CN201776666U - Cuter wear detector - Google Patents
Cuter wear detector Download PDFInfo
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- CN201776666U CN201776666U CN2010202797400U CN201020279740U CN201776666U CN 201776666 U CN201776666 U CN 201776666U CN 2010202797400 U CN2010202797400 U CN 2010202797400U CN 201020279740 U CN201020279740 U CN 201020279740U CN 201776666 U CN201776666 U CN 201776666U
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Abstract
The utility model relates to a cutter wear detector which comprises an acoustic emission sensor, a preamplifier, a signal conditioning module, a signal processing module and a display control module, wherein the acoustic emission sensor is adsorbed on the back side of a cutter frame with a cutter through a magnet of a shell; the output end of the acoustic emission sensor is connected with the preamplifier; the preamplifier is connected with the signal conditioning module by a signal cable A; the output end of the signal conditioning module is connected with the signal processing module through a signal cable B; an expert database system is stored in a storage in the signal processing module; and the display control module and the signal processing module are connected through a serial communication cable. In the utility model, the characteristics of sound of each phase in the process that the sharp cutters become worn when different cutters cut different workpieces are recorded and sorted according to the characteristics of acoustic emission signal generating sources, and then the expert database system is established. The expert database system is stored in the storage of the signal processing module, and can be used as an important reference for detecting the worn condition of the cutter in the process that an acquisition processing module identifies the different cutters cutting the different workpieces.
Description
Technical field: the utility model relates to a kind of detector, especially a kind of tool wear detector, and the real-time online that is mainly used in the tool wear in the difficult processing of the aviation field device Precision Machining detects.
Background technology: the local source phenomenon that produces the transient state elastic wave that releases energy fast is called acoustic emission (Acoustic Emission is called for short AE) in the material.In the process of metal cutting, can may comprise following several as the source of acoustic emission signal:
1, the plastic deformation of workpiece work in-process.
2, the plastic deformation of smear metal.
3, cutter is surveyed the friction of face and workpiece, and produces flank wear.
4, the friction of cutter front surface and workpiece, and produce the shape wearing and tearing of crescent moon gulf.
5, the bump of cutter and smear metal.
6, smear metal breaks.
7, the fracture of cutter.
According to the analysis of AE signal source in the above metal processing, AE comprises continuous signal and the different signal of instantaneous signal two classes.Continuous signal is accompanied by the positive and whole process of side from sharp to wearing and tearing of cutter.Instantaneous signal only can be created in that cutter breaks and moment of chip fracture.The friction of cutter and workpiece and smear metal then can produce continuous signal and instantaneous signal and alternately occur as important emission source.Cutting-tool by sound emission wear detector by Northwestern Polytechnical University's development is declared patent of invention in nineteen ninety, and its number of patent application is " 90109433.1 ".The name of this device is called " cutting-tool by sound emission failure detection instrument ".This patent of invention is characterised in that with acoustic emission signal " rate of rise and comprise the equal threshold voltage of some sampled points before the maximum peak voltage " as the standard of the degree of wear, judges the omen of the wearing and tearing of cutter.
Summary of the invention: at above-mentioned the deficiencies in the prior art, the utility model provides a kind of can detect cutter abrasion detection device exactly.
For achieving the above object, the technical solution adopted in the utility model is: the tool wear detector comprises calibrate AE sensor (4), preamplifier (5), signal condition module (6), signal processing module (7) and display control module (8).Calibrate AE sensor (4) is adsorbed on the back side of the knife rest (3) that is equipped with cutter (2) by the magnet of shell, and its output inserts preamplifier (5).Preamplifier (5) inserts signal condition module (6) by signal cable A (12), the output of signal condition module (6) is connected with signal processing module (7) by signal cable B (11), expert database (9) is stored in the interior memory of signal processing module (7), and display control module (8) is connected by serial communication cable (10) with signal processing module (7).
The characteristics in source take place according to acoustic emission signal in the utility model, when different cutters and different workpieces are cut, cutter from sharp to damaged in the process feature of each stage sound carry out interpretation of records, set up an expert database then.Expert database is deposited in the memory of signal processing module, can discern in the different Tool in Cutting different workpieces processes, detect the abrasion condition of cutter and make important basis for acquisition processing module.
Description of drawings:
Fig. 1 is a structural representation of the present utility model.
Fig. 2 is the circuit diagram of signal condition module.
Fig. 3 is an if bandpas filter U10 circuit diagram.
Fig. 4 is a medium-high frequency bandpass filter U9 circuit diagram.
Fig. 5 is the signal processing module theory diagram.
Fig. 6 is the digital signal waveform figure of acoustic emission.
Fig. 7 is the FB(flow block) of detection method of the present utility model.
Fig. 8 is a workflow diagram of the present utility model.
The specific embodiment:
As shown in Figure 1: the tool wear detector comprises calibrate AE sensor 4, preamplifier 5, signal condition module 6, signal processing module 7, display control module 8.Calibrate AE sensor 4 is adsorbed on the back side of the knife rest 3 that is equipped with cutter 2 by the magnet of shell, and its output inserts preamplifier 5.Preamplifier 5 inserts signal condition module 6 by signal cable A12, the output of signal condition module 6 is connected with signal processing module 7 by signal cable B11, expert database 9 is stored in the memory in the signal processing module 7, and display control module 8 is connected by serial communication cable 10 with signal processing module 7.
Calibrate AE sensor 4 is critical components of native system, is used to detect faint acoustic emission signal, converts acoustic emission signal to the signal of telecommunication and sends into preamplifier 5 and further change.Use the sensor of different structure and performance according to the different mining of testing goal and environment.Wherein, the resonant mode high sensor be use in the acoustic emission detection maximum a kind of.The selection of sensor should be determined according to tested acoustic emission signal.At first to consider the frequency range of tested acoustic emission signal and the feature of amplitude range and noise signal, select to pay close attention to acoustic emission signal sensitive of frequency domain then and the insensitive sensor of noise is tested, thus the sensor of selecting corresponding frequencies according to the feature and the testing goal of measurand.The single-ended resonant transducer of PXR30 that this device selects for use Beijing roc Xiang company to produce, its resonant frequency is the needs that 300khz satisfies this device, and it mainly is that piezoelectric chip constitutes, and just wafer one end is done reception work, the other end free time.This sensor is formed part and is also comprised diaphragm, shell, contact conductor, Outlet line, magnet, and the negative pole face of piezoelectric element is sticked on the base with conducting resinl; The another side lead-in wire is connected the earthing of casing with the heart yearn of high-frequency socket.
Preamplifier 5: the signal voltage of sensor output is very low, and these faint signals signal intensity attenuation after long Distance Transmission needs by preamplifier signal to be brought up to a certain degree, and improves the signal to noise ratio of signal.In acoustic emission system, preamplifier 5 is being controlled the size of whole system noise, and preamplifier occupies an important position.This device adopts the PXPA II type preamplifier of Beijing roc Xiang company, and gaining is 40db, and bandwidth is 15khz-1Mhz, and have that volume is little, advantage such as shock resistance, noise are low.
As shown in Figure 2, signal condition module 6 comprises: signal amplitude is adjusted circuit 21, filter channel is selected circuit 22,240k-310k medium-high frequency band-pass filter U9 and 20k-80k if bandpas filter filtering U10 and differential amplifier circuit 23.The signal voltage of preamplifier 5 outputs is imported by J1; pass through the DC component in capacitor C 28 filtered signals then; and adopt the mode of resistance R 47, R48 series connection dividing potential drop to adjust amplitude; voltage signal decay 1/5 with preamplifier 5 outputs; and the overvoltage crowbar of being made up of diode D1 and 2.5v voltage-stabiliser tube D2, D3 in parallel, the signal of assurance after dividing potential drop is less than 2.5v.Through signal after R47, the R48 dividing potential drop and the pin two of multi-channel gating device U7,7,10,15 are connected, the pin 3 of multi-channel gating device U7,14 link to each other with the medium-high frequency bandpass filter U9 input of 240k-310k, and the output pin 6,11 of U7 links to each other with the if bandpas filter U10 input of 20k-80k; 3,14 of the medium-high frequency bandpass filter U9 output of 240k-310k and multi-channel gating device U8 links to each other 6 of the if bandpas filter U10 of 20k-80k and U8,11 pins link to each other, 2,7 of U8,10,15 pins are imported 8 pins by resistance R 31 and the forward of differential amplifier U11 and are linked to each other.Control signal wire Ctrl_input and multi-channel gating device U7,8,9 pins of U8 link to each other and link to each other with the base stage of triode Q1 by resistance R 45, multi-channel gating device U7, and 1,16 pins of U8 are connected with the colelctor electrode of triode Q1.When control signal wire Ctrl_input was high level, 8,9 pins of U7, U8 were high level, and 1,16 pins of U7, U8 are low level, thereby the medium-high frequency bandpass filter U9 passage that makes 240k-310k is by gating; When control signal wire Ctrl_input was low level, 8,9 pins of U6, U7 were low level, and 1,16 pins of U6, U7 are high level, thus the time 20k-80k if bandpas filter U10 passage by gating.
Differential amplifier U10 be with filtered signal become two-way differential wave+OUTPUT and-OUTPUT, this two paths of signals is phase phasic difference 180 degree each other, has so also eliminated certain common mode disturbances.
Wave filter, generally form by reactance component, introduce according to the front, our interested frequency range is generally in distribution intermediate frequency or medium-high frequency, and 20k-80k if bandpas filter U10 carries out the midband pass filter and 240k-310k medium-high frequency bandpass filter U9 carries out the medium-high frequency bandpass filtering so the setting of this device has been designed.
As shown in Figure 3,20k-80k if bandpas filter U10 is made of the 5 rank high pass Butterworth filters 17 of a cut-off frequency 20khz and cut-off frequency 80khz5 rank low pass Butterworth filter 18 series connection.In the 5 rank high pass Butterworth filters 17 of 20khz by five electric capacity of C1=C2=C3=C4=C5=10nF of decision filtering cut-off frequency and five resistance of R3=R4=R3=R8=R9=800 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U1A, U2A, U2B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.8k Ω * 10nf=19.9khz.In the 5 rank high pass Butterworth filters (18) of 20khz by five electric capacity of C6=C7=C8=C9=C10=10nF of decision filtering cut-off frequency and five resistance of R3=R4=R3=R8=R9=200 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U1A, U3A, U3B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.2k Ω * 10nf=79.6khz.After two wave filter series connection, just formed an if bandpas filter U10 that passband is 20k-80khz.
As shown in Figure 4,240k-310 medium-high frequency bandpass filter U9 is made of the 5 rank high pass Butterworth filters 19 of a cut-off frequency 240khz and 5 rank low pass Butterworth filters, 20 series connection of a cut-off frequency 310khz.In the 5 rank high pass Butterworth filters 17 of 240khz by five electric capacity of C11=C12=C13=C14=C15=3.3nF of decision filtering cut-off frequency and five resistance of R25=R26=R27=R30=R31=155 Ω with determine the R23 of wave filter quality factor, R24, R28, R29, R32, R33 and three operational amplifier U4A, U5A, U5B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*155 Ω * 3.3nf=311khz.In the 5 rank high pass Butterworth filters 18 of 20khz by five electric capacity of C16=C17=C18=C19=C20=3.3nF of decision filtering cut-off frequency and five resistance of R34=R39=R40=R41=R42=200 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U4B, U6A, U6B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.2k Ω * 3.3nf=241kh.After two wave filter series connection, just formed a medium-high frequency bandpass filter U9 that passband is 240k-310khz.
As shown in Figure 5, signal condition module 6 is connected by cable with AD module in the signal processing module 7, signal processing module 7 comprises: AD module (ADC, Analog to Digital Converter), FPGA (Field Programmable Gate Array, field programmable gate array), RAM memory (Random Access Memory random access memory), DSP (Digital Signal Processor, digital processing chip), FLASH memory (flash memories chip), serial line interface, USB interface and peripheral circuit thereof are formed.The result of AD module access reference voltage analog digital conversion is connected with FPGA by 16 output port, and FPGA is connected with address wire by 32 position datawires with the RAM memory, and is connected with the DSP core with address bus for data/address bus by 32.DSP is connected with data/address bus by 16 bit address with the flash memory, and is connected by communication interface with USB interface with serial line interface.External power source is received on the input of power module, and the output port of power module is connected with FPGA with DSP, for it provides DC voltage-stabilizing.Cutter is in process, the acoustic emission signal that produces is received by calibrate AE sensor 4, and acoustic emission signal converted to behind the signal of telecommunication amplify by the preamplifier 5 that is attached thereto, carry out processing such as amplitude adjustment, filtering through signal condition module 6, signal processing module 7 converts thereof into digital waveform signal again.
Analog-digital converter is the system that analog signal conversion is become data signal.Two important indicators of digital to analog converter are sample frequencys of weighing the sampling resolution of conversion accuracy and influencing conversion speed.According to shannon formula, sample frequency is greater than 2 times of sampled signal highest frequency, will in this device the medium-high frequency signal of the highest 310khz carry out digital-to-analogue conversion, the sample frequency of selection digital to analog converter just must be greater than 620khz, in practice sample frequency preferably the sampled signal highest frequency 5-10 doubly, this device adopts the 16 figure place mould conversion chips of the AD7621 of AD company, and sample frequency 2.5MHz fully satisfies the needs of this device.
DSP (Digital Signal Processor) is a kind of microprocessor of uniqueness, is the device of handling bulk information with data signal.This device adopts dsp chip to carry out the collection and the analysis of data, and the output control signal is controlled wave filter and exported cutting-tool wear state information etc. by serial ports.
FPGA (Field Programmable Gate Array, field programmable gate array), it occurs as the semi-custom circuit in special IC (ASIC) field, and has solved the deficiency of custom circuit, has overcome original programming device door again and has counted the limited shortcoming of circuit number.FPGA also has inner abundant trigger and I/O pin and speed is fast, low in energy consumption, the compatible good advantage of level in addition.DSP and FPGA are integrated on the chip piece, can realize The Wideband Signal Processing, improve conversion speed greatly.This device adopts the SECO of collection, storage and the transmission of fpga chip control analog-digital converter and RAM memory and DSP.
RAM memory (Random Access Memory, easy assess memorizer) because RAM memory read writing rate is fast, uses the data that it comes buffer memory ADC to transmit in this device, treat that DSP handles through row.
FLASH memory (flash memories), the FLASH memory directly links to each other with DSP, the expert database that uses in the program of use FLASH memory stores DSP and the identification in this device.
Expert database 9: this device is at a built-in database that quantizes about cutting-tool wear state.In cutting tool state detects, system detects a large amount of real-time cutting tool state information, thereby demarcate the wearing and tearing rank of cutter in order to handle these information, need be according to experience and test for data was as judgment basis in the past, and different cutters is different during according to decision data with different processing work institute.Expert database 9 is with regard to good this problem that solved, and it is exactly a database that has different cutters and a judgment basis of different processing work combinations.
Be illustrated in figure 6 as the digital waveform figure of 15000 sampled points.The dsp chip of signal processing carries out Treatment Analysis to signal, and with expert database in the rate of exchange mutually of corresponding judgment basis data, thereby judge the tool wear rank, last dsp chip by serial line interface to real control section output result.
Shown in Fig. 7 detection method block diagram, this device carries out the feature extraction of 3 aspects to it after getting access to the digital waveform of acoustic emission signal.One carries out the frequency-domain analysis of FFT (FastFourier Transform, Fast Fourier Transform (FFT)) to the original figure waveform, and analysis result is as feature 1, for example the power spectral density of signal.Its two, original digital waveform is carried out time-domain analysis, analysis result is as feature 2, for example the peak-to-peak value of signal, root-mean-square value etc.Its three, primary signal is carried out the time-frequency domain analysis of DWT (Discrete Wavelet Transform, wavelet transform), analysis result is as feature 3, for example the energy of frequency band at all levels after the signal wavelet decomposition.From the feature of three aspects that original waveform extracts, comprising the information of some repeated content and some interference, so feature input feature vector analytical system will be carried out the optimization with characteristic parameter of deleting of duplicate keys and distracter.Wearing and tearing judgement system can be according to the sample characteristics parameter self training in the expert database, judges system from the wearing and tearing that the characteristic parameter of characteristic analysis system output will be sent into after the training, and the grade of the tool wear that is output as is reported to the police according to this grade at last.
As shown in Figure 8, after device was opened, the first step was sent filter channel by dsp chip and is selected signal to determine that filter range is the medium-high frequency of intermediate frequency or the 240k-310khz of 20k-80khz; In second step, device begins to gather the digital waveform of acoustic emission signal, and feature is extracted in its analysis of carrying out time domain, frequency domain, time-frequency domain; In the 3rd step, to being optimized of the characteristic parameter that repeats, what use in this example is that the method for pivot analysis (PCA, Principal Component Analysis) is optimized; The 4th step, judging weares and teares judges whether system trains, if not training, then reading the respective sample of expert database trains, if train, signal characteristic parameter input wearing and tearing judgement system after then will optimizing carries out the classification of the degree of wear, and what the wearing and tearing judgement system in this example used is neutral net; In the 5th step, system according to the alarm threshold value in wearing and tearing rank and the expert database relatively judges and reports to the police.
Claims (7)
1. the tool wear detector is characterized in that: comprise calibrate AE sensor (4), preamplifier (5), signal condition module (6), signal processing module (7) and display control module (8); Calibrate AE sensor (4) is adsorbed on the back side of the knife rest (3) that is equipped with cutter (2) by the magnet of shell, and its output inserts preamplifier (5); Preamplifier (5) inserts signal condition module (6) by signal cable A (12), the output of signal condition module (6) is connected with signal processing module (7) by signal cable B (11), expert database (9) is stored in the interior memory of signal processing module (7), and display control module (8) is connected by serial communication cable (10) with signal processing module (7).
2. tool wear detector as claimed in claim 1, it is characterized in that described signal condition module (6) comprising: signal amplitude is adjusted circuit (21), filter channel is selected circuit (22), 240k-310k medium-high frequency band-pass filter U9 and 20k-80k if bandpas filter filtering U10 and differential amplifier circuit (23); The signal voltage of preamplifier (5) output is imported by J1, pass through the DC component in capacitor C 28 filtered signals then, and adopt the mode of resistance R 47, R48 series connection dividing potential drop to adjust amplitude, voltage signal decay 1/5 with preamplifier (5) output, and the overvoltage crowbar of forming by diode D1 and 2.5v voltage-stabiliser tube D2, D3 in parallel, the signal of assurance after dividing potential drop is less than 2.5v; Through signal after R47, the R48 dividing potential drop and the pin two of multi-channel gating device U7,7,10,15 are connected, and the pin 3,14 of U7 is gone into end with the defeated U9 of the medium-high frequency bandpass filter of 240k-310k and linked to each other, the output pin 6,11 of U7 links to each other with the if bandpas filter U10 input of 20k-80k; 3 of the medium-high frequency bandpass filter U9 output of 240k-310k and multi-channel gating device U8,14 link to each other, 6 of the if bandpas filter U10 of 20k-80k and multi-channel gating device U8,11 pins link to each other, 2 of multi-channel gating device U8,7,10,15 pins are imported 8 pins by resistance R 31 and the forward of differential amplifier U11 and are linked to each other; Control signal wire Ctrl_input and multi-channel gating device U7,8,9 pins of U8 link to each other and link to each other with the base stage of triode Q1 by resistance R 45, multi-channel gating device U7, and 1,16 pins of U8 are connected with the colelctor electrode of triode Q1.
3. tool wear detector as claimed in claim 2, it is characterized in that described 20k-80k if bandpas filter U10 is made of the 5 rank high pass Butterworth filters (17) of a cut-off frequency 20khz and cut-off frequency 80khz5 rank low pass Butterworth filters (18) series connection; In the 5 rank high pass Butterworth filters 17 of 20khz by five electric capacity of C1=C2=C3=C4=C5=10nF of decision filtering cut-off frequency and five resistance of R3=R4=R3=R8=R9=800 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U1A, U2A, U2B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.8k Ω * 10nf=19.9khz; In the 5 rank high pass Butterworth filters (18) of 20khz by five electric capacity of C6=C7=C8=C9=C10=10nF of decision filtering cut-off frequency and five resistance of R3=R4=R3=R8=R9=200 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U1A, U3A, U3B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.2k Ω * 10nf=79.6khz.
4. tool wear detector as claimed in claim 2 is characterized in that: described 240k-310 medium-high frequency bandpass filter U9 is connected by the 5 rank low pass Butterworth filters (20) of the 5 rank high pass Butterworth filters (19) of a cut-off frequency 240khz and a cut-off frequency 310khz to constitute; In the 5 rank high pass Butterworth filters 17 of 240khz by five electric capacity of C11=C12=C13=C14=C15=3.3nF of decision filtering cut-off frequency and five resistance of R25=R26=R27=R30=R31=155 Ω with determine the R23 of wave filter quality factor, R24, R28, R29, R32, R33 and three operational amplifier U4A, U5A, U5B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*155 Ω * 3.3nf=311khz; In the 5 rank high pass Butterworth filters 18 of 20khz by five electric capacity of C16=C17=C18=C19=C20=3.3nF of decision filtering cut-off frequency and five resistance of R34=R39=R40=R41=R42=200 Ω with determine the R1 of wave filter quality factor, R2, R6, R7, R10, R11 and three operational amplifier U4B, U6A, U6B constitute, as calculated cut-off frequency f=1/2 π R1C1=1/2*3.14*0.2k Ω * 3.3nf=241kh.
5. tool wear detector as claimed in claim 1 is characterized in that, described signal processing module (7) comprising: analog-to-digital conversion module, FPGA, DSP, FLASH memory, serial line interface, USB interface and peripheral circuit thereof are formed; The result of AD module access reference voltage analog digital conversion is connected with FPGA by the output port of 16 position datawires, FPGA is connected with address wire by 32 position datawires with the RAM memory, and is connected with the DSP core with address bus for data/address bus by 32; DSP is connected with data/address bus by 16 bit address with the flash memory, and is connected by communication interface with USB interface with serial line interface; External power source is received on the input of power module, and the output port of power module is connected with FPGA with DSP; Signal condition module (6) is connected by cable with AD module in the signal processing module (7).
6. tool wear detector as claimed in claim 1 is characterized in that, its resonant frequency of described calibrate AE sensor (4) is 300khz.
7. tool wear detector as claimed in claim 1 is characterized in that, described preamplifier (5) gain is 40db, and bandwidth is 15khz-1Mhz.
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| CN102001023A (en) * | 2010-12-24 | 2011-04-06 | 沈阳飞机工业（集团）有限公司 | Tool wear detector |
| CN102680504A (en) * | 2012-05-11 | 2012-09-19 | 复旦大学 | Method for representing wear manner of ultrahard cubic boron nitride (CBN) cutting tool |
| CN102785127A (en) * | 2012-08-16 | 2012-11-21 | 北京理工大学 | Microminiature machining cutting force real-time wireless detection and control system |
| CN105352420A (en) * | 2015-11-09 | 2016-02-24 | 武汉大学 | TBM hobbing cutter wear online real-time monitoring device and monitoring method |
| CN108972152A (en) * | 2018-10-12 | 2018-12-11 | 哈尔滨理工大学 | A kind of sound-power detection method monitoring abrasion of cutting tool state |
| CN109834513A (en) * | 2017-11-28 | 2019-06-04 | 先驰精密仪器(东莞)有限公司 | Cutter state detection system and method |
| CN109974839A (en) * | 2017-12-27 | 2019-07-05 | 费希尔控制产品国际有限公司 | The method and apparatus for generating acoustic emission spectrum using amplitude demodulation |
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| CN110695766A (en) * | 2018-07-10 | 2020-01-17 | 先驰精密仪器(东莞)有限公司 | Cutter state detection system |
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| TWI732977B (en) * | 2017-01-20 | 2021-07-11 | 日商迪思科股份有限公司 | Cutting device |
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| CN102001023A (en) * | 2010-12-24 | 2011-04-06 | 沈阳飞机工业（集团）有限公司 | Tool wear detector |
| CN102001023B (en) * | 2010-12-24 | 2013-10-16 | 沈阳飞机工业（集团）有限公司 | Tool wear detector |
| CN102680504A (en) * | 2012-05-11 | 2012-09-19 | 复旦大学 | Method for representing wear manner of ultrahard cubic boron nitride (CBN) cutting tool |
| CN102785127A (en) * | 2012-08-16 | 2012-11-21 | 北京理工大学 | Microminiature machining cutting force real-time wireless detection and control system |
| CN102785127B (en) * | 2012-08-16 | 2014-07-02 | 北京理工大学 | Microminiature machining cutting force real-time wireless detection and control system |
| CN105352420A (en) * | 2015-11-09 | 2016-02-24 | 武汉大学 | TBM hobbing cutter wear online real-time monitoring device and monitoring method |
| CN105352420B (en) * | 2015-11-09 | 2017-11-14 | 武汉大学 | A kind of TBM hob abrasion on-line real time monitoring device and monitoring method |
| TWI732977B (en) * | 2017-01-20 | 2021-07-11 | 日商迪思科股份有限公司 | Cutting device |
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