TWM542534U - Device applying rigidity prediction of tool to suppress the chatter of cutting - Google Patents

Description

Tool rigidity prediction device for suppressing cutting flutter

The present invention relates to a device for predicting the rigidity of a tool for suppressing the chattering vibration, in particular to a spindle rigidity data which can be selected from the inside of a computer of the machine tool, and the operator selects the tool bar type and the tool parameter in the human machine interface. In turn, the conditions of the optimal rotation speed and depth of cut are obtained; this is a processing optimization method in which the control system detects an abnormality of the cutting signal during machining and calculates the optimum cutting condition according to the tool type of the tool holder.

When the traditional machine tool performs cutting, the machining master sets the rotation speed and cutting depth of the machining program according to the cutting conditions provided by the tool manufacturer, but the machine characteristics of different machine manufacturers are different, and the same tool and cutting conditions are not the same. It must be fully applicable. When abnormal sound or vibration occurs in the machining process and the surface of the workpiece is not well-fabricated, the abnormality is usually avoided by reducing the rotation speed and depth of cut, but this will lead to a decrease in production efficiency, and it is not the best to overcome the problem. method.

In recent years, due to the development of sensor technology and the maturity of computer computing processing technology, the application technology for processing instant suppression of cutting anomalies has become more and more extensive. The technology utilized is the Fourier transform analysis of digital signals, and the vibration of Altintas. Vibration theory. Referring to Fig. 1, a conventional method for suppressing cutting flutter by a known tool includes: (a) when flutter occurs, performing (b) stopping the machine, and exiting the tool, and then using (c) ) 槌 槌 槌 槌 , , , 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌 槌To the computer (f) computer signal analysis processing to obtain tool rigidity; then, use computer computing software (g) to calculate the cutting steady state map, (h) the user selects the appropriate cutting conditions, and then (i) the machine tool continues to cut In order to achieve (j) the target of flutter stop; however, the above method needs to stop the machine tool and spend a lot of time and manpower to carry out, which is not suitable for the operation cost control of the industry.

Therefore, in recent years, the sensor acceleration gauge is used to detect the cutting vibration or the microphone captures the noise signal, and the frequency of the cutting flutter is obtained by the Fourier transform analysis signal, and then the fast formula S=fc*60/Z/N(S) = spindle speed, fc = flutter frequency, Z = number of tool edges, N = 1, 2, 3...) Calculate the optimal cutting speed, suppress abnormal vibration and continue cutting for use by many machine tool operators. Although the method can quickly find the optimal rotational speed, the information about the optimal depth of cut is still not known, and the calculated optimal rotational speed is an approximate estimated value, so it is still very likely that the cutting condition is unstable. . Therefore, how to accurately provide stable cutting conditions information to operators is still a topic that needs to be improved in the integrated processing machine industry.

The main purpose of this creation is to provide a device for predicting the rigidity of the tool to suppress the chattering vibration. The spindle rigidity data, the tool rigidity model and the various types of tool bar database modules of the machine tool are established in the computer. During the process, the machining abnormality is detected, and the spindle rigidity data is combined with the tool holder module and the tool parameters, and the optimal cutting speed and depth of cut are calculated through the tool rigidity model to suppress the occurrence of abnormal machining conditions and improve the tool. The service life and machine processing efficiency are more time-saving and man-made than the previously known tool tapping test to find the best conditions, and there are no problems such as laboratory equipment consumables.

In order to achieve the above object, the tool rigidity prediction of the present invention is used for suppressing the device for cutting flutter. The preferred technical solution includes: detecting the vibration signal during processing by using the sensing unit, and converting the frequency response diagram of the signal by Fourier. When the non-tool cutting frequency (ie, flutter frequency) signal appears, the controller stops the machining program and warns the user that the machining has an abnormality. The user inputs the machining tool bar and the tool parameters. The computer will use the machining tool bar and the tool model. Combined with the rigid data of the spindle, the internal rotation is used to calculate the optimal speed and depth of cut for the user to select. The user can select the condition to avoid the flutter. At this time, the vibration signal is captured and the flutter frequency is cut. Disappeared, only the stable tool cutting frequency remains.

The structural features of the present creation and other functions and purposes are described in detail in the following embodiments:

The tool rigidity prediction is used to suppress the cutting flutter. It is a predictive tool rigidity technology based on the tool coupling theory. It can predict the optimal cutting speed and cutting depth under the current processing state, so that the comprehensive processing machine can avoid Open cutting flutter and improve tool life and machining efficiency. Referring to FIG. 2, a preferred embodiment includes at least one sensing unit 1, a capturing unit 2 and a computer 3 disposed in the integrated processing machine 10 as a hardware for performing the cutting suppression flutter technique. Device, where:

The sensing unit 1 is preferably a vibration sensor (for example, an acceleration gauge) for performing vibration monitoring on the integrated processing machine 10, and the vibration sensor is specifically disposed at a vibration generating position of the integrated processing machine 10, For example, the spindle 101 or other selected position is used to measure the vibration of the main shaft 101 of the integrated processing machine 10, and the measured vibration signal can be fed back to the following capturing unit 2 for reading;

The capturing unit 2 is a signal capturing device of the sensor, and is connected to the vibration sensor of the sensing unit 1 and the computer 3 for capturing the vibration obtained by the vibration sensor. The signal is converted into a computer readable signal and transmitted to the computer 3; the capture unit 2 includes a single chip processing and operation for high-speed sampling, digital conversion, and filtering of noise interference. To obtain the correct vibration data; in addition, a configuration storage device (such as an SD card) can be used for immediate abnormal vibration storage, and the capture unit is connected to the aforementioned computer;

The computer 3 is disposed in an industrial computer of the integrated processing machine 10, and a computer rigidity prediction unit is built in the computer 3, and is connected to the controller of the comprehensive processing machine 10 to perform a data collection bridge. Further, the vibration signal calculation analysis and the tool rigidity calculation of the integrated processing machine 10 are performed, and the vibration generated by the integrated processing machine 10 can be monitored by the vibration sensor and the capture unit 2 by the computer 3, and the computer 3 is used for calculation and analysis. It is judged whether or not the cutting flutter occurs, and the optimum cutting condition of the controller of the integrated processing machine 10 is fed back by the computer 3.

By means of the above-mentioned arrangement of the sensing unit 1, the capturing unit 2 and the computer 3, and the integrated processing machine 10, and referring to FIG. 3, the manner in which the tool rigidity prediction suppresses the execution of the cutting chatter is: The measuring unit 1 (vibration sensor) performs vibration monitoring to obtain the vibration signal and the rotational speed of the main shaft 101 of the integrated processing machine 10, and feeds back to the capturing unit 2, so that the capturing unit 2 captures the vibration signal and the rotational speed, and The capture unit 2 is transferred to the computer 3; the tool rigidity prediction unit in the computer 3 captures the vibration signal of the spindle 101 during the operation of the machining program by the integrated processing machine 10, and performs vibration information analysis through the fast Fourier The conversion finds the change of the processing flutter frequency of the main shaft 101, thereby determining whether the condition of the flutter is reached (determining whether the flutter occurs); if the condition of the flutter is reached, the processing program is immediately stopped, and the user is stopped. Inputting the cutting conditions of the integrated processing machine (including the processing tool bar and tool parameters, cutting parameter input) on the operation panel of the integrated processing machine; the tool rigidity prediction unit of the computer 3 is based on these parameters The spindle rigidity data is used to calculate the rigidity of the tool, and finally the optimal cutting parameters (rotation speed and depth of cut) are obtained, and output to the controller operation panel of the integrated processing machine 10, providing the user to select and use these optimal conditions for processing. This makes the cutting efficiency of the integrated processing machine effectively improved.

Referring to FIG. 4, the tool rigidity prediction unit 4 is built in the computer 3, and includes a spindle rigidity model 41, various types of tool magazine modules 42, a tool rigidity calculation module 43, and steady-state cutting. The condition calculation module 44; wherein the spindle rigidity model 41 includes the rigidity data of the main shaft 101 of the integrated processing machine 10, which is data of frequency (Hz) corresponding to rigidity (um/N); The group 42 includes simplified size data (length, outer diameter, inner diameter, taper, etc.) of various shanks; the tool rigidity calculation module 43 is an operation program combining material mechanics theory and finite element algorithm; The cutting condition calculation module 44 is a calculation program for quickly finding the optimal spindle rotation speed and cutting depth by the tool tip point rigidity and the cutting condition; the tool rigidity prediction unit 4 is input after the user inputs the tool bar type through the human machine interface (control panel). The corresponding tool bar data is captured from various tool bar database modules 42, and then the user continues to input tool parameters (diameter, number of blades, tool length, elongation), cutting parameters, and the tool rigidity prediction. single Element 4 combines the data of the tool bar data with the tool parameters and the cutting parameters, and performs a finite element segmentation operation. The tool rigidity calculation module 43 superimposes the segmented model with the spindle rigid module 41 to obtain a final The tool tip point is rigid, and then the optimal cutting condition is calculated via the steady state cutting condition calculation module 44.

Referring to FIG. 4 again, the technical method for suppressing the cutting flutter is predicted by the tool rigidity, and the method for implementing the method includes: when the machining machine 10 is in progress, the spindle 101 is automatically scooped by the capturing unit 2 The vibration signal is transmitted to the computer 3 for analysis; and then the computer program of the computer 3 determines whether flutter occurs. If the computer program determines that flutter occurs, the integrated processing machine 10 automatically controls the processing to be suspended; the integrated processing machine 10 The man-machine interface of the controller displays the input screen of the tool bar type, tool parameters and cutting parameters to provide the user with selection and input. After the input is completed, the controller then transmits the data to the computer 3 for tool rigidity prediction. The unit 4, the tool rigidity prediction unit 4 performs the above-mentioned actions by using the data, thereby obtaining the tool tip point rigidity, wherein the steady state cutting condition calculation module 44 captures the tool tip point rigidity data, and quickly calculates The best five sets of spindle speed (cutting speed) and cutting depth cutting conditions, and output to the human machine interface for the user to choose a cutting Then, the controller of the integrated processing machine 10 is modified to the optimal spindle speed and depth of cut according to the cutting condition selected by the user, and continues to be processed, and the computer 3 continues to perform vibration signal acquisition and computer program analysis and judgment. Whether flutter occurs.

Referring again to FIG. 5, the method for suppressing the cutting flutter of the tool rigidity prediction is compared with the conventional method for suppressing the cutting flutter shown in FIG. 1. The conventional tool rigidity is obtained by steps (a) to (f) of the method. The operation of stopping the machine and exiting the tool respectively, and using the instrument and equipment to perform the tapping measurement action, the machine has to go through the warm-up procedure before continuing the cutting. The method of this creation is to pause the machine (b'), without exiting the tool, and directly select the tool type (c'), input tool parameter (d') and input cutting parameter (e' directly on the man-machine board. ), the tool tip point rigidity can be obtained by the tool rigidity prediction unit 4 shown in FIG. 4, the process is fast, the downtime cost is greatly reduced, and no instrument (acceleration gauge, impact hammer, signal line, etc.) is consumed or damaged. Maintenance problem. Moreover, in the search for optimal cutting conditions, the conventional method is to manually find the optimal cutting point for cutting the steady state map, and the steady cutting condition calculation module 44 described in the present application can help the operator to stabilize quickly. The stable cutting point is found on the state map, and the optimal cutting condition is outputted on the operation screen for the user to directly click, and the cutting operation can be continued immediately after selecting the cutting condition, which is simpler and reduces the chance of human judgment time and error.

The tool rigidity prediction is used to suppress the effect achieved by the device for cutting flutter. In suppressing the cutting flutter, the rigid tool is predicted based on the tool coupling theory, and the tool rigidity is obtained by the tool coupling theory model. The method can improve the conventional anti-vibration technology, and the tool rigidity is required to obtain the rigidity of the tool through the experimental method of the instrument, the cost of stopping the machine and the manpower is stopped, or the flutter frequency is measured by the sensor, and the optimal speed is calculated by a simple formula. There is no problem with the best depth of cut information and calculation results may be inaccurate.

In summary, the tool rigidity prediction is used to suppress the device for cutting flutter. It has practicality and creativity. The application of its technical means is also novel and undoubted, and the effect is in line with the design purpose. Progress is clear. To this end, a new type of patent application is filed in accordance with the law, but the bureau is requested to give a detailed examination and grant the patent as a prayer.

10‧‧‧Comprehensive processing machine

101‧‧‧ Spindle

1‧‧‧Sensor unit

2‧‧‧Capture unit

3‧‧‧ computer

4‧‧‧Tool rigidity prediction unit

41‧‧‧ spindle stiffness model

42‧‧‧All types of toolholder database modules

43‧‧‧Tool rigidity calculation module

44‧‧‧Stable Steady Cutting Condition Calculation Module

FIG. 1 is a schematic diagram of an implementation step of a conventional method for suppressing chatter vibration. FIG. 2 is a schematic overall block diagram of the proposed suppression flutter system. FIG. 3 is a schematic diagram of the execution of the steps of the method for suppressing chatter vibration. FIG. 4 is a schematic diagram of the judgment and execution procedure of the steps of the method for suppressing chatter vibration. FIG. 5 is a schematic diagram showing the steps of implementing the method for suppressing chatter vibration.

10‧‧‧Comprehensive processing machine

101‧‧‧ Spindle

1‧‧‧Sensor unit

2‧‧‧Capture unit

3‧‧‧ computer

Claims (4)

A device for predicting cutting flutter, comprising: at least one sensing unit, a capturing unit and a computer disposed in an integrated processing machine; the sensing unit is mounted on a spindle of the integrated processing machine Measuring the vibration of the spindle, and feeding back the measured vibration signal to the capturing unit for reading; the capturing unit is connected to the sensing unit and the computer, and extracting the vibration signal obtained by the capturing unit And converting the vibration signal into a computer readable signal, which is transmitted to the computer; the computer has a built-in tool rigidity prediction unit connected between the capturing unit and the controller of the integrated processing machine, the tool rigidity The prediction unit comprises a spindle rigidity model, a type of tool bar database module, a tool rigidity calculation module, and a steady state cutting condition calculation module; the spindle rigidity model includes rigidity data of the main shaft of the integrated processing machine; Each type of tool bar database module includes simplified size data of various tool bars; the tool rigidity calculation module captures tool bar data of each type of tool bar database module, and combines and loses The finite element segmentation action is performed on the tool parameters and the cutting parameters, and the model after the segmentation is superimposed with the spindle rigid module to obtain the tool tip point rigidity; the steady state cutting condition calculation module performs the operation with the tip point rigidity To find the spindle speed and depth of cut. The tool rigidity prediction device according to claim 1 is for suppressing the device for cutting flutter, wherein the sensing unit is a vibration sensor. The tool rigidity prediction device according to claim 1 is for suppressing the device for cutting flutter, wherein the capturing unit comprises a single chip for sampling, digital conversion and filtering noise interference. The tool rigidity prediction device according to claim 1 is for suppressing the device for cutting flutter, wherein the capturing unit includes a storage device for immediate abnormal vibration storage.