TW201545833A - Devices and methods for machining process parameter estimation - Google Patents

Abstract

The present invention discloses a machining processing parameter assessment device and the method thereof. The device may comprise a signal sensing module, signal analysis module and machining status assessment module. The signal sensing module acquires vibration signals from a machining processing. The signal analysis module analyzes the vibration signals via operational modal analysis to produce system dynamic parameters; such as natural frequency and the damping ratio. The machining status assessment module determines the optimal spindle rotational speed in avoiding chatter according to a mathematical model created based on chatter theory and also a warning signal based on the vibration spectra. The method in determining the optimal machining parameters consists of two phases. In the first phase, the optimal spindle rotational speed is determined via the signal sensing module and the signal analysis module based on the operational modal analysis and chatter theory. In the second phase, with the spindle operated at the optimal speed determined in Phase one, varying cutting depths are assessed via the machining status assessment module in order to determine an optimal cutting depth that matches the optimal spindle speed without chatter.

Description

Cutting processing parameter estimating device and method thereof

The invention relates to a method for estimating a cutting processing parameter, in particular to an accurate estimation of an optimum rotation speed of a cutting machine for cutting a workpiece of a specific material, and at the same time calculating an optimum cutting depth matching the optimum rotation speed. Estimation method. The invention also relates to an apparatus for applying the cutting process parameter estimation method.

CNC lathes, milling machines, etc. are commonly used cutting machines in mechanical manufacturing processes. In the process of cutting, if flutter occurs, it will affect the cutting speed, stability and material removal rate. Therefore, the operator needs to find the best machining parameters (such as the rotation speed and the matching cutting depth) that can avoid the chattering as much as possible, thereby ensuring the cutting stability and the material removal rate. Generally speaking, the operator usually determines the tool and the tool spindle speed required for the workpiece of a specific material according to the rule of thumb, the information provided by the machine tool manufacturer, or the reference book. However, because the tools and machines manufactured by different manufacturers have different characteristics and various other factors, it is difficult to accurately find suitable processing parameters based on the rules of thumb and reference books. Furthermore, different workpieces are processed and their materials are processed. The clamping method also affects the processing stability.

The Republic of China Patent Publication No. 200630182 discloses a computer-aided cutting flutter detection and suppression system. The previous case uses a detection system to identify whether the cutting signal is a high frequency signal and whether it is a bit. Within a stable interval of a smoothing function to determine whether flutter occurs, and a warning is issued when the detection system determines that chattering has occurred.

The Republic of China Patent Publication No. 201131325 discloses an online vibration detection control module. In the previous case, the vibration detection control module is used to measure various vibration phenomena in the processing process and load signals output during tool machining, and analyze them. Calculate and judge whether the vibration signal exceeds the set rated value. If the vibration signal exceeds the rated value, send the control signal to change the spindle speed or feed speed to prevent too much vibration during machining.

The Republic of China Patent Publication No. 201332708 discloses a method for monitoring the vibration of a tool. The previous method divides the measured vibration signal into a plurality of segments, and determines whether the amplitude increase between each of the vibration signals exceeds a set threshold value, and The segment vibration signal performs fast Fourier transform and determines whether the vibration signal frequency is the cutting edge passing frequency. If both the above judgments coincide, the flutter occurs.

Most of the above-mentioned pre-existing cases disclose several methods for detecting flutter, which do not provide the best processing parameters before processing, and these methods are too complicated and expensive (for example, using a power meter), and are not suitable for general machine on-line inspection. The demand, or lack of information such as the dynamic characteristics of the machine or the rigidity of the cutting, so that the performance is not good, and therefore can not provide the most suitable depth of cut for a specific speed, it can not effectively improve the stability of the machine cutting and material movement Except rate.

Therefore, this patent proposes a cutting processing parameter estimating device and method, which can effectively improve the conventional technology, which is too complicated, expensive, inaccurate, and unable to provide optimized processing parameters has become an urgent problem.

In view of the above-mentioned problems of the prior art, it is an object of the present invention to provide a cutting tool parameter estimating apparatus and method for solving the problems that the prior art is complicated, expensive, inaccurate, and unable to provide optimized processing parameters.

According to one of the objects of the present invention, a cutting processing parameter estimating device is proposed. The device can include a signal sensing module, a signal analysis module, and a cutting state estimation module. The signal sensing module can capture the first vibration signal generated by the cutting machine during a cutting operation. The signal analysis module can perform operational modal analysis on the vibration signal to generate a plurality of system dynamic parameters (natural frequency and damping during machine processing). The cutting state estimation module can analyze the dynamic parameters of the system according to the mathematical model of the cutting flutter to calculate the optimal rotation speed of the cutting machine in the range of the rotation speed.

According to one of the objects of the present invention, a method for estimating a cutting process parameter is further proposed. The method may include the steps of: taking a first vibration signal generated by the cutting machine during a cutting operation in a range of speeds; performing an operational modal analysis on the first vibration signal to generate a plurality of system dynamic parameters; and, The vibration mathematical model analyzes the dynamic parameters of the system to calculate the optimum rotational speed of the cutting machine in this rotational speed range.

In one embodiment, the signal sensing module can further capture the second vibration signal of the cutting machine at an optimal rotation speed and a cutting depth, and the signal analysis module can analyze the second vibration signal to generate vibration. The characteristic signal is used to extract the processing vibration spectrum characteristic, and the cutting state estimation module can compare the vibration characteristic signal with the preset threshold value, and repeatedly adjust the cutting depth until the vibration characteristic signal meets the preset threshold value to obtain a match. The optimum depth of cut for this optimum speed.

In one embodiment, the cutting state estimation module can analyze the dynamic parameters of the system according to a mathematical model of the cutting flutter to generate a flutter stability boundary map to calculate an optimal rotational speed.

In an embodiment, the system dynamic parameters may include a natural frequency and a damping ratio.

In an embodiment, the cutting state estimation module can compare the vibration characteristic signal with a preset threshold value Yes, if the vibration characteristic signal exceeds the preset threshold, the cutting state estimation module can issue a warning signal.

In view of the above, the cutting process parameter estimating device and method thereof according to the present invention may have one or more of the following advantages:

(1) An embodiment of the present invention performs operational modal analysis on the extracted vibration signals to obtain a plurality of system dynamic parameters, and then uses the mathematical model of the cutting flutter to analyze the dynamic parameters of the systems to calculate the flutter stability boundary map. Therefore, it is possible to accurately estimate the optimum speed suitable for the current operation of the cutting machine.

(2) In one embodiment of the present invention, not only the operational modal analysis of the captured vibration signal can be performed, but also the optimum rotational speed suitable for the current operation of the cutting machine can be calculated, and the best matching speed can be found for the optimal rotational speed. The optimum machining parameters such as the cutting depth can greatly increase the cutting speed, stability and material removal rate of the cutting machine.

(3) In one embodiment of the present invention, the operational modal analysis of the vibration signal during the cutting can be performed. Therefore, the cutting rigidity is also included in the analysis model, so that the optimum rotational speed estimation of the machining is more accurate.

(4) The method of the invention is simple and efficient, and the operator does not need to perform experimental modal test on the machine platform and does not need to use a device such as a power meter or an impact hammer, so the cost is low, so that the requirements for on-line detection of the general machine can be met. .

1‧‧‧Cutting machine

11‧‧‧First vibration signal

12‧‧‧Second vibration signal

2‧‧‧Cutting processing parameter estimation device

20‧‧‧Signal Sensing Module

21‧‧‧Signal Analysis Module

211‧‧‧Operational modal analysis

212‧‧‧Visonic signal characteristics analysis

2111‧‧‧System Dynamic Parameters

2121‧‧‧Vibration signal

22‧‧‧Cutting State Estimation Module

221‧‧‧Cutting flutter mathematical model

222‧‧‧ Preset threshold

2211‧‧‧ flutter stability boundary map

S31~S43‧‧‧Step process

A‧‧‧Optimal speed

B‧‧‧Optimal depth of cut

Fig. 1 is a first schematic view showing a first embodiment of the cutting processing parameter estimating device of the present invention.

Fig. 2 is a second schematic view showing the first embodiment of the cutting processing parameter estimating device of the present invention.

Fig. 3 is a flow chart showing the first embodiment of the cutting processing parameter estimating device of the present invention.

Embodiments of the cutting tool parameter estimating device and the method thereof according to the present invention will be described below with reference to the related drawings. For ease of understanding, the same components in the following embodiments are denoted by the same reference numerals.

Please refer to FIG. 1 , which is a schematic diagram of a first embodiment of a cutting processing parameter estimating device of the present invention. As shown in the figure, the cutting parameter estimation device 2 can include a signal sensing module 20, a signal analysis module 21, and a cutting state estimation module 22.

First, when the operator uses a cutting machine 1, such as a CNC lathe, milling machine, etc., to perform a cutting operation on a workpiece of a specific material, the operator can select a rotational speed range that is more likely to conform to the material characteristics of the workpiece according to the rule of thumb. The speed range is subjected to trial cutting, and the signal sensing module 20 can capture the first vibration signal 11 generated by the cutting machine 1 at this time. The signal analysis module 21 can perform an operational modal analysis 211 on the first vibration signal 11 to generate a plurality of system dynamic parameters 2111, which can include natural frequencies and damping ratios, and the like. The cutting state estimation module 22 may analyze the system dynamic parameters 2111 using the cutting flutter mathematical model 221 to generate a jitter stability map 2211. Therefore, the optimum rotational speed A of the tool spindle in which the cutting machine 1 has the highest cutting stability in this rotational speed range can be calculated through the chatter stability boundary map 2211.

The flutter stability boundary diagram 2211 is as shown in Fig. 2, in which the horizontal axis is the cutting spindle rotation speed, and the vertical axis is the ratio of the cutting to the machine dynamic rigidity. Wherein, the portion above the flutter stability boundary diagram 2211 is the cutting instability region, and the portion below the flutter stability boundary diagram 2211 is the cutting stability region.

After estimating the optimal speed A, the operator can set the speed of the cutting machine 1 to the optimal speed A. At this time, the operator can first use the optimal speed A to set a conservative cutting depth to execute. Cutting operation, and using the signal sensing module 20 to take the cutting machine 1 The optimum rotational speed A and the second vibration signal 12 generated during the cutting operation of the workpiece by the cutting depth.

Since the vibration spectrum has unique characteristics when flutter occurs or is about to occur, for example, the edge frequency of the tool spindle and its frequency multiplication near the multiplier, the signal analysis module 21 can be used according to the vibration spectrum characteristics described above. Determine if there is chattering. Therefore, the signal analysis module 21 can perform the vibration signal feature analysis 212 on the second vibration signal 12 to extract the processed vibration spectrum feature to generate the vibration characteristic signal 2121.

The cutting state estimation module 22 compares the vibration characteristic signal 2121 with a preset threshold value 222, and determines whether the cutting is in an unstable state. If not, it indicates that the depth of cut has not reached the limit. At this time, the operator can gradually increase the depth of cut. When the vibration characteristic signal 2121 exceeds the preset threshold 222, the cutting state estimation module 22 can issue a warning signal to remind The operator, while the operator can slightly reduce the depth of cut, so that the vibration characteristic signal 2121 can meet the preset threshold 222, so that the best cutting depth B that best matches the optimal rotational speed A can be found. As can be seen from the above, the above-described method allows the operator to easily find the optimum machining parameters when performing cutting operations on the workpieces of various materials by the cutting machine 1, which is extremely convenient and effective in use.

Please refer to FIG. 3, which is a flow chart of the first embodiment of the cutting processing parameter estimating device of the present invention. This embodiment includes the following steps:

S31: Select a preferred speed range and use a cutting machine to perform the trial cutting.

S32: Capture the vibration signal of the cutting machine.

S33: Perform operation modal analysis on the vibration signal to obtain system dynamic parameters.

S34: Analyze system dynamic parameters using a mathematical model of cutting flutter.

S35: Obtain the optimum speed in this speed range.

S36: Set the cutting machine to this optimum speed.

S37: Trial cutting at a depth of cut.

S38: Take the vibration signal of the cutting machine.

S39: The vibration signal is obtained by dividing the vibration signal.

S40: Comparing the vibration characteristic signal with a preset threshold value to determine whether the cutting operation has reached an unstable state? If no, go to step 41; if yes, go to step 42.

S41: Increase the depth of cut and return to step 37.

S42: Reduce the depth of cut and return to step 37 to retest whether the depth of cut will cause the cutting to be unstable. If yes, go to step 42 again; if no, go to step 43.

S43: The optimum cutting depth is obtained. At this time, the optimum rotation speed and the optimum cutting depth have been obtained, so the optimum machining parameters have been estimated.

It is worth mentioning that, in general, if you want to calculate the flutter stability boundary diagram of the cutting machine, you need to perform experimental modal analysis (EMA) or system identification for the tool spindle and tool. Measurements are made using impact hammers or dynamometers, and the power meters are very expensive and do not meet the requirements of on-line inspection of general machines. In addition, there are limitations to performing experimental modal analysis. For example, experimental modal analysis can only be performed while the system is in a static state. At this time, the spindle has no rotation and the tool is not in contact with the workpiece. That is to say, the dynamic model parameters obtained under the experimental modal analysis are not the same as the modal parameters of the actual system under the cutting dynamics, so the precise level cannot be achieved in the actual machining process.

However, in one embodiment, the present invention extracts the vibration signal and performs operational modal analysis to obtain a plurality of system dynamic parameters, and then uses the cutting flutter mathematical model to analyze the dynamic parameters of the systems to obtain the flutter. Stable boundary diagram, which can obtain the modal parameters of the system under the cutting dynamic without using the power meter. It is not only simple and low cost, but also extremely accurate, and can effectively obtain the optimal speed for the cutting machine to perform specific operations.

In addition, the estimation methods of the prior art are not only accurate, but also cannot be accurately estimated at the same time. Measure the optimum speed for the cutting operation and the optimum depth of cut for this optimum speed. In contrast, in one embodiment, the present invention can not only accurately estimate the optimum rotational speed of the cutting machine for performing a specific operation, but also utilize the analytical comparison to determine the optimum rotational speed of the cutting machine. The characteristic signal of the generated vibration signal is used to calculate the optimum depth of cut that best matches the optimum rotational speed to find the most suitable processing parameter.

As can be seen from the above, the present invention can effectively improve the cutting speed, the stability, and the material removal rate, so that it is a progressive patent requirement.

In summary, an embodiment of the present invention provides an operational modal analysis of the extracted vibration signals to obtain a plurality of system dynamic parameters, and then uses the cutting flutter mathematical model to analyze the dynamic parameters of the system to calculate the flutter stability. The boundary diagram allows accurate calculation of the optimum speed for the current operation of the cutting machine.

In addition, in one embodiment of the present invention, not only the operational modal analysis and the like of the captured vibration signal can be calculated to calculate the optimal rotational speed suitable for the current operation of the cutting machine, and the matching can be found for the optimal rotational speed. The optimum processing parameters such as the optimum depth of cut, the present invention can maximize the cutting speed, stability and material removal rate of the cutting machine, and effectively improve the shortcomings of the prior art.

In addition, the present invention proposes that the method for estimating the cutting processing parameters is not only simple, but also can be measured without a power meter, so that it can achieve high efficiency without greatly increasing the cost, and can satisfy the general machine. The need for online testing.

It can be seen that the present invention has achieved the desired effect under the prior art, and is not familiar with the skill of the artist, and its progressiveness and practicability have been met with the patent application requirements.提出 Submit a patent application in accordance with the law, and ask your bureau to approve the application for this invention patent, in order to encourage creation, to the sense of virtue.

The above is intended to be illustrative only and not limiting. Any other essence that does not deviate from the invention God and the scope, and equivalent modifications or changes to them shall be included in the scope of the patent application attached.

S31~S43‧‧‧Step process

Claims (10)

A cutting processing parameter estimating device comprises: a signal sensing module, which is a first vibration signal generated when a cutting machine performs a cutting operation in a speed range; a signal analysis module is The first vibration signal performs an operational modal analysis to generate a plurality of system dynamic parameters; and a cutting state estimation module analyzes the dynamic parameters of the system by a cutting flutter mathematical model to calculate the rotational speed of the cutting machine One of the best speeds in the range. The cutting parameter estimation device according to claim 1, wherein the signal sensing module further captures the second vibration signal of the cutting machine at the optimal rotation speed and cutting operation at a cutting depth. The signal analysis module analyzes the second vibration signal to generate a vibration characteristic signal to capture the processing vibration spectrum characteristic, and the cutting state estimation module compares the vibration characteristic signal with a preset threshold value. The depth of cut is repeatedly adjusted until the vibration characteristic signal meets the preset threshold value to obtain an optimum depth of cut that matches one of the optimal rotational speeds. The cutting tool parameter estimating device according to claim 2, wherein the cutting state estimating module analyzes the system dynamic parameters by using the cutting flutter mathematical model to generate a flutter stability boundary map to calculate the The best speed. The cutting tool parameter estimating device according to claim 3, wherein the system dynamic parameters comprise a natural frequency and a damping ratio. The cutting tool parameter estimating device according to claim 3, wherein the cutting state estimating module compares the vibration characteristic signal with the preset threshold value, if the vibration characteristic signal exceeds the preset threshold value The cutting state estimation module sends a warning signal. A method for estimating a machining parameter includes the following steps: one of the first vibration signals is generated when a cutting machine performs a cutting operation in a range of speeds Performing an operational modal analysis on the first vibration signal to generate a plurality of system dynamic parameters; and analyzing the system dynamic parameters by a cutting flutter mathematical model to calculate one of the cutting machine positions in the rotational speed range Good speed. The method for estimating a cutting processing parameter according to claim 6, further comprising the steps of: taking a second vibration signal of the cutting machine at the optimum rotation speed and performing a cutting operation at a cutting depth; analyzing the The second vibration signal generates a vibration characteristic signal to extract the processing vibration spectrum characteristic; and compares the vibration characteristic signal with a preset threshold value, thereby repeatedly adjusting the cutting depth until the vibration characteristic signal conforms to the pre- Set the threshold value to obtain the optimum depth of cut that matches one of the optimal speeds. The method for estimating a cutting processing parameter according to claim 7 further includes the following steps: analyzing the dynamic parameters of the system by the mathematical model of the cutting flutter to generate a flutter stability boundary map to calculate the optimal rotational speed. The method for estimating a cutting processing parameter according to claim 8, wherein the system dynamic parameters include a natural frequency and a damping ratio. The method for estimating a cutting processing parameter as described in claim 8 further includes the step of: issuing a warning signal when the vibration characteristic signal exceeds the preset threshold value.