CN109834512A - Two tooth helical end mills cutter tooth radius error calculation methods - Google Patents
Two tooth helical end mills cutter tooth radius error calculation methods Download PDFInfo
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Abstract
The present invention relates to a kind of two tooth helical end mills cutter tooth radius error calculation methods, establish milling force test system, carry out signal acquisition；Abnormality value removing processing and WAVELET PACKET DECOMPOSITION threshold denoising are carried out to the milling force signal of acquisition, according to the asymmetrical characteristic of milling force signal in asymmetric cylinder slotting cutter milling process, construction length, short tooth name Milling Force, using length, the respective nominal Milling force parameter of the nominal Milling Force creation of short tooth, the characteristics of not changed with milling radius change according to Milling force parameter in milling process, establish cylindrical screw slotting cutter radius of turn error identification formula, according to the radius error of foundation identify formula can fast and easy realize cutter radius of turn error identification, it solves helical end mills radius of turn asymmetric error and is not easy the difficult point measured.The present invention can calculating that is accurate, fast implementing milling cutter radius of turn error, there is important practical significance to abrasion detection of milling cutter radius of turn in milling cutter accuracy detection, mechanical processing process etc..
Description
Technical field
The present invention relates to a kind of processing technology, in particular to a kind of two tooth helical end mills cutter tooth radius error calculating sides
Method.
Background technique
The geometric accuracy of milling cutter has direct influence to the processing quality of workpiece, and wherein milling cutter tooth radius error is shadow
One of the main reason for ringing workpiece processing quality mainly estimates milling cutter tooth half by measuring milling cutter diameter in industry at present indirectly
Diameter size, this detection method do not account for the eccentricity issues of milling cutter rotation centerline, i.e., reach technical requirements in milling cutter diameter
Under the premise of, due to the bias (in actual processing inevitable) of milling cutter rotation center in manufacturing process cause milling cutter occur it is long,
Short tooth.Meanwhile to will cause cutter Milling Force in a swing circle of different sizes for milling cutter tooth asymmetry, causes milling process
It is unstable, it is also easy to produce flutter.
Summary of the invention
The problem of directly affecting the processing quality of workpiece the present invention be directed to the accurate selection of milling cutter, proposes a kind of two teeth
Helical end mills cutter tooth radius error calculation method is constructed according to long and short tooth name Milling Force and is solved by constructing nominal Milling Force
Milling force parameter is analysed, two-edged helical end mills cutter tooth radius error equation is established according to the characteristics of parsing Milling force parameter, in turn
Obtain accurate cutter tooth radius error value, can it is accurate, quickly, facilitate the identification for realizing cutter tooth radius error, meanwhile, for cutter tooth
Radius is symmetrical and the asymmetric situation of machine tool chief axis radius of turn, can also obtain the jump of machine tool chief axis radius of turn through the invention
Dynamic degree.
The technical solution of the present invention is as follows: a kind of two tooth helical end mills cutter tooth radius error calculation methods, specifically include as
Lower step:
1) milling force test system is established, carry out signal acquisition: milling force test system includes two-edged helical bottom vertical milling
Knife, thin-wall workpiece, Kistler dynamometer, high impedance data line, charge amplifier, data collecting card and computer；
Thin-wall workpiece is the inverted T shaped workpiece being made of mounting seat and cantilever design, and mounting seat is under inverted T shaped workpiece
Plane has location hole in mounting seat, and the mounting seat of thin-wall workpiece is fixed on Kistler dynamometer by location hole,
Kistler dynamometer lower surface is fixed on workbench, and cantilever design intersects as the plane machining part for having thickness with mounting seat
Line direction is horizontal X axis direction, is in parallel processing plane with the X/Y plane of mounting seat；
When milling, mill principal axis drives milling cutter rotation, and it is vertical that milling cutter carries out side to the cantilever design side of thin-wall workpiece
Active force between cutter and workpiece is transformed into charge signal by milling, Kistler dynamometer, and signal is through high impedance data line
It is sent to charge amplifier, charge signal is converted to voltage signal by charge amplifier, and data collecting card adopts voltage signal
Collection, and store data into computer, the experiment of n group is carried out as needed；2) exceptional value is carried out to the milling force signal of acquisition to pick
Except processing, handled according to milling force signal of the formula (1) to acquisition,
|xi-μX| > ε σ (1)
Wherein xiFor the collection value of i-th, μXFor the average value of sample, σ is the variance of sample, and ε is adjusting parameter；3) small
The denoising of wave packet decomposition threshold: being filtered signal using wavelet packet noise-removed technology, obtain true milling force signal, with
Zero-drifting processing is carried out to filtered signal afterwards；
4) construct nominal Milling Force: nominal Milling Force constructs Milling Force by the Milling Force of single tooth, is believed according to Milling Force
Number feature, constructs long and short tooth name Milling Force；
5) milling cutter tooth radius asymmetric error formula is constructed, asymmetric error identification equation is established according to formula (9), is used
Newton Solving Nonlinear Equation method solves equation (9), obtains n group and tests corresponding long and short tooth radius；According to experiment
Data establish the confidence interval that cutter tooth radius confidence level is 0.975, real using the mean value of confidence interval of mean as long and short tooth
Border radius value；Corresponding helical end mills cutter tooth asymmetric error value is obtained by formula (12)；
Wherein,
pl, psRespectively milling edge long tooth, short tooth and cutting when the angle that turns over of cutter；
cl, cs is respectively long tooth, the feed engagement of short tooth；
rl, rsRespectively long tooth, short tooth radius of turn；
θex, θstIt respectively refers to cutter incision, cut out angle；A is axial cutting depth；λ is cutting edge inclination；
Respectively X, the average value of Y-direction long tooth, short tooth name Milling Force；
For the real-time rotational angle of milling cutter；
Milling cutter tooth semidiameter: rdeviation=rlmean-rsmean (12)
Take rlMean value, rsThe mean value of mean value interval is as long and short tooth radius of turn rlmean、rsmean。
Specific step is as follows for the WAVELET PACKET DECOMPOSITION threshold denoising of the step 3):
According to Milling Force signal characteristic, filtering threshold is determined using Sqtwolog rule:
(1) WAVELET PACKET DECOMPOSITION of signal: selection Daubechies wavelet basis carries out N layers of wavelet packet point to milling force signal
Solution；
(2) threshold value quantizing of WAVELET PACKET DECOMPOSITION high frequency coefficient: simultaneously to the high frequency coefficient threshold value under each decomposition scale
Carry out thresholding processing；
(3) wavelet reconstruction wavelet package reconstruction: is carried out according to n-th layer WAVELET PACKET DECOMPOSITION low frequency coefficient and quantification treatment coefficient；
(4) static null offset is rejected: there is static drift in entire measuring system, to the signal after wavelet packet threshold denoising
Carry out drift rejecting processing.
The beneficial effects of the present invention are: two tooth helical end mills cutter tooth radius error calculation methods of the invention, it can be accurate
The error for identifying cutter tooth radius, solves the problems, such as that cutter tooth radius is not easy to measure.The mentioned method of the present invention is applicable not only to two teeth
The identification of helical end mills radius of turn, the expansible identification problem for multiple tooth helical end mills radius of turn.The method
It can be applied to judge in tool wear quantifier elimination by milling force signal that there is important meaning in metal cutting process
Justice.
Detailed description of the invention
Fig. 1 is Milling Force measurement system diagram of the present invention；
Fig. 2 is thin-wall workpiece structure chart of the present invention；
Fig. 3 is that Milling Force acquisition system of the present invention acquires original signal figure；
Fig. 4 is that Milling Force acquisition system of the present invention acquires signal waveform diagram after abnormality value removing；
Fig. 5 is the waveform diagram after WAVELET PACKET DECOMPOSITION of the present invention denoising；
Fig. 6 is that the present invention eliminates the waveform diagram after drift；
Fig. 7 is milling cutter short tooth name Milling Force Model figure of the present invention；
Fig. 8 is milling cutter long tooth name Milling Force Model figure of the present invention；
Fig. 9 is two tooth milling cutters deviation of the invention and the practical milling thickness chart of per tooth.
Specific embodiment
Two tooth helical end mills cutter tooth radius asymmetric error calculation methods, by milling force test system to Milling Force into
Row acquisition constructs nominal Milling Force according to long and short tooth milling force signal, passes through nominal Milling Force and the spy of nominal Milling force parameter
Point identifies cutter tooth radius error.
In terms of the content of present invention mainly has following two:
1, the building of test platform.Test platform is mainly designed two parts and is formed by Milling Force test and thin-wall construction, such as
Milling Force measurement system diagram shown in Fig. 1, wherein milling force test system is mainly by two-edged spiral flat-bottom end mill 1, thin-wall workpiece
2, Kistler dynamometer 3, high impedance data line 4, charge amplifier 5, data collecting card 6 and computer 7 form；Such as Fig. 2
Shown 2 structure chart of thin-wall workpiece, thin-wall workpiece 2 are the inverted T shaped workpiece being made of mounting seat 10 and cantilever design, install bottom
Seat 10 is inverted T shaped workpiece lower plane, has 4 location holes 9 in mounting seat 10, the mounting seat 10 of thin-wall workpiece 2 passes through positioning
Hole 9 is fixed on Kistler dynamometer 3, and Kistler dynamometer lower surface is fixed on workbench, and cantilever design 11, which is used as, thickness
The plane machining part of degree, cantilever design 11 is Z-direction perpendicular to 10 direction of mounting seat, with 10 intersecting lens direction of mounting seat
For horizontal X axis direction, it is in parallel Y direction with 10 thickness direction of mounting seat, is in parallel to add with the X/Y plane of mounting seat 10
Work plane.When milling, mill principal axis 8 drives milling cutter 1 to rotate, and milling cutter 1 carries out side to 11 side of cantilever design of thin-wall workpiece 2
Active force between cutter and workpiece is transformed into charge signal by vertical milling, Kistler dynamometer 3, and signal is through high impedance data
Transmission line 4 is sent to charge amplifier 5, and charge signal is converted to voltage signal by charge amplifier 5, and data collecting card 6 is to voltage
Signal is acquired, and is stored data into computer 7.
The Milling Force generated when the Kistler dynamometer 3 is by piezoelectric effect by milling is converted to charge signal.
The high impedance data line 4 is to transmit charge signal, and the quantity of electric charge that dynamometer 3 obtains is smaller, and
It is easy leakage, small quantity of electric charge charge can be carried out safe transmission by high impedance data line.
The charge amplifier 5 is that voltage signal is amplified and be converted into charge, the charge signal of dynamometer output
It is fainter, to need charge amplifier 5 to amplify charge and being converted to voltage signal convenient for acquisition.
The data collecting card 6 is that the electric signal of amplification is acquired quantization.To store, handling convenient for computer and divide
Analysis needs to carry out binary quantization to signal, and capture card 6 can complete the purpose.
The computer 7 is to be stored, handled and analyzed to signal.The signal of acquisition algorithm pair by the method for the invention
Signal is handled, to obtain milling cutter radius asymmetric error value.
2, Milling Force signal denoising is handled.The milling force signal acquired by test macro unavoidably exists random dry
It disturbs, leading to the data of acquisition, there are abnormal datas, simultaneously because the radial cutting-in of thin-wall part is smaller in experiment, milling force signal is close
Like being impact signal, unavoidably there is the problems such as material is uneven in workpiece, the signal of actual measurement belongs to non-stationary signal, is
Signal is taken into account in the localization and overall picture of time domain and frequency domain, based on the above reasons, to improve Milling force parameter accuracy of identification, is needed
Measuring signal is pre-processed, according to measurement Milling Force characteristics of signals, using singular value rejecting and WAVELET PACKET DECOMPOSITION method pair
Milling force signal carries out denoising, denoises step mainly in two steps:
2.1 abnormal data elimination
Unavoidably there are random disturbances in Milling Force acquisition system, leading to the data of acquisition, there are abnormal datas, to obtain
It is stable as a result, needing rejecting abnormalities data.Abnormal data is rejected using Chauvenet and Gubbs formula in text, table
Up to formula are as follows:
|xi-μX| > ε σ (1)
Wherein xiFor the collection value of i-th, μXFor the average value of sample, σ is the variance of sample, and ε is that (ε's takes adjusting parameter
Value is determined according to signal characteristic).
Milling Force acquisition system acquisition original signal figure as shown in Figures 3 and 4 and the waveform diagram after abnormality value removing, comparison
It can be seen that abnormal data is all removed substantially.
2.2 WAVELET PACKET DECOMPOSITION threshold denoisings
According to Milling Force signal characteristic, filtering threshold is determined using Sqtwolog rule in text, data handling procedure is as follows:
(1) WAVELET PACKET DECOMPOSITION of signal: selection wavelet basis (text in select Daubechies small echo) to milling force signal into
N layers of row (3 layers of Wen Zhongwei) WAVELET PACKET DECOMPOSITION.
(2) threshold value quantizing of WAVELET PACKET DECOMPOSITION high frequency coefficient: simultaneously to the high frequency coefficient threshold value under each decomposition scale
Carry out thresholding processing.
(3) wavelet reconstruction wavelet package reconstruction: is carried out according to n-th layer WAVELET PACKET DECOMPOSITION low frequency coefficient and quantification treatment coefficient.
Waveform diagram after WAVELET PACKET DECOMPOSITION denoising as shown in Figure 5.
(4) static null offset is rejected: there is static drift in entire measuring system, to the signal after wavelet packet threshold denoising
Carry out drift rejecting processing.The waveform diagram after drift is eliminated as shown in Figure 6.
3, construct nominal Milling Force: as can be seen from Figure 6, the cutting force of two tooth of milling cutter is different for the building of nominal Milling Force,
Since milling cutter has mismachining tolerance in the fabrication process, cause two tooth milling radiuses different, establish nominal Milling Force in text thus,
Milling Force is constructed by the Milling Force of single tooth, waveform milling cutter as shown in Figure 7,8 is short for construction, the nominal Milling Force Model of long tooth
Figure.
4, cutter tooth radius error identification formula is established: can get corresponding nominal Milling Force according to nominal Milling Force
Coefficient, shown in calculation formula such as formula (2)-(5).
The tangential Milling force parameter of long tooth
Long tooth radial direction Milling force parameter
The tangential Milling force parameter of short tooth
Short tooth radial direction Milling force parameter
Wherein parameter pl,psRespectively milling edge long tooth, short tooth and the angle that cutter turns over when cutting, may be expressed as:
θex, θstIt respectively refers to cutter incision, cut out angle；R is tool radius；A is axial cutting depth；λ is cutting edge inclination；
cl,csRespectively long tooth, the feed engagement of short tooth；
Respectively X, Y
The average value of direction long tooth, short tooth name Milling Force,It is the real-time rotational angle of milling cutter.
Milling process schematic diagram when Fig. 9 show cutter tooth asymmetry, wherein rlFor long tooth radius of turn, rsFor short tooth rotation
Radius, c are the theoretical amount of feeding, and Ω is the angular speed of milling cutter rotation.As can be seen from Figure 9, asymmetric (or the pirouette half of cutter tooth
Diameter is different) cause the practical radial milling thickness of long and short tooth different, and then cause long and short tooth Milling Force different, below according to
The nominal Milling Force of long and short tooth estimates milling cutter radius of turn, and then calculates practical Milling force parameter.According to tangential, radial milling
Force coefficient is unrelated with cutter radius of turn it is assumed that available:
The long and short tooth radius of turn of cutter, note are calculated by taking formula (7) as an exampleThe long and short tooth of cutter
Radius is obtained by formula (9).
Wherein,
The corresponding cutter radius of turn r of 16 groups of experiments can be obtained according to formula (9)l、rs, the results are shown in Table 1.
Table 1
| Experiment | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| rl | 4.027 | 4.029 | 4.026 | 4.028 | 4.028 | 4.023 | 4.025 | 4.026 |
| rs | 3.973 | 3.971 | 3.974 | 3.972 | 3.972 | 3.977 | 3.975 | 3.974 |
| Experiment | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 |
| rl | 4.025 | 4.024 | 4.029 | 4.023 | 4.031 | 4.022 | 4.025 | 4.026 |
| rs | 3.975 | 3.976 | 3.971 | 3.977 | 3.969 | 3.978 | 3.975 | 3.974 |
In milling experiment, random meausrement error (can be approximately considered Normal Distribution) is widely present, according to the number of table 1
According to, when available confidence level is β, the confidence interval of long and short tooth radius of turn mean and variance, as shown in formula (10)-(11).
Average value, the S of 1 tool radius of table: the variance of 1 data of table, n: number, the t of experimentβ/2(n-1): being t distribution
In quantile,Refer to χ2Quantile in distribution,
Selecting confidence level is 0.975, can get the confidence interval of mean value and variance according to formula (10)-(11):
rlConfidence interval of mean: (4.0245,4.0276)
rlThe confidence interval of variance: (0.0018,0.0041)
rsConfidence interval of mean: (3.9724,3.9755)
rsThe confidence interval of variance: (0.0018,0.0041)
Take rlMean value, rsThe mean value of confidence interval of mean is as long and short tooth radius of turn rlmean、rsmean, can get knife
Tooth semidiameter:
rdeviation=rlmean-rsmean=4.026-3.9739=0.0521 (12)
Milling experiment is carried out in Milling Centre, and Milling Force signal test system detects cutting force, and when experiment uses
Become feed engagement milling mode (other milling usages are constant), carrying out 16 groups of experiments, (main purpose is to eliminate in experiment at random
Interfere the influence to processing result), Milling Force acquisition system sample frequency is set as 10kHz.Data handling procedure of the invention is such as
Under:
Step 1: abnormality value removing processing being carried out to milling force signal, is carried out according to milling force signal of the formula (1) to acquisition
Processing；
Step 2: signal being filtered using wavelet packet noise-removed technology, obtains true milling force signal, then
Zero-drifting processing is carried out to filtered signal；
Step 3: constructing nominal Milling Force according to Milling Force signal characteristic and construct long and short tooth name Milling Force；
Step 4: building milling cutter tooth radius asymmetric error formula establishes asymmetric error identification equation according to formula (9),
Equation (9) is solved using newton Solving Nonlinear Equation method, obtains the corresponding long and short tooth radius of 16 groups of experiments, such as
Shown in table 1.The confidence interval that cutter tooth radius confidence level is 0.975 is established according to experimental data, with confidence interval of mean
Mean value is as long and short tooth real radius value.Corresponding helical end mills cutter tooth asymmetric error value is obtained by formula (12).
Claims (2)
1. a kind of two tooth helical end mills cutter tooth radius error calculation methods, which is characterized in that specifically comprise the following steps:
1) establish milling force test system, carry out signal acquisition: milling force test system includes two-edged spiral flat-bottom end mill, thin
Walled workpieces, Kistler dynamometer, high impedance data line, charge amplifier, data collecting card and computer；
Thin-wall workpiece is the inverted T shaped workpiece being made of mounting seat and cantilever design, and mounting seat is to put down under inverted T shaped workpiece
There is location hole in face in mounting seat, and the mounting seat of thin-wall workpiece is fixed on Kistler dynamometer by location hole,
Kistler dynamometer lower surface is fixed on workbench, and cantilever design intersects as the plane machining part for having thickness with mounting seat
Line direction is horizontal X axis direction, is in parallel processing plane with the X/Y plane of mounting seat；
When milling, mill principal axis drives milling cutter rotation, and milling cutter carries out side vertical milling to the cantilever design side of thin-wall workpiece,
Active force between cutter and workpiece is transformed into charge signal by Kistler dynamometer, and signal is sent to through high impedance data line
Charge signal is converted to voltage signal by charge amplifier, charge amplifier, and data collecting card is acquired voltage signal, and
It stores data into computer, carries out the experiment of n group as needed；
2) abnormality value removing processing is carried out to the milling force signal of acquisition, according to formula (1) to the milling force signal of acquisition at
Reason,
|xi-μX| > ε σ (1)
Wherein xiFor the collection value of i-th, μXFor the average value of sample, σ is the variance of sample, and ε is adjusting parameter；
3) WAVELET PACKET DECOMPOSITION threshold denoising: being filtered signal using wavelet packet noise-removed technology, obtains true milling
Force signal then carries out Zero-drifting processing to filtered signal；
4) construct nominal Milling Force: nominal Milling Force constructs Milling Force by the Milling Force of single tooth, special according to milling force signal
Point constructs long and short tooth name Milling Force；
5) milling cutter tooth radius asymmetric error formula is constructed, asymmetric error identification equation is established according to formula (9), using newton
Solving Nonlinear Equation method solves equation (9), obtains n group and tests corresponding long and short tooth radius；According to experimental data
The confidence interval that cutter tooth radius confidence level is 0.975 is established, using the mean value of confidence interval of mean as long and short tooth practical half
Diameter value；Corresponding helical end mills cutter tooth asymmetric error value is obtained by formula (12)；
Wherein,
pl, psRespectively milling edge long tooth, short tooth and cutting when the angle that turns over of cutter；
cl, cs is respectively long tooth, the feed engagement of short tooth；
rl, rsRespectively long tooth, short tooth radius of turn；
θex, θstIt respectively refers to cutter incision, cut out angle；A is axial cutting depth；λ is cutting edge inclination；
Respectively X, the average value of Y-direction long tooth, short tooth name Milling Force；
For the real-time rotational angle of milling cutter；
Milling cutter tooth semidiameter: rdeviation=rlmean-rsmean (12)
Take rlMean value, rsThe mean value of mean value interval is as long and short tooth radius of turn rlmean、rsmean。
2. two tooth helical end mills cutter tooth radius error calculation method according to claim 1, which is characterized in that the step
3) specific step is as follows for WAVELET PACKET DECOMPOSITION threshold denoising:
According to Milling Force signal characteristic, filtering threshold is determined using Sqtwolog rule:
(1) WAVELET PACKET DECOMPOSITION of signal: selection Daubechies wavelet basis carries out N layers of WAVELET PACKET DECOMPOSITION to milling force signal；
(2) it the threshold value quantizing of WAVELET PACKET DECOMPOSITION high frequency coefficient: to the high frequency coefficient threshold value under each decomposition scale and carries out
Thresholding processing；
(3) wavelet reconstruction wavelet package reconstruction: is carried out according to n-th layer WAVELET PACKET DECOMPOSITION low frequency coefficient and quantification treatment coefficient；
(4) static null offset is rejected: there is static drift in entire measuring system, carry out to the signal after wavelet packet threshold denoising
Drift rejecting processing.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110625437A (en) * | 2019-09-04 | 2019-12-31 | 中国工程物理研究院材料研究所 | Method for calibrating eccentric parameters of cutter in milling process |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3986010A (en) * | 1973-08-23 | 1976-10-12 | International Business Machines Corporation | Automatic tool deflection calibration system |
| CN101491844A (en) * | 2009-01-15 | 2009-07-29 | 西北工业大学 | Milling force coefficient and cutter radial eccentricity calibrating method in circular milling process |
| CN102436527A (en) * | 2011-11-10 | 2012-05-02 | 西北工业大学 | Milling force modeling method of milling process of countersinking vertical milling cutter |
| CN102500800A (en) * | 2011-09-26 | 2012-06-20 | 哈尔滨工业大学 | Open type intelligent milling system and milling method based on same |
| CN103258095A (en) * | 2013-05-14 | 2013-08-21 | 西北工业大学 | Universal milling force modeling method for flat-bottom end mill |
| CN103487189A (en) * | 2013-09-16 | 2014-01-01 | 同济大学 | Thin-walled part milling force coefficient identification method based on kernel partial least squares |
| CN103481121A (en) * | 2013-09-16 | 2014-01-01 | 同济大学 | Two-tooth helical end mill tooth radius asymmetry error detection system and method |
| CN105014461A (en) * | 2015-07-10 | 2015-11-04 | 河南科技大学 | High-efficiency gear milling processing method of spiral bevel gear precision forging tooth form mold |
-
2017
- 2017-11-27 CN CN201711204940.2A patent/CN109834512A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3986010A (en) * | 1973-08-23 | 1976-10-12 | International Business Machines Corporation | Automatic tool deflection calibration system |
| CN101491844A (en) * | 2009-01-15 | 2009-07-29 | 西北工业大学 | Milling force coefficient and cutter radial eccentricity calibrating method in circular milling process |
| CN102500800A (en) * | 2011-09-26 | 2012-06-20 | 哈尔滨工业大学 | Open type intelligent milling system and milling method based on same |
| CN102436527A (en) * | 2011-11-10 | 2012-05-02 | 西北工业大学 | Milling force modeling method of milling process of countersinking vertical milling cutter |
| CN103258095A (en) * | 2013-05-14 | 2013-08-21 | 西北工业大学 | Universal milling force modeling method for flat-bottom end mill |
| CN103487189A (en) * | 2013-09-16 | 2014-01-01 | 同济大学 | Thin-walled part milling force coefficient identification method based on kernel partial least squares |
| CN103481121A (en) * | 2013-09-16 | 2014-01-01 | 同济大学 | Two-tooth helical end mill tooth radius asymmetry error detection system and method |
| CN105014461A (en) * | 2015-07-10 | 2015-11-04 | 河南科技大学 | High-efficiency gear milling processing method of spiral bevel gear precision forging tooth form mold |
Non-Patent Citations (1)
| Title |
|---|
| 何光伟等: "基于切削力的刀具磨损检测", 《控制与检测》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110625437A (en) * | 2019-09-04 | 2019-12-31 | 中国工程物理研究院材料研究所 | Method for calibrating eccentric parameters of cutter in milling process |
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Application publication date: 20190604 |