JP2012206230A - Processing chatter detector and machine tool - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a processing chatter detector and a machine tool capable of promptly identifying the constituents of chatter in processing.SOLUTION: The CPU 11 of the processing chatter detector 10 carries out a measuring processing at first and presumes a disturbed torque during a cutting processing in the measuring processing, and then executes an analysis processing. The CPU 11, during the analysis processing, analyzes the disturbed torque presumed in the measuring processing by way of a filtering processing using a digital filter, and checks the constituents of the chatter in the processing of cutting, that is, whether the chatter is due to a self-excitation or a forced processing chatter. The CPU 11 draws up a diagrammatic chart information based on the data analyzed in the analysis processing, outputting it on a display device 14. The display device 14 indicates the information of diagrammatic chart received from the CPU 11. An operator checks the diagrammatic chart displayed on the screen and can clearly and easily grasp what sort of vibration is occurring during the cutting process.

Description

  The present invention relates to a machining chatter vibration detection device and a machine tool.

  A machine tool cuts a workpiece by mounting the tool on a rotatable spindle and sending the tool to the workpiece. When a machine tool has a cutting depth larger than necessary, a so-called “work chatter vibration” occurs during machining. Therefore, the finished surface finish accuracy deteriorates. Processing chatter vibration can be classified into “self-excited chatter vibration” and “forced chatter vibration”. Self-excited chatter vibration is a vibration component generated between a tool and a workpiece. Forced chatter vibration is a vibration component having a machine tool as a vibration source. It is important to specify which component of self-excited chatter vibration or forced chatter vibration is occurring in order to suppress and avoid machining chatter vibration. Patent Document 1 discloses a vibration suppression device for a machine tool that determines the frequency of machining chatter vibration by FFT processing and determines whether it is self-excited chatter vibration or forced chatter vibration depending on whether it is close to N times the machining frequency of one blade. To do.

Japanese Patent No. 4582660

  The vibration suppression device for a machine tool disclosed in Patent Document 1 obtains the frequency of machining chatter vibration by FFT processing. The FFT processing has a high calculation load. There is a problem that processing chatter vibration of a machine tool changes every moment, so that processing cannot catch up.

  An object of the present invention is to provide a machining chatter vibration detection device and a machine tool that can quickly identify a machining chatter vibration component.

  The processing chatter vibration detecting apparatus according to the first aspect of the present invention analyzes a processing chatter vibration or processing load of a processing machine that processes a workpiece, and analyzes the processing chatter vibration or processing load measured by the measuring means. In the processing chatter vibration detecting apparatus including an analyzing means, the analyzing means extracts a forced chatter digital filter section that extracts forced chatter from the machining chatter vibration or processing load measured by the measuring means, and extracts self-excited chatter. Self-excited chatter digital filter section and at least one of high-frequency chatter digital filter section for extracting high-frequency chatter, forced chatter digital filter, self-excited chatter digital filter, forced chatter extracted by high-frequency chatter digital filter, self-excited chatter, Output means for outputting at least one of the high-frequency chatters

  In the processed chatter vibration detecting apparatus according to the first aspect, the analyzing means is provided with at least one of a forced chatter digital filter unit, a self-excited chatter digital filter unit, and a high-frequency digital filter unit. The output means outputs the result extracted by the forced chatter digital filter unit, the self-excited chatter digital filter unit, and the high frequency digital filter unit. Therefore, according to the present aspect, it is possible to easily and quickly identify the component of processing chatter vibration generated in the processing machine or processing load. The operator can easily and quickly grasp the processing chatter vibration generated in the processing machine or the component of the processing load from the result output by the output means.

  In the first aspect, the measuring means may measure position information of a drive shaft provided in the processing machine, and measure the processing chatter vibration or processing load based on the position information. Therefore, the measuring means can measure the processing chatter vibration or processing load of the processing machine based on the position information of the drive shaft.

  In the first aspect, the measuring means may be a disturbance observer that estimates a disturbance based on position information and torque of a drive shaft provided in the processing machine. Therefore, the measuring means can measure the processing chatter vibration or processing load of the processing machine. Since this embodiment does not require an external sensor, an increase in cost can be suppressed.

  In the first aspect, the self-excited chatter digital filter unit and the forced chatter digital filter unit may include a band-pass filter and a notch filter, and the high-frequency chatter digital filter unit may include a high-pass filter. Therefore, forced chatter, self-excited chatter, and high-frequency chatter can be extracted easily and quickly from the machining chatter vibration or machining load measured by the measuring means.

  In the first aspect, the cutoff frequency of the low-pass filter is lower than the frequency at which the main shaft self-excited chatter and forced chatter occur, and the passband frequency of the band-pass filter is the same as that of the main shaft self-excited chatter. The notch frequency of the notch filter is an integral multiple of the product of the number of cutting edges of the tool and the spindle speed during machining, and a plurality of notches within the frequency range of the pass band of the band pass filter. A filter having a frequency may be used. Therefore, forced chatter, self-excited chatter, and high-frequency chatter can be extracted easily and quickly from the machining chatter vibration or machining load measured by the measuring means.

  Further, in the first aspect, the analyzing means calculates an average value of each amplitude of forced chatter, self-excited chatter, and high-frequency chatter extracted in the forced chatter digital filter unit, the self-excited chatter digital filter unit, and the high-frequency digital filter unit. Based on the comparison between the average value calculation means to be calculated and the respective average values calculated by the average value calculation means, it is time-sequentially indicating which vibration is dominantly generated among forced chatter, self-excited chatter, and high-frequency chatter. A determination unit for determining, and the output unit may output a determination result of the determination unit. Therefore, the worker can more easily grasp the chatter vibration generated in the processing machine or the component of the processing load in time series.

  A machine tool according to a second aspect of the present invention includes the machining chatter vibration detection device according to any one of claims 1 to 6.

  Since the machine tool according to the second aspect includes the processing chatter vibration detection device according to any one of claims 1 to 6, the effect described in the first aspect can be obtained.

1 is a block diagram illustrating a configuration of a vibration detection device 10 connected to a machine tool 1. FIG. It is a flowchart of a processing chatter vibration detection process. It is a figure which shows the estimation procedure of the disturbance torque which applied the disturbance observer in a measurement process. It is a table | surface which shows the cutting conditions of a side surface experiment. It is a figure which shows the positional relationship of the workpiece 9 and the tool 8 which were used for the side surface experiment. It is a graph which shows the relationship between the disturbance torque estimated on the conditions of rotational speed 6400min < ^-1 >, and time. It is a graph which shows the relationship between the disturbance torque estimated on condition of rotational speed 7800min < ^-1 >, and time. It is a microscope picture of the processing surface of the work material 9 cut on condition of rotational speed 6400min- ¹ . It is a microscope picture of the processing surface of the work material 9 cut on condition of rotational speed 7800min- ¹ . It is a graph which shows the FFT analysis result of the disturbance torque estimated on condition of rotational speed 6400min- ¹ . It is a graph which shows the FFT analysis result of the disturbance torque estimated on condition of rotational speed 7800min- ¹ . It is a figure which shows the process sequence of the filtering process in an analysis process. It is a table | surface which shows the amplitude characteristic of a digital filter. It is a graph which shows the filtering result of the disturbance torque estimated on the conditions of rotational speed 6400min- ¹ . It is a graph which shows the filtering result of the disturbance torque estimated on condition of rotational speed 7800min- ¹ . It is the graph which averaged the filtering result of rotational speed 6400min < ^-1 > (1st modification). It is the graph which averaged the filtering result of rotational speed 7800min < ^-1 > (1st modification). It is the graph which showed the ratio of the vibration component of rotational speed 6400min < ^-1 > (2nd modification). It is the graph which showed the ratio of the vibration component of rotational speed 7800min ^-1 (2nd modification). It is a flowchart of the processing chatter vibration detection process of a 3rd modification. It is a flowchart of a processing chatter component determination process. It is the graph which showed the change of the vibration component of rotational speed 6400min ^-1 (3rd modification). It is the graph which showed the change of the vibration component of rotational speed 7800min- ¹ (3rd modification).

  Hereinafter, a vibration detection device 10 according to an embodiment of the present invention will be described with reference to the drawings. The drawings to be referred to are used for explaining the technical features that can be adopted by the present disclosure, and the configuration and flowcharts of the apparatus described are not intended to be limited only to them, but are merely illustrative examples. is there.

  A configuration of the vibration detection apparatus 10 will be described. As shown in FIG. 1, the vibration detection device 10 detects “work chatter vibration” generated in a spindle 7 rotatably provided in the spindle head 5 of the machine tool 1 and specifies a component of the machining chatter vibration. Device. The machine tool 1 is a machine that cuts a work material 9 on a table (not shown) with a tool 8 mounted on a spindle 7.

  The vibration detection device 10 includes a CPU 11, a ROM 12, a RAM 13, a display device 14, and an operation unit 15. The CPU 11 comprehensively controls the operation of the vibration detection device 10. The ROM 12 stores a control program for the vibration detection device 10, a machining chatter vibration detection program, and the like. The RAM 13 temporarily stores various data for executing processing chatter vibration detection processing to be described later. The display device 14 displays the graph information output by the CPU 11 on a screen (not shown). The operation unit 15 includes various input keys for operating the vibration detection device 10.

  Processing chatter vibration detection processing executed by the CPU 11 of the vibration detection apparatus 10 will be described with reference to the flowchart of FIG. When the CPU 11 recognizes that the machine tool 1 is machining based on the machining signal of the machine tool 1, the CPU 11 reads the machining chatter vibration detection program stored in the ROM 12 and executes this processing.

  The CPU 11 first executes a measurement process (S1). The CPU 11 measures machining chatter vibration generated during cutting of the machine tool 1 in the measurement process. The CPU 11 indirectly measures the machining chatter vibration by estimating the disturbance torque of the spindle motor 6. The CPU 11 applies a “disturbance observer” to the current monitor value of the spindle motor 6 and the spindle angular velocity to estimate the disturbance torque during the cutting process. The CPU 11 executes analysis processing (S2). The CPU 11 analyzes the component of vibration chatter vibration during cutting by filtering the disturbance torque estimated in the measurement process of S1 using a digital filter. The CPU 11 creates graph information based on the analysis information of S2 and outputs it to the display device 14 (S5). The display device 14 displays a graph on a screen (not shown) based on the graph information received from the CPU 11. By checking the graph displayed on the screen, the operator can clearly and quickly grasp what kind of vibration component is generated during the cutting process. The CPU 11 determines whether or not the cutting of the machine tool 1 has been completed (S6). When the CPU 11 determines that cutting of the machine tool 1 is continuing (S6: NO), the CPU 11 returns to S1 and repeats the process. When the CPU 11 determines that the cutting of the machine tool 1 has been completed (S6: YES), the processing chatter vibration detection process ends. Hereinafter, the principle, procedure, effect, etc. in each processing of the processing chatter vibration detection processing will be described in detail.

The principle of chatter vibration measurement using a disturbance observer in the measurement process will be described. The equation of motion of the spindle 7 of the machine tool 1 can be expressed as the following formula 1 in consideration of the motor torque T _m and the load torque T _l (total of cutting torque and friction torque).
ω [rad / s] is the spindle angular velocity. I _a [A] is a current monitor value. J [kg / m ² ] is the spindle inertia moment. K _t [Nm / A] is a torque constant of the spindle motor 6.

Moment of inertia and torque constant, due mechanical structure and torque ripple, respectively .DELTA.J, there are variations in [Delta] K _t. Usually, it is negligible compared with the cutting load and can be ignored. Thus the disturbance torque _{T dis} is defined as the sum of the cutting torque _{T cut} and friction torque _{T Fric.} Therefore, the disturbance torque _Tdis can be estimated from the current monitor value and the spindle angular velocity as in the following equation (2).

As shown in FIGS. 1 and 3, the CPU 11 acquires a current monitor value from the spindle motor 6 as torque information in the measurement process. The CPU 11 calculates a torque (T _m ) based on the acquired current monitor value and a torque constant. Further, the CPU 11 acquires the spindle angular velocity (ω) as the drive shaft position information from the encoder 6A (see FIG. 1) provided in the spindle motor 6.

  Differentiating the spindle angular velocity increases the noise in the high frequency range. As shown in FIG. 3, the CPU 11 uses a low-pass filter (LPF) in the measurement process to block high-frequency noise and estimate disturbance torque. The frequency of the disturbance torque that can be estimated depends on the LPF. The CPU 11 sets the cutoff frequency of the LPF higher than the chatter vibration frequency in order to estimate the disturbance torque. Therefore, the CPU 11 can estimate the disturbance torque during the cutting process.

  Machining chatter vibration is generated by fluctuations in cutting torque accompanying changes in the amount of cut. As described above, the disturbance torque is the sum of the cutting torque and the friction torque. In the machine tool 1, the spindle rotation speed is constant between certain operations, so the friction is substantially constant. Therefore, the vibration detection apparatus 10 can detect fluctuations in the cutting torque, which is a cause of machining chatter vibration, by monitoring disturbance torque in the measurement process. Since this embodiment does not require an external sensor, an increase in cost can be suppressed.

  The disturbance torque estimated by the measurement process is verified. In this example, in order to verify the disturbance torque estimated in the measurement process, the same side surface machining experiment was performed on the work material 9 (see FIG. 1) under two cutting conditions in which the rotation speed of the main shaft 7 was changed. went. The table in FIG. 4 shows the cutting conditions of this example. In the side machining experiment, a square end mill (tool 8 shown in FIG. 5) having a diameter of 10 mm was used. The side machining experiment used a machine tool 1 that is a three-axis machining center. As the work material, a work material 9 as shown in FIG. 5 is used in order to change the cutting amount in the Z-axis direction from 5 to 20 mm. The CPU 11 of the vibration detection apparatus 10 estimated the disturbance torque when side machining was performed under two cutting conditions. The time variation of the estimated disturbance torque is shown in the graphs of FIGS.

As shown in FIG. 6, chatter vibration is generated between 2.8 and 7.8 seconds after the start of measurement according to the disturbance torque when cutting is performed at a rotational speed of 6400 min ⁻¹ . On the other hand, as shown in FIG. 7, chatter vibration is generated between 1.5 and 6.0 seconds after the start of measurement according to the disturbance torque when cutting is performed under the condition of the rotational speed of 7800 min ⁻¹ . . As chatter vibration occurs, the disturbance torque increases. The behavior of disturbance torque with respect to time differs between the cutting condition of 6400 min ^{−1 and} the cutting condition of 7800 min ⁻¹ . As shown in FIGS. 8 and 9, the processed surface of the work material 9 is also different. Specifically, when the machining surface of the work material 9 machined under the cutting condition of 6400 min ⁻¹ is seen, the shape of the chatter mark generated in the cutting has changed to at least (a) and (b) in FIG. . On the other hand, when the processing surface of the work material 9 processed under the cutting condition of 7800 min ⁻¹ is seen, the shape of the chatter mark generated in the cutting is at least (a), (b), (c), (d ). Therefore, it can be estimated that machining chatter vibrations of different components occurred during cutting.

In order to specify the component of machining chatter vibration, the disturbance torque estimated by the CPU 11 of the vibration detection apparatus 10 was subjected to FFT analysis. The time transition results of the FFT analysis are shown in the graphs of FIGS. The horizontal axis represents time, the left vertical axis represents frequency, and the right vertical axis represents peak value. The higher the peak value, the darker the frequency. FIG. 10 is a graph of an FFT analysis result at a rotational speed of 6400 min ⁻¹ . FIG. 11 is a graph of an FFT analysis result at a rotational speed of 7800 min ⁻¹ . As shown in FIGS. 10 and 11, each FFT analysis result shows a plurality of peaks. The peak frequency changed in the same manner as the change in the processed surface of the work material 9. Therefore, it can be estimated that different chatter vibration components were generated.

As shown in FIG. 10, according to the analysis result of 6400 min ⁻¹ , a peak was observed at 1800 to 2000 Hz in 2.8 to 7.0 seconds. It was found that high-frequency chatter vibration occurred. Past research has revealed that self-excited chatter vibration occurs near the resonance frequency of the main shaft 7. From the impulse response method performed in advance, the resonance frequencies of the main shaft 7 were 838 Hz and 2300 Hz. Since the tool and the workpiece are in contact during machining, the dynamic model differs depending on whether the contact is not considered. Therefore, in the impulse response method, it is considered that chatter vibration caused by the resonance frequency in the dynamic model considering the contact that cannot be identified occurred. The chatter marks formed on the processed surface of the work material 9 were oblique to the feed direction (see (a) in FIG. 8). This proved to be self-excited chatter vibration. Further, a peak was observed at 793 Hz in 7.0 to 7.7 seconds. This is chatter vibration caused by the resonance frequency of the main shaft 7 of 838 Hz. The chatter marks formed on the processed surface of the work material 9 were oblique to the feed direction (see (b) in FIG. 8). This proved to be self-excited chatter vibration.

As shown in FIG. 11, according to the analysis result at 7800 min ⁻¹ , a peak was observed at 780 Hz in 1.5 to 1.9 seconds. It can be seen that this is three times the frequency at which the blade of the tool 8 contacts the work material 9. This is based on the fact that (chatter frequency / (number of rotations / 60 × number of blades) = 780 / (7800/60 × 2) = 3 times Further, chatter marks formed on the processed surface of the work material 9 are (See (a) in Fig. 9.) For the chatter vibration, the chatter vibration and the frequency at which the blade of the tool 8 contacts are synchronized, so the chatter mark is perpendicular to the feed direction. Therefore, this chatter vibration is likely to be forced chatter vibration, peaking at 1800 to 2000 Hz and 793 Hz at 1.9 to 2.6 seconds, and 3.7 to 6.0 seconds. As with 6400 min ⁻¹ , it was found that self-excited chatter vibration was caused by the resonance frequency of the main shaft 7. Peaks were observed at 773 Hz and 793 Hz in 2.6 to 3.7 seconds. Therefore, it is strong in this section It was found that the chatter vibration is transitioning to self-excited chatter.

  The change in disturbance torque shown in FIGS. 6 and 7, the machining surface shown in FIGS. 8 and 9, and the FFT analysis results in FIGS. 10 and 11 substantially coincide with each other. Therefore, it can be seen that the disturbance torque estimated by the CPU 11 in the measurement process reflects not only the presence or absence of machining chatter vibration but also the chatter vibration component.

  A filtering process in the analysis process will be described. The CPU 11 performs a filtering process using a plurality of digital filters on the disturbance torque estimated by the measurement process. The CPU 11 can quickly analyze whether the chatter vibration generated during cutting is self-excited chatter vibration or forced chatter vibration. The digital filter has a smaller delay and a smaller calculation load than the FFT analysis. Therefore, the CPU 11 can quickly analyze the component of machining chatter vibration.

The configuration of the digital filter will be described. As illustrated in FIG. 12, the CPU 11 performs analysis processing using a low-pass filter (H _LPF ) 51, a high-pass filter (H _HPF ) 52, a band-pass filter (H _BPF ) 53, and a notch filter (H _NF ) 54. . As shown in the table of FIG. 13, the low-pass filter 51 passes the band of 0 to 300 Hz. The cutoff frequency of the low-pass filter 51 is a frequency lower than the frequency at which the self-excited chatter and the forced chatter of the main shaft 7 occur, and is 300 Hz in this embodiment. The high pass filter 52 passes a band of 1600 Hz or higher. The cutoff frequency of the high pass filter 52 of this embodiment is 1600 Hz. The band pass filter 53 passes a band of 600 to 1000 Hz. The passband frequency of the bandpass filter 53 is a frequency band in which self-excited chatter and forced chatter of the main shaft 7 occur. The cut-off frequency of the band pass filter 53 is 600 or 1000 Hz. The notch filter 54 is a filter having a plurality of notch frequencies within an integral multiple of the product (tool contact frequency) of the number of cutting blades of the tool and the spindle rotation number during machining (tool contact frequency). is there. The bandwidth 30Hz in this embodiment, the cutoff frequency is when processed at 6400min ^-1 640Hz and 853Hz, if processed in 7800Min ^-1 is 780Hz.

CPU11 performs the filtering process of the disturbance torque estimated by the measurement process using the filtering procedure shown in FIG. The bandpass filter 53 extracts a disturbance torque near the main shaft resonance frequency (838 Hz). Furthermore, the notch filter 54 cuts off the tool contact frequency and an integral multiple thereof. Therefore, the CPU 11 can block the forced chatter vibration component and take out the _self -excited chatter vibration component (T _self ). Conversely, by inverting it as in the procedure shown in FIG. 12, the CPU 11 can extract only the component of _forced chatter vibration ( _Tforced ).

The high pass filter 52 extracts high-frequency chatter vibration (T _HPF ). The low-pass filter 51 extracts low-frequency disturbance torque (T _LPF ) as friction torque and cutting torque during normal cutting. The CPU 11 converts the analysis information of the filtering result into graph information and outputs it to the display device 14. The display device 14 displays each analyzed graph on a screen (not shown) based on the graph information received from the CPU 11.

14 and 15 show each graph displayed on the screen of the display device 14. FIG. 14 is a graph showing a disturbance torque filtering result estimated under the condition of the rotational speed of 6400 min ⁻¹ . FIG. 15 is a graph showing a filtering result of disturbance torque estimated under the condition of the rotational speed of 7800 min ⁻¹ . 14 and 15 show the high-frequency chatter vibration component (T _HPF ), the self-excited chatter vibration component (T _self ), and the forced chatter vibration (T _forced ) in order from the top.

In both the graphs of FIGS. 14 and 15, each component of the disturbance torque subjected to the filtering process is changed by the component of the machining chatter vibration. As shown in FIG. 14, according to the filtering result of 6400 min ⁻¹ , the amplitude of the high-frequency disturbance torque filtered by the high-pass filter 52 is large in 2.8 to 7.0 seconds in which a peak is observed at 1800 to 2000 Hz. It has become. Furthermore, the amplitude of the self-excited chatter vibration component increases at 7.0 to 7.7 seconds when a peak is observed at 793 Hz.

On the other hand, as shown in FIG. 15, according to the filtering result of 7800 min ⁻¹ , the amplitude of the forced chatter vibration component increases in 1.5 to 1.9 seconds when a peak three times the tool contact frequency is seen. ing. In 2.0 to 2.7 seconds in which a peak is observed at 1800 to 2000 Hz, the amplitude of the high-frequency disturbance torque filtered by the high-pass filter 52 is large. In 3.6 to 6.0 seconds where a peak was observed at 793 Hz, the amplitude of the self-excited chatter vibration component increased. In 2.7 to 4.0 seconds, which is a transition state from forced chatter vibration to self-excited chatter vibration, both the forced chatter vibration component and the self-excited chatter vibration component have large amplitudes.

  Therefore, the CPU 11 can clearly identify the component of the processed chatter vibration by performing the filtering process using the digital filter on the disturbance torque estimated by the measurement process. The operator checks the graph of FIG. 14 or 15 displayed on the screen of the display device 14. The operator can clearly and quickly confirm what component causes the chatter vibration generated during the cutting of the machine tool 1. Further, the machine tool 1 can be used as important information for suppressing and avoiding machining chatter vibration.

  As described above, in the machining chatter vibration detection device 10 of the present embodiment, the CPU 11 first executes a measurement process. The CPU 11 estimates the disturbance torque during the cutting process in the measurement process. The CPU 11 executes analysis processing. The CPU 11 analyzes the disturbance torque estimated by the measurement process in the analysis process by a filtering process using a digital filter, which is a component of chatter vibration during cutting, that is, self-excited chatter vibration or forced chatter vibration. The CPU 11 creates graph information based on the data analyzed in S <b> 2 and outputs it to the display device 14. The display device 14 displays the graph information received from the CPU 11 on a screen (not shown). By checking the graph information displayed on the screen, the operator can clearly and easily grasp what kind of vibration is occurring during the cutting process.

  Further, particularly in the present embodiment, the CPU 11 acquires position information of the drive shaft of the spindle motor 6 by the encoder 6A provided in the spindle motor 6 of the machine tool 1 when executing the measurement process. Therefore, this embodiment can measure the chatter vibration during the cutting process based on the acquired position information of the drive shaft.

  In this embodiment, in particular, the disturbance torque during cutting is easily and quickly estimated by applying a disturbance observer to the position information of the drive shaft of the spindle motor 6 of the machine tool 1 and the current monitor value of the spindle motor 6. it can.

  In the present embodiment, in particular, the CPU 11 performs a disturbance torque filtering process using the low-pass filter 51, the high-pass filter 52, the band-pass filter 53, and the notch filter 54 in the analysis process. Therefore, the present embodiment can clearly and quickly identify the component of machining chatter vibration (self-excited chatter vibration, forced chatter vibration) from the estimated disturbance torque.

  In the present embodiment, in particular, in the analysis processing of the CPU 11, the cutoff frequency of the low-pass filter 51 is set to a frequency lower than the frequency at which the main shaft 7 generates self-excited chatter and forced chatter. The passband frequency of the bandpass filter 53 is a frequency band in which self-excited chatter and forced chatter of the main shaft 7 occur. The notch frequency of the notch filter 54 is a filter having a plurality of notch frequencies within the range of the frequency of the pass band of the band pass filter 53, which is an integral multiple of the product of the number of cutting edges of the tool 8 and the spindle rotational speed. Therefore, the present embodiment can clearly and quickly identify the component of machining chatter vibration (self-excited chatter vibration, forced chatter vibration) from the estimated disturbance torque.

  In the above description, the machine tool 1 is an example of the “processing machine” in the present invention. The CPU 11 that executes the process of S1 in FIG. 2 is an example of the “measuring unit” in the present invention. The CPU 11 that executes the process of S2 is an example of the “analyzing means” in the present invention. The CPU 11 that executes the process of S5 is an example of the “output unit” in the present invention.

  In addition, this invention is not limited to the said embodiment, A various deformation | transformation is possible. For example, in the above embodiment, the CPU 11 converts the analysis information filtered by the digital filter into graph information and outputs it to the display device 14 in the analysis processing. For example, the CPU 11 performs another process on the filtering result analyzed in the analysis process, thereby displaying a graph on the screen of the display device 14 that makes the change in chatter vibration components generated during cutting easier to understand. You can also.

  A description will be given of first to third modified examples in which the analysis information obtained by the analysis process is further processed to more clearly display the chatter vibration component. Since the following first to third modified examples have the same configuration and the same processing as those of the above-described embodiment, different points will be mainly described.

  A first modification will be described. The CPU 11 of the first modified example calculates the absolute value of each component data of the machining chatter vibration analyzed by the above-described machining chatter vibration detection process, and calculates, for example, a moving average of 400 pieces of data. The CPU 11 converts the calculated average value of each component of the processed chatter vibration into graph information and outputs it to the display device 14. The display device 14 displays each analyzed graph on a screen (not shown) based on the graph information received from the CPU 11.

16 and 17 show the respective graphs displayed on the screen of the display device 14. Low-frequency component of the amplitude average value _{T Ave_LPF,} shows the amplitude average value _{T Ave_HPF} of the high-frequency component, self-excited chatter vibration component of the average amplitude value _{T Ave_self,} the average amplitude value of the forced chatter vibration component as _{T ave_forced.} As shown in FIGS. 16 and 17, it can be confirmed that the amplitude value of each component of the machining chatter vibration varies with time.

Specifically, as shown in FIG. 16, at a rotational speed of 6400 min ⁻¹ , the amplitude of the high-frequency disturbance torque increases from 2.8 to 7.0 seconds. Furthermore, the amplitude of the self-excited chatter vibration component increases in 7.0 to 7.7 seconds. This is the same as the result of the above embodiment. On the other hand, as shown in FIG. 17, at the rotational speed of 7800 min ⁻¹ , the amplitude of the forced chatter vibration component increases from 1.5 to 1.9 seconds. From 2.0 to 2.7 seconds, the amplitude of the high-frequency disturbance torque increases. In 3.6 to 6.0 seconds, the amplitude of the self-excited chatter vibration component increases. In the transition state from forced chatter vibration to self-excited chatter vibration of 2.7 to 4.0 seconds, both the forced chatter vibration component and the self-excited chatter vibration component have large amplitudes. These results are the same as the results of the above embodiment. Therefore, compared with the said embodiment, the 1st modification can display clearly which component of processing chatter vibration has generate | occur | produced with progress of time by one graph.

A second modification will be described. The CPU 11 of the second modification example uses the average value of each component of the machining chatter vibration calculated in the first modification example to calculate the ratio of each component when the sum of the components is 1. The CPU 11 creates graph information from the calculated ratio of each component of the processed chatter vibration and outputs it to the display device 14. The display device 14 displays each analyzed graph on a screen (not shown) based on the graph information received from the CPU 11. As an example, the ratio of the self-excited chatter vibration component is shown in the following Expression 3. The forced chatter vibration component, the low frequency component, and the high frequency component may be calculated similarly.

18 and 19 show each graph displayed on the screen of the display device 14. FIG. 18 is a graph showing the ratio of vibration components at a rotational speed of 6400 min ⁻¹ . FIG. 19 is a graph showing the ratio of vibration components at a rotational speed of 7800 min ⁻¹ . Low-frequency component of the amplitude average value _{T Ave_LPF,} shows the amplitude average value _{T Ave_HPF} of the high-frequency component, self-excited chatter vibration component of the average amplitude value _{T Ave_self,} the average amplitude value of the forced chatter vibration component as _{T ave_forced.}

  Each graph of FIGS. 18 and 19 can more clearly display which chatter vibration component is most generated as compared with the graphs of FIGS. 16 and 17. These results are the same as the results of the above embodiment. Therefore, the second modification can clearly display which component of the machining chatter vibration is generated with time in one graph as compared with the above embodiment.

  A third modification will be described. The CPU 11 of the third modification uses the average value of each component of machining chatter vibration calculated in the first modification to determine which machining chatter vibration component is most dominant over time. judge. The CPU 11 creates graph information based on the determined change in each component of the processed chatter vibration and outputs the graph information to the display device 14.

  Processing chatter vibration detection processing executed by the CPU 11 of the third modification will be described with reference to the flowcharts of FIGS. When the CPU 11 recognizes that the machine tool 1 is machining based on the machining signal of the machine tool 1, the CPU 11 reads the machining chatter vibration detection program (modified example) stored in the ROM 12 and executes this processing. The CPU 11 first executes the above measurement process (S1). The CPU 11 executes the above analysis process (S2).

  The CPU 11 further executes an average value calculation process (S3). The CPU 11 calculates the absolute value of each of the disturbance torques filtered in the analysis process in real time, and calculates the average value of each component of chatter vibration. The CPU 11 executes processing chatter component determination processing (S4).

The processing chatter component determination processing will be described with reference to the flowchart of FIG. Or CPU11, rather than the amplitude average value of the high frequency component _{(T ave_HPF)} is 3, than the self-excited chatter average amplitude value of the vibration component _{(T ave_self),} greater than the average amplitude of the forced chatter vibration component _{(T ave_forced)} It is determined whether or not (S11). If the CPU 11 determines that the average amplitude value of the high-frequency component is greater than 3 than the average amplitude value of the self-excited chatter vibration component (S11: YES), that is the high-frequency vibration. Judge as a component. Therefore, CPU11 memorize | stores in RAM13 (refer FIG. 1) as a high frequency vibration component (S14).

When the CPU 11 determines that the average amplitude value of the high-frequency component is smaller than 3 or less than the average amplitude value of the forced chatter vibration component than the average amplitude value of the self-excited chatter vibration component (S11: NO), It is determined whether or not the amplitude average value (T _{ave — self} ) of the chatter vibration component is larger than 4 and the amplitude average value (T _{ave — HPF} ) of the high frequency component is larger than the amplitude average value (T _{ave —} forced) of the forced chatter vibration component. (S12). When the CPU 11 determines that the amplitude average value of the self-excited chatter vibration component is larger than 4, the amplitude average value of the high-frequency component is larger than the amplitude average value of the forced chatter vibration component (S12: YES), it is self-excited. Judged as chatter vibration component. Therefore, CPU11 memorize | stores in RAM13 (refer FIG. 1) as a self-excited chatter vibration component (S14).

When the CPU 11 determines that the amplitude average value of the self-excited chatter vibration component is less than 4 or less than the amplitude average value of the forced chatter vibration component than the amplitude average value of the high frequency component (S12: NO), the forced average amplitude of chatter vibration component _{(T ave_forced)} than 15, than the self-excited chatter average amplitude value of the vibration component _{(T ave_self),} determines whether greater than the amplitude average value of the high frequency component _{(T ave_HPF)} (S13). When the CPU 11 determines that the average amplitude value of the forced chatter vibration component is larger than 15 than the average amplitude value of the self-excited chatter vibration component (S13: YES), it is forced chatter. Determined as vibration component. Therefore, CPU11 memorize | stores in RAM13 (refer FIG. 1) as a forced chatter vibration component (S14). CPU11 complete | finishes a processing chatter vibration determination process, and returns to S5 of the main flow of FIG. Since the values of “3”, “4”, and “15” in S11, S12, and S13 to be compared with the average amplitude value (T _{ave — HPF} ) of the high frequency component vary depending on the type of tool, it is desirable to set as a parameter for each tool.

The CPU 11 converts the determination result stored in the RAM 13 into graph information and outputs it to the display device 14 (S5). The display device 14 displays a graph on the screen based on the graph information received from the CPU 11. 22 and 23 show each graph displayed on the screen of the display device 14. FIG. 22 is a graph showing changes in the dominant component of vibration at a rotational speed of 6400 min ⁻¹ . FIG. 23 is a graph showing changes in the dominant component of vibration at a rotational speed of 7800 min ⁻¹ . As shown in FIGS. 22 and 23, it is possible to clearly display which vibration component is the most dominant. These results are the same as the results of the above embodiment. Therefore, also in the third modified example, it is possible to clearly indicate which component of the machining chatter vibration is dominant with the passage of time in one graph as compared with the above embodiment.

  The CPU 11 determines whether or not the cutting of the machine tool 1 has been completed (S6). When the CPU 11 determines that cutting of the machine tool 1 is continuing (S6: NO), the CPU 11 returns to S1 and repeats the process. When the CPU 11 determines that the cutting of the machine tool 1 has been completed (S6: YES), the processing chatter vibration detection process ends.

  In addition to the first to third modifications, the embodiment can be variously modified. In the above embodiment, machining chatter vibration generated during cutting of the machine tool 1 is estimated by applying a disturbance observer based on torque information of the spindle motor 6 and position information from the encoder 6A. Measure indirectly. For example, the vibration acceleration of the main shaft 7 may be detected by using a vibration sensor (vibration pickup) or the like, and machining chatter vibration generated during cutting may be measured. In this case, the data obtained by the vibration sensor may be subjected to a filtering process using a digital filter.

  The chatter frequency is as high as several hundred Hz or higher, which is higher than the response range of servo feedback control. Since the torque information does not actually change at the chatter frequency, the same result can be obtained as the chatter mode determination even if the disturbance is estimated using only the position information without using the torque information.

  In the above embodiment, the vibration detection device 10 has been described as an example of the processing chatter vibration detection device of the present invention. However, a numerical control device that numerically controls the machine tool 1 may be used. In this case, for example, the cutting condition or the like may be changed by feeding back the analysis result obtained by the processing chatter vibration detection process.

  In the above embodiment, the description has been made using the position information and torque information of the main shaft motor. However, information on the X, Y, and Z axis motors may be used, or a plurality of main shafts, X, Y, and Z axes may be used. You may judge comprehensively based on information.

DESCRIPTION OF SYMBOLS 1 Machine tool 5 Spindle head 6 Spindle motor 6A Encoder 7 Spindle 8 Tool 9 Workpiece 10 Vibration detection apparatus 11 CPU
14 Display Device 51 Low Pass Filter 52 High Pass Filter 53 Band Pass Filter 54 Notch Filter

Claims (7)

In a processing chatter vibration detecting apparatus comprising a measuring means for measuring a processing chatter vibration or processing load of a processing machine for processing a workpiece, and an analysis means for analyzing the processing chatter vibration or processing load measured by the measuring means.
The analysis unit extracts a forced chatter digital filter unit that extracts forced chatter from the machining chatter vibration or processing load measured by the measuring unit, a self-excited chatter digital filter unit that extracts self-excited chatter, and a high-frequency chatter. Provide at least one of the high-frequency digital filter section,
And output means for outputting at least one of forced chatter, self-excited chatter, and high-frequency chatter extracted by the forced chatter digital filter unit, self-excited chatter digital filter unit, and high-frequency chatter digital filter unit. Processing chatter vibration detector.   2. The processing chatter vibration according to claim 1, wherein the measuring unit measures position information of a drive shaft provided in the processing machine, and measures the processing chatter vibration or a processing load based on the position information. Detection device.   The processing chatter vibration detection device according to claim 2, wherein the measuring means is configured by a disturbance observer that estimates a disturbance based on position information and torque of a drive shaft provided in the processing machine. The self-excited chatter digital filter unit and the forced chatter digital filter unit include a bandpass filter and a notch filter,
The processing chatter vibration detection device according to claim 1, wherein the high-frequency chatter digital filter unit includes a high-pass filter. The cut-off frequency of the low-pass filter is a frequency lower than the frequency at which the main shaft self-excited chatter and forced chatter occur,
The passband frequency of the bandpass filter is a frequency band where the self-excited chatter and forced chatter of the main shaft occur,
The notch frequency of the notch filter is a filter having a plurality of notch frequencies within the range of the frequency of the pass band of the band pass filter, which is an integral multiple of the product of the number of cutting edges of the tool and the spindle speed at the time of machining. The processing chatter vibration detection device according to claim 4, wherein The analysis means includes
An average value calculating means for calculating an average value of each amplitude of forced chatter, self-excited chatter, and high-frequency chatter extracted in the forced chatter digital filter unit, the self-excited chatter digital filter unit, and the high-frequency digital filter unit;
Based on a comparison of each average value calculated by the average value calculation means, comprising a determination means for determining, in a time series, which vibration is dominantly occurring among forced chatter, self-excited chatter, and high-frequency chatter,
The processing chatter vibration detection apparatus according to claim 1, wherein the output unit outputs a determination result of the determination unit.   A machine tool comprising the machining chatter vibration detection device according to any one of claims 1 to 6.