tool replacement decision for a numerical control system interface input module. The system is applied to the condition offluctuating cutting parameters in mass production, and can achieve relatively higher accuracy under the condition of constant cutting parameters.

The invention discloses an on-line automatic tool setting and breakage detection device for a minitype milling tool. The device comprises a shell, a device base, an optical tool detection system, a centralized control system and a tool abrasion alarming system, wherein the optical tool detection system is fixedly installed on the device base by a device bracket; the optical tool detection system is a planar-array type image sensor system and is in signal connection with the centralized control system; the centralized control system is in signal connection with the tool abrasion alarming system; the optical tool detection system comprises a radial tool measurement device and a tool end measuring device; the radial tool measurement device collects the local detailed image data of a cutting blade abrasion zone along the radial direction of the tool to realize automatic tool setting and breakage detection; and the tool part measuring device assists the breakage detection of the tool; and the main shaft of the machine tool of the tool is provided with a calibrated target object. The detection device is characterized in that the radius and length offset of the tool can be automatically measured when the tool rotates and the breakage situation of the minitype milling tool can be detected.

The invention discloses a tool wear condition prediction method of a numerical control machine tool based on a parallel deep neural network. A dynamometer, an acceleration sensor and an acoustic sensor are installed on a workbench and a fixture of the numerical control machine tool; a milling experiment is conducted, the cutting force and vibration and acoustic signals of a milling process are collected so as to obtain multisensor data, and the wear capacity of a tool is collected; pretreatment is performed so as to obtain training data and to-be-tested data; a parallel deep neural network model is established; the treated training data and the label of the wear capacity of the tool are input into an offline training model in the parallel deep neural network model; and the to-be-tested multisensor data are introduced into the trained model so as to predict the wear capacity of the tool in real time and on line. According to the method, the implied characteristics during tool processingof the numerical control machine tool are fully mined, and the wear capacity of the tool can be predicted in real time. The method has the advantage of wide applicability and can be widely applied tovarious numerical control machine tools.

If a tool breakage occurs, a cutting time T and a maximum value (absolute value) G of a slope of a drop in a cutting load become small. A cutting load integrated value S increases as a tool wears and becomes small when the breakage occurs. Therefore, these values T, G, and S are obtained in a machining cycle, moving variable thresholds are obtained (updated) based on values T, G, and S obtained in a preceding machining cycle, and the thresholds and the values T, G, and S obtained in the current machining cycle are compared with each other to thereby determine an abnormal condition of the tool.

The invention discloses an in-site measuring method and device of cutter abrasion, and belongs to the technical field of the in-site measuring method and device of cutter abrasion. The method comprises the first step of installing a linear structure laser device and a CCD camera on the lateral of a cutter, wherein the CCD camera is connected to a computer through an image collecting card; the second step of making ray laser be vertically projected to the knife blade of the cutter, wherein deformed laser rays image on a photosensitive surface of the CCD camera and are then transmitted to the computer; the third step of obtaining a two-dimensional size of a ray bar point on a laser plane through image processing and calibration calculation; the fourth step of making the device rotate along with the cutter to scan the cutter for one round to obtain three-dimensional size data of the whole cutter; the fifth step of comparing the three-dimensional size data with a standard cutter three-dimensional model to obtain abrasion loss. The in-site measuring method and device of cutter abrasion have the advantages that the cost is low, the precision is high, the strip image information is easy to obtain, the practicability is high, the active control is achieved, the measuring precision at the micrometer level can be reached, and thus the measuring method and device of cutter abrasion are suitable for in-site measuring of cutter abrasion.

The present invention relates to an improved planed and cut thin bamboo and its production method. Said invention method includes the following steps: pretreating natural colour or carbonized bamboo sheets, applying glue, pressing, overlapping to obtain bamboo block, pressing and impregnating the integrated bamboo block, drying, applying glue, pressing to obtain bamboo squared timber, then planing and cutting said bamboo squared timber, drying so as to obtain the invented bamboo thin sheet whose thickness is 0.15-2.00 mm, then applying glue layer and technological layer on the thin bamboo sheet.

The invention discloses a turning cutter wear state monitoring system. The turning cutter wear state monitoring system comprises a signal collecting system and a cutter wear state identifying system; the signal collecting system comprises a temperature collecting system and a vibration signal collecting system, wherein the temperature collecting system collects temperature of a cutter point of a rake face of the cutter, and the vibration signal collecting system collects a three-dimensional vibrating signal at the lower surface of a cutter handle corresponding to the utter point of the rake face of the cutter; after pretreating the signal collected by the signal collecting system, the sensitive characteristic of the cutter wear state is obtained and transmitted to the well-trained cutter wear state identifying system; thus the wear state of the cutter is judged through the cutter wear state identifying system. The turning cutter wear state monitoring system is simple and applicable, and is convenient to operate; moreover, the sensor in use is relatively universal in use, moderate in cost, and easy to build up a testing system; the turning cutter wear state monitoring system can largely reduce the monitoring cost, effectively identify the wear state of the cutter and reduce the cutter waste.

The invention relates to a cutter wear monitoring method based on current and acoustic emission compound signals. According to the cutter wear monitoring method, the current signal of a spindle motor and acoustic emission signals of a turning tool wear state in cutting machining are detected, processing and analyzing are conducted based on the current and acoustic emission compound signals, and then the wear state of a cutter is monitored in real time; the current signals of the cutting motor and the cutter wear state features in the acoustic emission signals are obtained in a self-adaptive mode, the abundant cutter wear state information in the current signals of the cutting motor and the acoustic emission compound signals are fully excavated, through a wavelet packet analysis method, a correlation analysis method, a principle compound analysis method and the like, the feature information reflecting the current wear state of the cutter is extracted in a self-adaptive mode, and the wear degree of the cutter is judged by analyzing the relevance between the feature information reflecting the current wear state and initial wear state features.

The invention relates to a cutter abrasion online monitoring method based on wavelet packet analysis and a radial basis function (RBF) neural network. The method comprises the steps that shear force coefficients and cutting edge force coefficients of tangential force and radial force in different cutter abrasion states are calibrated by means of an instantaneous cutting force coefficient recognition method; and by analyzing the correlation between cutting force coefficients and cutter abrasion, the coefficients are taken as cutter abrasion characteristic parameters and input into a RBF neutralnetwork model after being subjected to normalization processing. An input layer of a RBF neutral network monitoring model training process comprises cutting force characteristics, cutting vibration characteristics, the shear force coefficients and the cutting edge force coefficients after being subjected to normalization processing; and an output layer comprises the cutter rear cutter surface abrasion capacity after being subjected to normalization processing; a hidden layer comprises neurons obtained through radial basis function iterative optimization; and it is verified that the RBF neuralnetwork monitoring model has the advantages of high response speed and high recognition precision through cutter abrasion monitoring experiments.

The invention relates to a real-time online tool wear monitoring method which comprises the steps of: firstly, under different cutting parameters, respectively acquiring acoustic emission signals in different wear states, current signals of a spindle motor and a feed motor in a machine tool, cutting speed, cutting depth and feed rate; taking the acquired values as condition attributes, and establishing a decision table; carrying out discretization treatment on the continuous attribute values in the decision table by adopting a self-organizing map neural network; reducing the number of the attributes by adopting the Johnson algorithm; optimizing the initial weight value and the threshold values of a back propagation (BP) neural network by the genetic algorithm, and using the reduced attribute value which is taken as an input neuron of the BP neural network to train and learn the optimized BP neural network; using the trained BP neural network to predict the tool wear degree. The method not only simplifies the structure of the neural network so as to enable the neural network to have rapid neural astringency and stronger learning ability, but also improves the recognition rate of tool wear detection.

The invention relates to a monitoring method based on image features and an LLTSA algorithm for a tool wear state. According to the method, an image texture feature extraction technology is introduced into the field of tool wear fault diagnosis, and monitoring for the tool wear state is realized in combination with three flows of ' signal denoising', 'feature extraction and optimization' and 'mode recognition'. The method comprises the steps of firstly, acquiring an acoustic emission signal in a tool cutting process through an acoustic emission sensor, and carrying out signal denoising processing through an EEMD diagnosis; secondly, carrying out time-frequency analysis on a denoising signal through S transformation, converting a time-frequency image to a contour gray-level map, extracting image texture features through a gray-level co-occurrence matrix diagnosis, and then further carrying out dimensionality reduction and optimization on an extracted feature vector through a scatter matrix and the LLTSA algorithm to obtain a fusion feature vector; and finally training a discrete hidden Markov model of the tool wear state through the fusion feature vector, and establishing a classifier, thereby realizing automatic monitoring and recognition for the tool wear state.

The invention provides a cutter abrasion on-line monitoring method to monitor cutter abrasion of a lathe in the machining process on the basis that considering the influence of the cutter abrasion capacity and machining parameters on cutting power, a corresponding regression model is established, namely the invention discloses a cutter abrasion on-line monitoring method of numerical control turning batch machining based on the cutting power. The method comprises the following steps that firstly, the influence of the cutter abrasion capacity and the machining parameters on the cutting power is analyzed; then the regression model of the cutting power, the cutter abrasion capacity and the machining parameters is established through orthogonal test design and a response surface method; and finally, on the basis of establishing of the regression model of the cutting power, the cutter abrasion capacity and the machining parameters, the cutter abrasion on-line monitoring method where a cutting power threshold value is updated in real time is obtained.

The invention discloses a cutter wear state monitoring method based on a deep gated cycle unit neural network. The method comprises the steps that vibration signals generated in the tool machining process are collected in real time through a sensor, after wavelet threshold denoising, the signals are input into a one-dimensional convolutional neural network for single time step time sequence signallocal feature extraction; then, inputting the time series signal into an improved deep gated recurrent unit neural network CABGRUs to carry out time series signal time series feature extraction; an Attention mechanism is introduced to calculate network weights and reasonably distribute the network weights, and finally, signal feature information with different weights is put into a Softmax classifier to classify tool wear states, so that complexity and limitation caused by manual feature extraction are avoided; meanwhile, the problem that a single convolutional neural network ignores correlation before and after a time sequence signal is effectively solved, and the accuracy of the model is improved by introducing an Attention mechanism. Therefore, the method has the characteristic of improving the real-time performance and accuracy of cutter wear state monitoring.

A stable rotation speed is acquired by finely changing a rotation speed of a rotary shaft 3 based on an expected stable rotation speed, and calculating an amount of change of a k′ number, and the like. Therefore, a more accurate rotation speed can be acquired, and “chatter vibration” generated during machining can be suppressed more effectively than a conventional method. As a result, a quality of a workpiece surface can be improved, and a tool wear and the like can be suppressed.

The invention relates to a micro-milling-force modeling method based on a tool abrasion effect and belongs to the field of precision and efficient machining of micro-parts. The method comprises the steps that the influence of tool tooth top trochoid motion trail, radial run-out of tooth tops, elastic recovery of machined surfaces and other factors is comprehensively considered to obtain a micro-milling-force prediction model which is not based on tool abrasion; then, the tool abrasion situation in the micro-milling process is obtained based on a finite element method, and the positive pressure and tangential friction force produced due to the fact that tool abrasion causes that the rear tool surface extrudes a workpiece are calculated based on a simulation result; finally, models of the two forces are superposed to obtain the micro-milling-force modeling method based on tool abrasion. The micro-milling-force modeling method achieves accurate micro-milling-force prediction through one model, improves the model robustness, is wide in application range and improves the micro-milling machining quality and efficiency of the micro-parts.

A monitoring apparatus for monitoring one or more manufacturing machines having a plurality of component tools and engaged in repetitive machining of a part is provided. An input device detects occurrence of a machine cycle. A counter stores the number of detected machine cycles as a count value. A machine speed processor estimates a temporal rate at which the machine cycles occur. A data storage device stores a maintenance schedule indicating the number of machine cycles between recommended replacements for each tool. A tools processor estimates a remaining operating time for each tool before scheduled replacement. A machine viability processor estimates a remaining operating time for the machine before schedule replacement of each of the component tools. A display device displays the operating time for the machine before scheduled replacement of each of the component tools. A method for monitoring a cycling manufacturing machine includes detecting machine cycles of the manufacturing machine, estimating a machine operating rate based on the detecting step over time, and projecting tool change times for each of the plurality of tools based on the estimated machine operating rate and pre-selected tool cycle lifetime values for each of the plurality of tools.

The present invention relates to a multi-target cutting data generation algorithm and cutting parameter optimization method of a numerical control machine tool. The core algorithms of a database comprise calculation of cutting processing states such as cutting force and dynamic cutting vibration, and calculation of load conditions such as cutting power and main shaft torque, processing quality such as processing precision and surface roughness, processing efficiency information such as processing time and material removal rate and benefit assessment such as cutter wearing and production cost.Cutting parameters are optimized according to a calculation result to improve the usage rate and part processing efficiency of a machine tool. A cutting database algorithm developed aiming at a numerical control lathe and numerical control turning center is integrated on a domestic I5 intelligent numerical control system platform to allow machine tool users to conveniently call and select cuttingparameters according to concrete processing demands and to predetermine cutting effects, which are likely to generate, before actual cutting.

The invention belongs to a device for detecting the abrasion of a machining cutting tool, and in particular relates to a device for intelligently detecting the abrasion of a numerical control cutting tool. In the device, a sensor signal processing circuit is used for detecting a cutting temperature and a cutting vibration value of the cutting tool in the machining process on line; a liquid crystal display circuit is used for displaying measured parameter values and dynamic curves of the measured parameter values along time variation; a singlechip control circuit is used for determining the abrasion rate according to the curves, predetermining the abrasion of the cutting tool and performing analysis processing on the abrasion; and when a measured temperature value and any value in vibration quantity are greater than a critical value, an alarming circuit is used for automatically giving an alarm. By the device, the cutting temperature and the cutting vibration value of the numerical control cutting tool can be detected and the abrasion of the numerical control cutting tool can be alarmed without the dependence on the sensation and the manual estimation of detection personnel, so that the cutting tool and a machine tool exert the highest machining capability and are effectively protected, the service life of the cutting tool is prolonged, and the machining quality of the cutting tool is improved; and the device has low cost and a simple circuit structure, is convenient to control and stably operated, can be applied to different machining operating conditions and improves the compatibility and the adaptability of a system.

The invention discloses an on-line monitoring device for tool wear of a shield tunneling machine based on a resistance row type. inside the tool of the machine. The part where the resistor row contacts the cutter is filled with epoxy resin to ensure the insulation between the resistor row and the cutter. There is a rubber pad at the contact part between the resistance row base and the cutter, and the rubber pad also has a sealing effect, and the resistance row base is fixed with the cutter as a whole with a lock nut. There are three signal amplifiers on the cutterhead, three transmitting antennas are installed on the back of the cutterhead corresponding to the signal amplifiers, receiving antennas are installed on the inner wall of the soil pressure chamber opposite to the transmitting antennas, and signal receiving antennas are installed in the main cabin of the shield tunneling machine. device. The invention can predict the wear state of the excavating tool on-line, effectively reducing or avoiding the occurrence of huge economic losses, personal casualties and other dangerous accidents caused by tool accident shutdown.

The invention relates to a synchronous trenching machine comprising a high-pressure air inlet pipe, a slurry discharging bent pipe, a slurry outlet steel pipe and two guide rails, wherein the two guide rails are fixed at both sides of the slurry outlet steel pipe. The synchronous trenching machine is characterized in that synchronous submersible motors A and B are respectively arranged at both sides of the slurry outlet steel pipe; a crank A is arranged below the submersible motors A and articulated with the upper end of a rocking arm A through a connecting rod A, and the lower end of the rocking arm A is articulated with a tool arm A; a crank B is arranged below the submersible motor B and articulated with the upper end of a rocking arm B through a connecting rod B, and the lower end of the rocking arm B is articulated with a tool arm B; and the tool arm A and the tool arm B are both provided with cutting tools. The synchronous trenching machine is a special appliance for trenching an underground continuous wall.

The invention discloses a two-dimensional ultrasound vibration platform and relates to the technical field of non-traditional machining. The two-dimensional ultrasound vibration platform aims at solving the problems that cutting force is large and a tool is worn badly when a common micro milling machine is used for machining hard and brittle materials. The two-dimensional ultrasound vibration platform comprises a bearing plate, an upper vibrating plate, a lower vibrating plate, linear moving guide rails, bow spring pieces, fine adjusting devices, an ultrasonic power supply, ultrasonic amplitude transformers and ultrasonic transducers. The bottom of the bearing plate is directly fixed to a platform of a machine tool through bolts. The lower vibrating plate is mounted on the bearing plate. The middle of one side of the upper vibrating plate and the middle of one side of the lower vibrating plate are each connected with a vibrator. The bow spring pieces are arranged in the middles of the other sides of the vibrating plates. The two ends of each bow spring piece are fixed to the output end of the corresponding fine adjusting device. The amplitude transformers and the transducers are connected through threads to form the vibrators. According to the two-dimensional ultrasound vibration platform, the vibrators produce ultrasonic vibration to drive the upper vibrating plate and the lower vibrating plate to vibrate, different motion tracks can be coupled out according to different demands, and the two-dimensional ultrasound vibration platform is high in transportability and suitable for being popularized in vibration milling or other vibration screening fields.

The invention relates to the technical field of machining, in particular to a cutter wear estimating and monitoring method and system based on characteristic fusion. The method comprises the steps ofdata flexible acquisition, working condition division, data preprocessing, characteristic extraction, characteristic fusion and estimation and monitoring. The system comprises a working condition division module, a data preprocessing module, a characteristic extraction module, a characteristic fusion module, an estimation and monitoring module and a self-learning module serially connected in sequence. The method and the system can realize multi-signal, multi-working-condition and multi-dimension fusion of original signals to obtain characteristic indexes capable of comprehensively reflecting the cutter wear state for estimating cutter real performance state and change rules to give more precise timely prewarning, alarm and feedback optimization policies. Through improvement of cutter wearonline estimation and monitoring performances, the machining problems caused by cutter wear are gradually solved, and the cost reduction, the quality improvement and the efficiency improvement in themachining process are finally achieved.

The invention discloses a tool wear condition monitoring method based ona conditional random field model. The method comprises the steps of allowing an acoustic emission signal collected ina cutting process to undergo preprocessing and relevant feature extraction, taking the extracted feature vector as a training sample and a testing sample of a conditional random field model, employing the acquired training sample to establish a conditional random field model of tool wear condition monitoring, inputting the testing sample into the established model, and outputting the corresponding wear condition. The method accurately detects different wear conditions ofthe tool and predicts the tool wear condition simply by only analyzing the acoustic emission signal produced inthe cutting process. Detection results show that the method can accurately identify different wear conditions of tool in different wear stages, and has great practical significance to on-linetool wear monitoring.

The invention relates to an abrasion detection device of a mixed type rotary cutter, which belongs to the field of mechanical processing. In the invention, the abrasion image of the cutter is obtained by utilizing an area array type CCD industrial camera and is transmitted to an upper computer by a USB. In order to realize the multi-angle shooting of the cutter, the camera has three degrees of freedom aggregately: a translation platform realizes the focusing function of the camera to the cutter to be detected, a horizontal rotation platform realizes the multi-direction shooting of the camera to the cutter, and a pitching rotation platform realizes the shooting of the camera to a plurality of angles of the cutter. In order to realize the measurement of the abrasion of the cutter in a processing process, the design has the function of water prevention and can prevent cutting fluid and metal swarfs from entering the inside of the device.

The present invention relates to a method and a device for suppressing vibration generated during machining in a machine tool for performing machining while rotating a tool or a work. A stable rotation speed is acquired by finely changing a rotation speed of a rotary shaft 3 based on an expected stable rotation speed, and calculating an amount of change of a k' number, and the like. Therefore, a more accurate rotation speed can be acquired, and 'chatter vibration' generated during machining can be suppressed more effectively than a conventional method. As a result, a quality of a workpiece surface can be improved, and a tool wear and the like can be suppressed.

A tool wear monitoring and predicting method is provided, and uses a hybrid dynamic neural network (HDNN) to build a tool wear prediction model. The tool wear prediction model adopts actual machining (cutting) conductions, sensing data detected at the current tool run of operation and the predicted tool wear value at the previous tool run of operation to predict a predicted tool wear value at the current tool run. A cyber physical agent (CPA) is adopted for simultaneously monitoring and predicting tool wear values of plural machines of the same machine type.

The invention discloses a coal roadway tunneling machine with double round cutter heads. The coal roadway tunneling machine comprises round cutter heads, a shield, a scraper conveyer, an annular girder, an anchor rod drilling machine, a girder beam, supporting shoes, a rear support and a belt conveyor, wherein the cutter heads of a host machine employs double round cutter heads which are arranged in a staggered way; the length between two crossing points where two rounds are overlapped is the height of the section of a rectangular roadway. An operator carries out anchoring operation under the shield so as to realize the safe production. A thrust cylinder provides a reacting force through the supporting shoes which are tightly supported against the side wall; a thrusting force acts on the cutter heads through the crossbeam of the host machine cutter; the supporting shoes are matched with rear support, thereby realizing the continuous tunneling of the whole coal roadway tunneling machine. Cut coals and rocks are conveyed out of a feed bin through the scraper conveying machine. The coal roadway tunneling machine with double round cutter heads has the advantages of fast tunneling speed, low abrasion of cutters, integrated construction of tunneling and anchoring, etc. and the cost of unit tunneling number is greatly reduced. In addition, tunneling and anchoring are carried out simultaneously, therefore, the continuous operation is realized, and the labor productivity is improved.

The invention relates to a tool wear automatic compensation method and system, and corresponding numerically-controlled machine tool machining equipment. The method comprises the following steps of: A, measuring actual size of a finished product by an image measuring instrument; B, obtaining tool compensation information of the numerically-controlled machine tool based on the actual size and standard size of the finished product; and C, carrying out the tool compensation to the numerically-controlled machine tool based on the tool compensation information. The tool wear automatic compensation method and system, and the corresponding numerically-controlled machine tool machining equipment provided by the invention can carry out the tool compensation automatically, save time and labor, and avoid the defects that the existing tool compensation method and system is time-consuming when the tool compensation is carried out and the requirement to the operators is high.

The present invention relates to a numerical control device cutter wearing detection method based on a cloud knowledge base and machine learning. The method comprises the steps of: A, constructing andtraining a cutter wearing detection model: (1) establishing a cloud knowledge base, (2) collecting condition data of a workshop and storing the condition data, (3) designing a cutter wearing detection model, and employing a support vector machine to perform training of the cutter wearing detection model; and B, performing cutter wearing detection through the cutter wearing detection model: (4) updating the cutter wearing detection model to a local numerical control machine tool, performing detection of a cutter on the local numerical control machine tool, and when the cutter wearing amount achieve a dulling standard, replacing the cutter, and (5) taking newly detected condition data and the detected cutter wearing amount as feedback information, and transmitting the feedback information to the local numerical control machine tool through a network. The cutter wearing cutter prediction accuracy rate and the detection speed are improved.