CN112327757A - Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement - Google Patents
Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement Download PDFInfo
- Publication number
- CN112327757A CN112327757A CN202011306678.4A CN202011306678A CN112327757A CN 112327757 A CN112327757 A CN 112327757A CN 202011306678 A CN202011306678 A CN 202011306678A CN 112327757 A CN112327757 A CN 112327757A
- Authority
- CN
- China
- Prior art keywords
- workpiece
- speed
- error
- optimization
- machining
- 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
Links
Images
Classifications
-
- 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
- G05B19/4097—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 using design data to control NC machines, e.g. CAD/CAM
-
- 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
- G05B2219/35188—Project workpiece and sheet on screen, position layout to be cut, store contour
Abstract
The invention discloses an intelligent optimization method and device for acceleration and deceleration of a numerical control machine tool by using online measurement, wherein the method is applied to a CNC platform to realize closed-loop optimization inside the CNC, and comprises the following steps: step S1, acquiring workpiece trial machining data and measuring the workpiece contour error on line; step S2, judging whether the workpiece contour error meets the preset processing requirement, and if not, optimizing a speed curve; step S3, performing trial machining on the workpiece again, and repeatedly executing the steps S1 and S2 until the contour error of the workpiece meets the preset machining requirement, so as to obtain a speed curve optimization result; and step S4, performing normal machining on the whole workpiece by using the speed curve optimization result. The method can ensure the reliability and stability of the final processing quality of the processed workpiece, does not need to import data into CAM and recalculate the tool path, and improves the speed planning optimization efficiency on the premise of ensuring the contour accuracy.
Description
Technical Field
The invention relates to the technical field of numerical control machining, in particular to an intelligent optimization method and device for acceleration and deceleration of a numerical control machine tool by using online measurement.
Background
The scheme of the related technology is as follows:
the first step is as follows: measuring the error of the processed workpiece on line/off line to obtain contour error data and evaluating whether the workpiece meets the precision requirement;
the second step is that: if the precision requirement is not met, adjusting the path track of the tool by using the CAD model and the contour error data in CAM software, and adjusting and repairing the machining;
the third step: clamping a new part, and processing by using the path track of the cutter obtained in the second step to meet the requirement of processing precision.
However, the related art solution has the following drawbacks:
disadvantage 1: automation is difficult to achieve. The optimization process spans multiple systems and sets of processes, such as CAM, CNC, measurement systems, etc., requiring operators to manually import and export data in different systems, and thus automation of contour error control is difficult to achieve.
And (2) disadvantage: the actual processing speed cannot be optimized for the feature. The actual feed speed in the machining process is controlled by a CNC (computer numerical control), the CAM can only control the tool track and the command feed speed, and an operator cannot intervene in the speed control process in the machining process of the CNC, so that the machining speed cannot be adjusted according to machining errors in the prior art.
Disadvantage 3: multiple processes are required. Because the traditional online measurement or offline measurement mode is only used for detecting whether the profile error is within the precision requirement range, the method is a detection process after machining, and a new workpiece needs to be machined when a part meeting the precision requirement is required.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, one objective of the present invention is to provide an intelligent optimization method for acceleration and deceleration of a numerical control machine using online measurement, which can ensure reliability and stability of final processing quality of a processed workpiece, and improve speed planning optimization efficiency without importing data into a CAM and recalculating a tool path on the premise of ensuring contour accuracy.
The invention also aims to provide an intelligent acceleration and deceleration optimizing device of the numerical control machine tool by using online measurement.
In order to achieve the above object, an embodiment of an aspect of the present invention provides an intelligent optimization method for acceleration and deceleration of a CNC machine using online measurement, where the method is applied to a CNC platform to implement closed-loop optimization inside the CNC, and the method includes the following steps: step S1, acquiring workpiece trial machining data and measuring the workpiece contour error on line; step S2, judging whether the workpiece contour error meets a preset processing requirement, and carrying out speed curve optimization when the workpiece contour error does not meet the preset processing requirement; step S3, performing trial machining on the workpiece again, and repeatedly executing the steps S1 and S2 until the workpiece contour error meets the preset machining requirement, and obtaining a speed curve optimization result; and step S4, using the speed curve optimization result to carry out normal processing on the whole workpiece.
According to the intelligent acceleration and deceleration optimization method for the numerical control machine tool by using online measurement, an online measurement mode is adopted, and extra time and operation brought by workpiece loading and unloading are avoided; by adopting the method of optimizing speed planning, the additional calculation caused by changing the cutter location point and the cutter shaft is avoided; the optimization process is limited in the CNC platform, so that data are prevented from being transmitted back to the CAM and the tool path is prevented from being recalculated, and automatic calculation can be realized; therefore, the machining speed curve can be optimized on the basis of an on-line measurement technical means, the machining precision of the machine tool for a specific workpiece is improved, the reliability and the stability of the final machining quality of the machined workpiece are further ensured, data do not need to be led into a CAM (computer-aided manufacturing) and a tool path does not need to be recalculated, and the speed planning optimization efficiency is improved on the premise of ensuring the contour precision.
In addition, the intelligent optimization method for acceleration and deceleration of the numerical control machine tool using on-line measurement according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, when the preset machining requirement is not satisfied, performing speed curve optimization includes: solving according to the workpiece trial machining data to obtain the coordinate system position of the workpiece and the speed of the cutter movement; establishing a corresponding relation between the speed and the workpiece contour error distribution; and optimizing the speed curve by using an optimization strategy to obtain the optimized speed curve.
Further, in one embodiment of the present invention, the speed profile is optimized using an optimization strategy comprising: and changing the acceleration and deceleration movement of the cutter movement according to the corresponding relation between the speed and the workpiece contour error distribution so as to optimize a speed curve, wherein the speed is reduced when the error is greater than a first preset error value, and the speed is increased when the error is less than a second error value.
Further, in an embodiment of the present invention, the collecting data of the trial machining of the workpiece includes: and processing the workpiece by using the initialized speed curve, and acquiring workpiece trial processing data in the processing process.
Further, in one embodiment of the present invention, the workpiece trial machining data includes machine tool motor position data and speed data.
In order to achieve the above object, an embodiment of another aspect of the present invention provides an intelligent optimization apparatus for acceleration and deceleration of a CNC using online measurement, which is applied to a CNC platform to implement closed-loop optimization inside the CNC, including: the trial processing module is used for acquiring trial processing data of the workpiece; the error online measurement module is used for online measuring the profile error of the workpiece; the judging module is used for judging whether the workpiece contour error meets a preset processing requirement or not; the optimization module is used for optimizing a speed curve when the preset machining requirement is not met; the iteration module is used for carrying out trial machining on the workpiece again, and repeatedly executing the trial machining module, the error online measurement module, the judgment module and the optimization module until the workpiece contour error meets the preset machining requirement, so that a speed curve optimization result is obtained; and the normal processing module is used for performing normal processing on the whole workpiece by using the speed curve optimization result.
The intelligent acceleration and deceleration optimizing device of the numerical control machine tool using online measurement in the embodiment of the invention adopts an online measurement mode, thereby avoiding extra time and operation brought by loading and unloading workpieces; by adopting the method of optimizing speed planning, the additional calculation caused by changing the cutter location point and the cutter shaft is avoided; the optimization process is limited in the CNC platform, so that data are prevented from being transmitted back to the CAM and the tool path is prevented from being recalculated, and automatic calculation can be realized; therefore, the machining speed curve can be optimized on the basis of an on-line measurement technical means, the machining precision of the machine tool for a specific workpiece is improved, the reliability and the stability of the final machining quality of the machined workpiece are further ensured, data do not need to be led into a CAM (computer-aided manufacturing) and a tool path does not need to be recalculated, and the speed planning optimization efficiency is improved on the premise of ensuring the contour precision.
In addition, the intelligent optimization device for acceleration and deceleration of the numerical control machine tool using on-line measurement according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, the optimization module is further configured to solve the position of the coordinate system of the workpiece and the speed of the tool movement according to the workpiece trial machining data, establish a corresponding relationship between the speed and the profile error distribution of the workpiece, and optimize the speed curve by using an optimization strategy to obtain an optimized speed curve.
Further, in an embodiment of the present invention, the optimization module is further configured to change the acceleration and deceleration movement of the tool movement according to a corresponding relationship between the speed and the workpiece profile error distribution to optimize the speed curve, wherein the speed is decreased when the error is greater than a first preset error value, and the speed is increased when the error is smaller than a second error value.
Further, in an embodiment of the present invention, the trial machining module is further configured to perform workpiece machining using the initialized speed profile, and collect workpiece trial machining data during the machining process.
Further, in one embodiment of the present invention, the workpiece trial machining data includes machine tool motor position data and speed data.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for intelligently optimizing acceleration and deceleration of a numerically controlled machine tool using online measurement according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a main structure of software and hardware of the system according to the embodiment of the present invention;
FIG. 3 is a flow chart of a method for intelligent optimization of acceleration and deceleration of a numerically controlled machine tool using on-line measurement according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an intelligent optimization device for acceleration and deceleration of a numerically-controlled machine tool using online measurement according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The present invention is based on the recognition and discovery by the inventors of the following problems:
(1) the method for ensuring the profile precision in the traditional numerical control machine tool processing has two types: firstly, a workpiece is unloaded from a machine tool, the contour error is detected, error data is transmitted into CAM software, a tool path is adjusted by a CAD model, and a new workpiece is clamped again for processing; and secondly, the contour error is detected by using an online measurement mode, but online measurement data are only used for detecting the contour accuracy of the workpiece generally and evaluating whether the workpiece is qualified or not, the online measurement data belong to the detection process after machining, no contribution is made to the optimization of the workpiece machining, and if the machined workpiece does not meet the error requirement, the workpiece needs to be machined again.
The optimization process is limited in the CNC platform, so that data are prevented from being transmitted back to the CAM and the tool path is prevented from being recalculated, and automatic calculation can be realized; by means of online measurement and trial cutting processing, an optimal processing technology (an optimized speed curve) is found, and the purposes of improving processing precision and increasing the qualified rate of processed products are achieved.
(2) The related art also provides an online optimization method for the feeding speed in the multi-axis numerical control milling process of the complex curved surface, but the method needs to change coordinate points, the modification process does not depend on a CAD model, and therefore the changed curve characteristics may not meet the requirements of a workpiece model.
The invention does not need to change coordinate points in a numerical control program, only changes the acceleration and deceleration movement of the cutter, thereby not causing the modification of coordinate positions to influence the processing effect, and does not need to clamp a new workpiece for processing, thereby saving the material cost and the operation complexity.
The method and the device for intelligently optimizing acceleration and deceleration of a numerical control machine tool by using online measurement according to the embodiment of the invention are described below with reference to the attached drawings, and firstly, the method for intelligently optimizing acceleration and deceleration of a numerical control machine tool by using online measurement according to the embodiment of the invention is described with reference to the attached drawings.
Fig. 1 is a flowchart of an intelligent optimization method for acceleration and deceleration of a numerical control machine using on-line measurement according to an embodiment of the present invention.
As shown in fig. 1, the intelligent optimization method for acceleration and deceleration of a numerically-controlled machine tool using on-line measurement is applied to a CNC platform to realize closed-loop optimization inside the CNC, and comprises the following steps:
and step S1, acquiring workpiece trial machining data and measuring the workpiece contour error on line.
The workpiece may be an impeller, or may be another specific workpiece, which is not particularly limited. In the embodiment of the invention, the workpiece trial machining data comprises position data and speed data of each shaft of a machine tool motor; the contour error means: deviation of the theoretical machined workpiece shape from the actual machined workpiece shape.
It can be understood that the embodiment of the invention completes data acquisition (including position and speed information of a motion axis) through CNC, on-line measurement uses a measuring head to measure a workpiece, and a measuring object is the workpiece by using a measuring function of CNC.
In one embodiment of the present invention, collecting data of trial processing of a workpiece includes: using the initialized speed curve to process the workpiece, collecting the trial processing data of the workpiece in the processing process,
it can be understood that trial processing judges whether the initialized speed curve meets the processing requirement, and data acquisition provides a basis for optimizing the subsequent speed curve.
Further, the embodiment of the invention uses a measuring head of the machine tool to measure the trial machining data of the workpiece, and solves the machined contour error through software, wherein the contour error is used for evaluating the result of the trial machining (whether the error meets the requirement or not).
And step S2, judging whether the workpiece contour error meets the preset processing requirement, and if not, optimizing a speed curve.
It can be understood that the embodiment of the present invention determines whether the profile error meets the processing requirement, including: maximum value of profile error, average value, whether error distribution is uniform, etc.
In one embodiment of the present invention, when the preset machining requirement is not satisfied, the speed curve optimization is performed, including: solving to obtain the coordinate system position of the workpiece and the movement speed of the cutter according to the trial machining data of the workpiece; establishing a corresponding relation between the speed and the profile error distribution of the workpiece; and optimizing the speed curve by using an optimization strategy to obtain the optimized speed curve.
In one embodiment of the present invention, the speed curve is optimized by using an optimization strategy, including: and changing the acceleration and deceleration movement of the cutter movement according to the corresponding relation between the speed and the workpiece contour error distribution so as to optimize a speed curve, and when the error is greater than a first preset error value, performing deceleration, and when the error is less than a second error value, performing acceleration.
The first preset error value and the second preset error value may be set according to an actual situation, and are not specifically limited herein. For example, when the error is greater than the first preset error value, the error is large, and the speed is required to be reduced; when the error is smaller than the second error value, it indicates that the error is small, and the speed increase may be performed.
Specifically, if the error requirement is not met, the speed curve is optimized, and the specific steps are as follows:
(1) according to the collected position and speed of each shaft of the machine tool motor, the position and speed of a workpiece coordinate system (virtual shaft) are solved;
(2) establishing a corresponding relation between the speed and the obtained profile error distribution;
(3) the speed profile is adjusted/optimized using an optimization strategy: for example: large error, reduced speed, small error and increased speed;
(4) and obtaining an optimized speed curve.
The speed profile is optimized in order to reduce the profile error (improve the machining accuracy) in the next machining.
And step S3, performing the trial machining of the workpiece again, and repeatedly executing the steps S1 and S2 until the contour error of the workpiece meets the preset machining requirement, so as to obtain the speed curve optimization result.
It can be understood that, in the embodiment of the present invention, the trial machining of the workpiece is performed again, and the steps S1 and S2 are repeated until the profile error of the workpiece meets the machining requirement, the error distribution is uniform, the speed is smooth, and thus the optimization is repeated until the machining requirement is met. And then, recording the final speed curve optimization structure, and fixing the impeller machining process to separate the trial cutting process from the normal machining process.
And step S4, performing normal machining on the whole workpiece by using the speed curve optimization result.
According to the embodiment of the invention, the processing contour error can be calculated only according to the online measurement result without the support of CAM (computer aided manufacturing), so that closed loop optimization inside CNC is realized, the whole process from trial cutting to final processing is completed under the condition of not disassembling a workpiece (unified reference), and the closed loop of the online detection process is realized. The main structure of the software and hardware of the system according to the embodiment of the present invention is shown in fig. 2.
For further explanation of the intelligent optimization method for acceleration and deceleration of the numerical control machine using online measurement, the following description will be made by referring to fig. 3 by using an embodiment, in which the workpiece is taken as an impeller, and the following details are provided:
step 1, initializing a speed curve: the speed curve obtained by the existing process scheme before optimization is uncertain whether the requirement of machining error is met or not and needs to be optimized.
Wherein, step 1 is an initialization step.
Step 2, trial processing of the impeller (cutter 1): using the speed curve in step 1 to perform impeller machining, and collecting machining data in the machining process, such as: the position, speed, etc. of each shaft of the machine tool motor.
The function of the step 2: trial processing judges whether the initialized speed curve meets the processing requirements, and data acquisition provides a basis for optimizing the subsequent speed curve.
Step 3, measuring the blade profile error on line: measuring the data of the impeller processed in the step 2 by using a measuring head of a machine tool, and solving a processed contour error through software, wherein the contour error refers to: deviations of the theoretical machining blade shape from the actual machining blade shape,
the function of the step 3: for evaluating the result of this trial process (whether the error satisfies the requirement)
Step 4, judging whether the contour error meets the processing requirement, comprising the following steps: maximum value of profile error, average value, whether error distribution is uniform, etc.
And 5, if the error requirement is not met, optimizing a speed curve, and specifically comprising the following steps:
step 5.1: solving the position and the speed of a workpiece coordinate system (virtual axis) according to the position, the speed and the like of each axis of the machine tool motor acquired in the step 2;
step 5.2: establishing a corresponding relation between the speed and the profile error distribution obtained in the step 3;
step 5.3: the speed profile is adjusted/optimized using an optimization strategy: for example: large error, reduced speed, small error and increased speed;
step 5.4: and obtaining an optimized speed curve.
The function of the step 5: the speed curve is optimized in order to reduce the profile error (improve the machining precision) of the next machining.
And 6, performing the trial machining of the impeller again (step 2), and repeating the steps 2-5 until the contour error of the impeller meets the machining requirement, the error is uniformly distributed, and the speed is smooth.
The function of the step 6: and repeating the optimization until the processing requirement is met.
And 7, recording the final speed curve optimization structure and fixing the impeller machining process.
The function of the step 7: separating trial cutting process and normal processing process.
And 8, using the speed curve optimization result to complete the processing of the whole impeller
In summary, the embodiment of the present invention utilizes a technical means of online measurement to detect the profile error of the impeller numerical control machining, and optimizes acceleration and deceleration of the machine tool by analyzing distribution of the profile error, so as to improve the profile machining precision and obtain the impeller machining speed curve meeting the machining requirements.
According to the intelligent acceleration and deceleration optimization method for the numerical control machine tool by using online measurement, which is provided by the embodiment of the invention, the online measurement mode is adopted, so that extra time and operation brought by loading and unloading workpieces are avoided; by adopting the method of optimizing speed planning, the additional calculation caused by changing the cutter location point and the cutter shaft is avoided; the optimization process is limited in the CNC platform, so that data are prevented from being transmitted back to the CAM and the tool path is prevented from being recalculated, and automatic calculation can be realized; therefore, the machining speed curve can be optimized on the basis of an on-line measurement technical means, the machining precision of the machine tool for a specific workpiece is improved, the reliability and the stability of the final machining quality of the machined workpiece are further ensured, data do not need to be led into a CAM (computer-aided manufacturing) and a tool path does not need to be recalculated, and the speed planning optimization efficiency is improved on the premise of ensuring the contour precision.
The intelligent acceleration and deceleration optimizing device for the numerical control machine tool using on-line measurement, which is proposed according to the embodiment of the invention, is described next with reference to the accompanying drawings.
Fig. 4 is a schematic structural diagram of an intelligent optimization device for acceleration and deceleration of a numerically-controlled machine tool using online measurement according to an embodiment of the present invention.
As shown in fig. 4, the intelligent optimization device 10 for acceleration and deceleration of a numerical control machine tool using on-line measurement is applied to a CNC platform to realize closed-loop optimization of the interior of the CNC, and the device 10 comprises: the system comprises a trial processing module 100, an error online measurement module 200, a judgment module 300, an optimization module 400, an iteration module 500 and a normal processing module 600.
The trial processing module 100 is used for acquiring trial processing data of the workpiece; the error online measurement module 200 is used for online measuring the workpiece profile error; the judging module 300 is used for judging whether the workpiece contour error meets a preset processing requirement; the optimization module 400 is configured to perform speed curve optimization when the preset processing requirement is not met; the iteration module 500 is used for performing the trial machining of the workpiece again, and repeatedly executing the trial machining module, the error online measurement module, the judgment module and the optimization module until the contour error of the workpiece meets the preset machining requirement, so as to obtain a speed curve optimization result; the normal machining module 600 is used to perform normal machining of the entire workpiece using the speed profile optimization results.
Further, in an embodiment of the present invention, the optimization module 400 is further configured to solve the coordinate system position of the workpiece and the speed of the tool movement according to the workpiece trial machining data, establish a corresponding relationship between the speed and the workpiece contour error distribution, and optimize the speed curve by using an optimization strategy to obtain an optimized speed curve.
Further, in an embodiment of the present invention, the optimization module 400 is further configured to change the acceleration and deceleration movement of the tool movement according to a corresponding relationship between the speed and the error distribution of the workpiece profile to optimize the speed curve, wherein the speed is decreased when the error is greater than a first preset error value, and the speed is increased when the error is less than a second error value.
Further, in an embodiment of the present invention, the trial machining module 100 is further configured to perform workpiece machining using the initialized speed profile and collect workpiece trial machining data during the machining process.
Further, in one embodiment of the invention, the trial workpiece machining data includes machine tool motor position data and speed data.
It should be noted that the above explanation of the embodiment of the intelligent optimization method for acceleration and deceleration of a numerical control machine using online measurement is also applicable to the intelligent optimization device for acceleration and deceleration of a numerical control machine using online measurement in this embodiment, and is not repeated here.
According to the intelligent acceleration and deceleration optimizing device for the numerical control machine tool using online measurement, which is provided by the embodiment of the invention, the online measurement mode is adopted, so that extra time and operation brought by loading and unloading workpieces are avoided; by adopting the method of optimizing speed planning, the additional calculation caused by changing the cutter location point and the cutter shaft is avoided; the optimization process is limited in the CNC platform, so that data are prevented from being transmitted back to the CAM and the tool path is prevented from being recalculated, and automatic calculation can be realized; therefore, the machining speed curve can be optimized on the basis of an on-line measurement technical means, the machining precision of the machine tool for a specific workpiece is improved, the reliability and the stability of the final machining quality of the machined workpiece are further ensured, data do not need to be led into a CAM (computer-aided manufacturing) and a tool path does not need to be recalculated, and the speed planning optimization efficiency is improved on the premise of ensuring the contour precision.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. An intelligent optimization method for acceleration and deceleration of a numerical control machine tool by using online measurement is characterized in that the method is applied to a CNC platform to realize closed-loop optimization inside the CNC, and comprises the following steps:
step S1, acquiring workpiece trial machining data and measuring the workpiece contour error on line;
step S2, judging whether the workpiece contour error meets a preset processing requirement, and carrying out speed curve optimization when the workpiece contour error does not meet the preset processing requirement;
step S3, performing trial machining on the workpiece again, and repeatedly executing the steps S1 and S2 until the workpiece contour error meets the preset machining requirement, and obtaining a speed curve optimization result;
and step S4, using the speed curve optimization result to carry out normal processing on the whole workpiece.
2. The method of claim 1, wherein when the preset machining requirement is not met, performing a speed profile optimization comprising:
solving according to the workpiece trial machining data to obtain the coordinate system position of the workpiece and the speed of the cutter movement;
establishing a corresponding relation between the speed and the workpiece contour error distribution;
and optimizing the speed curve by using an optimization strategy to obtain the optimized speed curve.
3. The method of claim 2, wherein the speed profile is optimized using an optimization strategy comprising:
and changing the acceleration and deceleration movement of the cutter movement according to the corresponding relation between the speed and the workpiece contour error distribution so as to optimize a speed curve, wherein the speed is reduced when the error is greater than a first preset error value, and the speed is increased when the error is less than a second error value.
4. The method of claim 1, wherein collecting workpiece pilot-processing data comprises:
and processing the workpiece by using the initialized speed curve, and acquiring workpiece trial processing data in the processing process.
5. A method according to any one of claims 1 to 4, wherein the trial workpiece machining data includes machine tool motor shaft position data and speed data.
6. An intelligent optimization device for acceleration and deceleration of a numerical control machine tool using on-line measurement, which is applied to a CNC platform to realize closed loop optimization of the interior of the CNC, comprising:
the trial processing module is used for acquiring trial processing data of the workpiece;
the error online measurement module is used for online measuring the profile error of the workpiece;
the judging module is used for judging whether the workpiece contour error meets a preset processing requirement or not;
the optimization module is used for optimizing a speed curve when the preset machining requirement is not met;
the iteration module is used for carrying out trial machining on the workpiece again, and repeatedly executing the trial machining module, the error online measurement module, the judgment module and the optimization module until the workpiece contour error meets the preset machining requirement, so that a speed curve optimization result is obtained;
and the normal processing module is used for performing normal processing on the whole workpiece by using the speed curve optimization result.
7. The device of claim 6, wherein the optimization module is further configured to solve the coordinate system position of the workpiece and the speed of the tool movement according to the workpiece trial machining data, establish a correspondence between the speed and the workpiece profile error distribution, and optimize the speed curve by using an optimization strategy to obtain an optimized speed curve.
8. The apparatus of claim 7, wherein the optimization module is further configured to modify the acceleration and deceleration of the tool motion according to a relationship between the velocity and the profile error distribution of the workpiece to optimize the velocity profile, wherein the deceleration is performed when the error is greater than a first predetermined error value and the acceleration is performed when the error is less than a second error value.
9. The apparatus of claim 61 wherein the pilot processing module is further configured to perform workpiece processing using the initialized speed profile and to collect pilot processing data for the workpiece during the processing.
10. Apparatus according to any of claims 6 to 9, wherein the trial workpiece machining data comprises machine tool motor shaft position data and speed data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011306678.4A CN112327757A (en) | 2020-11-19 | 2020-11-19 | Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011306678.4A CN112327757A (en) | 2020-11-19 | 2020-11-19 | Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112327757A true CN112327757A (en) | 2021-02-05 |
Family
ID=74321793
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011306678.4A Pending CN112327757A (en) | 2020-11-19 | 2020-11-19 | Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112327757A (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101025620A (en) * | 2006-02-24 | 2007-08-29 | 同济大学 | Hierarchical fuzzy control method for numerical control milling process |
| CN101206472A (en) * | 2007-12-06 | 2008-06-25 | 上海交通大学 | Method for smoothing speed of high speed numerical control processing track corner |
| CN101446994A (en) * | 2008-12-18 | 2009-06-03 | 浙江大学 | Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool |
| CN101923335A (en) * | 2010-08-10 | 2010-12-22 | 济南大学 | Open type numerical control system directly facing to machining path points based on kernel platform |
| CN102004466A (en) * | 2010-10-25 | 2011-04-06 | 武汉华中数控股份有限公司 | Method for compensating numerical control machine processing dynamic error based on instruction sequence analysis |
| CN102033508A (en) * | 2010-12-01 | 2011-04-27 | 沈阳工业大学 | Method for improving machining precision of contour of directly driven XY platform |
| US20130211573A1 (en) * | 2012-02-10 | 2013-08-15 | Chung Yuan Christian University | Online real-time cutter breakage monitoring method |
| CN105045210A (en) * | 2015-07-13 | 2015-11-11 | 苏州谷夫道自动化科技有限公司 | Smooth interpolation method for CNC (Computer Numerical Control) equipment self-adaptive control chord error |
| US20180164783A1 (en) * | 2014-01-22 | 2018-06-14 | Omax Corporation | Generating optimized tool paths and machine commands for beam cutting tools |
| CN108732996A (en) * | 2017-04-17 | 2018-11-02 | 华中科技大学 | Numeral control processing method based on dual code synergy and related device |
| CN108723888A (en) * | 2018-06-05 | 2018-11-02 | 西安交通大学 | Straight-line feed axis point of a knife point is relative to Grating examinations position deviation method of estimation |
| CN111459099A (en) * | 2020-05-22 | 2020-07-28 | 南京高传四开数控装备制造有限公司 | Feeding speed online optimization method in complex curved surface multi-axis numerical control milling process |
-
2020
- 2020-11-19 CN CN202011306678.4A patent/CN112327757A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101025620A (en) * | 2006-02-24 | 2007-08-29 | 同济大学 | Hierarchical fuzzy control method for numerical control milling process |
| CN101206472A (en) * | 2007-12-06 | 2008-06-25 | 上海交通大学 | Method for smoothing speed of high speed numerical control processing track corner |
| CN101446994A (en) * | 2008-12-18 | 2009-06-03 | 浙江大学 | Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool |
| CN101923335A (en) * | 2010-08-10 | 2010-12-22 | 济南大学 | Open type numerical control system directly facing to machining path points based on kernel platform |
| CN102004466A (en) * | 2010-10-25 | 2011-04-06 | 武汉华中数控股份有限公司 | Method for compensating numerical control machine processing dynamic error based on instruction sequence analysis |
| CN102033508A (en) * | 2010-12-01 | 2011-04-27 | 沈阳工业大学 | Method for improving machining precision of contour of directly driven XY platform |
| US20130211573A1 (en) * | 2012-02-10 | 2013-08-15 | Chung Yuan Christian University | Online real-time cutter breakage monitoring method |
| US20180164783A1 (en) * | 2014-01-22 | 2018-06-14 | Omax Corporation | Generating optimized tool paths and machine commands for beam cutting tools |
| CN105045210A (en) * | 2015-07-13 | 2015-11-11 | 苏州谷夫道自动化科技有限公司 | Smooth interpolation method for CNC (Computer Numerical Control) equipment self-adaptive control chord error |
| CN108732996A (en) * | 2017-04-17 | 2018-11-02 | 华中科技大学 | Numeral control processing method based on dual code synergy and related device |
| CN108723888A (en) * | 2018-06-05 | 2018-11-02 | 西安交通大学 | Straight-line feed axis point of a knife point is relative to Grating examinations position deviation method of estimation |
| CN111459099A (en) * | 2020-05-22 | 2020-07-28 | 南京高传四开数控装备制造有限公司 | Feeding speed online optimization method in complex curved surface multi-axis numerical control milling process |
Non-Patent Citations (2)
| Title |
|---|
| 邓朝晖，等: "《凸轮轴智能高速磨削理论及其关键技术》", 31 October 2018, 华中科技大学出版社 * |
| 金致富，等: "基于进给速度修调的轮廓误差控制研究", 《工艺与检测》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110434671B (en) | Cast member surface machining track calibration method based on characteristic measurement | |
| US8090557B2 (en) | Quality assurance method when operating an industrial machine | |
| EP0879674B1 (en) | Generation of measurement program in nc machining and machining management based on the measurement program | |
| CN111687652B (en) | Grip force adjusting device and grip force adjusting system | |
| US8977382B2 (en) | Automatic method for milling complex channel-shaped cavities | |
| EP1146407A1 (en) | Method for writing nc program and nc machining system | |
| US4963805A (en) | Numerical control apparatus for machining non-circular workpieces | |
| CN110471368A (en) | A kind of prediction interpolating method that High Speed NC Machine Tools process velocity is adaptive | |
| CN103529751B (en) | Five-axis linkage machine tools digital control system and job operation thereof | |
| EP1298507A2 (en) | Method for setting a machining feed rate and a machine tool using the same | |
| CN106886197B (en) | Method for controlling machine to implement machining, device and application thereof | |
| Vavruska et al. | Reducing machining time by pre-process control of spindle speed and feed-rate in milling strategies | |
| CN112318319A (en) | Programming-free robot online constant-force grinding control system and method | |
| JP3587363B2 (en) | Numerical control device and numerical control method | |
| RU2528923C2 (en) | Article adaptive machining at nc machines | |
| CN106886195B (en) | Machining control method, device and application thereof | |
| CN114019910A (en) | Real-time global fairing method for small-line-segment tool path | |
| CN110045680B (en) | Measuring method for online detection of spatial dimension of arm support on numerical control machine tool | |
| CN112757307B (en) | Equipment and method for machining ternary impeller blade welding groove by robot | |
| CN112327757A (en) | Intelligent optimization method and device for acceleration and deceleration of numerical control machine tool by using online measurement | |
| Chu et al. | Spline-constrained tool-path planning in five-axis flank machining of ruled surfaces | |
| CN114274047A (en) | Efficient precise polishing track optimization method based on force sensing measurement | |
| KR100871456B1 (en) | Method for estimating 5-axis milling machining time based on machine characteristics | |
| CN1067619C (en) | Roll grinder digital control system | |
| CN113399685B (en) | Double-swing diamond cutter cutting device and cutting method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210205 |
|
| RJ01 | Rejection of invention patent application after publication |