JP7803296B2 - Tool abnormality detection system - Google Patents

Description

The present invention relates to a tool abnormality detection system.

Tool abnormality detection systems for detecting abnormalities in tools used in machine tools have been proposed (see, for example, Patent Document 1). Specifically, these tool abnormality detection systems include a detection unit that detects sound waves generated when a workpiece is machined with a tool, and a control unit. The control unit then extracts the intensity of sound waves in a specified frequency band to reduce the influence of noise sound waves caused by background noise, and then compares the intensity of the extracted frequency band with a threshold value to determine tool abnormalities (i.e., wear). Examples of noise sound waves caused by background noise include the voices of workers monitoring the area around the machine tool, the operating sounds of other machine tools installed near the target machine tool, and chimes from the factory where the machine tool is located. Examples of sound waves caused by background noise also include sound waves from equipment installed on the target machine tool, such as the operating sounds of motors, automatic tool changers (ATCs), coolant systems, and oil mister collectors.

Japanese Patent Application Laid-Open No. 2007-222997

However, even with the tool abnormality detection system described above, there is a possibility that tool abnormalities may be erroneously detected if noise sound waves caused by background noise are included in the set frequency band.

In view of the above, the present invention aims to provide a tool abnormality detection system that is less likely to erroneously detect tool abnormalities.

Claim 1 for achieving the above object is a tool abnormality detection system comprising a detection unit (10) that detects sound waves generated when a workpiece (200) is machined using a tool (140, 410), and a control unit (30) that determines tool wear based on the sound waves detected by the detection unit, and has a resonance unit (20) that resonates with wear sound waves generated when the tool wears and generates resonance sound waves, the detection unit also detects the resonance sound waves from the resonance unit, the control unit compares the intensity of a determination signal based on the sound waves detected by the detection unit with a wear threshold, and determines that wear has occurred in the tool if the intensity of the determination signal is equal to or greater than the wear threshold , and the resonance unit is provided in plurality, each with a different natural frequency, and each natural frequency is included in the range of wear sound waves that can be generated depending on the condition of the workpiece .

In this way, a resonating section that can resonate with abrasion sound waves is arranged, and the determination signal is based on the abrasion sound waves and resonant sound waves. This allows the strength of the determination signal to be increased and the influence of noise sound waves to be reduced, thereby preventing erroneous determinations.

Note that the reference symbols in parentheses attached to each component indicate an example of the correspondence between that component and the specific components described in the embodiments described below.

FIG. 1 is a schematic diagram of a tool abnormality detection system according to a first embodiment. FIG. 2 is a block diagram of a control unit. FIG. 10 is a diagram illustrating the relationship between frequency and intensity. 10 is a flowchart executed by a control unit. FIG. 10 is a schematic diagram of a tool abnormality detection system according to a second embodiment. FIG. 10 is a schematic diagram of a tool abnormality detection system according to a third embodiment. FIG. 10 is a schematic diagram of a control unit in a fourth embodiment.

Embodiments of the present invention will be described below with reference to the accompanying drawings. Note that in the following embodiments, identical or equivalent parts will be denoted by the same reference numerals.

(First embodiment)
A tool abnormality detection system according to a first embodiment will be described with reference to Fig. 1. The tool abnormality detection system according to this embodiment is used in cutting work and detects abnormalities in the tool of a target machine tool. In this embodiment, an abnormality detection system that detects abnormalities in a drill used when drilling a workpiece as a cutting process will be described as an example.

The target machine tool 100 is, for example, a machining center having a processing chamber. In this embodiment, the machine tool 100 includes a stage 110, a vise 120 placed on the stage 110 to secure the workpiece 200, a spindle holder 130, and a drill 140 attached to the spindle holder 130 to process the workpiece 200. The machine tool 100 displaces the drill 140 to form a hole 201 in the workpiece 200. In this embodiment, the drill 140 corresponds to the tool. The workpiece 200 may be made of a material used in metal cutting, such as SUS or AL.

The tool abnormality detection system 1 includes a detection unit 10, a resonance unit 20, and a control unit 30.

The detection unit 10 outputs a detection signal corresponding to the detected sound waves, and is composed of a highly waterproof and dustproof sound-collecting microphone or the like, and is placed near the workpiece 200 and the resonator 20, which will be described later. In this embodiment, the detection unit 10 detects machining sound waves generated when the workpiece 200 is cut, and resonance sound waves generated from the resonator 20, as will be described later. The machining sound waves in this embodiment include direct sound waves generated directly when the workpiece 200 is cut with the drill 140, as well as abrasion sound waves generated when the drill 140 wears and the workpiece 200 vibrates, as will be described later.

The resonating portion 20 is configured to resonate with abrasion sound waves generated when the drill 140 wears and the workpiece 200 vibrates. Specifically, the resonating portion 20 is configured to have the same natural frequency as the workpiece 200 so that it can resonate with abrasion sound waves. For example, the resonating portion 20 is made of the same material and has the same shape as the workpiece 200. In this case, the resonating portion 20 is, for example, the workpiece 200 before drilling. Alternatively, the resonating portion 20 is, for example, the workpiece 200 after drilling. However, as long as the resonating portion 20 is configured to resonate with abrasion sound waves, it does not have to be made of the same material as the workpiece 200 or have the same shape as the workpiece 200. The natural frequencies of the workpiece 200 and the resonating portion 20 are derived, for example, by structural simulation or the impulse hammer method, but if the shape is simple, such as a rectangular parallelepiped, they may also be derived based on mechanical engineering formulas.

The resonating unit 20 is positioned in a location where it can resonate with the wear sound waves. For example, the resonating unit 20 is positioned near the workpiece 200, but it may also be positioned inside the detection unit 10, stage 110, vise 120, spindle holder 130, or drill 140. The resonating unit 20 resonates with the wear sound waves and generates resonant sound waves with frequency components equivalent to those of the wear sound waves.

The control unit 30 is composed of a microcomputer or the like equipped with a CPU and a storage unit composed of non-transient physical storage media such as ROM, RAM, flash memory, and HDD. As shown in FIG. 2, the control unit 30 of this embodiment is equipped with an amplifier unit 31, a signal processing unit 32, a determination unit 33, and the like. Note that CPU stands for Central Processing Unit, ROM stands for Read Only Memory, RAM stands for Random Access Memory, and HDD stands for Hard Disk Drive. Storage media such as ROM are non-transient physical storage media.

The amplifier unit 31 is connected to the detector unit 10 and amplifies the detection signal detected by the detector unit 10. The amplifier unit 31 may be connected to the detector unit 10 via wireless communication or via wired communication. The detection signal transmitted from the detector unit 10 is a signal based on processed sound waves and resonant sound waves, but also includes the influence of noise sound waves caused by background noise.

The signal processing unit 32 derives a judgment signal indicating the intensity in a predetermined frequency band. In this embodiment, the signal processing unit 32 is configured to include an FFT (short for Fast Fourier Transform) circuit that performs a discrete Fourier transform at high speed, a bandpass filter, and the like. The predetermined frequency band is a predetermined range that includes the natural frequency of the workpiece 200.

When the determination unit 33 receives the determination signal derived by the signal processing unit 32, it compares the intensity of the determination signal with the wear threshold to perform a wear determination as an abnormality determination to determine wear on the drill 140. Specifically, as shown in FIG. 3, when the drill 140 wears, the determination signal exceeds the wear threshold at the natural frequency of the workpiece 200. In this case, in this embodiment, as will be described in detail later, when the drill 140 wears, the workpiece 200 vibrates at its natural frequency, and the wear sound waves generated at this time resonate with the resonator 20, generating resonant sound waves. Therefore, the intensity of the determination signal obtained when the drill 140 wears can be increased compared to when the resonator 20 is not provided. This reduces the influence of noise sound waves caused by background noise, preventing erroneous determination of wear on the drill 140.

Furthermore, in this embodiment, if the determination unit 33 determines that the drill 140 is worn in the wear determination, it then performs a damage determination to determine whether the intensity of the determination signal has fallen below a damage threshold, which is lower than the wear threshold. Specifically, if the drill 140 breaks, the abrasion between the drill 140 and the workpiece 200 decreases, the wear sound waves decrease, and the intensity of the determination signal decreases. Therefore, the determination unit 33 determines that the drill 140 has broken when the intensity of the determination signal falls below the damage threshold.

The determination unit 33 in this embodiment is connected to the notification unit 40, which has a display unit, audio unit, etc., and if it determines that an abnormality such as wear or breakage has occurred in the drill 140, it sends an abnormality signal to the notification unit 40 indicating that an abnormality has occurred in the drill 140. In this embodiment, if the determination unit 33 determines that the drill 140 is worn, it sends a wear abnormality signal to the notification unit 40. If the determination unit 33 determines that the drill 140 is damaged, it sends a damage abnormality signal to the notification unit 40. The notification unit 40 then issues a notification according to the content of the abnormality signal to notify the operator that an abnormality has occurred in the drill 140.

The determination unit 33 may operate independently of the numerical control device (i.e., NC (abbreviation for Numerical Control) device) typically provided in the machine tool 100, or may send an abnormality signal to the numerical control device as well. If an abnormality signal is also sent to the numerical control device, the numerical control device may, for example, reset the set movement direction, movement amount, etc. based on wear on the drill 140.

The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, we will explain the abnormality detection method using the tool abnormality detection system 1. In this embodiment, we will explain the abnormality detection method when drilling a workpiece 200 using the drill 140 as described above.

First, when drilling a workpiece 200, the workpiece 200 is fixed in the vise 120, and the spindle holder 130 is rotated and displaced downward to press the drill 140 against the workpiece 200, thereby forming a hole 201 in the workpiece 200. As the cutting edge of the drill 140 wears down with continued drilling, the contact friction between the cutting edge of the drill 140 and the workpiece 200 at the bottom of the hole 201 increases, resulting in increased cutting resistance.

When contact friction increases, it becomes difficult for the spindle holder 130, which rotates and displaces the drill 140 downward, to operate properly, causing the spindle holder 130 to vibrate slightly, causing the drill 140 to scrape against the side wall of the hole 201. When the drill 140 scrapes against the side wall of the hole 201, the workpiece 200 begins to vibrate freely due to its natural vibration. In other words, when the drill 140 wears, wear sound waves are generated from the workpiece 200 due to the wear of the drill 140.

In this embodiment, as described above, the resonating unit 20, which has the same natural frequency as the workpiece 200, is placed near the workpiece 200. As a result, the resonating unit 20 generates resonant sound waves in response to wear sound waves.

The detection unit 10 detects sound waves and outputs a detection signal. Specifically, if the drill 140 is not worn, it detects direct sound waves and noise sound waves, and if the drill 140 is worn, it detects wear sound waves and resonant sound waves in addition to direct sound waves and noise sound waves, and transmits a detection signal.

The determination unit 33 then compares the intensity of the determination signal based on the detection signal with the wear threshold to determine whether the drill 140 is worn. In this case, when the drill 140 is worn, the detection unit 10 detects resonance sound waves in addition to wear sound waves. Therefore, when the drill 140 is worn, the intensity of the determination signal becomes higher compared to when the resonance unit 20 is not provided. This reduces the influence of noise sound waves. Furthermore, when the determination unit 33 determines that the drill 140 is worn, it performs a damage determination by comparing the intensity of the determination signal with the damage threshold.

The above is the abnormality detection method in this embodiment. Next, the operations performed by the control unit 30 will be explained with reference to Figure 4. Note that the control unit 30 performs the following operations, for example, when machining of the workpiece 200 begins.

First, in step S101, the control unit 30 receives a detection signal from the detection unit 10 and generates a determination signal. Then, in step S102, the control unit 30 determines whether or not a wear abnormality signal has been transmitted. In other words, the control unit 30 determines whether or not it has already determined that the drill 140 is in a worn state. Then, if the control unit 30 determines that a wear abnormality signal has been transmitted (i.e., step S102: YES), it performs the processing from step S105 onwards, which will be described later.

If the control unit 30 determines in step S102 that a wear abnormality signal has not been transmitted (i.e., step S102: NO), it determines in step S103 whether the strength of the determination signal is equal to or greater than the wear threshold value.

If the control unit 30 determines that the strength of the determination signal is less than the wear threshold (i.e., step S103: NO), the drill 140 is not worn and the process ends. On the other hand, if the control unit 30 determines that the strength of the determination signal is equal to or greater than the wear threshold (i.e., step S103: YES), the control unit 30 sends an abnormal wear signal to the notification unit 40 in step S104. This causes the notification unit 40 to perform a process of notifying the operator that wear has occurred in the drill 140.

After transmitting the wear abnormality signal in step S104, or if the control unit 30 determines that a wear abnormality signal has been transmitted in step S102 (i.e., step S102: YES), the control unit 30 determines in step S105 whether the intensity of the determination signal is equal to or less than the damage threshold. If the control unit 30 determines that the intensity of the determination signal is equal to or less than the damage threshold (i.e., step S105: YES), the drill 140 is damaged, and the control unit 30 transmits a damage abnormality signal to the notification unit 40. This causes the notification unit 40 to perform processing to notify the operator that damage has occurred to the drill 140. On the other hand, if the control unit 30 determines that the intensity of the determination signal is greater than the damage threshold (i.e., step S105: NO), the control unit 30 terminates processing.

In the present embodiment described above, a resonating unit 20 that can resonate with abrasion sound waves is provided, and the judgment signal is based on abrasion sound waves and resonance sound waves. This allows the strength of the judgment signal to be increased and the influence of noise sound waves to be reduced, thereby preventing erroneous judgments. Furthermore, since the tool abnormality detection system 1 of this embodiment can prevent erroneous judgments by increasing the strength of the judgment signal using resonance sound waves, it can also be applied when the diameter of the hole 201 is small or when the abrasion sound waves are small due to the material of the workpiece 200.

(Modification of the first embodiment)
A modification of the first embodiment will now be described. In the first embodiment, the control unit 30 performs the processes in step S105 and thereafter after transmitting the wear abnormality signal in step S104. However, the control unit 30 may perform the processes in step S105 and thereafter, for example, when the wear abnormality signal is transmitted multiple times.

Second Embodiment
A second embodiment will be described. This embodiment differs from the first embodiment in that it is adapted to detect abnormalities in a tool during turning, which is a cutting process. As the rest of the configuration is the same as the first embodiment, a description thereof will be omitted here.

The tool abnormality detection system 1 of this embodiment detects abnormalities in a tool used in turning, a cutting process. To this end, the machine tool 100 of this embodiment, as shown in FIG. 5, is equipped with a cutting tool 410 as a tool for turning the workpiece 200, and a vise 420 for holding the cutting tool 410. The cutting tool 410 is rod-shaped with one end shaped like a blade, and the other end opposite the one end is fixed by the vise 420.

As will be described in more detail below, in this embodiment, when the cutting edge of the bit 410 wears, the bit 410 vibrates at its natural frequency, generating wear acoustic waves. For this reason, the detection unit 10 is positioned near the bit 410. Note that Figure 5 shows the bit 410 in a state where it is worn and vibrating.

As in the first embodiment, the resonating unit 20 is positioned in a location where it can resonate with wear acoustic waves. For example, the resonating unit 20 is positioned near the workpiece 200, but it may also be positioned inside the cutting tool 410 or vise 420.

In addition, as described above, when the tool bit 410 wears, the tool bit 410 vibrates at its natural frequency, so the resonating part 20 in this embodiment is made of a material with the same natural frequency as the tool bit 410. For example, the resonating part 20 is made of an unused tool bit 410 that is the same as the tool bit 410 fixed to the vise 420.

As in the first embodiment, the control unit 30 compares the determination signal with a wear threshold to determine wear. The control unit 30 also compares the determination signal with a damage threshold to determine damage. However, in this embodiment, the control unit 30 (i.e., the signal processing unit 32) derives a determination signal in a predetermined frequency band that is within a predetermined range including the natural frequency of the tool bit 410.

The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, we will explain the abnormality detection method using the above-mentioned tool abnormality detection system 1. In this embodiment, we will explain the abnormality detection method when performing turning on the workpiece 200 using the cutting tool 410 as described above.

First, when performing turning, the rotating workpiece 200 is brought into contact with the tool bit 410 to form the desired shape. In this case, as the turning continues, the cutting edge of the tool bit 410 wears, the contact friction between the cutting edge and the workpiece 200 increases, resulting in higher turning resistance. When the force relationship between the tool bit 410 and the workpiece 200 becomes unbalanced and the relative velocity becomes zero, the tool bit 410 experiences a stick-slip phenomenon, and the spring force as the tool bit 410 returns to its original position causes the tool bit 410 to begin free vibration due to its natural vibration. In other words, when the tool bit 410 wears, it generates wear sound waves specific to wear. In this embodiment, as described above, the resonating unit 20, which has the same natural frequency as the tool bit 410, is positioned near the workpiece 200. Therefore, the resonating unit 20 resonates with the wear sound waves and generates resonant sound waves.

The stick-slip phenomenon refers to an intermittent movement in which two objects in contact do not slide continuously and smoothly, but alternate between slipping and sticking.

When the bit 410 is not worn, the detection unit 10 detects direct sound waves and noise sound waves, and when the bit 410 is worn, it detects wear sound waves and resonance sound waves in addition to direct sound waves and noise sound waves and transmits a detection signal.

Then, as in the first embodiment, the control unit 30 compares the intensity of the determination signal based on the detection signal with the wear threshold and the damage threshold to determine whether there is an abnormality in the bit 410.

According to the present embodiment described above, a resonating portion 20 that resonates with abrasion sound waves is provided, thereby achieving the same effects as the first embodiment.

(Third embodiment)
A third embodiment will be described. This embodiment differs from the first embodiment in that a plurality of resonating parts 20 are arranged. As the rest of the configuration is the same as the first embodiment, a description thereof will be omitted here.

First, when drilling a workpiece 200 as in the first embodiment, the mass of the workpiece 200 changes as a result of the drilling process, which may change the natural frequency of the workpiece 200. In other words, the wear acoustic waves generated from the workpiece 200 when the drill 140 wears may change depending on the situation. In particular, when forming multiple holes 201 or a large hole 201, the change in mass of the workpiece 200 becomes greater, and the natural frequency of the workpiece 200 is likely to change.

For this reason, in this embodiment, as shown in Figure 6, multiple resonating parts 20 are provided. Specifically, each resonating part 20 has a different natural frequency. However, each resonating part 20 has a natural frequency that corresponds to the natural frequency of the workpiece 200, which changes as the workpiece 200 is drilled. In other words, the natural frequency of each resonating part 20 is within the range of wear sound waves that can be generated depending on the condition of the workpiece 200.

The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, we will explain the abnormality detection method using the above tool abnormality detection system.

Similar to the first embodiment described above, when the drill 140 wears, wear acoustic waves are generated from the workpiece 200 due to the wear of the drill 140. In this case, the frequency of the wear acoustic waves changes depending on the mass of the workpiece 200. However, in this embodiment, multiple resonating parts 20 are provided, and each resonating part 20 has a different natural frequency. This prevents the problem of not generating resonant sound waves corresponding to wear acoustic waves.

According to the present embodiment described above, a resonating portion 20 that resonates with abrasion sound waves is provided, thereby achieving the same effects as the first embodiment.

(1) In this embodiment, multiple resonating units 20 are arranged, and the natural frequencies of each resonating unit 20 are set to different values. This prevents the occurrence of a problem in which resonant sound waves corresponding to wear sound waves are not generated.

(Fourth embodiment)
A fourth embodiment will be described. In this embodiment, the configuration of the control unit 30 is changed from that of the first embodiment. As the rest is the same as in the first embodiment, a description thereof will be omitted here. Note that in this embodiment, the wear determination in the first embodiment will be described, but damage determination may also be performed.

The control unit 30 in this embodiment determines wear on the drill 140 using the self-learning anomaly detection system already applied for by the applicant in Japanese Patent Application Laid-Open No. 2020-129233.

As shown in FIG. 7, the control unit 30 of this embodiment includes a signal acquisition unit 301, a learning target data storage unit 302, a monitoring target data storage unit 303, a state observer generation unit 304, a state observer information storage unit 305, a normal model generation unit 306, a normal model parameter storage unit 307, an anomaly degree calculation unit 308, a judgment unit 309, a factor analysis unit 310, and the like.

The signal acquisition unit 301 acquires learning target data and monitoring target data. In this embodiment, the monitoring target data and learning target data are detection signals based on sound waves detected by the detection unit 10.

The learning target data may be acquired by downloading it from a database that stores reference values, rather than detection signals. Furthermore, the monitoring target data in this embodiment may be data to be monitored, and may or may not be used for other purposes; for example, it may also be data to be used as a learning target. Furthermore, the learning target data in this embodiment may be data to be used for learning, and may or may not be used for other purposes.

The learning target data storage unit 302 stores the learning target data acquired by the signal acquisition unit 301. The stored learning target data is then input to the normal model generation unit 306, which will be described later.

The monitoring target data storage unit 303 stores the monitoring target data acquired by the signal acquisition unit 301. The stored monitoring target data is then input to the anomaly degree calculation unit 308, which will be described later.

The learning target data storage unit 302 and the monitoring target data storage unit 303 are expected to be configured with a HDD, flash memory, etc., but may also be configured with RAM, etc. Furthermore, the learning target data storage unit 302 and the monitoring target data storage unit 303 may be configured with either volatile memory or non-volatile memory.

The state observer generation unit 304 generates a state observer using variables included in the input variable configuration. The state observer is a value including a predetermined coefficient generated by linearly combining variables included in the input variable configuration with a preset mathematical formula. The state observer preferably reflects the state of the drill 140 for which anomalies are detected by the tool anomaly detection system 1, and preferably reflects wear on the drill 140. In this embodiment, variables are variables corresponding to the learning target data and monitoring target data acquired by the signal acquisition unit 301, and a variable configuration is one variable or a combination of multiple variables.

The state observer information storage unit 305 stores the coefficients of the state observer calculated by the state observer generation unit 304. It also stores the variable configuration used to generate the state observer.

The state observer generation unit 304 only needs to be included when generating a state observer. In other words, the state observer generation unit 304 may be configured to be disconnected from the control unit 30 after generating a state observer and storing the variable configuration and coefficients of the state observer in the state observer information storage unit 305.

The normal model generation unit 306 derives a first state observation value obtained by inputting the learning target data into the state observer. In this embodiment, the variable configuration and coefficients of the state observer are read from the state observer information storage unit 305, and the first state observation value is obtained by applying the learning target data read from the learning target data storage unit 302 to these variables. The normal model generation unit 306 then generates a normal model by combining the derived first state observation value and the learning target data and inputting them into a competitive neural network (i.e., NN). For example, in this embodiment, the material of the drill 140, the diameter of the hole, etc. are input into the competitive neural network (NN) as learning target data.

When there are multiple combinations of input data attributes, such as measurement season and time, it is desirable to sample the initial values given to the competitive neural network evenly or randomly. This allows for faster convergence during learning of neuron weight vectors on the map in the competitive neural network.

Here, a competitive neural network is a network consisting only of an input layer and an output layer, and is composed of multiple input layer neurons and multiple output layer neurons that are fully connected to the input layer neurons.

The normal model generation unit 306 then calculates the degree of anomaly, which is the difference between the learning data and first state observation values input to the competitive neural network and the neuron weight data of the winning unit, and calculates the wear threshold using the set of differences. For example, a constant multiple of the 99.9% quantile of the set of differences (i.e., absolute values) is used as the wear threshold.

The normal model parameter storage unit 307 stores the wear threshold value calculated by the normal model generation unit 306.

The anomaly degree calculation unit 308 derives a second state observation value obtained by inputting the monitored data into the state observer. In this embodiment, the variable configuration and coefficients of the state observer are read from the state observer information storage unit 305, and the monitored data read from the monitored data storage unit 303 are applied to these variables to obtain a second state observation value. The anomaly degree calculation unit 308 then combines the derived second state observation value and the monitored data and inputs them into a competitive neural network (i.e., NN), thereby calculating the degree of anomaly using the weight data of the output layer neurons. For example, in this embodiment, the material of the drill 140, the diameter of the hole, etc. are input into the competitive neural network (NN) as monitored data.

The determination unit 309 performs wear determination by comparing the wear threshold value read from the normal model parameter storage unit 307 with the abnormality level output from the abnormality level calculation unit 308. Specifically, if the abnormality level is equal to or greater than the wear threshold value, it determines that the drill 140 is worn, and if the abnormality level is less than the wear threshold value, it determines that there is no wear.

When the determination unit 309 determines that wear exists, the factor analysis unit 310 identifies the cause of the wear using the second state observation value and monitored data that caused the determination that wear exists. In this case, the factor analysis unit 310 may further use the second state observation value and monitored data that caused the determination that wear exists as a reference and identify the cause of the abnormality using the second state observation value and monitored data that occurred before, after, or both before and after in time.

According to the present embodiment described above, a resonating portion 20 that resonates with abrasion sound waves is provided, thereby achieving the same effects as the first embodiment described above.

(1) As in this embodiment, the control unit 30 may determine the wear on the drill 140 while self-learning. This allows wear determination to be made according to the situation, which is expected to further reduce erroneous determinations.

(Other embodiments)
Although the present disclosure has been described with reference to the embodiments, it is understood that the present disclosure is not limited to the embodiments or structures. The present disclosure also encompasses various modifications and modifications within the scope of equivalents. In addition, various combinations and forms, as well as other combinations and forms including only one element, more than one element, or less than one element, are also within the scope and spirit of the present disclosure.

For example, in the first to third embodiments, wear and damage determinations are performed, but it is also possible to perform only wear determination.

Furthermore, in the first, third, and fourth embodiments, a drill 140 was used as an example of the tool, and in the second embodiment, a cutting tool 410 was used as an example of the tool. However, the tool can be changed as appropriate and may be an end mill, a grinding wheel, or the like.

The control unit and method described in this disclosure may be implemented by a special-purpose computer configured by configuring a processor and memory programmed to perform one or more functions embodied in a computer program. Alternatively, the control unit and method described in this disclosure may be implemented by a special-purpose computer configured by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the control unit and method described in this disclosure may be implemented by one or more special-purpose computers configured by combining a processor and memory programmed to perform one or more functions with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory tangible recording medium.

10 Detector 20 Resonator 30 Controller 140 Drill (tool)
200 Work material

Claims (2)

A tool abnormality detection system,
a detection unit (10) that detects sound waves generated when a workpiece (200) is machined using a tool (140, 410);
a control unit (30) that determines wear of the tool based on the sound waves detected by the detection unit,
a resonance part (20) that resonates with abrasion sound waves generated by the tool being worn to generate resonance sound waves,
The detection unit also detects resonance sound waves from the resonance unit,
the control unit compares the intensity of a determination signal based on the sound wave detected by the detection unit with a wear threshold, and determines that wear has occurred in the tool when the intensity of the determination signal is equal to or greater than the wear threshold ;
A tool abnormality detection system in which multiple resonating parts are provided, each with a different natural frequency, and each of the natural frequencies is included in the range of wear sound waves that can be generated depending on the condition of the workpiece . The tool abnormality detection system described in claim 1, wherein when the control unit determines that wear has occurred in the tool, it compares whether the intensity of the determination signal is equal to or less than a damage threshold that is smaller than the wear threshold, and determines that the tool is damaged if the intensity of the determination signal is equal to or less than the damage threshold.