CN107179742B - A kind of numerical control cutting sharpener rail data de-noising method - Google Patents
A kind of numerical control cutting sharpener rail data de-noising method Download PDFInfo
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- CN107179742B CN107179742B CN201710367277.1A CN201710367277A CN107179742B CN 107179742 B CN107179742 B CN 107179742B CN 201710367277 A CN201710367277 A CN 201710367277A CN 107179742 B CN107179742 B CN 107179742B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/19—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by positioning or contouring control systems, e.g. to control position from one programmed point to another or to control movement along a programmed continuous path
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/35—Nc in input of data, input till input file format
- G05B2219/35349—Display part, programmed locus and tool path, traject, dynamic locus
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Abstract
The present invention discloses a kind of denoising method of numerical control cutting sharpener rail data, according to a series of knife rail data of numerical control cutting process cutter running track, compare the situation of change for the knife rail geometric coordinate data that condition conversion and state in cutter finite state machine are kept, it extracts cutter and operates in the knife rail data generated when cutting state, it filters out cutter dallying, empty shifting, cutting the knife rail noise data generated under the operating statuses such as process, cutter lifting process, to realize the denoising of numerical control cutting sharpener rail data.The present invention uses the knife rail data de-noising methods and techniques of cutter finite state machine, can theoretically guarantee 100% denoising rate；While satisfaction denoising requires, the quality risk of work pieces process is reduced, the generation of substandard products is reduced；Can pretreatment by software to numerical control cutting process knife rail data, realize the real-time de-noising of knife rail data, carry out data mining and the functions such as the early warning of failure are realized in data analysis, improve work pieces process efficiency.
Description
Technical field
The present invention relates to the data minings and analysis technical field more particularly to a kind of numerical control cutting in numerical control cutting processing
The methods and techniques of knife rail data de-noising, this method and technology can be applied to meet data mining and data in NC Machining Process
Analyze the requirement to the normalization and validity of data.
Background technique
The complex environment and complex working condition of NC Machining Process determine that the noise of knife rail data in process is relatively low
Status, i.e., really can be used for follow-up data in knife rail data, to excavate the valid data proportion analyzed with data lower.Such as
Shown in Fig. 1, numerical control cutting process generate true knife rail data in, not only contain generated by Tool in Cutting workpiece it is effective
Data further comprise a large amount of cutter idle running, the empty noise data for moving, cutting the generations such as process, cutter lifting process, and wherein cutter is empty
Turn, the empty height for moving the noise data generated and can accounting for the 40%-50% of all knives rail data, these knife rail noise datas have knife rail
The extraction and subsequent analysis for imitating data produce great interference, therefore, the knife rail data how numerical control cutting process generated
Denoising optimization is carried out to improve the validity of knife rail data, is to carry out data mining to numerical control cutting process and analyze primary solve
Problem.
Data mining for numerical control cutting process at present and data analysis, remain in the trend based on mathematical statistics point
The analysis stage.Since really effective data specific gravity is not high, signal-to-noise ratio is low in the Cutting data of magnanimity, this will result directly in number
It is unsatisfactory according to the effect excavated and data are analyzed, data characteristics can not be defined further also to carry out deeper data
Analysis and data mining.This field generallys use to the method for knife rail Noise reducing of data and improves numerical control processing technology scheme at present
Mode is dropped with this such as by reducing the idle running of cutter, empty shift time to the modification of process and cutting, cutter lifting frequency
Low numerical control cutting sharpener rail noise data improves the signal-to-noise ratio of knife rail data, but not yet for the cutting characteristic of NC Machining Process
There are effective numerical control cutting sharpener rail data de-noising methods and techniques.
Summary of the invention
The invention aims to propose a kind of cutting characteristic according to NC Machining Process, by identifying different numerical controls
Variation between cutting tool operating status and state, the method for Lai Jinhang bite rail data de-noising.
A kind of numerical control cutting sharpener rail data de-noising method of the present invention, comprising:
In numerical control processing cutting process, using workpiece surface as machining benchmark plane, i.e., (X, Y, 0) reference coordinate is flat
Face；Acquisition numerical control cutting cutter moves in process forms knife rail data；A kind of finite-state automata of cutter is constructed,
The idle running of corresponding cutter, empty shifting cut process, cutting, cutter lifting process and abnormal six states:
1) dally: Z is constant, and (X, Y) is constant；
2) empty to move: Z is constant, (X, Y) variation；
3) cut process: Z becomes smaller, and (X, Y) is constant；
4) cut: Z is basically unchanged, (X, Y) variation；
5) cutter lifting process: Z becomes larger, and (X, Y) is constant；
6) abnormal: other states apart from the above；
In six states, wherein the sampled data of bite rail is the valid data that actual cut workpiece generates, and
Idle running knife rail, it is empty move knife rail, cut process knife rail, cutter lifting process knife rail is invalid noise data, removed.
The finite-state automata of a kind of cutter of the numerical control processing cutting process, along between cutter operating status
Mutual inversion of phases, variation, condition conversion can also be generated by running the situation of change of knife rail geometric coordinate data (X, Y, Z) generated
Situation are as follows:
1) idle running-sky moves；
2) dally-cut process；
3) sky move-cut process；
4) process-idle running is cut；
5) process-cutting is cut；
6) cutting-cutter lifting process；
7) cutter lifting process-sky moves；
8) cutter lifting process-idle running.
The condition conversion specifically:
1) idle running-sky moves: Z is constant, and (X, Y) does not fade to variation；
2) dally-cutting process: Z, which is not faded to, to become smaller, and (X, Y) is constant；
3) sky move-cut process: Z, which is not faded to, to become smaller, and (X, Y) is changed to constant；
4) cut process-idle running: Z becomes smaller to constant, and (X, Y) is constant；
5) cut process-cutting: Z becomes smaller to being basically unchanged, and (X, Y) does not fade to variation；
6) cutting-cutter lifting process: Z is basically unchanged to becoming larger, and (X, Y) is changed to constant；
7) cutter lifting process-sky is moved: Z becomes larger to constant, and (X, Y) does not fade to variation；
8) cutter lifting process-idle running: Z becomes larger to constant, and (X, Y) is constant.
In the real process for carrying out numerical control cutting workpiece, mutual inversion of phases or the state between cutter operating status can be generated
Holding, have cutter by idle up to empty shifting condition conversion, cutter is by cutting the cutting of process to the condition conversion, cutter cut
State holding etc..
For the characteristics of conversion of cutter operating status is with keeping during the above numerical control cutting, numerical control proposed by the invention
The denoising method of bite rail data is mainly, according to a series of collected knife rail numbers of numerical control cutting process cutter running track
According to three-dimensional geometry coordinate value (X, Y, Z) situation of change, compare cutter finite state machine in condition conversion and state keep
Knife rail geometric coordinate data (X, Y, Z) situation of change, extract cutter and operate in the knife rail data generated when cutting state,
That is the knife rail valid data of numerical control cutting process, with this come filter out cutter in idle running, empty move, cut process, cutter lifting process etc.
The knife rail noise data generated under operating status, to realize the denoising of numerical control cutting sharpener rail data.
Compared to the knife rail data de-noising mode that processing method is improved in traditional use, certainly using cutter finite state
The beneficial effect of the denoising method of motivation is:
1. traditional knife rail data de-noising mode for improving processing method can only pass through the works such as change cutting route
Skill parameter reduces cutter idle running, the empty noise data for moving, cutting the generation of the operating statuses such as process, cutter lifting process, and numerical control adds
The cutting characteristic of work process determines the generation that can not veritably avoid noise data.And use the knife rail of cutter finite state machine
Data de-noising methods and techniques can theoretically guarantee 100% denoising rate.
2. if blindly pursue higher signal-to-noise ratio, and carrying out data de-noising by way of changing process program, pole has
Probably due to the technological parameters such as cutting route are unreasonable and cause quality fault, and use the knife rail data of cutter finite state machine
Denoising method and technology can reduce the quality risk of work pieces process, reduce the generation of substandard products while satisfaction denoising requires.
3. the knife rail data de-noising method of cutter finite-state automata can be realized by writing software, in software program
In by the pretreatment to numerical control cutting process knife rail data, realize the real-time de-noising of knife rail data, utilize the knife rail extracted
Valid data are analyzed to carry out data mining and data, and then the functions such as early warning of realization failure, improve work pieces process indirectly
Efficiency.
Detailed description of the invention
Fig. 1 is numerical control cutting process knife rail real time data figure；
Fig. 2 is cutter finite-state automata schematic diagram；
Fig. 3 is numerical control cutting procedure division knife rail schematic diagram.
Specific embodiment
The present invention is further illustrated with example with reference to the accompanying drawing.
See Fig. 1, Fig. 2 and Fig. 3:
The part knife rail that numerical control processing cutting process generates, by workpiece surface 1 as machining benchmark plane, i.e., (X, Y,
0) reference coordinate plane；Numerical control cutting cutter 2 moves in process forms knife rail (dotted line in Fig. 3)；Normally processing
In the case of, processing just start when cutter be in idling conditions (cutter idle running when its three-dimensional coordinate do not change, knife rail is
One fixed point), subsequent cutter sequentially enters empty shifting, cuts process, cutting, cutter lifting process, empty shifting state, knife when process finishing
Tool returns idling conditions, is sequentially generated empty shifting knife rail 3, cuts process knife rail 4, bite rail 5, cutter lifting process knife rail 6, empty shifting
Knife rail 7；The sampled data of knife rail is made of a series of three-dimensional geometry coordinate datas, and wherein the sampled data of bite rail 5 is real
The valid data that border cutting workpiece generates, and the knife rail that dallies, it is empty move knife rail 3, cut process knife rail 4, cutter lifting process knife rail 6 is nothing
The noise data of effect.
According to the three-dimensional geometry coordinate values of the collected knife rail data of numerical control cutting process cutter running track a series of (X,
Y, Z) situation of change, comparison as Fig. 2 cutter finite state machine in condition conversion and state keep knife rail geometric coordinate
The situation of change of data (X, Y, Z) distinguishes and judges to the knife rail of cutter difference operating status, extracts cutter and operate in
The knife rail data generated when cutting state, i.e. the knife rail valid data of numerical control cutting process, with this come filter out cutter idle running,
Sky moves, cuts the knife rail noise data generated under the operating statuses such as process, cutter lifting process, to realize numerical control cutting sharpener rail data
Denoising.Six state descriptions run to cutter in cutter finite state machine are as follows:
1) dally: Z is constant, and (X, Y) is constant；
2) empty to move: Z is constant, (X, Y) variation；
3) cut process: Z becomes smaller, and (X, Y) is constant；
4) cut: Z is basically unchanged, (X, Y) variation；
5) cutter lifting process: Z becomes larger, and (X, Y) is constant；
6) abnormal: other states apart from the above.
By cutter three-dimensional geometry coordinate (X, Y, Z) situation of change of above six states, can obtain to cutter operating status
Between convert be described as follows:
1) idle running-sky moves: Z is constant, and (X, Y) does not fade to variation；
2) dally-cutting process: Z, which is not faded to, to become smaller, and (X, Y) is constant；
3) sky move-cut process: Z, which is not faded to, to become smaller, and (X, Y) is changed to constant；
4) cut process-idle running: Z becomes smaller to constant, and (X, Y) is constant；
5) cut process-cutting: Z becomes smaller to being basically unchanged, and (X, Y) does not fade to variation；
6) cutting-cutter lifting process: Z is basically unchanged to becoming larger, and (X, Y) is changed to constant；
7) cutter lifting process-sky is moved: Z becomes larger to constant, and (X, Y) does not fade to variation；
8) cutter lifting process-idle running: Z becomes larger to constant, and (X, Y) is constant.
Such as the denoising step of the data of knife rail shown in Fig. 3 are as follows:
1. the movement of cutter generates knife rail shown in dotted line in Fig. 3, in numerical control processing cutting process with the workpiece surface
As machining benchmark plane, i.e. (X, Y, 0) reference coordinate plane, wherein setting the direction far from workpiece as the pros of Z coordinate axis
To three-dimensional geometry coordinate information when to Tool in Cutting workpiece carries out data acquisition, can get this section of knife rail data；
2. knife rail data by a series of D coordinates value (X, Y, Z) form, according in cutter finite-state automata not
With (X, Y, Z) changes in coordinates situation of cutter operating status, it can be determined that identify the sky of cutter corresponding to each section of knife rail data
Turn, empty shifting, cut process, cutting, cutter lifting process, abnormality, the stream of samples data of part knife rail as shown in 5 in Fig. 3
In, as the time is along moving, being basically unchanged of Z coordinate value of data point, (X, Y) coordinate value is constantly changing, then according to cutter
Finite-state automata judges it for bite rail data.
3. assume according to (X, Y, Z) changes in coordinates situation of different cutter operating statuses identify it is empty move knife rail data 3,
Sky moves knife rail data 7, cuts process knife rail data 4, bite rail data 5, cutter lifting process knife rail data 6, only extracts cutting
Knife rail data 5 are valid data, remove remaining knife rail noise data, realize the denoising of numerical control cutting sharpener rail data.
Claims (3)
1. a kind of numerical control cutting sharpener rail data de-noising method characterized by comprising
In numerical control processing cutting process, using workpiece surface as machining benchmark plane, i.e. (X, Y, 0) reference coordinate plane；It obtains
Access control cutting tool moves in process forms knife rail data；A kind of finite-state automata of cutter is constructed, it is corresponding
The idle running of cutter, empty shifting cut process, cutting, cutter lifting process and abnormal six states:
1) dally: Z is constant, and (X, Y) is constant；
2) empty to move: Z is constant, (X, Y) variation；
3) cut process: Z becomes smaller, and (X, Y) is constant；
4) cut: Z is basically unchanged, (X, Y) variation；
5) cutter lifting process: Z becomes larger, and (X, Y) is constant；
6) abnormal: other states in addition to idle running, sky move, cut process, cutting, cutter lifting process；
In six states, wherein the sampled data of bite rail is the valid data that actual cut workpiece generates, and is dallied
It is invalid noise data that knife rail, sky, which move knife rail, cut process knife rail, cutter lifting process knife rail, exception, is removed.
2. a kind of numerical control cutting sharpener rail data de-noising method according to claim 1, which is characterized in that the numerical control processing
A kind of finite-state automata of cutter of cutting process, along with the mutual inversion of phases between cutter operating status, operation is produced
The situation of change of raw knife rail geometric coordinate data (X, Y, Z) can also generate variation, condition conversion situation are as follows:
1) idle running-sky moves；
2) dally-cut process；
3) sky move-cut process；
4) process-idle running is cut；
5) process-cutting is cut；
6) cutting-cutter lifting process；
7) cutter lifting process-sky moves；
8) cutter lifting process-idle running.
3. a kind of numerical control cutting sharpener rail data de-noising method according to claim 2, which is characterized in that the condition conversion
Specifically:
1) idle running-sky moves: Z is constant, and (X, Y) does not fade to variation；
2) dally-cutting process: Z, which is not faded to, to become smaller, and (X, Y) is constant；
3) sky move-cut process: Z, which is not faded to, to become smaller, and (X, Y) is changed to constant；
4) cut process-idle running: Z becomes smaller to constant, and (X, Y) is constant；
5) cut process-cutting: Z becomes smaller to being basically unchanged, and (X, Y) does not fade to variation；
6) cutting-cutter lifting process: Z is basically unchanged to becoming larger, and (X, Y) is changed to constant；
7) cutter lifting process-sky is moved: Z becomes larger to constant, and (X, Y) does not fade to variation；
8) cutter lifting process-idle running: Z becomes larger to constant, and (X, Y) is constant.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5762415A (en) * | 1980-10-01 | 1982-04-15 | Mitsubishi Electric Corp | Numeric control working machine |
| JPH06114694A (en) * | 1992-09-30 | 1994-04-26 | Sumitomo Metal Ind Ltd | Cutter failure sensing device of machining device |
| JPH0973309A (en) * | 1995-09-01 | 1997-03-18 | Honda Motor Co Ltd | Checking method for 5-axes nc data |
| US9207265B1 (en) * | 2010-11-12 | 2015-12-08 | Cirrus Logic, Inc. | Dimmer detection |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US9866658B2 (en) * | 2005-04-29 | 2018-01-09 | Microsemi Storage Solutions, Inc. | Method and apparatus for SAS open address frame processing in SAS expanders |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS5762415A (en) * | 1980-10-01 | 1982-04-15 | Mitsubishi Electric Corp | Numeric control working machine |
| JPH06114694A (en) * | 1992-09-30 | 1994-04-26 | Sumitomo Metal Ind Ltd | Cutter failure sensing device of machining device |
| JPH0973309A (en) * | 1995-09-01 | 1997-03-18 | Honda Motor Co Ltd | Checking method for 5-axes nc data |
| US9207265B1 (en) * | 2010-11-12 | 2015-12-08 | Cirrus Logic, Inc. | Dimmer detection |
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