Tool abnormality detecting system

Abstract

To provide a tool abnormality detecting system that can be prevented from erroneously determining abnormality of a tool.SOLUTION: The tool abnormality detecting system comprises a detecting part 10 that detects a sound wave generated when processing a material 200 to be ground using a tool 140, and a control part 30 that determines the abrasion of the tool 140 on the basis of the sound wave detected by the detecting part 10. The detecting part 10 further comprises a resonance part 20 that generates a resonant sound wave in resonance with a sound wave generated when the tool 140 is abraded. The detecting part 10 detects the resonant sound wave generated by the resonance part 20 as well. The control part 30 compares an intensity of a determination signal based on the sound wave detected by the detecting part 10 with an abrasion threshold, and when the intensity of the determination signal is equal to or more than the abrasion threshold, determines that the tool has abrasion.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a tool abnormality detection system. [Background technology]

[0002] Conventionally, a tool abnormality detection system for detecting abnormalities in a tool in a machine tool has been proposed (see, for example, Patent Document 1). Specifically, this tool abnormality detection system includes a detection unit for detecting sound waves generated when a workpiece is machined using a tool, and a control unit. The control unit extracts the intensity of sound waves in a predetermined frequency band in order 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 abnormality (i.e., wear) of the tool. Note that examples of noise sound waves caused by background noise include the voice of an operator monitoring the vicinity of the machine tool, the operating sound of another machine tool installed in the vicinity of the target machine tool, and the chime of a factory in which the machine tool is installed. Examples of sound waves caused by background noise include sound waves of equipment, etc., provided in the target machine tool, such as the operating sound of a motor, an automatic tool changer (i.e., ATC (short for Automatic Tool Changer)), a coolant device, an oil mister collector, etc. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2007-222997 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, even in the above-described tool abnormality detection system, if noise sound waves caused by background noise are included in the set frequency band, there is a possibility that a tool abnormality will be erroneously determined.

[0005] In view of the above, an object of the present invention is to provide a tool abnormality detection system that can reduce the likelihood of erroneous determination of a tool abnormality. [Means for solving the problem]

[0006] 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 with 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 resonant sound waves, the detection unit also detects the resonant sound waves from the resonance unit, and 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 the tool is worn when the intensity of the determination signal is equal to or greater than the wear threshold.

[0007] According to this, a resonating portion capable of resonating with the abrasion sound waves is disposed, and the determination signal is based on the abrasion sound waves and the resonance sound waves. Therefore, the strength of the determination signal can be increased and the influence of noise sound waves can be reduced, thereby suppressing erroneous determination.

[0008] Note that the reference symbols in parentheses attached to each component indicate an example of the correspondence between the component and specific components described in the embodiments described below. [Brief description of the drawings]

[0009] [Figure 1] 1 is a schematic diagram of a tool abnormality detection system according to a first embodiment. FIG. [Diagram 2] FIG. 2 is a block diagram of a control unit. [Diagram 3] FIG. 13 is a diagram showing the relationship between frequency and intensity. [Figure 4] 11 is a flowchart executed by a control unit. [Diagram 5] FIG. 11 is a schematic diagram of a tool abnormality detection system according to a second embodiment. [Figure 6] FIG. 11 is a schematic diagram of a tool abnormality detection system according to a third embodiment. [Figure 7] FIG. 13 is a schematic diagram of a control unit in a fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following embodiments, parts that are the same or equivalent to each other will be denoted by the same reference numerals.

[0011] (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 for cutting processing and detects abnormalities in a tool of a target machine tool. In this embodiment, an abnormality detection system that detects abnormalities in a drill used when performing drilling processing as cutting processing on a workpiece will be described as an example.

[0012] The target machine tool 100 is, for example, a machining center having a machining chamber. In this embodiment, the machine tool 100 includes a stage 110, a vice 120 placed on the stage 110 to fix a workpiece 200, a spindle holder 130, and a drill 140 attached to the spindle holder 130 to machine 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 a tool. Examples of the workpiece 200 include materials used in metal cutting, such as SUS and AL.

[0013] The tool abnormality detection system 1 includes a detection unit 10, a resonance unit 20, a control unit 30, and the like.

[0014] The detection unit 10 outputs a detection signal according to the detected sound waves, is composed of a highly waterproof and dustproof sound collecting microphone or the like, and is disposed near the workpiece 200 and the resonance unit 20 described below. As described below, the detection unit 10 of this embodiment detects machining sound waves generated when the workpiece 200 is cut and resonance sound waves generated from the resonance unit 20. The machining sound waves of this embodiment include direct sound waves generated directly when the workpiece 200 is cut with the drill 140, as well as wear sound waves generated when the drill 140 wears and the workpiece 200 vibrates, as described below.

[0015] The resonating portion 20 is configured to be capable of resonating with wear sound waves generated by the wear of the drill 140 and the vibration of the workpiece 200. Specifically, the resonating portion 20 is configured to have the same natural frequency as the workpiece 200 so as to be capable of resonating with wear sound waves. For example, the resonating portion 20 is made of the same material as the workpiece 200 and has the same shape as the workpiece 200. In this case, the resonating portion 20 is made of, for example, the workpiece 200 before drilling. Also, the resonating portion 20 is made of, for example, the workpiece 200 after drilling. However, the resonating portion 20 does not need to be made of the same material as the workpiece 200 or have the same shape as the workpiece 200 as long as it is configured to resonate with wear sound waves. 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 when the shape is a simple shape such as a rectangular prism, they may be derived based on mechanical engineering formulas, for example.

[0016] The resonance unit 20 is disposed at a position where it can resonate with the wear sound waves. For example, the resonance unit 20 is disposed near the workpiece 200, but may also be disposed inside the detection unit 10, the stage 110, the vice 120, the spindle holder 130, or the drill 140. The resonance unit 20 resonates with the wear sound waves and generates resonant sound waves having a frequency component equivalent to that of the wear sound waves.

[0017] The control unit 30 is configured with a microcomputer or the like equipped with a storage unit configured with a non-transient substantial storage medium such as a CPU, a ROM, a RAM, a flash memory, and a 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 is an abbreviation for Central Processing Unit, ROM is an abbreviation for Read Only Memory, RAM is an abbreviation for Random Access Memory, and HDD is an abbreviation for Hard Disk Drive. Storage media such as ROM are non-transient substantial storage media.

[0018] The amplifier 31 is connected to the detector 10 and amplifies the detection signal detected by the detector 10. The amplifier 31 may be connected to the detector 10 by wireless communication or by wired communication. The detection signal transmitted from the detector 10 is a signal based on the processed sound waves and the resonant sound waves, but is also a signal that includes the influence of noise sound waves caused by background noise.

[0019] 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 have an FFT (abbreviation of Fast Fourier Transform) circuit unit that performs Discrete Fourier Transform at high speed, a bandpass filter, etc. The predetermined frequency band is a predetermined range including the natural frequency of the workpiece 200.

[0020] When the determination unit 33 receives the determination signal derived by the signal processing unit 32, the determination unit 33 performs wear determination as an abnormality determination for determining wear of the drill 140 by comparing the intensity of the determination signal with the wear threshold value. Specifically, as shown in FIG. 3, when the drill 140 is worn, the determination signal becomes equal to or higher than the wear threshold value at the natural frequency of the workpiece 200. In this case, in this embodiment, as will be specifically described later, when the drill 140 is worn, the workpiece 200 vibrates at the natural frequency, and the resonance unit 20 resonates with the wear sound waves generated at this time, generating resonance sound waves. Therefore, the intensity of the determination signal obtained when the drill 140 is worn can be increased compared to when the resonance unit 20 is not arranged. Therefore, the influence of noise sound waves caused by background noise can be reduced, and erroneous determination of wear of the drill 140 can be suppressed.

[0021] Furthermore, when the determination unit 33 of this embodiment determines that the drill 140 is worn in the wear determination, it performs a damage determination to determine whether or not the intensity of the determination signal is equal to or lower than a damage threshold value that is lower than the wear threshold value after the wear determination. Specifically, when the drill 140 is damaged, 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 is damaged when the intensity of the determination signal is equal to or lower than the damage threshold value.

[0022] The determination unit 33 of this embodiment is connected to the notification unit 40 having a display unit, an audio unit, etc., and when it is determined that an abnormality such as wear or breakage has occurred in the drill 140, it transmits an abnormality signal indicating that an abnormality has occurred in the drill 140 to the notification unit 40. In this embodiment, when the determination unit 33 determines that the drill 140 is worn, it transmits a wear abnormality signal to the notification unit 40. When the determination unit 33 determines that the drill 140 is broken, it transmits a damage abnormality signal to the notification unit 40. Then, the notification unit 40 issues a notification according to the content of the abnormality signal to notify the operator that an abnormality has occurred in the drill 140.

[0023] Determination unit 33 may operate independently of a numerical control device (i.e., an NC (abbreviation of Numerical Control) device) that is generally provided in machine tool 100, but may also transmit an abnormality signal to the numerical control device. When an abnormality signal is also transmitted to the numerical control device, the numerical control device may, for example, reset the set movement direction, movement amount, etc. based on wear of drill 140.

[0024] The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, a description will be given of an abnormality detection method using the tool abnormality detection system 1. In this embodiment, as described above, a description will be given of an abnormality detection method when drilling a hole in a workpiece 200 using the drill 140.

[0025] First, when drilling a hole in the workpiece 200, the workpiece 200 is fixed in the vice 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. When the cutting edge of the drill 140 wears down as the drilling process continues, the contact friction between the cutting edge of the drill 140 and the workpiece 200 increases at the bottom of the hole 201, and the cutting resistance increases.

[0026] When the contact friction increases, it becomes difficult for the spindle holder 130, which rotates to displace the drill 140 downward, to operate properly, and the spindle holder 130 vibrates 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 starts 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.

[0027] In this embodiment, as described above, the resonance part 20 having the same natural frequency as the workpiece 200 is disposed in the vicinity of the workpiece 200. Therefore, the resonance part 20 generates a resonance sound wave by the wear sound wave.

[0028] The detector 10 detects sound waves and outputs a detection signal. Specifically, when the drill 140 is not worn, the detector 10 detects direct sound waves and noise sound waves, and when the drill 140 is worn, the detector 10 detects wear sound waves and resonance sound waves in addition to the direct sound waves and noise sound waves, and transmits a detection signal.

[0029] Then, the determination unit 33 compares the intensity of the determination signal based on the detection signal with the wear threshold value 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 arranged. Therefore, the influence of noise sound waves can be reduced. Furthermore, when the determination unit 33 determines that the drill 140 is worn, it performs damage determination by comparing the intensity of the determination signal with the damage threshold value.

[0030] The above is the abnormality detection method in this embodiment. Next, the operation performed by the control unit 30 will be described with reference to Fig. 4. The control unit 30 performs the following operation, for example, when machining of the workpiece 200 is started.

[0031] 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. That is, the control unit 30 determines whether or not the drill 140 has already been determined to be in a worn state. Then, when the control unit 30 determines that a wear abnormality signal has been transmitted (i.e., step S102: YES), it performs the processes in and after step S105, which will be described later.

[0032] When the control unit 30 determines in step S102 that the wear abnormality signal has not been transmitted (that is, step S102: NO), the control unit 30 determines in step S103 whether or not the intensity of the determination signal is equal to or greater than the wear threshold value.

[0033] When the control unit 30 determines that the intensity 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, when the control unit 30 determines that the intensity of the determination signal is equal to or greater than the wear threshold (i.e., step 103: YES), the control unit 30 transmits a wear abnormality signal to the notification unit 40 in step S104. As a result, the notification unit 40 performs a process of notifying the operator that the drill 140 is worn.

[0034] After transmitting the wear abnormality signal in step S104, or when it is determined that the wear abnormality signal has been transmitted in step S102 (i.e., step S102: YES), the control unit 30 determines whether or not the intensity of the determination signal is equal to or less than the damage threshold in step S105. When 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 therefore transmits a damage abnormality signal to the notification unit 40. As a result, the notification unit 40 performs a process of notifying the operator that damage has occurred in the drill 140. On the other hand, when the control unit 30 determines that the intensity of the determination signal is greater than the damage threshold (i.e., step S105: NO), the process ends.

[0035] According to the present embodiment described above, the resonating portion 20 capable of resonating with the wear sound waves is disposed, and the judgment signal is based on the wear sound waves and the resonance sound waves. Therefore, the strength of the judgment signal can be increased and the influence of noise sound waves can be reduced, so that erroneous judgment can be suppressed. And, since the tool abnormality detection system 1 of the present embodiment can suppress erroneous judgment by increasing the strength of the judgment signal by the resonance sound waves, it can be applied even when the diameter of the hole 201 is small or when the wear sound waves are small due to the material of the workpiece 200.

[0036] (Modification of the first embodiment) A modified example of the first embodiment will be described. In the first embodiment, the control unit 30 performs the process of step S105 and thereafter after sending the wear abnormality signal in step S104. However, the control unit 30 may perform the process of step S105 and thereafter when the wear abnormality signal is sent multiple times, for example.

[0037] Second embodiment A second embodiment will be described. This embodiment is different from the first embodiment in that it detects abnormalities in a tool during turning as cutting. As the rest is the same as the first embodiment, a description thereof will be omitted here.

[0038] The tool abnormality detection system 1 of this embodiment detects an abnormality in a tool that performs turning as a cutting process. For this reason, the machine tool 100 of this embodiment includes a cutting tool 410 as a tool for turning a workpiece 200, a vice 420 for holding the cutting tool 410, and the like, as shown in Fig. 5. The cutting tool 410 is rod-shaped with one end portion formed into a blade shape, and the other end portion opposite to the one end portion is fixed by the vice 420.

[0039] In this embodiment, when the cutting edge of the cutting tool 410 is worn, the cutting tool 410 vibrates at its natural frequency, generating wear sound waves. For this reason, the detector 10 is disposed in the vicinity of the cutting tool 410. Note that FIG. 5 shows a state in which the cutting tool 410 is worn and vibrating.

[0040] The resonance unit 20 is disposed at a position where it can resonate with the wear sound wave, similarly to the first embodiment. For example, the resonance unit 20 is disposed near the workpiece 200, but may be disposed inside the cutting tool 410 or the vice 420.

[0041] In addition, since the bit 410 vibrates at its natural frequency when it becomes worn as described above, the resonating part 20 of this embodiment is made of a material having the same natural frequency as the bit 410. For example, the resonating part 20 uses an unused bit 410 that is the same as the bit 410 fixed to the vice 420 as it is.

[0042] The control unit 30 performs wear determination by comparing the determination signal with a wear threshold value, similarly to the first embodiment. The control unit 30 also performs damage determination by comparing the determination signal with a damage threshold value. However, the control unit 30 (i.e., the signal processing unit 32) of this embodiment derives a determination signal in a predetermined range including the natural frequency of the tool bit 410 as a determination signal in a predetermined frequency band.

[0043] The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, a description will be given of an abnormality detection method using the above-mentioned tool abnormality detection system 1. In this embodiment, as described above, a description will be given of an abnormality detection method when turning the workpiece 200 using the cutting tool 410.

[0044] First, when performing turning, the workpiece 200 is turned into a desired shape by contacting the rotating workpiece 200 with the tool bit 410. In this case, when the cutting edge of the tool bit 410 wears as the turning process continues, the contact friction between the cutting edge and the workpiece 200 increases, and the turning resistance increases. When the force relationship between the tool bit 410 and the workpiece 200 becomes unbalanced and the relative speed becomes zero, the tool bit 410 causes a stick-slip phenomenon, and the tool bit 410 starts to vibrate freely due to its natural vibration due to the spring force when the tool bit 410 returns to its fixed position. In other words, when the tool bit 410 wears, a wear sound wave specific to the wear is generated from the tool bit 410. In this embodiment, as described above, the resonating portion 20 having the same natural frequency as the tool bit 410 is disposed near the workpiece 200. For this reason, the resonating portion 20 resonates with the wear sound wave to generate a resonating sound wave.

[0045] The stick-slip phenomenon refers to an intermittent motion in which, when two objects in contact slide, the sliding motion is not continuous and smooth, but occurs alternately between slipping and sticking.

[0046] When the bit 410 is not worn, the detection unit 10 detects direct acoustic waves and noise acoustic waves, and when the bit 410 is worn, the detection unit 10 detects wear acoustic waves and resonant acoustic waves in addition to the direct acoustic waves and noise acoustic waves, and transmits a detection signal.

[0047] Then, 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 the tool bit 410 is abnormal, in the same manner as in the first embodiment.

[0048] According to the present embodiment described above, since the resonating portion 20 that resonates with the abrasion sound waves is disposed, it is possible to obtain the same effects as those of the first embodiment.

[0049] Third embodiment A third embodiment will be described. In this embodiment, a plurality of resonance units 20 is arranged in comparison with the first embodiment. As the rest is similar to the first embodiment, a description thereof will be omitted here.

[0050] First, when drilling the workpiece 200 as in the first embodiment, the mass of the workpiece 200 may change due to the drilling, and the natural frequency of the workpiece 200 may change. In other words, the wear sound waves generated from the workpiece 200 when the drill 140 is worn may change depending on the situation. In particular, when forming a plurality of holes 201 or a large hole 201, the change in the mass of the workpiece 200 becomes large, and the natural frequency of the workpiece 200 is likely to change.

[0051] For this reason, in this embodiment, as shown in Fig. 6, a plurality of resonating parts 20 are provided. Specifically, each resonating part 20 has a different natural frequency. However, each resonating part 20 has a natural frequency corresponding to the natural frequency of the workpiece 200 that changes with the drilling of the workpiece 200. 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.

[0052] The above is the configuration of the tool abnormality detection system 1 in this embodiment. Next, an abnormality detection method using the tool abnormality detection system will be described.

[0053] As in the first embodiment, when the drill 140 wears, wear sound waves are generated from the workpiece 200 due to the wear of the drill 140. In this case, the frequency of the wear sound waves changes depending on the mass of the workpiece 200. However, in this embodiment, a plurality of resonance parts 20 are provided, and each resonance part 20 has a different natural frequency. Therefore, it is possible to suppress the occurrence of a problem in which a resonance sound wave corresponding to the wear sound wave is not generated.

[0054] According to the present embodiment described above, since the resonating portion 20 that resonates with the abrasion sound waves is disposed, it is possible to obtain the same effects as those of the first embodiment.

[0055] (1) In the present embodiment, a plurality of resonating parts 20 are arranged, and the natural frequencies of the respective resonating parts 20 are different from each other. This makes it possible to prevent a problem that a resonant sound wave corresponding to abrasion sound waves is not generated.

[0056] (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, the description will be omitted here. In this embodiment, the wear determination in the first embodiment will be described, but damage determination may also be performed.

[0057] The control unit 30 of this embodiment determines wear of the drill 140 using self-learning of an anomaly detection system already applied for by the present applicant in JP 2020-129233 A.

[0058] As shown in FIG. 7 , the control unit 30 of this embodiment has 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, etc.

[0059] The signal acquiring unit 301 acquires the learning target data and the monitoring target data. In this embodiment, a detection signal based on a sound wave detected by the detecting unit 10 is acquired as the monitoring target data and the learning target data.

[0060] The learning target data may be acquired by downloading from a database that stores reference values, instead of detection signals. The monitoring target data in this embodiment may be data to be monitored, and may be used for other purposes as desired, for example, data to be used as a learning target. The learning target data in this embodiment may be data to be used for learning, and may be used for other purposes as desired.

[0061] The learning object data storage unit 302 stores the learning object data acquired by the signal acquisition unit 301. The stored learning object data is then input to a normal model generation unit 306, which will be described later.

[0062] 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 an abnormality degree calculation unit 308, which will be described later.

[0063] The learning target data storage unit 302 and the monitoring target data storage unit 303 are assumed to be configured with a HDD, a flash memory, or the like, but may be configured with a RAM, etc. Furthermore, the learning target data storage unit 302 and the monitoring target data storage unit 303 may be configured with either a volatile memory or a non-volatile memory.

[0064] The state observer generating unit 304 generates a state observer by 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 expression. The state observer preferably reflects the state of the drill 140 whose abnormality is detected by the tool abnormality detection system 1, and preferably reflects wear of the drill 140. In this embodiment, the variables are variables corresponding to the learning target data and the monitoring target data acquired by the signal acquiring unit 301, and the variable configuration is one variable or a combination of multiple variables.

[0065] The state observer information storage unit 305 stores the coefficients of the state observer calculated by the state observer generation unit 304. In addition, the variable configuration used to generate the state observer is also stored at the same time.

[0066] The state observer generating unit 304 may be provided when generating a state observer. In other words, the state observer generating unit 304 may be separated from the control unit 30 after once generating a state observer and storing the variable configuration of the state observer and the coefficients of the state observer in the state observer information storage unit 305.

[0067] The normal model generation unit 306 derives a first state observation value obtained by inputting the learning target data to 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 learning target data read from the learning target data storage unit 302 are applied to these variables to obtain a first state observation value. Then, the normal model generation unit 306 combines the derived first state observation value and the learning target data and inputs them to a competitive neural network (i.e., NN) to generate a normal model. For example, in this embodiment, the material of the drill 140, the diameter of the hole, etc. are input to the competitive neural network (NN) as the learning target data.

[0068] In addition, when there are multiple combinations of attributes of input data, such as measurement season and time, it is desirable to sample the initial values ​​given to the competitive neural network evenly or randomly. This makes it possible to speed up the convergence of the neuron weight vectors during learning on the map in the competitive neural network.

[0069] Here, the competitive neural network is a network consisting of only an input layer and an output layer, and is composed of a plurality of input layer neurons and a plurality of output layer neurons that are fully connected to the input layer neurons.

[0070] Then, the normal model generating unit 306 calculates the degree of abnormality, which is the difference between the learning data and the first state observation value input to the competitive neural network and the neuron weight data of the winning unit, and calculates the wear-out 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-out threshold.

[0071] The normal model parameter storage unit 307 stores the wear threshold value calculated by the normal model generation unit 306 .

[0072] The anomaly degree calculation unit 308 derives a second state observation value obtained by inputting the monitored data to 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. Then, the anomaly degree calculation unit 308 combines the derived second state observation value and the monitored data and inputs them to 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 to the competitive neural network (NN) as the monitored data.

[0073] The determination unit 309 performs wear determination by comparing the wear threshold value read from the normal model parameter storage unit 307 with the degree of abnormality output from the abnormality degree calculation unit 308. Specifically, if the degree of abnormality is equal to or greater than the wear threshold value, it is determined that the drill 140 is worn, and if the degree of abnormality is less than the wear threshold, it is determined that there is no wear.

[0074] When the determination unit 309 determines that wear exists, the factor analysis unit 310 identifies the cause of wear using the second state observation value and the monitored data that caused the determination that wear exists. In this case, the factor analysis unit 310 may further identify the cause of the abnormality using the second state observation value and the monitored data that are temporally before, after, or before and after the second state observation value and the monitored data that caused the determination that wear exists as a reference.

[0075] According to the present embodiment described above, since the resonating portion 20 that resonates with the abrasion sound waves is disposed, it is possible to obtain the same effects as those of the first embodiment.

[0076] (1) As in the present embodiment, the control unit 30 may perform self-learning to determine the wear of the drill 140. This is expected to further reduce erroneous determinations since wear determination can be performed according to the situation.

[0077] (Other embodiments) Although the present disclosure has been described based on the embodiment, it is understood that the present disclosure is not limited to the embodiment or structure. The present disclosure also encompasses various modifications and modifications within the equivalent range. 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 concept of the present disclosure.

[0078] For example, in the first to third embodiments, the wear judgment and the damage judgment are performed, but it is also possible to perform only the wear judgment.

[0079] In the above first, third and fourth embodiments, the drill 140 is used as an example of the tool, and in the above second embodiment, the tool is used as an example of the cutting tool 410. However, the tool can be changed as appropriate and may be an end mill, a grindstone, or the like.

[0080] The control unit and the method described in the present disclosure may be implemented by a special-purpose computer provided by configuring a processor and a memory programmed to execute one or more functions embodied in a computer program. Alternatively, the control unit and the method described in the present disclosure may be implemented by a special-purpose computer provided by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the control unit and the method described in the present disclosure may be implemented by one or more special-purpose computers configured by a combination of a processor and a memory programmed to execute one or more functions and a processor configured with one or more hardware logic circuits. The computer program may also be stored in a computer-readable non-transitory tangible recording medium as instructions executed by the computer. [Explanation of symbols]

[0081] 10. Detection section 20 Resonance section 30 Control section 140 Drill (Tool) 200 Work material

Claims

1. 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 portion (20) that resonates with wear sound waves generated by the tool being worn to generate a resonance sound wave, The detection unit also detects resonance sound waves from the resonance unit, the control unit compares an intensity of a determination signal based on the sound waves detected by the detection unit with a wear threshold, and determines that wear is occurring on 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 a plurality of resonating parts are provided, each with a different natural vibration frequency, and each of the natural vibration frequencies is included in the range of the wear sound waves that can be generated depending on the condition of the workpiece.

2. 2. The tool abnormality detection system according to 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 lower than a damage threshold which is lower than the wear threshold, and determines that the tool is damaged when the intensity of the determination signal is equal to or lower than the damage threshold.

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