CN102073300A - Tool wear monitoring system capable of realizing self-learning in numerical control machining state - Google Patents
Tool wear monitoring system capable of realizing self-learning in numerical control machining state Download PDFInfo
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Abstract
The invention discloses a tool wear monitoring system capable of realizing self-learning in a numerical control machining state. The structure of the system is that: a tool wear rule learning library stores learned tool wear rules; a data acquisition and judgment module provides a servo drive current digital signal for a data processing module to perform format conversion and store the signal as a monitoring current signal; a characteristic extraction and selection module selects signal characteristics strongly correlated with tool wear; a fitted predicted trend curve module establishes a signal characteristic-tool machining service life relationship curve; a tool wear rule module obtains the learned tool wear rules from the tool wear rule learning library, and substitutes the trend signal characteristics into the learned tool wear rules to obtain a tool wear extent; and a tool wear compensation and tool replacement module makes a tool wear compensation and tool replacement decision according to the tool wear extent, and provides the tool wear compensation and tool replacement decision for a numerical control system interface input module. The system is applied to the condition of fluctuating cutting parameters in mass production, and can achieve relatively higher accuracy under the condition of constant cutting parameters.
Description
Technical field
The invention belongs to cutting tool for CNC machine wear measurement field, be a kind of online, real-time monitoring system of cutting-tool wear state that embeds digital control system.
Background technology
For many years, Chinese scholars is being done a large amount of work aspect the tool wear on-line monitoring, and has obtained remarkable achievement in selection, the signal Processing identification field of monitoring method, monitoring parameter, and some method has been used for producing.Traditional cutting-tool wear state monitoring method is based on the correlated characteristic of cutter VOLUME LOSS, by contact measurement or CCD imaging etc., directly obtains the attrition value of cutter.For example see that Chinese patent application number is: CN200910031737.9, denomination of invention is: based on the method for measuring wear of numerical control milling cutting tool of shape copying, the shape of tool is replicated on the photocopying materials, realizes the cutter wear measurement.Chinese patent application number is: CN200910082547.X, denomination of invention is: based on the online detection of the cutter of image and bucking-out system and method, utilize camera head to obtain the image of cutter, know tool abrasion by Flame Image Process.Chinese patent application number is: CN94201963.6, and denomination of invention is: measurement mechanism in the cutting tool for CNC machine abrading machine, measure the tool wear value by mechanical hook-up.Simultaneously, by the monitoring various signals relevant with tool wear, comprising: acoustic emission, vibration, moment of torsion and power signal also have relevant research to use.For example see that Chinese patent application number is: CN92111137.1, denomination of invention is: a kind of cutter failure comprehensive monitoring and controlling method and device have proposed to utilize acoustic emission and vibration signal combined method.Chinese patent application number is: CN97192053.2, and denomination of invention is: the automatic monitoring of cutting tool state, adopt main shaft drives cutting torque monitoring method.Chinese patent application number is: CN98808722.7, denomination of invention is: diagnostic rule base tool condition monitoring system, monitoring power feature, index rule base tool state.Method based on the VOLUME LOSS feature need be shut down detection, takies man-hour, is difficult to realize the monitoring of online in real time.Method such as acoustic emission, vibration is all deposited the signal monitoring inconvenience, and sensor is installed trouble, influence the normal process of lathe, even needs to change machine tool structure, so can only use in laboratory study, and it is bigger to be applied in the actual production difficulty.The method that adopts monitoring cutting torque and pass through power features index cutter state all is can only be applicable under the fixing finishing condition of cutting parameter.And in the actual production in enormous quantities, rough machined cutting parameter fluctuates within the specific limits, is not definite value, thereby can't use.Above-mentioned sensor-based monitoring method, basically all be to adopt independently signal monitoring and processing module, do not make full use of the lathe existing information, and owing to be module independently, do not embed in the digital control system, in operation, need to dispose in addition independently hardware handles, increase cost, operation inconvenience.
Summary of the invention
Purpose of the present invention is intended to overcome the deficiencies in the prior art, the tool wear supervisory system of a kind of digital control processing state self study is provided, this supervisory system not only can be applicable to the situation that the cutting parameter fluctuation changes in the production in enormous quantities, and also has higher precision for the fixing situation of cutting parameter.
The tool wear supervisory system of a kind of digital control processing state provided by the invention self study, it is characterized in that this system comprises that data are obtained and judge module, data processing module, feature extraction and selection module, match anticipation trend curve module, tool wear rule module, tool wear compensation and tool changing module, tool wear study module and tool wear rule learning database;
Tool wear rule learning database is used to store cutter study wear law;
Data are obtained with judge module and are linked to each other with digital control system interface output module, receive the servo driving current digital signal of digital control system output, and when receiving the tool wear monitored instruction servo driving current digital signal are offered data processing module;
The form of data processing module identification servo driving current digital signal is converted to the used unified file layout of subsequent analysis with current digital signal; Preserve current digital signal behind the format transformation as the monitor current signal, and offer feature extraction and select module;
Feature extraction adopts the WAVELET PACKET DECOMPOSITION technology that the monitor current signal is decomposed with selecting module, obtains the signal average and the variance of each frequency band, selects wherein the signal characteristic with the tool wear strong correlation, and offers match anticipation trend curve module;
Match anticipation trend curve module is set up signal characteristic and cutter processing life-span relation curve by fitting of a polynomial, and promptly match anticipation trend curve obtains the trend signal characteristic, and offers tool wear rule module;
Tool wear rule module obtains cutter study wear law from tool wear rule learning database; The trend signal characteristic is brought in the cutter study wear law, drawn tool abrasion, and offer tool wear compensation and tool changing module;
Wear extent when the cutter that tool wear compensation and tool changing module will monitors the tool abrasion that obtains and setting arrives the blunt standard relatively, the wear extent when reaching the blunt standard as if tool abrasion is then pointed out lathe replacing cutter; If the wear extent when tool abrasion does not reach the blunt standard is then changed the setting value of cutting tool for CNC machine compensation rate, and is offered digital control system interface load module.
The present invention obtains the drive current digital signal in the servo-drive system; By tool-information and the cutting tool state that from the digital control system instruction, obtains; Utilize the WAVELET PACKET DECOMPOSITION technology that signal is decomposed in frequency domain; Adopt advantageous characteristic to select technology, select feature with the cutting-tool wear state strong correlation; Obtain cutter signal characteristic variation tendency learning curve to be monitored by the fitting of a polynomial technology.Utilize the neural metwork training technology again, training obtains cutter study wear law to be monitored; Monitor cutter processing signal to be monitored in real time, set up cutter signal characteristic variation tendency prediction curve to be monitored, draw the real-time tendency signal characteristic on the curve, bring in the cutter study wear law to be monitored, draw the tool wear value, realize monitoring cutting-tool wear state.The present invention not only can be applicable to the situation that the cutting parameter fluctuation changes in the production in enormous quantities, and also has higher precision for the fixing situation of cutting parameter.The present invention has broken through existing method and has required shutdown detection, sensor installation influence processing, machining condition to fix.Can realize on-line real time monitoring tool wear situation, and sensor is easy for installation, do not influence the carrying out of production run, can adapt to the chipping allowance situation of random fluctuation within the specific limits simultaneously, has improved range of application, agrees with more with practical condition.
Supervisory system provided by the invention can be used as the merge module of digital control system, utilize digital control system secondary development function interface and serial ports, can realize communication easily with existing digital control system, utilize the digital control system existing information, realization is to the monitoring of tool wear, and the tool wear result of monitoring fed back in the digital control system, realize the tool wear monitoring of digital control system to the self study of numerical control machining state.
Description of drawings
Fig. 1 is the structural representation of system of the present invention;
Fig. 2 is tool wear study module synoptic diagram in the system of the present invention.
Embodiment
Supervisory system provided by the invention is by obtaining lathe drive motor current signal, and the machine tool machining information of from digital control system, knowing, through a series of signal Processing and feature extraction selection course, at last by the tool abrasion monitor procedure, realization is to the monitoring of tool abrasion VB, and monitored results fed back in the digital control system, digital control system is made corresponding reaction according to the abrasion condition of cutter, and cutter or change cutter benefit amount are changed in prompting.
As shown in Figure 1, supervisory system comprises that data are obtained and judge module 1, data processing module 2, feature extraction and selection module 3, match anticipation trend curve module 4, tool wear rule module 5, tool wear compensate and tool changing module 6, tool wear study module 7 and tool wear rule learning database 8.
Tool wear rule learning database 8 is used to store cutter study wear law.
Data are obtained with judge module 1 and are linked to each other with digital control system interface output module, receive the servo driving current digital signal of digital control system output, and when receiving the tool wear monitored instruction servo driving current digital signal are offered data processing module 2.
The form of data processing module 2 identification servo driving current digital signals is converted to the used unified txt file form of subsequent analysis with current digital signal; Preserve current digital signal behind the format transformation as the monitor current signal, and offer feature extraction and select module 3.
Feature extraction adopts the WAVELET PACKET DECOMPOSITION technology that the monitor current signal is decomposed with selecting module 3, obtains signal average, the variance of each frequency band, selects wherein the signal characteristic with the tool wear strong correlation, and offers match anticipation trend curve module 4.Specific implementation process is as follows:
At first the monitor current signal that data processing module 2 is provided decomposes in a plurality of frequency bands by the WAVELET PACKET DECOMPOSITION technology.One deck WAVELET PACKET DECOMPOSITION can be divided into two the original frequency band, and k layer wavelet packet can be decomposed into 2 with the primary frequency band
kIndividual frequency band is realized the frequency band segmentation, has improved the resolution of frequency domain.The k value is obtained by following formula usually:
In the formula, f is that the signals sampling frequency is calculated average, variance and the gross energy etc. of monitor current signal at each frequency band respectively, draws a plurality of signal characteristics.Analyze the correlativity of tool wear and each signal characteristic, selection wherein with the highest signal characteristic of tool wear strong correlation.
Match anticipation trend curve module 4 is set up signal characteristic and cutter processing life-span relation curve by fitting of a polynomial, and promptly match anticipation trend curve obtains the trend signal characteristic, and offers tool wear rule module 5.
Tool wear rule module 5 obtains cutter study wear law from tool wear rule learning database 8.The trend signal characteristic is brought in the cutter study wear law, drawn tool abrasion, and offer tool wear compensation and tool changing module 7.
Wear extent when the cutter that tool wear compensation and tool changing module 7 will monitors the tool abrasion that obtains and setting arrives the blunt standard relatively, the wear extent when reaching the blunt standard as if tool abrasion is then pointed out lathe replacing cutter; If the wear extent when tool abrasion does not reach the blunt standard is then changed the setting value of cutting tool for CNC machine compensation rate, and is offered digital control system interface load module.
As shown in Figure 2, tool wear study module 8 comprises calling interface module 9, match study trend curve module 10 and tool wear rule study module 11.
Calling interface module 9 is used to call data processing module 2 and feature extraction and selection module 3, will offer match study trend curve module 10 with the signal characteristic of tool wear strong correlation.
Match study trend curve module 10 is set up signal characteristic and cutter processing life-span relation curve by fitting of a polynomial, i.e. match study trend curve obtains the trend signal characteristic, and offers tool wear rule study module 11.
Tool wear rule study module 11 by neural metwork training, is set up tool wear rule learning model, draws the tool wear rule, deposits in the tool wear rule learning database 8.
The detailed process that tool wear study module 7 is set up cutter study wear law is as follows:
The form of data processing module 3 identification servo driving current digital signals is converted to the used unified txt file form of subsequent analysis with current digital signal; Preserve current digital signal behind the format transformation as the monitor current signal, and offer feature extraction and select module 4.
Feature extraction adopts the WAVELET PACKET DECOMPOSITION technology that the monitor current signal is decomposed with selecting module 4, obtains signal average, the variance of each frequency band, selects wherein the signal characteristic with the tool wear strong correlation, and offers match study trend curve module 10.Specific implementation process is as follows:
At first the monitor current signal that data processing module 3 is provided decomposes in a plurality of frequency bands by the WAVELET PACKET DECOMPOSITION technology.One deck WAVELET PACKET DECOMPOSITION can be divided into two the original frequency band, and k layer wavelet packet can be decomposed into 2 with the primary frequency band
kIndividual frequency band is realized the frequency band segmentation, has improved the resolution of frequency domain.The k value is obtained by following formula usually:
In the formula, f is that the signals sampling frequency is calculated average, variance and the gross energy etc. of monitor current signal at each frequency band respectively, draws a plurality of signal characteristics.Analyze the correlativity of tool wear and each signal characteristic, selection wherein with the highest signal characteristic of tool wear strong correlation.
Corresponding one group of cutter point process time with this group study trend signal characteristic of the trend signal characteristic that utilizes match study trend curve module 10 to obtain is measured a series of tool abrasions that obtain respectively, with of the input of this group study trend signal characteristic as neural network, corresponding a series of tool abrasions are as the output of neural network, pass through neural metwork training, set up the relation between study trend signal characteristic and the tool abrasion, the study cutter repeatedly from new cutter to this process of wearing and tearing, obtain cutter study wear law.The specific implementation process of neural metwork training is: at first determine 3 layers of neural network hidden layer node number, generally select 3～5 layers to get final product; Then, the initial value of relevant weights or threshold value is set according to the neural metwork training principle; Learn the trend signal characteristic as input with one group again, corresponding a series of tool abrasions carry out the training of neural network as output.
The present invention not only is confined to above-mentioned embodiment; persons skilled in the art are according to content disclosed by the invention; can adopt other multiple embodiment to implement the present invention; therefore; every employing project organization of the present invention and thinking; do some simple designs that change or change, all fall into the scope of protection of the invention.
Claims (2)
1. the tool wear supervisory system of digital control processing state self study, it is characterized in that this system comprises that data are obtained and judge module (1), data processing module (2), feature extraction and selection module (3), match anticipation trend curve module (4), tool wear rule module (5), tool wear compensation and tool changing module (6), tool wear study module (7) and tool wear rule learning database (8);
Tool wear rule learning database (8) is used to store cutter study wear law;
Data are obtained with judge module (1) and are linked to each other with digital control system interface output module, receive the servo driving current digital signal of digital control system output, and when receiving the tool wear monitored instruction, the servo driving current digital signal offered data processing module (2);
The form of data processing module (2) identification servo driving current digital signal is converted to the used unified file layout of subsequent analysis with current digital signal; Preserve current digital signal behind the format transformation as the monitor current signal, and offer feature extraction and select module (3);
Feature extraction adopts the WAVELET PACKET DECOMPOSITION technology that the monitor current signal is decomposed with selecting module (3), obtain the signal average and the variance of each frequency band, select wherein the signal characteristic with the tool wear strong correlation, and offer match anticipation trend curve module (4);
Match anticipation trend curve module (4) is set up signal characteristic and cutter processing life-span relation curve by fitting of a polynomial, and promptly match anticipation trend curve obtains the trend signal characteristic, and offers tool wear rule module (5);
Tool wear rule module (5) obtains cutter study wear law from tool wear rule learning database (8); The trend signal characteristic is brought in the cutter study wear law, drawn tool abrasion, and offer tool wear compensation and tool changing module (7);
Wear extent when the cutter that tool wear compensation and tool changing module (7) will monitors the tool abrasion that obtains and setting arrives the blunt standard relatively, the wear extent when reaching the blunt standard as if tool abrasion is then pointed out lathe replacing cutter; If the wear extent when tool abrasion does not reach the blunt standard is then changed the setting value of cutting tool for CNC machine compensation rate, and is offered digital control system interface load module.
2. tool wear supervisory system according to claim 1 is characterized in that, tool wear study module (8) comprises calling interface module (9), match study trend curve module (10) and tool wear rule study module (11);
Calling interface module (9) is used to call data processing module (2) and feature extraction and selects module (3), will offer match study trend curve module (10) with the signal characteristic of tool wear strong correlation;
Match study trend curve module (10) is set up signal characteristic and cutter processing life-span relation curve by fitting of a polynomial, i.e. match study trend curve obtains the trend signal characteristic, and offers tool wear rule study module (11);
Tool wear rule study module (11) by neural metwork training, is set up tool wear rule learning model, draws the tool wear rule, deposits in the tool wear rule learning database (8).
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