CN105500115A - Detection system for tool chattering in milling and detection method thereof - Google Patents

Detection system for tool chattering in milling and detection method thereof Download PDF

Info

Publication number
CN105500115A
CN105500115A CN201610101766.8A CN201610101766A CN105500115A CN 105500115 A CN105500115 A CN 105500115A CN 201610101766 A CN201610101766 A CN 201610101766A CN 105500115 A CN105500115 A CN 105500115A
Authority
CN
China
Prior art keywords
cutter
signal
sigma
flutter
center
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201610101766.8A
Other languages
Chinese (zh)
Inventor
王保升
张蒙蒙
左健民
汪木兰
候军明
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing Institute of Technology
Original Assignee
Nanjing Institute of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing Institute of Technology filed Critical Nanjing Institute of Technology
Priority to CN201610101766.8A priority Critical patent/CN105500115A/en
Publication of CN105500115A publication Critical patent/CN105500115A/en
Pending legal-status Critical Current

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/09—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring cutting pressure or for determining cutting-tool condition, e.g. cutting ability, load on tool
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23Q—DETAILS, COMPONENTS, OR ACCESSORIES FOR MACHINE TOOLS, e.g. ARRANGEMENTS FOR COPYING OR CONTROLLING; MACHINE TOOLS IN GENERAL CHARACTERISED BY THE CONSTRUCTION OF PARTICULAR DETAILS OR COMPONENTS; COMBINATIONS OR ASSOCIATIONS OF METAL-WORKING MACHINES, NOT DIRECTED TO A PARTICULAR RESULT
    • B23Q17/00—Arrangements for observing, indicating or measuring on machine tools
    • B23Q17/12—Arrangements for observing, indicating or measuring on machine tools for indicating or measuring vibration

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)

Abstract

The invention discloses a detection system for tool chattering in milling and a detection method thereof, characterized by comprising following steps: 1), selecting a suitable displacement sampling window; 2), determining a center of a tool and vibration changes corresponding to the center of the tool by using a radius constrained least square method; 3), subjecting a tool vibration signal to empirical mode decomposition, and obtaining a time-frequency spectrum using HHT (Hilbert Huang transform); 4), verifying whether the time-frequency spectrum meets chattering rule. The invention has the advantages that the use of a non-contact detection method, using a laser displacement sensor, overcomes limitations such as size of a workpiece under processing, mass, a mounting mode, and high precision is provided; by studying the influence of milling chattering and tool eccentricity upon positional changes of the center of the tool, positional flutter of the center of circle of the tool is determined, and thus chattering change conditions of the tool are directly reflected; by using Hilbert Huang transform, the limitations of Fourier transform can be overcome and a time-frequency spectrum of signals can be better described.

Description

The detection system of cutter flutter in a kind of Milling Process and detection method thereof
Technical field
The present invention relates to detection system and the detection method thereof of cutter flutter in a kind of Milling Process, belong to processing detection technique field.
Background technology
High-rate wireless LAN has the outstanding advantages such as high efficiency, high machined surface quality, low manufacturing cost and short sawn timber construction cycle, is widely used in the manufacturing industry such as Aeronautics and Astronautics, mould, automobile, meets the demand of manufacturing industry development.But the various advantages of high-speed milling must be premised on the friction stable milling process under high rotating speed.In the process of milling, due to Milling Force and the effect of other uncertain load, often there is chatter phenomenon in process system.The generation of milling parameter not only can reduce the quality of workpiece machined surface, and can affect the service life of cutter and even lathe.In " made in China 2025 ", propose will develop high-end numerical control machine as " accelerate strategic must strive field ", vibrate and the modern machine of precise treatment is affected more so, the high accuracy that precision machine tool can ensure will in vibration processes degradation.Therefore, in order to ensure the high accuracy of this kind of lathe, often adopting measures such as reducing cutting data, reducing the stock-removing efficiency of processing, the value maximization that can not realize high precision machine tool uses.Meanwhile, the noise that flutter produces also can stimulation applications workman, reduces operating efficiency.
The detection method of milling parameter is mainly divided into contact and contactless two kinds.The fast development of sensor is that the detection of milling parameter provides more convenient method, the change analyzing cutting force in milling process is considered to the most direct, reflect oscillation phenomenon in working angles the most reliably, but the method practical operation is complicated, equipment needed thereby is very expensive.At the initial stage twenties, a lot of experts and scholars adopt contact type measurement mode, as piezoelectric type, strain-type force meter, measure the cutting force in milling process.In the processing environment that the modern times are changeable, contact type measurement mode also exists the limitation such as processing work size, mounting means.Voice signal also can reflect vibration signal, and at present, conventional is that ultrasonic sensor detects, and by the spectrum analysis to acoustical signal, thus analyze oscillation phenomenon, but this method exists the not high defect of precision.Correspondingly, find a kind of more perfect flutter detection technique, become the problem that this area needs solution badly.
Summary of the invention
For solving the deficiencies in the prior art, the object of the present invention is to provide detection system and the detection method thereof of cutter flutter in a kind of Milling Process, solve at present in Milling Processes, the very difficult poor efficiency of acquisition of a large amount of vibration signal, also can be subject to the problem of the composition influence had nothing to do with flutter to the analysis of vibrating signal.
In order to realize above-mentioned target, the present invention adopts following technical scheme:
A detection system for cutter flutter in Milling Process, is characterized in that, comprises displacement detecting unit, data acquisition unit, CPU; Described displacement detecting unit is arranged on Digit Control Machine Tool periphery; Described displacement detecting unit is for detecting the coordinate of the corresponding points of each moment tool surface; The signal transmission that described data acquisition unit is used for displacement detecting unit to detect is to CPU; The coordinate data that described CPU detects according to displacement detecting unit, determines the center of cutter and beating of center, is analyzed the vibration signal detected by HHT algorithm.
The detection system of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, described displacement detecting unit adopts multiple spot laser displacement sensor or several single-point laser sensors.
The detection system of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, described displacement acquisition unit adopts multi-channel data acquisition board.
The detection system of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, described displacement detecting unit is connected with CPU by USB data transmission line.
A detection method for cutter flutter in Milling Process, is characterized in that, comprises the steps:
1) suitable displacement sampling window is selected;
2) center of Radius Constraint least square method determination cutter and the vibration change at corresponding cutters center is adopted;
3) empirical mode decomposition is carried out to cutter vibration signal, utilize HHT to convert and obtain time-frequency spectrum;
4) verify whether time-frequency spectrum meets flutter rule, if meet, detect end, if inconsistent, return step 1), re-start detection, check whether other processes of Milling Process flutter occur.
The detection method of cutter flutter in aforesaid a kind of Milling Process, it is characterized in that, described step 2) in, CPU is when determining the center of cutter, the general principle of circle is become based on 3, extract the sampled point on circular arc, and in conjunction with the radius data of milling cutter, adopt the least square method based on Radius Constraint to carry out the determination of center cutter.
The detection method of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, described step 2) in, when Radius Constraint least square method adopts to the displacement signal of cutter acquisition surface, comprise the steps:
21) t is supposed ithe center cutter position of sampling instant is O (x i, y i), known cutter radius is R, utilizes displacement detecting unit to record m discrete sampling point (x ij, y ij), j=1,2,3..., m, m are t iinstance sample is counted, and makes (x ij, y ij) to O (x i, y i) quadratic sum of distance is minimum;
22) (x-x can be expressed as based on general equation of a circle i) 2+ (y-y i) 2=R 2, establish the Least Square Circle matching of Radius Constraint: C = Σ j = 1 m ( ( x - x i j ) 2 + ( y - y i j ) 2 - R 2 ) 2 , And object function is F ( a , b , c ) = Σ j = 1 m ( x i j 2 + y i j 2 + ax i j + by i j + c ) 2 , In formula: a = - 2 x i , b = - 2 y i , c = a 2 + b 2 - 4 R 2 4 ;
23) necessary condition of extreme value is asked to obtain according to the function of many variables: be expressed in matrix as: Σ j = 1 m x i j 2 Σ j = 1 m x i j y i j Σ j = 1 m x i j Σ j = 1 m x i j y i j Σ j = 1 m y i j 2 Σ j = 1 m y i j Σ j = 1 m x i j Σ j = 1 m y i j m a b c = - Σ j = i m ( x i j 3 + x i j y i j 2 ) - Σ j = i m ( x i j 2 y i j + y i j 3 ) - Σ j = i m ( x i j 2 + y i j 2 ) , Try to achieve corresponding x i, y icoordinate;
24) to all sampling instant t i, i=1,2,3 ..., n, n are sampling number, solve corresponding center cutter coordinate all as stated above, then can obtain cutter at X, Y-direction vibrating signal, X=[x 1, x 2..., x n], Y=[y 1, y 2..., y n].
The detection method of cutter flutter in aforesaid a kind of Milling Process, it is characterized in that, described step 3) in, when CPU adopts HHT algorithm to the analysis of cutter the center displacement signal, in Milling Processes, X, flutter rule in Y both direction is identical, just varies in size, and supposes in the flutter of X-direction maximum, carry out HHT change in X-direction, comprise the steps:
31) empirical modal EMD resolution process is carried out to displacement signal and obtain intrinsic mode IMF;
32) screening acquisition feature IMF component c is carried out to decomposing the N number of IMF component obtained i(t), i=1,2 ..., n, n are the number of feature IMF component, and signal remainder r (t), then primary signal X (t) can be expressed as all IMF and surplus sum: X (t)=c 1(t)+c 2(t)+... + c n(t)+r (t);
33) time-frequency spectrum of n feature IMF component is calculated respectively: according to formula: carry out HHT conversion, wherein p represents cauchy main value;
34) c (t) and y (t) synthesizes analytic signal z (t), z (t)=c (t)+iy (t), i.e. z (t)=a (t) exp [t θ (t)], the amplitude become during definition and phase place: a ( t ) = c 2 ( t ) + y 2 ( t ) , θ ( t ) = arctan ( y ( t ) / c ( t ) ) ;
35) instantaneous frequency ω (t)=d θ (t)/dt is combined, time Variable Amplitude a (t) time-frequency distributions be just defined as component c (t) Hilbert spectrum: H (ω, t)=H (ω (t), t)=a (t);
36) gather important Hilbert spectrum, just obtain the Hilbert spectrum of primary signal: H ( ω ) = Σ i = 1 n H i ( ω , t ) .
The detection method of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, in described step 32) middle IMF screening, component c (n) need meet: (1) extreme point number is equal with zero crossing number or differ one at the most; (2) to any point on signal, the mean value of the lower envelope line of the coenvelope line of the local maximum definition of signal and the local minimum definition of signal is zero; R) t) or c (n) need meet: remainder r (t) or c (n) be a monotonic signal (r (t) is called discrepance, only represent signal x (t) average or trend).
The detection method of cutter flutter in aforesaid a kind of Milling Process, is characterized in that, described step 4) in by drawing the time-frequency spectrum of HHT, whether checking meets flutter rule.
The beneficial effect that the present invention reaches: 1, by adopting this contactless detection method of laser displacement sensor, not only can overcome the limitation such as processing work size, quality, mounting means, and there is high accuracy; 2, by the impact that research milling parameter and cutter deflection change cutter center, become the general principle of circle according to 3, determine that cutter home position is beated, thus directly react the flutter situation of change of cutter; 3, adopt Hilbert transform, not only can overcome the limitation of Fourier transformation, and better can depict time-frequency spectrum and the amplitude-frequency spectrum of signal.
Accompanying drawing explanation
Fig. 1 is overhaul flow chart of the present invention;
Fig. 2 is system architecture schematic diagram of the present invention;
Fig. 3 is the realization flow figure that EMD of the present invention decomposes;
Fig. 4 is the overall realization flow figure of HHT algorithm of the present invention.
The implication of Reference numeral in figure:
1-main shaft, 2-milling cutter, 3-workpiece, 4-lathe, 5-multiple spot laser displacement sensor, 6-displacement acquisition unit, 7-displacement processing unit.
Detailed description of the invention
Below in conjunction with accompanying drawing, the invention will be further described.Following examples only for technical scheme of the present invention is clearly described, and can not limit the scope of the invention with this.
As shown in Figure 2, detection system comprises displacement detecting unit, data acquisition unit, CPU.In the present embodiment, multiple spot laser displacement sensor is set at Digit Control Machine Tool periphery, in process, multiple points on each the moment bottom tool surface recorded by laser displacement sensor.
Multiple spot laser displacement sensor is connected with CPU by USB data transmission line, the displacement signal that sensor detects is passed to CPU, thus gathers corresponding data-signal.
Displacement signal is expressed as: X = [ x 1 ( 1 , 2 , ... , m ) , x 2 ( 1 , 2 , ... , m ) , ... , x n ( 1 , 2 , ... , m ) ] Y = [ y 1 ( 1 , 2 , ... , m ) , y 2 ( 1 , 2 , ... , m ) , ... , y n ( 1 , 2 , ... , m ) ] , X, Y represent the delta data of correspondence direction vibrating signal, and m represents that laser displacement sensor inscribes counting of measured tool surface at each time, and n represents that laser displacement sensor measures how many times altogether, i.e. the length of signal.
When detecting, carry out as follows:
1) suitable displacement sampling window is selected.
2) center of Radius Constraint least square method determination cutter and the vibration change at corresponding cutters center is adopted; CPU, when determining the center of cutter, becomes the general principle of circle based on 3, extract the sampled point on circular arc, and in conjunction with the radius data of milling cutter, adopt the least square method based on Radius Constraint to carry out the determination of center cutter, step is as follows:
21) t is supposed ithe center cutter position of sampling instant is O (x i, y i), known cutter radius is R, utilizes displacement detecting unit to record m discrete sampling point (x ij, y ij), j=1,2,3..., m, m are t iinstance sample is counted, and makes (x ij, y ij) to O (x i, y i) quadratic sum of distance is minimum;
22) (x-x can be expressed as based on general equation of a circle i) 2+ (y-y i) 2=R 2, establish the Least Square Circle matching of Radius Constraint: C = Σ j = 1 m ( ( x - x i j ) 2 + ( y - y i j ) 2 - R 2 ) 2 , And object function is F ( a , b , c ) = Σ j = 1 m ( x i j 2 + y i j 2 + ax i j + by i j + c ) 2 , In formula: a = - 2 x i , b = - 2 y i , c = a 2 + b 2 - 4 R 2 4 .
23) necessary condition of extreme value is asked to obtain according to the function of many variables: be expressed in matrix as: Σ j = 1 m x i j 2 Σ j = 1 m x i j y i j Σ j = 1 m x i j Σ j = 1 m x i j y i j Σ j = 1 m y i j 2 Σ j = 1 m y i j Σ j = 1 m x i j Σ j = 1 m y i j m a b c = - Σ j = i m ( x i j 3 + x i j y i j 2 ) - Σ j = i m ( x i j 2 y i j + y i j 3 ) - Σ j = i m ( x i j 2 + y i j 2 ) , Try to achieve corresponding x i, y icoordinate.
24) to all sampling instant t i, i=1,2,3 ..., n, n are sampling number, solve corresponding center cutter coordinate all as stated above, then can obtain cutter at X, Y-direction vibrating signal, X=[x 1, x 2..., x n], Y=[y 1, y 2..., y n].
3) empirical mode decomposition is carried out to cutter vibration signal, in Milling Processes, X, Vibration Condition rule in Y both direction is identical, just varies in size, and supposes in the vibration of X-direction maximum, carry out HHT conversion in X-direction, utilize HHT to convert and obtain time-frequency spectrum, step is as follows:
When CPU adopts HHT algorithm to the analysis of cutter the center displacement signal, comprise the steps:
31) empirical modal EMD resolution process is carried out to displacement signal and obtain intrinsic mode IMF.
32) screening acquisition feature IMF component c is carried out to decomposing the N number of IMF component obtained i(t), i=1,2 ..., n, n are the number of feature IMF component, and signal remainder r (t), then primary signal X (t) can be expressed as all IMF and surplus sum: X (t)=c 1(t)+c 2(t)+... + c n(t)+r (t);
Wherein, IMF screens, component c it () need meet: (1) extreme point number is equal with zero crossing number or differ one at the most; (2) to any point on signal, the mean value of the lower envelope line of the coenvelope line of the local maximum definition of signal and the local minimum definition of signal is zero.In accompanying drawing 3, carry out above-mentioned condition to component h (t) and delete choosing, satisfactory assignment is to component c i(t).
R (t) or c (n) need meet: remainder r (t) or c (n) are a monotonic signal, and wherein r (t) is called discrepance, only represents average or the trend of signal x (t).
33) time-frequency spectrum of n feature IMF component is calculated respectively: according to formula: carry out HHT conversion, wherein p represents cauchy main value;
34) c (t) and y (t) synthesizes analytic signal z (t), z (t)=c (t)+iy (t), i.e. z (t)=a (t) exp [t θ (t)], the amplitude become during definition and phase place: a ( t ) = c 2 ( t ) + y 2 ( t ) , θ ( t ) = arctan ( y ( t ) / c ( t ) ) ;
35) instantaneous frequency ω (t)=d θ (t)/dt is combined, time Variable Amplitude a (t) time-frequency distributions be just defined as component c (t) Hilbert spectrum: H (ω, t)=H (ω (t), t)=a (t);
36) gather important Hilbert spectrum, just obtain the Hilbert spectrum of primary signal: H ( ω ) = Σ i = 1 n H i ( ω , t ) .
4) by drawing the time-frequency spectrum of HHT, whether unanimously with flutter rule analyzing, if consistent, detect end, if inconsistent, returning step 1), whether inspection other stages of Milling Process there is flutter.
The technical scheme that the present invention conceives compared with prior art, mainly possesses following technological merit:
1, by adopting this contactless detection method of laser displacement sensor, not only can overcome the limitation such as processing work size, quality, mounting means, and there is high accuracy.
2, by the impact that research milling parameter and cutter deflection change cutter center, become the general principle of circle according to 3, determine that cutter home position is beated, thus directly react the flutter situation of change of cutter.
3, cutter vibrating signal be a kind of transient state there is probabilistic signal, adopt Hilbert transform, not only can overcome the limitation of Fourier transformation, and better can depict the time-frequency spectrum of signal.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and distortion, these improve and distortion also should be considered as protection scope of the present invention.

Claims (10)

1. a detection system for cutter flutter in Milling Process, is characterized in that, comprises displacement detecting unit, data acquisition unit, CPU;
Described displacement detecting unit is arranged on Digit Control Machine Tool periphery; Described displacement detecting unit is for detecting the coordinate of the corresponding points of each moment tool surface;
The signal transmission that described data acquisition unit is used for displacement detecting unit to detect is to CPU;
The coordinate data that described CPU detects according to displacement detecting unit, determines the center of cutter and beating of center, is analyzed the vibration signal detected by HHT algorithm.
2. the detection system of cutter flutter in a kind of Milling Process according to claim 1, is characterized in that, described displacement detecting unit adopts multiple spot laser displacement sensor or several laser sensors.
3. the detection system of cutter flutter in a kind of Milling Process according to claim 1, is characterized in that, described displacement acquisition unit adopts multi-channel data acquisition board.
4. the detection system of cutter flutter in a kind of Milling Process according to claim 1, is characterized in that, described displacement detecting unit is connected with CPU by USB data transmission line.
5., based on a detection method for the detection system of cutter flutter in the Milling Process according to claim 1-4 any one, it is characterized in that, comprise the steps:
1) suitable displacement sampling window is selected;
2) center of Radius Constraint least square method determination cutter and the vibration change at corresponding cutters center is adopted;
3) empirical mode decomposition is carried out to cutter vibration signal, utilize HHT to convert and obtain time-frequency spectrum;
4) verify whether time-frequency spectrum meets flutter rule, if consistent, detect end, if inconsistent, return step 1), whether other stages in Milling Processes of detecting there is flutter.
6. the detection method of cutter flutter in a kind of Milling Process according to claim 5, it is characterized in that, described step 2) in, CPU is when determining the center of cutter, the general principle of circle is become based on 3, extract the sampled point on circular arc, and in conjunction with the radius data of milling cutter, adopt the least square method based on Radius Constraint to carry out the determination of center cutter.
7. the detection method of cutter flutter in a kind of Milling Process according to claim 5, is characterized in that, described step 2) in, when Radius Constraint least square method adopts to the displacement signal of cutter acquisition surface, comprise the steps:
21) t is supposed ithe center cutter position of sampling instant is O (x i, y i), known cutter radius is R, utilizes displacement detecting unit to record m discrete sampling point (x ij, y ij), j=1,2,3..., m, m are t iinstance sample is counted, and makes (x ij, y ij) to O (x i, y i) quadratic sum of distance is minimum;
22) (x-x can be expressed as based on general equation of a circle i) 2+ (y-y i) 2=R 2, establish the Least Square Circle matching of Radius Constraint: and object function is F ( a , b , c ) = Σ j = 1 m ( x i j 2 + y i j 2 + ax i j + by i j + c ) 2 , In formula: a=-2x i, b=-2y i, c = a 2 + b 2 - 4 R 2 4 ,
23) necessary condition of extreme value is asked to obtain according to the function of many variables: be expressed in matrix as: Σ j = 1 m x i j 2 Σ j = 1 m x i j y i j Σ j = 1 m x i j Σ j = 1 m x i j y i j Σ j = 1 m y i j 2 Σ j = 1 m y i j Σ j = 1 m x i j Σ j = 1 m y i j m a b c = - Σ j = i m ( x i j 3 + x i j y i j 2 ) - Σ j = i m ( x i j 2 y i j + y i j 3 ) - Σ j = i m ( x i j 2 + y i j 2 ) , Try to achieve corresponding x i, y icoordinate;
24) to all sampling instant t i, i=1,2,3 ..., n, n are sampling number, solve corresponding center cutter coordinate all as stated above, then can obtain cutter at X, Y-direction vibrating signal, X=[x 1, x 2..., x n], Y=[y 1, y 2..., y n].
8. the detection method of cutter flutter in a kind of Milling Process according to claim 7, is characterized in that, described step 3) in, when CPU adopts HHT algorithm to the analysis of cutter the center displacement signal, comprise the steps:
31) empirical modal EMD resolution process is carried out to displacement signal and obtain intrinsic mode IMF;
32) screening acquisition feature IMF component c is carried out to decomposing the N number of IMF component obtained i(t), i=1,2 ..., n, n are the number of feature IMF component, and signal remainder r (t), then primary signal X (t) can be expressed as all IMF and surplus sum: X (t)=c 1(t)+c 2(t)+... + c n(t)+r (t);
33) time-frequency spectrum of n feature IMF component is calculated respectively: according to formula: carry out HHT conversion, wherein p represents cauchy main value;
34) c (t) and y (t) synthesizes analytic signal z (t), z (t)=c (t)+iy (t), i.e. z (t)=a (t) exp [t θ (t)], the amplitude become during definition and phase place: a ( t ) = c 2 ( t ) + y 2 ( t ) , θ ( t ) = arctan ( y ( t ) / c ( t ) ) ;
35) instantaneous frequency ω (t)=d θ (t)/dt is combined, time Variable Amplitude a (t) time-frequency distributions be just defined as component c (t) Hilbert spectrum: H (ω, t)=H (ω (t), t)=a (t);
36) gather important Hilbert spectrum, just obtain the Hilbert spectrum of primary signal: H ( ω ) = Σ i = 1 n H i ( ω , t ) .
9. the detection method of cutter flutter in a kind of Milling Process according to claim 8, is characterized in that, in described step 32) in IMF screening in,
Component c (n) need meet: (1) extreme point number is equal with zero crossing number or differ one at the most; (2) to any point on signal, the mean value of the lower envelope line of the coenvelope line of the local maximum definition of signal and the local minimum definition of signal is zero;
R (t) or c (n) need meet: remainder r (t) or c (n) are a monotonic signal, and wherein r (t) is called discrepance, only represents average or the trend of signal x (t).
10. the detection method of cutter flutter in a kind of Milling Process according to claim 5, is characterized in that, described step 4) in by drawing the time-frequency spectrum of HHT, observe whether meet flutter rule.
CN201610101766.8A 2016-02-24 2016-02-24 Detection system for tool chattering in milling and detection method thereof Pending CN105500115A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610101766.8A CN105500115A (en) 2016-02-24 2016-02-24 Detection system for tool chattering in milling and detection method thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610101766.8A CN105500115A (en) 2016-02-24 2016-02-24 Detection system for tool chattering in milling and detection method thereof

Publications (1)

Publication Number Publication Date
CN105500115A true CN105500115A (en) 2016-04-20

Family

ID=55708613

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610101766.8A Pending CN105500115A (en) 2016-02-24 2016-02-24 Detection system for tool chattering in milling and detection method thereof

Country Status (1)

Country Link
CN (1) CN105500115A (en)

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106002489A (en) * 2016-07-07 2016-10-12 上海师范大学 Automatic compensation device and method for eliminating cutting chatter of numerical control machine tool
CN106141815A (en) * 2016-07-15 2016-11-23 西安交通大学 A kind of high-speed milling tremor on-line identification method based on AR model
CN106363463A (en) * 2016-08-15 2017-02-01 大连理工大学 Milling flutter on-line monitoring method based on energy occupation ratio
CN107932189A (en) * 2017-11-27 2018-04-20 上海卫星装备研究所 Satellite structure dressing process monitoring chatter System and method for
CN109202536A (en) * 2018-11-02 2019-01-15 浙江工业大学 Circular saw bench saw blade single vibration test macro
CN109759899A (en) * 2018-12-30 2019-05-17 深圳市五湖智联实业有限公司 A kind of numerically-controlled machine tool intelligent online knife pendulum monitoring system
CN109947045A (en) * 2019-03-27 2019-06-28 南京工业大学 It is a kind of that correction numerical control chamfering algorithm is exempted from based on polar-coordinate machine tool
CN112338633A (en) * 2020-09-27 2021-02-09 哈尔滨工业大学（深圳） Novel ultrasonic real-time amplitude on-line measurement device
CN112809462A (en) * 2019-11-18 2021-05-18 株式会社捷太格特 Flutter evaluation system
CN112974945A (en) * 2021-03-19 2021-06-18 天津大学 Milling chatter monitoring method based on variational modal decomposition and tracking threshold

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000009289A1 (en) * 1998-08-12 2000-02-24 Nt Engineering Kabushiki Kaisha Apparatus for detecting operation of machine tool
EP1816451A2 (en) * 2006-02-01 2007-08-08 JTEKT Corporation Abnormality diagnosing method for sound or vibration and abnormality diagnosing apparatus for sound or vibration.
CN102284888A (en) * 2011-02-25 2011-12-21 华中科技大学 Online monitoring method for turning stability of digital control machine tool
CN102581701A (en) * 2012-02-28 2012-07-18 西安交通大学 Milling cutter equivalent model establishing method for rapidly obtaining frequency response characteristics
CN102672539A (en) * 2011-03-10 2012-09-19 株式会社捷太格特 Chattering detection method
JP2012206230A (en) * 2011-03-30 2012-10-25 Brother Industries Ltd Processing chatter detector and machine tool
CN103786069A (en) * 2014-01-24 2014-05-14 华中科技大学 Flutter online monitoring method for machining equipment
CN104390697A (en) * 2014-11-06 2015-03-04 西安交通大学 C0 complexity and correlation coefficient-based milling chatter detection method
KR101514147B1 (en) * 2013-10-30 2015-04-21 현대위아 주식회사 Chatter vibration control method of machine tool using destructive interference effects and apparatus thereof
CN105290434A (en) * 2015-11-02 2016-02-03 宁波大学 Turning chatter predicting method based on power flow

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000009289A1 (en) * 1998-08-12 2000-02-24 Nt Engineering Kabushiki Kaisha Apparatus for detecting operation of machine tool
EP1816451A2 (en) * 2006-02-01 2007-08-08 JTEKT Corporation Abnormality diagnosing method for sound or vibration and abnormality diagnosing apparatus for sound or vibration.
CN102284888A (en) * 2011-02-25 2011-12-21 华中科技大学 Online monitoring method for turning stability of digital control machine tool
CN102672539A (en) * 2011-03-10 2012-09-19 株式会社捷太格特 Chattering detection method
JP2012206230A (en) * 2011-03-30 2012-10-25 Brother Industries Ltd Processing chatter detector and machine tool
CN102581701A (en) * 2012-02-28 2012-07-18 西安交通大学 Milling cutter equivalent model establishing method for rapidly obtaining frequency response characteristics
KR101514147B1 (en) * 2013-10-30 2015-04-21 현대위아 주식회사 Chatter vibration control method of machine tool using destructive interference effects and apparatus thereof
CN103786069A (en) * 2014-01-24 2014-05-14 华中科技大学 Flutter online monitoring method for machining equipment
CN104390697A (en) * 2014-11-06 2015-03-04 西安交通大学 C0 complexity and correlation coefficient-based milling chatter detection method
CN105290434A (en) * 2015-11-02 2016-02-03 宁波大学 Turning chatter predicting method based on power flow

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
刘珂等: "半径约束最小二乘圆拟合方法及误差分析", 《光电子·激光》 *
李欣: "基于经验模态分解和希尔伯特_黄变换的精密孔镗削颤振特征提取", 《光学精密工程》 *
王龙飞等: "最小二乘圆法在对刀仪中的应用", 《机电一体化》 *
祝强: "大型数控磨齿机中心定位算法研究", 《工具技术》 *
程瑶: "经验模态分解在切削颤振分析与监测中的应用研究", 《工程科技Ⅰ辑》 *

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106002489B (en) * 2016-07-07 2018-05-22 上海师范大学 A kind of autocompensation installation and method for eliminating numerical control machine tool cutting flutter
CN106002489A (en) * 2016-07-07 2016-10-12 上海师范大学 Automatic compensation device and method for eliminating cutting chatter of numerical control machine tool
CN106141815A (en) * 2016-07-15 2016-11-23 西安交通大学 A kind of high-speed milling tremor on-line identification method based on AR model
CN106141815B (en) * 2016-07-15 2018-07-17 西安交通大学 A kind of high-speed milling flutter on-line identification method based on AR models
CN106363463B (en) * 2016-08-15 2019-05-28 大连理工大学 Based on the Milling Process flutter on-line monitoring method for accounting for energy ratio
CN106363463A (en) * 2016-08-15 2017-02-01 大连理工大学 Milling flutter on-line monitoring method based on energy occupation ratio
CN107932189A (en) * 2017-11-27 2018-04-20 上海卫星装备研究所 Satellite structure dressing process monitoring chatter System and method for
CN109202536A (en) * 2018-11-02 2019-01-15 浙江工业大学 Circular saw bench saw blade single vibration test macro
CN109759899A (en) * 2018-12-30 2019-05-17 深圳市五湖智联实业有限公司 A kind of numerically-controlled machine tool intelligent online knife pendulum monitoring system
CN109947045A (en) * 2019-03-27 2019-06-28 南京工业大学 It is a kind of that correction numerical control chamfering algorithm is exempted from based on polar-coordinate machine tool
CN109947045B (en) * 2019-03-27 2021-09-10 南京工业大学 Correction-free numerical control chamfering algorithm based on polar coordinate machine tool
CN112809462A (en) * 2019-11-18 2021-05-18 株式会社捷太格特 Flutter evaluation system
CN112809462B (en) * 2019-11-18 2024-04-09 株式会社捷太格特 Flutter Evaluation System
CN112338633A (en) * 2020-09-27 2021-02-09 哈尔滨工业大学（深圳） Novel ultrasonic real-time amplitude on-line measurement device
CN112338633B (en) * 2020-09-27 2021-09-24 哈尔滨工业大学（深圳） Ultrasonic real-time amplitude online measuring device
CN112974945A (en) * 2021-03-19 2021-06-18 天津大学 Milling chatter monitoring method based on variational modal decomposition and tracking threshold

Similar Documents

Publication Publication Date Title
CN105500115A (en) Detection system for tool chattering in milling and detection method thereof
US20100004777A1 (en) S-shape detection test piece and a detection method for detecting the precision of the numerical control milling machine
EP0762248A1 (en) Characterising a machine tool system
CN103753353A (en) Milling cutter eccentricity rapidly measured non-contact type laser measuring method
CN104657526A (en) Method for predicting machining quality of machine tool
KR102224333B1 (en) An inspection system of spindle run-out in cnc machines and a method thereof
CN109794805A (en) A kind of cone hole machine bus deviation automatic detection device and its detection method
CN101187538A (en) Screw gauge detection method
CN107462415A (en) Utilize the high-speed spindle system kinetic test device and method of testing of gas exciting
CN104122840A (en) Standard track test analysis system for numerically-controlled machine tool
CN102121816A (en) Horizontal roundness and cylindricity automatic-measuring device
CN106168497A (en) A kind of hard state turning machine stability comprehensive detection system
CN103394972A (en) Milling surface roughness online prediction method based on acoustic emission signals
CN103097884A (en) Method and device for determining an orientation of a defect present within a mechanical component
CN112733298B (en) Machining performance evaluation method of series-parallel robot at different poses based on spiral hole milling
CN206430758U (en) A kind of new high-speed milling machine performance test part
CN103630604B (en) The recognition methods of centrifugal compressor half-opened impeller crack fault
CN109531270B (en) Modal testing method of numerical control machine tool feeding system based on built-in sensor
CN109238198B (en) Method for obtaining maximum processing error of curved surface parts processed in batch
CN202630899U (en) High-speed detection device of end jumping of circular saw web
CN112729731B (en) Machine tool sensitive part identification method and device based on dynamic stiffness sensitivity
CN201532393U (en) Laser rotating speed measuring instrument
CN101982749B (en) Method and device for measuring dynamic characteristics of indexing motion of tool holder
CN108994664A (en) A kind of five-axis machine tool RTCP accuracy detection and bearing calibration
CN110370077B (en) Numerical control lathe continuous fault propagation probability analysis method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20160420

RJ01 Rejection of invention patent application after publication