JP2014213412A - Device and method of detecting abnormality of cutting tool - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect abnormality of a cutting tool without carrying out update work of updating a threshold or the like in conjunction with setting operation of previously setting the threshold or the like prior to abnormality detection of the cutting tool, and changes in combinations of material of a workpiece, a type of the cutting tool, a processed shape or the like.SOLUTION: A device includes: a sound collection section which collects a sound wave generated during cutting processing; a wavelet transformation processing section which executes wavelet transformation to a waveform of the sound wave collected by the sound collection section, and divides it into sound waves of a plurality of frequency ranges; a first arithmetic processing section which calculates an effective value on each sound wave of the plurality of frequency ranges divided by the wavelet transformation processing section; a determination data storage section which calculates and stores a threshold for determination on the basis of the effective value calculated by the first arithmetic processing section in a teaching mode; and a determination processing section which determines presence of abnormality of the cutting tool by comparing the effective value calculated by the first arithmetic processing section in a processing execution mode and the threshold for determination stored in the determination data storage section.

Description

  The present invention relates to a cutting tool abnormality detection device and an abnormality detection method for detecting an abnormality that occurs in a cutting tool during cutting.

  Conventionally, a sound wave generated during processing by a processing machine is input as a sound wave signal, a sound wave signal in a preset frequency band is extracted from the sound wave signal by a band pass filter, and a sound pressure level of the extracted sound wave signal is measured and measured. There has been proposed a tool abnormality detection device that compares a measured sound pressure level with a preset sound pressure level threshold and outputs a tool abnormality detection signal when the measured sound pressure level is equal to or higher than the sound pressure level threshold (for example, , See Patent Document 1).

JP 2007-2222997 A

However, the prior art has the following problems.
In the conventional tool abnormality detection apparatus, as described above, a sound wave signal in a preset frequency band is extracted from the sound wave signal by a bandpass filter, and the measured sound pressure level is compared with a preset sound pressure level threshold value. Yes.

  That is, in order to detect an abnormality of the cutting tool, it is necessary to set in advance a frequency band for extracting a sound wave signal with a bandpass filter and a sound pressure level threshold for comparison with the measured sound pressure level. There is a problem that it is necessary to set the frequency band and the sound pressure level threshold value in advance.

  In addition, since the characteristics of sound waves generated during machining by the machine change due to changes in workpiece material, cutting tool type, machining shape, etc., changes in the combination of workpiece material, cutting tool type, machining shape, etc. Along with this, there is a problem that it is necessary to update the frequency band and the sound pressure level threshold.

  The present invention has been made to solve the above-described problems. Prior to detection of abnormalities in a cutting tool, setting work for setting a threshold value in advance, work material, cutting tool type, and processing shape It is an object of the present invention to obtain a cutting tool abnormality detection device and an abnormality detection method capable of detecting an abnormality of a cutting tool without performing an update operation for updating a threshold value or the like in accordance with a change in combination.

  A cutting tool abnormality detection device according to the present invention is a cutting tool abnormality detection device that detects an abnormality that occurs in a cutting tool in a cutting process, and a teaching mode that sets a threshold for determination used for abnormality detection of the cutting tool; An abnormality detection device for a cutting tool capable of switching between a machining execution mode for performing a cutting process, a sound collecting unit for collecting a sound wave generated during the cutting process, and a waveform of the sound wave collected by the sound collecting unit A wavelet transform processing unit that performs wavelet transform on the sound wave and divides the sound wave into a plurality of frequency bands, and a first calculation process that calculates an effective value for each sound wave in the plurality of frequency bands divided by the wavelet transform processing unit A determination data storage unit that calculates and stores a determination threshold based on the effective value calculated by the first arithmetic processing unit in the teaching mode, and processing execution A determination processing unit that compares the effective value calculated by the first arithmetic processing unit with the determination threshold value stored in the determination data storage unit to determine whether there is an abnormality in the cutting tool. It is a thing.

  Further, the abnormality detection method for a cutting tool according to the present invention is an abnormality detection method executed by an abnormality detection device for a cutting tool that detects an abnormality occurring in a cutting tool in the cutting process, and a sound wave generated during the cutting process is detected. The sound collection step for collecting the sound, the wavelet transform on the sound wave waveform collected at the sound collection step, and the wavelet transform processing step for dividing the sound wave into a plurality of frequency bands, and the wavelet transform processing step. In a calculation processing step for calculating an effective value for each sound wave in a plurality of frequency bands and a teaching mode for setting a determination threshold value used for detecting an abnormality of the cutting tool, based on the effective value calculated in the calculation processing step. , In the judgment data storage step for calculating and saving the judgment threshold, and in the machining execution mode for executing cutting By comparing the determination threshold value stored in the determination data storage step and the effective value calculated in physical step, those having a determination process determining the presence or absence of abnormality of the cutting tool.

According to the abnormality detection device and abnormality detection method for a cutting tool according to the present invention, a sound collection unit that collects sound waves generated during cutting processing, and a wavelet transform on the waveform of the sound waves collected by the sound collection unit , A wavelet transform processing unit that divides the sound wave into a plurality of frequency bands, a first arithmetic processing unit that calculates an effective value for each sound wave in the plurality of frequency bands divided by the wavelet transform processing unit, and a cutting tool In a teaching mode for setting a determination threshold value used for abnormality detection, a determination data storage unit that calculates and stores a determination threshold value based on the effective value calculated by the first arithmetic processing unit, and a cutting process In the machining execution mode to be executed, the determination for comparing the effective value calculated by the first arithmetic processing unit and the determination threshold value stored in the determination data storage unit to determine whether there is an abnormality in the cutting tool And it includes a processing section, a.
Therefore, prior to detection of abnormalities in the cutting tool, setting work for setting a threshold value or the like in advance, or update work for updating the threshold value or the like in accordance with a change in the combination of the workpiece material, the type of cutting tool and the machining shape, etc. Therefore, the abnormality of the cutting tool can be detected.

It is a block diagram which shows the abnormality detection apparatus of the cutting tool which concerns on Embodiment 1 of this invention with a processing machine. It is a block diagram which shows the abnormality detection apparatus of the cutting tool which concerns on Embodiment 2 of this invention with a processing machine. It is a block diagram which shows the abnormality detection apparatus of the cutting tool which concerns on Embodiment 3 of this invention with a processing machine.

  Hereinafter, preferred embodiments of a cutting tool abnormality detection apparatus and abnormality detection method according to the present invention will be described with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals. To do.

Embodiment 1 FIG.
1 is a block diagram showing an abnormality detecting device for a cutting tool according to Embodiment 1 of the present invention together with a processing machine. In FIG. 1, a cutting tool 2 attached to a processing machine main body 1 is driven and rotated by a motor to process a workpiece 3 to be processed.

  Further, in FIG. 1, this cutting tool abnormality detection device includes a sensor 4, an amplifier 5, an A / D conversion unit 6, a wavelet conversion processing unit 7, a first calculation processing unit 8, a determination data storage unit 9, and determination processing. Part 10 and alarm output part 11.

  The sensor (sound collecting unit) 4 is a microphone or the like that collects sound waves generated during machining of the workpiece 3 to be machined. The amplifier 5 amplifies the waveform of the sound wave picked up by the sensor 4. The A / D conversion unit 6 converts the waveform of the sound wave that is an analog signal output from the amplifier 5 into a digital signal. The wavelet transform processing unit 7 performs wavelet transform on the waveform of the digital signal output from the A / D conversion unit 6 and divides the sound wave into a plurality of frequency bands.

  The first arithmetic processing unit 8 calculates an effective value (feature value) for each sound wave of a plurality of frequency bands divided by the wavelet transform processing unit 7. The determination data storage unit 9 calculates and stores a determination threshold based on the effective value calculated for each sound wave in a plurality of frequency bands by the first arithmetic processing unit 8 in the teaching mode (described later).

  In the processing execution mode (described later), the determination processing unit 10 includes an effective value calculated for each sound wave in a plurality of frequency bands by the first calculation processing unit 8 and a determination threshold stored in the determination data storage unit 9. And the effective value is determined to be abnormal when the effective value exceeds the threshold value for determination. The alarm output unit 11 displays an abnormality detection of the cutting tool when the determination processing unit 10 determines that there is an abnormality.

  The operation of the cutting tool abnormality detection device according to Embodiment 1 of the present invention will be described below. First, the teaching mode will be described. The teaching mode is executed at the first stage of machining a new lot by changing the material of the workpiece, the type of cutting tool, the machining shape, or the like.

  First, the cutting tool 2 is attached to the processing machine main body 1, and the workpiece 3 to be processed is set. Subsequently, the mode of the cutting tool abnormality detection device is set to the teaching mode, and machining is started. When machining is started, the cutting tool 2 is driven and rotated by a motor, and machining is started on the workpiece 3 to be machined.

  The sound wave being processed by the sensor 4 is picked up by the trigger signal for starting the processing. The waveform of the sound wave picked up by the sensor 4 is converted into an electric signal and amplified by the amplifier 5. The A / D converter 6 converts the electric signal of the sound wave amplified by the amplifier 5 into a digital signal.

  The wavelet transform processing unit 7 executes wavelet transform processing on the waveform of the sound wave converted into the digital signal, and the sound wave is divided into sound waves of a plurality of frequency bands. By dividing into sound waves of a plurality of frequency bands, the cutting sound of the cutting tool 2 can be separated from the sound waves including various frequencies collected by the sensor 4.

  From the sound waves of the plurality of frequency bands divided by the wavelet transform processing unit 7, the first calculation processing unit 8 calculates an effective value for each of the sound waves of the plurality of frequency bands, and is calculated for each sound wave of the plurality of frequency bands. The determination threshold value calculated based on the effective value is stored in the determination data storage unit 9.

  Next, the machining execution mode will be described. In the processing execution mode, first, the same cutting tool 2 is attached to the same processing machine main body 1 used in the teaching mode, and the workpiece 3 having the same material and processing shape is set. Subsequently, the mode of the cutting tool abnormality detection device is set to the machining execution mode, and machining is started. When machining is started, the cutting tool 2 is driven and rotated by a motor, and machining is started on the workpiece 3 to be machined.

  The sound wave being processed by the sensor 4 is picked up by the trigger signal for starting the processing. The waveform of the sound wave picked up by the sensor 4 is converted into an electric signal and amplified by the amplifier 5. The A / D converter 6 converts the electric signal of the sound wave amplified by the amplifier 5 into a digital signal. The wavelet transform processing unit 7 executes wavelet transform processing on the waveform of the sound wave converted into the digital signal, and the sound wave is divided into sound waves of a plurality of frequency bands.

  From the sound waves in a plurality of frequency bands divided by the wavelet transform processing unit 7, the first calculation processing unit 8 calculates an effective value for each sound wave in the plurality of frequency bands. In the determination processing unit 10, the effective value calculated for each sound wave in the plurality of frequency bands by the first arithmetic processing unit 8 is compared with the determination threshold stored in the determination data storage unit 9 in the teaching mode.

  The effective value calculated by the first arithmetic processing unit 8 is compared with the threshold value for determination stored in the data storage unit 9 for determination for each frequency band, and the effective value calculated by the first arithmetic processing unit 8 is compared. Is larger or smaller than the threshold value for determination, the determination processing unit 10 outputs an alarm signal to the alarm output unit 11, and the alarm output unit 11 notifies the operator of the abnormality of the cutting tool 2.

  As described above, the determination threshold value is calculated based on the sound wave collected in the teaching mode, so that various labors for setting the determination threshold value can be saved. In addition, the wavelet transform divides the waveform of the sound wave into sound waves of multiple frequency bands, and the effective value for each frequency band is used for determination, so the sound pressure difference that cannot be detected with sound waves that are not subjected to signal processing. Can be detected with high accuracy.

  In a processing pattern in which a processing shape such as a processing diameter changes during processing, the size of the sound wave and the frequency band change depending on the processing location. In such a case, with respect to the sound waves collected from the start of processing to the end of processing, the wavelet transform processing unit 7 sets the effective values in all time zones for the sound waves divided into a plurality of frequency bands. Rather than calculating, the effective value for each short time is calculated by dividing the time from the start of processing to the end of processing in a short time (divided into a plurality of times).

  In the teaching mode, a threshold for determination is calculated every short time for each sound wave in a plurality of frequency bands, and even in the machining execution mode, a plurality of frequency bands are recorded every short time at the same interval as the time divided in the teaching mode. By calculating the effective value for each sound wave and comparing the effective value with the threshold for determination in the same frequency band in the same time zone, the processing pattern changes during processing, and the characteristics of the sound wave change. Even in such a case, the abnormality of the cutting tool 2 can be detected with high accuracy.

As described above, according to the first embodiment, the sound collection unit that collects the sound wave generated during the cutting process, and the wavelet transform is performed on the waveform of the sound wave collected by the sound collection unit. A wavelet transform processing unit that divides the sound wave into a frequency band of the first frequency, a first arithmetic processing unit that calculates an effective value for each sound wave of the plurality of frequency bands divided by the wavelet transform processing unit, and an abnormality detection of the cutting tool In a teaching mode for setting a determination threshold value, a determination data storage unit that calculates and stores a determination threshold value based on the effective value calculated by the first arithmetic processing unit, and a machining execution mode in which cutting is performed And a determination processing unit that compares the effective value calculated by the first arithmetic processing unit with the determination threshold value stored in the determination data storage unit to determine whether there is an abnormality in the cutting tool. .
Therefore, prior to detection of abnormalities in the cutting tool, setting work for setting a threshold value or the like in advance, or update work for updating the threshold value or the like in accordance with a change in the combination of the workpiece material, the type of cutting tool and the machining shape, etc. Therefore, the abnormality of the cutting tool can be detected.

Embodiment 2. FIG.
In the first embodiment, the waveform of the collected sound wave is divided into sound waves of a plurality of frequency bands by the wavelet transform processing unit 7, and the characteristic amount of the sound wave is calculated by the first calculation processing unit 8. In the second embodiment, sound waves divided into a plurality of frequency bands are reproduced as sound, and the frequency band including the air-conditioning sound that is not related to the cutting process is confirmed by the listener to delete the frequency band required for the cutting process. By selecting only the band, the determination process can be performed.

  FIG. 2 is a configuration diagram showing a cutting tool abnormality detection device according to Embodiment 2 of the present invention together with a processing machine. In FIG. 2, this cutting tool abnormality detection device includes a frequency selection unit 12, a D / A conversion unit 13, and an acoustic regenerator 14 in addition to the cutting tool abnormality detection device shown in FIG. 1.

  The frequency selection unit 12 selects a (desired) frequency band to be reproduced as sound from the sound waves divided into a plurality of frequency bands by the wavelet transform processing unit 7. The D / A converter 13 converts the waveform of the sound wave in the frequency band selected by the frequency selector 12 from a digital signal to an analog signal. The sound player 14 is, for example, a speaker, and outputs the sound wave waveform of the analog signal converted by the D / A converter 13 as sound. Other configurations and functions are the same as those in FIG.

  The operation of the cutting tool abnormality detection device according to Embodiment 2 of the present invention will be described below. Note that the description of the same operation as that of the first embodiment will be omitted.

  In the teaching mode, the sound wave being processed by the sensor 4 is collected. The collected sound wave is divided by the wavelet transform processing unit 7 into sound waves of a plurality of frequency bands. The divided sound waves of a plurality of frequency bands are displayed as a time axis waveform for each frequency band by the frequency selection unit 12, and a change in amplitude can be visually confirmed as a waveform.

  By selecting an arbitrary frequency band with the reproduction frequency selection function of the frequency selection unit 12, only the sound wave waveform of the selected frequency band is converted from a digital signal to an analog signal by the D / A conversion unit 13, The sound is output from the sound player 14 as sound, and the reproduced sound can be heard.

  In addition, the frequency selection unit 12 selects a frequency band that is determined to be unnecessary for the determination process by reproducing the sound by the determination threshold selection function. As a result, the determination threshold value for the selected frequency band is deleted from the determination data storage unit 9.

  As described above, in the teaching mode, the sound wave divided into a plurality of frequency bands by the wavelet transform processing unit 7 is reproduced as sound and confirmed by the listener, and the frequency band unnecessary for the determination process is selected by the frequency selection unit 12. By collecting the effective value and the determination threshold frequency band stored in the determination data storage unit 9 and eliminating the frequency band of the sound wave not related to the abnormality detection of the cutting tool 2, the abnormality detection is performed. The accuracy can be improved and the processing speed can be improved.

Embodiment 3 FIG.
In the first embodiment, the abnormality of the cutting tool 2 is detected based on the feature amount of the sound wave generated during processing by the processing machine. In the third embodiment, the current flowing through the spindle motor that drives and rotates the cutting tool 2 is measured, and when the magnitude of the current becomes larger than the current threshold, it can be determined that there is an abnormality.

  FIG. 3 is a block diagram showing a cutting tool abnormality detection device according to Embodiment 3 of the present invention together with a processing machine. In FIG. 3, the cutting tool abnormality detecting device includes a current measuring device 21 and a second arithmetic processing unit 22 in addition to the cutting tool abnormality detecting device shown in FIG. 2. In addition, you may add the current measuring device 21 and the 2nd arithmetic processing part 22 to the abnormality detection apparatus of the cutting tool shown in FIG.

  The current measuring device 21 measures the current flowing through the spindle motor that drives and rotates the spindle connected to the cutting tool 2. The second arithmetic processing unit 22 calculates an effective value from the waveform of the current measured by the current measuring device 21. Other configurations and functions are the same as those in FIG.

  The operation of the cutting tool abnormality detection device according to Embodiment 3 of the present invention will be described below. The description of the same operation as in the first and second embodiments is omitted.

  First, the teaching mode will be described. The teaching mode is executed at the first stage of machining a new lot by changing the material of the workpiece, the type of cutting tool, the machining shape, or the like.

  First, the cutting tool 2 is attached to the processing machine main body 1, and the workpiece 3 to be processed is set. Subsequently, the mode of the cutting tool abnormality detection device is set to the teaching mode, and machining is started. When machining is started, the cutting tool 2 is driven and rotated by a motor, and machining is started on the workpiece 3 to be machined.

  The current flowing through the spindle motor is measured by the current measuring device 21 in accordance with the machining start trigger signal. From the current waveform measured by the current measuring device 21, an effective value is calculated by the second arithmetic processing unit 22. The current threshold value calculated based on the effective value of the current waveform calculated by the second arithmetic processing unit 22 is stored in the determination data storage unit 9.

  Next, the machining execution mode will be described. In the processing execution mode, first, the same cutting tool 2 is attached to the same processing machine main body 1 used in the teaching mode, and the workpiece 3 having the same material and processing shape is set. Subsequently, the mode of the cutting tool abnormality detection device is set to the machining execution mode, and machining is started. When machining is started, the cutting tool 2 is driven and rotated by a motor, and machining is started on the workpiece 3 to be machined.

  The current flowing through the spindle motor from the machining start to the machining end is measured by the current measuring device 21 by the machining start trigger signal. From the current waveform measured by the current measuring device 21, an effective value is calculated by the second arithmetic processing unit 22. In the determination processing unit 10, the effective value of the current waveform calculated by the second arithmetic processing unit 22 is compared with the current threshold value stored in the determination data storage unit 9 in the teaching mode.

  When the effective value calculated by the second arithmetic processing unit 22 is larger or smaller than the width of the current threshold stored in the determination data storage unit 9, an alarm signal is sent from the determination processing unit 10 to the alarm output unit 11. And the alarm output unit 11 notifies the operator of the abnormality of the cutting tool 2.

  Further, in a machining pattern in which a machining shape such as a machining diameter changes during machining, the load current may change due to a change in the machining shape. In such a case, like the sound wave, the second arithmetic processing unit 22 reduces the time from the start of processing to the end of processing for a current waveform measured from the start of processing to the end of processing. The effective value of the current waveform for each short time is calculated.

  In the teaching mode, the current threshold value is calculated based on the calculated effective value of the current waveform for each short time. In the machining execution mode, the effective current waveform is calculated from the short time current waveform at the same interval as the time divided in the teaching mode. Even when the load pattern changes due to a change in the machining pattern during machining by calculating the value and comparing the current value with the effective value in the same time zone, the cutting tool 2 abnormalities can be detected with high accuracy.

  As described above, the current flowing through the spindle motor that drives and rotates the cutting tool 2 is measured, and when the magnitude of the current becomes larger than the current threshold value, it is determined that there is an abnormality. Since the abnormality determination of the cutting tool 2 can be performed with the increasing motor current, the abnormality of the cutting tool 2 can be detected with higher accuracy than the determination based on the sound pressure alone.

  DESCRIPTION OF SYMBOLS 1 Processing machine main body, 2 Cutting tool, 3 Work object, 4 Sensor, 5 Amplifier, 6 A / D conversion part, 7 Wavelet conversion process part, 8 1st arithmetic process part, 9 Data storage part for judgment, 10 Judgment process Unit, 11 alarm output unit, 12 frequency selection unit, 13 D / A conversion unit, 14 sound regenerator, 21 current measuring device, 22 second arithmetic processing unit.

Claims (7)

An abnormality detection device for a cutting tool that detects an abnormality occurring in a cutting tool in a cutting process, and includes a teaching mode for setting a determination threshold value used for detecting an abnormality of the cutting tool, and a processing execution mode for executing the cutting process. A switchable cutting tool abnormality detection device,
A sound collection unit that collects sound waves generated during the cutting process;
Wavelet transformation is performed on the waveform of the sound wave collected by the sound collection unit, and a wavelet transformation processing unit that divides the sound wave into a plurality of frequency bands,
A first arithmetic processing unit that calculates an effective value for each sound wave of a plurality of frequency bands divided by the wavelet transform processing unit;
In the teaching mode, a determination data storage unit that calculates and stores the determination threshold based on the effective value calculated by the first arithmetic processing unit;
In the machining execution mode, a determination process for comparing the effective value calculated by the first arithmetic processing unit with a determination threshold value stored in the determination data storage unit to determine whether the cutting tool is abnormal. And
An abnormality detection device for a cutting tool comprising: The first calculation processing unit calculates an effective value for each time by dividing the sound collected by the sound collecting unit into a plurality of times for the sound wave divided into a plurality of frequency bands by the wavelet transform processing unit. The abnormality detection device for a cutting tool according to claim 1. A frequency selection unit that selects a desired frequency band from sound waves divided into a plurality of frequency bands by the wavelet transform processing unit;
An acoustic regenerator that outputs the sound wave waveform of the frequency band selected by the frequency selection unit as sound; and
The abnormality detection device for a cutting tool according to claim 1 or 2, further comprising: The frequency selection unit deletes, from the determination data storage unit, a determination threshold value related to a sound wave in a frequency band that is selected based on the sound output from the sound regenerator and is unnecessary for abnormality detection of the cutting tool. The cutting tool abnormality detection device according to claim 3. A current measuring device for measuring a current flowing in a spindle motor for driving and rotating a spindle connected to the cutting tool;
A second arithmetic processing unit for calculating an effective value from a waveform of a current measured by the current measuring device;
The abnormality detection apparatus for a cutting tool according to any one of claims 1 to 4, further comprising: The cutting according to claim 5, wherein the second arithmetic processing unit calculates an effective value for each time by dividing a time measured by the current measuring device into a plurality of times for the current measured by the current measuring device. Tool abnormality detection device. An abnormality detection method executed by an abnormality detection device for a cutting tool that detects an abnormality that occurs in a cutting tool during cutting,
A sound collection step for collecting sound waves generated during the cutting process;
Wavelet transformation is performed on the waveform of the sound wave collected in the sound collection step, and a wavelet transformation processing step for dividing the sound wave into a plurality of frequency bands, and
An arithmetic processing step for calculating an effective value for each sound wave in a plurality of frequency bands divided in the wavelet transform processing step;
In a teaching mode for setting a threshold value for determination used for abnormality detection of the cutting tool, based on the effective value calculated in the calculation processing step, a determination data storage step for calculating and storing the determination threshold value;
In the machining execution mode in which the cutting is performed, the effective value calculated in the calculation processing step is compared with the determination threshold stored in the determination data storage step to determine whether the cutting tool is abnormal. A determination processing step to perform,
An abnormality detection method for a cutting tool having

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