Abnormality detection method and device during cutting machining

Abstract

To accurately detect chatter sound generated from a workpiece and reliably detect the occurrence of chatter vibration even when the background noise level is high, such as when cutting sound generated from another machine tool and environmental noise are both high.SOLUTION: There is provided an abnormality detection method during cutting machining. In order to separate an abnormal sound caused by a cutting abnormality from background noise, sound in a band of 10 kHz or higher is detected and an acoustic signal is subjected to Fourier transformation, and Fourier-transformation data during abnormal cutting machining is obtained by comparison with Fourier-transformation data during normal cutting machining, thereby performing abnormality detection. In this process, a cutting instrument that moves between a cutting machining position and an initial position away from the cutting machining position is used as a cutting instrument for cutting machining. A movement state of the cutting instrument is detected by a sensor, and abnormality detection is performed using Fourier-transformation data at the time when the cutting instrument is present at the cutting machining position.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a method and device for detecting abnormalities during cutting work. [Background technology]

[0002] Chatter vibration is an abnormality that can occur during cutting processes such as lathe turning of workpieces. An apparatus and method for detecting chatter vibration are described, for example, in Patent Document 1. Patent Document 1 focuses on chatter frequencies caused by vibrations of several kHz in the workpiece, and detects chatter vibration by subjecting the vibrations to Fourier analysis.

[0003] When focusing on vibrations of several kHz in a workpiece, chatter vibration can be detected not only by detecting the vibration itself, but also by detecting the vibration noise in the frequency band of several kHz that occurs in conjunction with the vibration. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-260117 Summary of the Invention [Problem to be solved by the invention]

[0005] The technique described in Patent Document 1 can be effectively implemented when the background noise level is not too high. However, in actual cutting work sites using machine tools such as lathes, there is a high possibility that high levels of background noise will be generated in addition to the sounds generated during cutting work. Examples of such background noise include cutting sounds generated by other machine tools when multiple machine tools are installed and operating, and environmental noise in the area where the machine tool whose chatter noise is to be detected is installed. Examples of environmental noise include human voices, wind noise, rain noise, and announcements made within the factory.

[0006] When the background noise level is high like this, it is difficult to distinguish between chatter noise and background noise simply by focusing on vibrations of several kHz in the workpiece and detecting vibration noise in that frequency band. In this case, detecting vibration noise in the band of 10 kHz or higher generated in the workpiece is an improvement over detecting vibration noise of several kHz. However, even in this case, the detection accuracy is still not sufficient if both cutting noise generated by other machine tools and environmental noise are high.

[0007] Therefore, an object of the present invention is to solve these problems and to accurately detect chatter noise generated from a workpiece, even when the background noise level is high, such as when cutting noise generated by other machine tools and environmental noise are both high, thereby making it possible to reliably detect the occurrence of chatter vibration. [Means for solving the problem]

[0008] In order to achieve this object, the method for detecting an abnormality during cutting processing of the present invention comprises the steps of: In order to separate abnormal sounds caused by cutting abnormalities from background noise, the sound in the band above 10 kHz is detected and the acoustic signal is Fourier transformed. Abnormalities are detected by comparing the Fourier transform data during normal cutting with the Fourier transform data during abnormal cutting. At this time, a cutting tool that moves between a cutting position and an initial position away from the cutting position is used as the cutting tool, The movement state of the blade is detected by a sensor, and the abnormality is detected using Fourier transform data when the blade is present at the cutting position.

[0009] In this way, the movement state of the blade is detected by the sensor, it is recognized that the blade is in the cutting position, and the Fourier transform data at that time is utilized to reliably detect the occurrence of abnormalities during cutting.

[0010] According to the method for detecting an abnormality during cutting work of the present invention, it is preferable to use an acceleration sensor as the sensor for detecting the movement state of the cutting tool.

[0011] In this way, when the blade starts or stops moving, acceleration occurs in the blade, making it possible to accurately detect the timing when the blade reaches the position of the workpiece, stops moving, and starts cutting, as well as the timing when the blade finishes cutting and moves away from the position of the workpiece. This makes it possible to detect the period during which the workpiece is being cut by the blade, and by performing signal analysis on the Fourier transform data during this period, it is possible to reliably detect the occurrence of any abnormalities during cutting.

[0012] According to the method for detecting an abnormality during cutting work of the present invention, it is preferable to detect sounds in a frequency band of 10 kHz or more and 20 kHz or less.

[0013] In this way, in an environment where a machine tool for cutting processing is installed and operated, the level of background noise in the band of 10 kHz or more and 20 kHz or less is generally low, so Fourier transform data during abnormal cutting processing can be easily obtained.

[0014] According to the method for detecting an abnormality during cutting work of the present invention, Using a device for detecting sound and processing the data, As a device for detecting the sound and processing the data, it is preferable to use a device having at least one of the following functions: a sound collection function, a function for Fourier transforming the collected sound data, a function for displaying the Fourier transformed data, a function for acquiring an image of the workpiece, a function for displaying the acquired image, a function for detecting the movement state of the blade from the acceleration of the blade, and a function for communicating data with an external device.

[0015] In this way, it is possible to reliably detect the occurrence of chatter vibrations, which are abnormal cutting operations, using only one device.

[0016] For this purpose, it is preferable to use a smartphone as a device for detecting sound and processing the data.

[0017] The abnormality detection device for detecting an abnormality during cutting processing of the present invention comprises: A device for detecting abnormalities when cutting a workpiece using a cutting tool, the cutting blade is a blade that moves between a cutting position and an initial position away from the cutting position, The device for detecting an abnormality comprises: a first device that detects sounds in a frequency band of 10 kHz or higher and then performs a Fourier transform on the acoustic signal to separate abnormal sounds caused by cutting abnormalities from background noise; a second device that detects an abnormality by obtaining Fourier transform data during abnormal cutting processing in comparison with Fourier transform data during normal cutting processing; a sensor that detects the movement state of the blade; The present invention is characterized by having a third device that causes the second device to perform the abnormality detection using Fourier transform data from the first device and the second device when the blade is present at the cutting processing position, based on the detection results of a sensor that detects the movement state of the blade.

[0018] According to the abnormality detection device for cutting processing of the present invention, the movement state of the cutting tool is detected by a sensor, it is recognized that the cutting tool is present at the cutting processing position, and the Fourier transform data at that time is utilized, thereby making it possible to reliably detect the occurrence of abnormalities during cutting processing.

[0019] In the cutting abnormality detection device of the present invention, the sensor that detects the movement state of the cutting tool is preferably an acceleration sensor.

[0020] With this arrangement, it is possible to accurately detect that the blade is in the cutting position, and to reliably detect any abnormality when the blade is cutting the workpiece.

[0021] In the cutting abnormality detection device of the present invention, the first device, the second device, the sensor that detects the movement state of the cutting tool, and the third device are preferably incorporated into a single device.

[0022] In this way, abnormality detection can be reliably performed by using only a single device when the cutting tool is cutting a workpiece.

[0023] In the cutting abnormality detection device of the present invention, the single device is preferably a smartphone.

[0024] With this, abnormalities can be reliably detected when the cutting tool is cutting a workpiece using a smartphone, which is widely available in the world, without using any special device. [Effects of the Invention]

[0025] According to the present invention, the movement state of the blade is detected by a sensor, it is recognized that the blade is present at the cutting position, and the Fourier transform data at that time is utilized, thereby making it possible to reliably detect the occurrence of abnormalities during cutting. [Brief explanation of the drawings]

[0026] [Figure 1] FIG. 10 is a diagram showing an example of the results of a Fourier transform of the sound produced when chatter vibration is intentionally generated by performing cutting on a lathe using a worn tip, in a case where neither mechanical noise caused by the operation of other machine tools nor environmental noise at the location where the machine tool is installed is being generated. [Figure 2] FIG. 10 is a diagram showing an example of the results of a Fourier transform of the sound produced when chatter vibration is intentionally generated by increasing the protruding length of the cutting tool from the tool post in a case where neither mechanical noise caused by the operation of other machine tools nor environmental noise at the location where the machine tool is installed is being generated. [Figure 3]FIG. 10 is a diagram showing an example of the results of Fourier transform of the sound produced when chatter vibration is intentionally generated by performing cutting on a lathe using a worn tip, in a case where environmental noise is generated at the installation location of the machine tool, but no mechanical noise is generated due to the operation of other machine tools. [Figure 4] FIG. 10 is a diagram showing an example of the results of a Fourier transform of the sound produced when chatter vibration is intentionally generated by increasing the protruding length of the cutting tool from the tool post in a case where environmental noise is generated at the location where the machine tool is installed, but no mechanical noise is generated due to the operation of other machine tools. [Figure 5] FIG. 10 is a diagram showing how a tool post equipped with a cutting tool automatically moves between a cutting position and an initial position during lathe machining. [Figure 6] FIG. 10 is a diagram illustrating an example of detection by an acceleration sensor. [Figure 7] FIG. 10 is a diagram showing an example of the measurement results of sound pressure changes under conditions in which there is no chatter vibration and no on-site work noise as environmental noise. [Figure 8] FIG. 10 is a diagram showing an example of measurement results of sound pressure changes in a situation where there is no chatter vibration and there is work noise from the site as environmental noise. [Figure 9] FIG. 10 is a diagram showing an example of measurement results of sound pressure changes in a situation where chatter vibration is present and there is no on-site work noise as environmental noise. [Figure 10] FIG. 10 is a diagram showing an example of measurement results of sound pressure changes in a situation where chatter vibrations are present and on-site work noise is present as environmental noise. DETAILED DESCRIPTION OF THE INVENTION

[0027] When cutting with a lathe as a machine tool, chatter vibrations can occur. Chatter vibrations are accompanied by "chatters," or vibrations, in the cutting tool, which can lead to irregular machining marks on the machined surface of the workpiece. This can significantly reduce the quality of the machined surface of the workpiece.

[0028] When an operator directly monitors an operating machine tool, if chatter vibration occurs, the operator can immediately recognize the occurrence of chatter vibration by the sound or the like. However, when the machine tool is an automatic machine and is not directly monitored by an operator, if chatter vibration occurs, the operator, who is located away from the machine tool, must be immediately notified of the situation so that the operator can take appropriate measures. To achieve this, when chatter vibration occurs, it is necessary to immediately detect it using some kind of device.

[0029] When the background noise level during cutting using a machine tool such as a lathe is low, it is relatively easy to detect abnormal sounds that occur due to chatter vibrations, which are abnormal cutting noises, using some kind of device. This is because it is easy to distinguish between abnormal sounds and background noise. However, when the background noise level is high, such a distinction can become difficult.

[0030] The inventor of the present invention has experimentally confirmed that the degree of difficulty in detecting abnormal sounds varies depending on the level of background noise, as follows.

[0031] Typical sources of background noise when cutting with a lathe or other machine tool include (a) the mechanical noise caused by other machine tools in operation, and (b) the environmental noise of the area where the machine tool is installed. Specific examples of environmental noise include human voices, wind noise, rain noise, and announcements within the factory.

[0032] The results of a verification into the degree of difficulty in detecting abnormal sounds at an installation site where (a) mechanical sounds caused by the operation of other machine tools and (b) environmental noise at the installation site of the machine tool may occur are as follows: Below, we will explain the results of a verification into the degree of difficulty in detecting abnormal sounds for four different cases [(Case 1) to (Case 4)].

[0033] (Case 1) When there is neither mechanical noise caused by other machine tools in operation nor environmental noise in the machine tool installation location.

[0034] Cutting was performed using a cutting tool with a cutting tip. Chatter vibration was intentionally generated by (a) using a worn tip during cutting, and (b) by increasing the protrusion length of the cutting tool from the tool post.

[0035] (a) Figure 1 shows the results of a Fourier transform of the sound generated when chatter vibrations were intentionally generated by cutting on a lathe using a worn tip. Here, the thin line shows the results of the Fourier transform in a normal cutting state where chatter vibrations were not generated, and the solid line shows the results of the Fourier transform in a chatter vibration state. The frequency band of the detected sound was set to approximately 0 to 8 kHz, as shown on the horizontal axis of Figure 1. As shown in the figure, when chatter vibrations were generated, a large peak occurred at around 5 kHz, making it easy to detect the occurrence of chatter vibrations.

[0036] Any detector can be used to detect the occurrence of chatter vibration. It is preferable that the detector has at least one of the following functions: collecting abnormal sounds generated by chatter vibration, performing a Fourier transform on the collected sound data, displaying the Fourier transformed data to an operator, acquiring an image of the workpiece where chatter vibration has occurred, displaying the acquired image, and communicating data with an external device. It is particularly preferable that the detector has all of these functions.

[0037] Various types of devices can be used as such a detection device. A smartphone is a particularly suitable example. Among the above-mentioned functions, the function of Fourier transforming collected sound data is typically not provided on typical smartphones. However, it is entirely possible to develop a smartphone OS application to implement this function. With a smartphone, when data communication with an external device is completed, a display indicating that communication has been completed can be displayed on the screen. In addition to smartphones, a detection device for detecting chatter vibrations can also be configured using a system that includes a microcomputer, an acceleration sensor, a microphone, and the like.

[0038] Figure 2 (b) shows the results of a Fourier transform of the sound when chatter vibration was intentionally generated by increasing the protruding length of the tool holder. Here, as in Figure 1, the thin line shows the results of the Fourier transform in a normal machining state where chatter vibration was not occurring, and the solid line shows the results of the Fourier transform in a chatter vibration state. The frequency band of the detected sound was set to approximately 0 to 8 kHz, as in Figure 1. As shown in the figure, large peaks occurred in various places when chatter vibration was occurring, making it easy to detect the occurrence of chatter vibration.

[0039] As described above, it was found that when there is neither mechanical noise caused by other operating machine tools nor environmental noise at the location where the machine tool is installed, the occurrence of chatter vibration can be detected well by detecting sounds in the frequency band of about 0 to 8 kHz and performing a Fourier transform.

[0040] (Case 2) When there is mechanical noise due to the operation of other machine tools, but there is no environmental noise in the area where the machine tools are installed.

[0041] When there is mechanical noise due to the operation of other machine tools, but no environmental noise in the area where the machine tools are installed, it is possible to estimate the number of machines in operation from the level of the sound signal from the operating noise.In other words, by detecting sounds in the 0 to 8 kHz band for each level and performing a Fourier transform, it is possible to estimate which lathe is experiencing chatter vibration.

[0042] (Case 3) When there is environmental noise at the location where the machine tool is installed, but there is no mechanical noise caused by other machine tools operating.

[0043] As mentioned above, specific examples of environmental noise include human voices, wind noise, rain noise, and factory announcements. The frequencies of these environmental noises are often below 10 kHz. Therefore, detecting sounds in the 0 to 8 kHz band and performing a Fourier transform, as described above, can result in a high rate of false positives.

[0044] Therefore, in this case, the occurrence of chatter vibration can be detected by detecting and signal processing sounds in a band of 10 kHz or more, preferably sounds in a band of 10 kHz or more and 20 kHz or less.

[0045] As in the case of Figure 1, Figure 3 (a) shows the results of a Fourier transform of the sound generated when chatter vibration was intentionally generated by performing cutting on a lathe using a worn tip. As in the case of Figure 1, the thin line shows the results of the Fourier transform in a normal cutting state where chatter vibration was not generated, and the solid line shows the results of the Fourier transform in a chatter vibration state. In this case, the frequency band of the detected sound was set to 10 to 20 kHz, as shown on the horizontal axis of Figure 3. As shown in the figure, when chatter vibration was generated, a large peak occurred at around 15 kHz, which made it easy to detect the occurrence of chatter vibration.

[0046] As in Figure 2, Figure 4 (b) shows the results of a Fourier transform of the sound produced when chatter vibration was intentionally generated by increasing the protrusion length of the tool bit from the tool post. Here, as in Figure 1, the thin line shows the Fourier transform results for normal machining conditions where chatter vibration was not occurring in the presence of environmental noise, while the solid line shows the Fourier transform results for conditions where chatter vibration was present. The frequency band of the detected sound was in the 10-20 kHz range, as in Figure 3. As shown in the figure, when chatter vibration was present, noticeable peaks were observed in places compared to normal machining conditions where chatter vibration was not occurring, making it easy to detect the occurrence of chatter vibration.

[0047] As described above, when there is no mechanical noise due to the operation of other machine tools, but there is environmental noise at the location where the machine tool is installed, it was found that the occurrence of chatter vibration can be detected well by detecting sounds in the 10 to 20 kHz band and performing a Fourier transform.

[0048] (Case 4) When there is both mechanical noise from other machine tools in operation and environmental noise from the machine tool installation location.

[0049] In this case, according to the present invention, As a cutting tool, a cutting tool that automatically moves between a cutting position and an initial position away from the cutting position is used, The movement of the blade is detected by a sensor, and when the blade is in the cutting position, sound in the band above 10 kHz is detected. The acoustic signal is then Fourier transformed and abnormalities are detected using the Fourier transformed data.

[0050] In a typical machine tool, a cutting tool moves between a cutting position and an initial position away from the cutting position, as described above. For example, in the lathe shown in FIG. 5, workpiece 1 is gripped by chuck 2 and rotates together with chuck 2. Tool bit 3, which serves as a cutting tool, has a structure in which cutting tip 4 is attached to the tip of shank 5, and is fixed to tool rest 6 by attaching shank 5 to tool rest 6. Tool rest 6 automatically moves between cutting position 7, shown by a solid line in FIG. 5, and initial position 8, shown by a virtual line in FIG. 5. Tool bit 3 also moves together with tool rest 6 between cutting position 7 and initial position 8. Initial position 8 is a retracted position where tool bit 3 is separated from workpiece 1.

[0051] That is, in the present invention, data when the cutting tool 3 is not present at the cutting position 7 is not used, but rather, sound in a band of 10 kHz or higher is detected when the cutting tool 3 is present at the cutting position 7, and then abnormality detection is performed using the Fourier transformed data. Therefore, when a high-level signal is detected while cutting is being performed, it can be determined that chatter vibration is occurring.

[0052] 5, any sensor can be used to detect the movement of the cutting tool 3. In particular, by using the acceleration sensor 9 shown in the figure, it is possible to accurately detect when the cutting tool 3 has reached the cutting position 7 and started cutting, or when cutting has ended and the cutting tool 3 has started to retreat from the cutting position 7. The acceleration sensor 9 can be provided on the tool post 6.

[0053] As described above, when a smartphone is used as a detection device for detecting the occurrence of chatter vibration, there is an advantage that a separate special acceleration sensor does not need to be prepared, since general smartphones usually have an acceleration sensor built in. Furthermore, when a smartphone is used as a detection device for detecting the occurrence of chatter vibration, the movement state of the tool bit 3 as a cutter can be detected from the acceleration occurring in the tool rest 6 simply by placing the smartphone on the tool rest 6, for example.

[0054] FIG. 6 shows an example of detection by the acceleration sensor 9. This FIG. 6 shows the negative acceleration when the tool bit 3 starts moving from the initial position 8, and the positive acceleration when the tool bit 3 reaches the cutting position 7 and stops moving. Also shown is the positive acceleration when the tool bit 3 starts moving from the cutting position 7 after the cutting process is completed, and the negative acceleration when the tool bit 3 returns to the initial position 8 and stops moving. Through these operations, the tool bit 3 performs one cycle of movement, but FIG. 6 shows two cycles of movement separated in time.

[0055] In order to achieve the above functions, the abnormality detection device according to the embodiment of the present invention includes: a first device that detects sounds in a frequency band of 10 kHz or higher and then performs a Fourier transform on the acoustic signal to separate abnormal sounds caused by cutting abnormalities from background noise; a second device that detects an abnormality by obtaining Fourier transform data during abnormal cutting processing in comparison with Fourier transform data during normal cutting processing; a sensor for detecting the movement state of the tool bit;

[0056] It is preferable that the apparatus has a third device that causes the second device to perform the abnormality detection using Fourier transform data from the first device and the second device when the bit is present at the cutting processing position, based on the detection results of a sensor that detects the movement state of the bit.

[0057] As described above, according to the present invention, it is possible to reliably detect the occurrence of abnormalities during cutting processing. Therefore, even if the machine tool is an automatic machine and is not directly monitored by an operator, if chatter vibration occurs, the situation can be immediately notified to an operator located away from the machine tool, and the operator can take measures. [Example]

[0058] An experiment on cutting using a general-purpose lathe was conducted in the laboratory. Dry cutting, without the use of cutting oil, was performed on an S55C material with an initial diameter of 32 mm and a protrusion of 49 mm from the chuck, using an internal boring tool with a triangular cermet tip. The cutting was performed approximately 20 mm in the feed direction under the conditions of a chuck rotation speed of 1150 rpm, a cutting depth of 0.3 mm, and a feed rate of 3 mm / sec. The start and end of cutting were then detected by detecting the acceleration during cutting. The sound signals detected under these conditions were analyzed.

[0059] At this time, by changing the protrusion length of the bit from the tool post, normal machining and machining that generated chatter were performed and the two were compared. Specifically, sound signals in the range of 13 to 17 kHz based on the natural vibration frequency of the bit were added, and the changes in sound pressure were verified.

[0060] In addition, the sounds generated at actual cutting work sites were collected as environmental noise, and these collected sounds were played back in the laboratory as background noise when the noise was generated.

[0061] Fig. 7 shows the measurement results of sound pressure changes without chatter vibration and without work noise. Fig. 8 shows the measurement results of sound pressure changes without chatter vibration and with work noise. Fig. 9 shows the measurement results of sound pressure changes with chatter vibration and without work noise. Fig. 10 shows the measurement results of sound pressure changes with chatter vibration and with work noise. In the cases with work noise shown in Figs. 8 and 10, acceleration measurements were performed based on the present invention.

[0062] Comparing Figure 7 and Figure 8, the sound pressure before cutting was -31,432 dBFS in Figure 7, where there was no work noise, but rose to -27,908 dBFS in Figure 8, where there was work noise. On the other hand, the sound pressure during normal cutting without chatter vibration was 26,717 dBFS in Figure 9, where there was no work noise, but only changed to -26,237 dBFS in Figure 8, where there was work noise, a change of only about -500 dBFS, and the impact of the work noise as background noise was small.

[0063] In the chatter vibration state shown in Figures 9 and 10, the sound pressure during cutting was approximately 25,000 dBFS, regardless of whether there was on-site work noise. In other words, a sound pressure increase of approximately -1,000 dBFS compared to the sound pressure during normal cutting when chatter vibration was not occurring was detected. This confirmed that the occurrence of chatter vibration can be accurately detected.

[0064] In the experimental system used, cutting began 8 seconds after the tool bit moved to the cutting position. In particular, in the chart shown in Figure 10, the acceleration sensor responded 9 seconds before cutting began, which was almost the same timing as the automatic movement to the cutting position. [Explanation of symbols]

[0065] 1 workpiece 3 Bits (cutting tools) 6 Tool post 7 Cutting position 8 Initial position 9 Acceleration Sensor

Claims

1. When detecting an abnormality when cutting a workpiece, In order to separate abnormal sounds caused by cutting abnormalities from background noise, the sound in the frequency band above 10 kHz is detected and the acoustic signal is subjected to Fourier transform. Abnormalities are detected by comparing the Fourier transform data during normal cutting with the Fourier transform data during abnormal cutting. At this time, a cutting tool that moves between a cutting position and an initial position away from the cutting position is used as the cutting tool, A method for detecting abnormalities during cutting work, characterized in that the movement state of the blade is detected by a sensor and the abnormality is detected using Fourier transform data when the blade is present at the cutting work position.

2. 2. The method for detecting abnormalities during cutting work according to claim 1, wherein an acceleration sensor is used as the sensor for detecting the movement state of the cutting tool.

3. 2. The method for detecting abnormalities during cutting work according to claim 1, wherein sounds in a band of 10 kHz or more and 20 kHz or less are detected.

4. Using a device for detecting sound and processing the data, The method for detecting abnormalities during cutting processing according to claim 1, characterized in that the device used for detecting the sound and processing the data has at least one of the following functions: a sound collection function, a function for Fourier transforming the collected sound data, a function for displaying the Fourier transformed data, a function for acquiring an image of the workpiece, a function for displaying the acquired image, a function for detecting the movement state of the blade from the acceleration of the blade, and a function for communicating data with an external device.

5. The method for detecting an abnormality during cutting processing according to claim 4, characterized in that a smartphone is used as a device for detecting sound and processing the data.

6. A device for detecting abnormalities when cutting a workpiece using a cutting tool, the cutting blade is a blade that moves between a cutting position and an initial position away from the cutting position, The device for detecting an abnormality comprises: a first device that detects sounds in a frequency band of 10 kHz or more and then performs a Fourier transform on the acoustic signal to separate abnormal sounds caused by cutting abnormalities from background noise; a second device for detecting an abnormality by comparing Fourier transform data obtained during abnormal cutting with Fourier transform data obtained during normal cutting; a sensor that detects the movement state of the blade; and a third device that causes the second device to perform the abnormality detection using Fourier transform data from the first device and the second device when the blade is present at the cutting position, based on the detection results of a sensor that detects the movement state of the blade.

7. 7. The abnormality detection device for use in cutting work according to claim 6, wherein the sensor for detecting the movement state of the cutting tool is an acceleration sensor.

8. 8. The abnormality detection device for use during cutting processing according to claim 7, wherein the first device, the second device, the sensor for detecting the movement state of the cutting tool, and the third device are incorporated into a single device.

9. The abnormality detection device for use in cutting processing according to claim 8, wherein the single device is a smartphone.

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