Wear determination device

Abstract

To improve determination accuracy of a wear state of a rotary tool.SOLUTION: A wear determination device 6 for a tap 7 which is a rotary tool for machining a workpiece 2 includes an acquisition part 23 for acquiring machining waveform data related to a time-series waveform of a parameter related to an operation state of a spindle motor 8a for rotationally driving the rotary tool for each machining, an averaging part 24 for calculating an average value of each machining waveform data, a variance calculation part 25 for calculating variance of the average value for each predetermined number of machinings, a regression part 26 for calculating cubic curve information obtained by regressing time-series distribution information of the variance with a cubic curve, a differentiation part 27 for differentiating the cubic curve information to calculate quadratic curve information, and a determination part 28 for determining a wear state of the rotary tool by using presence or absence of a local minimum value of the quadratic curve information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a wear determination device. [Background technology]

[0002] For example, a workpiece is machined using a rotary tool such as a tap. For example, Patent Document 1 describes a method for determining the lifespan of a rotary tool by calculating an increase in power consumption of a motor that drives the rotary tool. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6864394 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when measuring parameters such as power consumption of a rotary tool, the measurement results may be affected by noise, etc. Using measurement results affected by noise, etc., may lead to erroneous determination. Therefore, there is room for improving the accuracy of determining the wear state of a rotary tool.

[0005] In view of the above-mentioned problems, an object of the present invention is to provide a wear determining device that can improve the accuracy of determining the wear state of a rotary tool. [Means for solving the problem]

[0006] In order to solve the above problems, the wear determination device of the present invention is a wear determination device for a rotary tool that processes a workpiece, and includes an acquisition unit that acquires, for each machining operation, machining waveform data relating to time-series waveforms during machining of parameters related to the operating state of a rotary motor that rotates the rotary tool, an averaging unit that calculates the average value of each of the machining waveform data, a dispersion unit that calculates the variance of the average value for each predetermined number of machining operations, a regression unit that calculates cubic curve information by regressing the time-series distribution information of the variance with a cubic curve, a differentiation unit that differentiates the cubic curve information to calculate quadratic curve information, and a determination unit that determines the wear state of the rotary tool using the presence or absence of a minimum value in the quadratic curve information.

[0007] In addition, in the wear determination device, the determination unit determines the wear state of the rotating tool based on the minimum value of the quadratic curve information, a first value which is the value of the quadratic curve information corresponding to the first variance, and a second value which is the value of the quadratic curve information corresponding to the last variance.

[0008] In the wear determination device, the determination unit determines that the rotary tool is in an abnormal wear state when the minimum value exists in the quadratic curve information and the second value is equal to or greater than the first value.

[0009] The wear determination device further includes a state acquisition unit that acquires first waveform data, which is time-series waveform data of the parameters of the rotary motor, and second waveform data, which is time-series waveform data of the rotational speed of a feed motor that provides feed to the rotary tool in response to the operation of the rotary motor; an identification unit that identifies a location in the second waveform data where the rotational speed is within a predetermined range and the time width is equal to or greater than a predetermined value, and sets the first waveform data corresponding to that location as partial waveform data; and an extraction unit that extracts, from the partial waveform data, a location where the workpiece is being machined by the rotary tool based on a start point or an end point, as the machining waveform data.

[0010] The wear determination device further includes a correction unit that corrects the machining waveform data by taking the point in the partial waveform data where the rotary tool is in an air-cut state based on the start point or the end point as air-cut waveform data and subtracting the average value of the air-cut waveform data from the machining waveform data. [Effects of the Invention]

[0011] According to the wear determining device of the present invention, it is possible to improve the accuracy of determining the wear state of a rotary tool. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a schematic diagram showing an example of the overall configuration of a machining system including a wear determination device according to an embodiment of the present invention. [Figure 2] 10A and 10B are diagrams showing an example of first waveform data relating to a spindle torque and second waveform data relating to a feed shaft rotation speed. [Figure 3] FIG. 10 is a diagram illustrating an example of the relationship between processing numbers and dispersions. [Figure 4] FIG. 10 is a diagram showing an example of a quadratic curve when machining is performed until the beginning of steady wear. [Figure 5] FIG. 10 is a diagram showing an example of a quadratic curve when machining is performed until the later stage of steady wear. [Figure 6] FIG. 10 is a diagram showing an example of a quadratic curve when machining is performed until abnormal wear occurs. [Figure 7] 10 is a flowchart showing an example of the flow of a wear state determination process. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. To facilitate understanding of the description, the same components in the drawings will be denoted by the same reference numerals as much as possible, and duplicate descriptions will be omitted where appropriate.

[0014] === Implementation form === <Overall structure> 1 is a schematic diagram showing an example of the overall configuration of a machining system 1 including a wear determination device 6 according to this embodiment. The machining system 1 performs machining on a workpiece 2.

[0015] As shown in FIG. 1, the processing system 1 includes a processing machine 4, a measuring instrument 5, and a wear determination device 6 as main components.

[0016] The processing machine 4 is equipped with a tap 7 as a rotary tool. The tap 7 is a type of processing tool that drills a thread into the inside of a hole in the workpiece 2. The processing machine 4 is a device that controls the rotation and feed (movement of the tap 7) of the tap 7. The processing machine 4 is equipped with a spindle motor 8a, which is a rotation motor that rotates the tap 7, and a feed motor that provides feed. The spindle motor 8a rotates the tap 7, and in synchronization with this, the feed motor 8b rotates and feeds the tap 7, thereby drilling the workpiece 2. For example, the processing machine 4 drills a thread into the workpiece 2 by rotating the tap 7 forward and providing a feed. The processing machine 4 then unscrews the tap 7 from the workpiece 2 by rotating the tap 7 backward and providing a feed in the opposite direction. The spindle motor 8a and feed motor 8b operate in correspondence with each other to perform the desired processing operations.

[0017] The measuring instrument 5 measures parameters related to the operating states of the spindle motor 8a and the feed shaft motor 8b. In this embodiment, the torque in the spindle motor 8a is referred to as the "spindle torque," and the current flowing through the spindle motor 8a is referred to as the "spindle current." Therefore, the spindle torque is correlated with the spindle current. Also, in this embodiment, the rotation speed of the feed shaft motor 8b is referred to as the "feed shaft rotation speed." The measuring instrument 5 has a first measuring unit 5a and a second measuring unit 5b. The first measuring unit 5a measures the spindle torque, and the second measuring unit 5b measures the feed shaft rotation speed.

[0018] The wear determination device 6 is an information processing device that determines the wear state of the rotary tool that machines the workpiece 2. Note that each process by the wear determination device 6 may be performed using AI (machine learning) or according to a preset program. The wear determination device 6 includes, for example, a control device, a communication device, a storage device, an operation device, and a display device. The control device is mainly configured with a CPU (Central Processing Unit) and a memory. The control device functions as various functional components described below by the CPU executing a predetermined program stored in the memory or storage device. The communication device includes a communication interface for communicating with external devices. The storage device includes a hard disk or the like, and stores various programs and information required to execute the processes in the control device, as well as information on the processing results. The operation device is a device for operating the wear determination device 6, such as a keyboard, mouse, or touch panel. The display device is a device for displaying various information and processing results, such as a display or touch panel. Note that the wear determination device 6 may be configured with a single information processing device or multiple information processing devices. Furthermore, the wear determining device 6 may have other configurations. The wear determining device 6 may be configured using a CPU unit or a computing unit such as a PC or PLC.

[0019] <Functional configuration> 1 shows an example of various functions of the wear determination device 6. The wear determination device 6 includes a cutting unit 21, a counting unit 22, an acquisition unit 23, an averaging unit 24, a dispersion unit 25, a regression unit 26, a differentiation unit 27, a determination unit 28, and a display unit 29.

[0020] The cutout unit 21 processes the time-series waveform of the spindle torque, and cuts out the waveform when the tap 7 is cutting the workpiece 2 as the cutting waveform data C1. "During cutting" means the state when the tap 7 is performing a cutting process on the workpiece 2. In other words, the state when the tap 7 is cutting the internal thread of the workpiece 2 is "during cutting." The cutout unit 21 cuts out waveforms corresponding to operations (non-cutting operations) that are not actually cutting the workpiece 2 from the time-series waveform of the spindle torque, and cuts out the waveform during cutting as the cutting waveform data C1. Non-cutting operations include, for example, an operation of moving the tap 7 to a predetermined position, a standby operation between cuts, an operation in an air cut state, etc.

[0021] The cutout unit 21 includes a state acquisition unit 31, a specification unit 32, an excerpt unit 33, and a correction unit .

[0022] The status acquisition unit 31 acquires first waveform data A1, which is time-series waveform data of the spindle torque. The status acquisition unit 31 also acquires second waveform data A2, which is time-series waveform data of the feed shaft rotation speed corresponding to the operation of the spindle motor 8a. Specifically, the status acquisition unit 31 acquires the time-series waveform of the spindle torque from the first measurement unit 5a and sets it as the first waveform data A1, and acquires the time-series waveform of the feed shaft rotation speed from the second measurement unit 5b and sets it as the second waveform data A2. For example, the status acquisition unit 31 A / D converts (analog-to-digital converts) the analog data from the measurement instrument 5 to digital data.

[0023] FIG. 2 shows an example of first waveform data A1 relating to spindle torque and second waveform data A2 relating to feed axis rotation speed. In FIG. 2, the horizontal axis represents time, and the vertical axis represents spindle torque and feed axis rotation speed. FIG. 2 also shows an example of parameters corresponding to one machining operation. For example, when the feed axis rotation speed is negative, the tap 7 is fed toward the workpiece 2; when it is zero, the feed stops; and when it is positive, the tap 7 is fed away from the workpiece 2. Specifically, after time T1 has elapsed, the tap 7 begins to rotate forward when the rotation speed of the feed axis motor 8b reaches its deceleration extreme, and the spindle torque increases accordingly. At time T2, the tap 7 enters an air-cut state, and the spindle torque approaches zero. At the same time, a constant feed (feed of the tap 7 toward the workpiece 2) is applied to the tap 7. At time T3, the tap 7 begins to contact the workpiece 2, and the spindle torque increases accordingly, resulting in female thread machining. After time T4 has elapsed, the forward rotation of the tap 7 is decelerated and the feed speed is also decelerated. Furthermore, the feed axis rotation speed is 0 and the feed of the tap 7 stops. After this, the tap 7 rotates in the reverse direction and is fed in the opposite direction, and is removed from the workpiece 2. In this way, the first waveform data A1 and the second waveform data A2 include each state associated with machining by the tap 7. The spindle motor 8a and the feed axis motor 8b operate in conjunction (synchronization) with each other.

[0024] Returning to FIG. 1 , the identifying unit 32 identifies a portion of the second waveform data A2 where the feed shaft rotation speed is within a predetermined range and the time width is equal to or greater than a predetermined value, and designates the first waveform data A1 corresponding to that portion of the second waveform data A2 as partial waveform data B1. The predetermined range is preset as a lower limit R1 and an upper limit R2 of the feed shaft rotation speed when machining the workpiece 2 with the tap 7. For example, the predetermined range is preset as the feed shaft rotation speed (e.g., lower limit R1) immediately before the tap 7 starts rotating in the forward direction and the feed shaft rotation speed (e.g., upper limit R2) when the tap 7 is stopped to transition from forward rotation to reverse rotation. The predetermined value of the time width is preset to be equal to or greater than the desired forward rotation machining time. The forward rotation machining time is the time it takes for the tap 7 to machine the workpiece 2 (to machine a female thread) while rotating in the forward direction.

[0025] Specifically, the specifying unit 32 specifies a location where the feed shaft rotation speed is within a predetermined range by referring to the second waveform data A2. If the time width of the location is equal to or greater than a predetermined value, the specifying unit 32 specifies a portion of the first waveform data A1 that corresponds to the location in the second waveform data A2 and sets the portion as partial waveform data B1. As a result, the state of the spindle torque, including each operation when the tap 7 performs machining in the forward direction, is specified as partial waveform data B1.

[0026] The extracting unit 33 extracts a portion of the partial waveform data B1 where the workpiece 2 is being machined by the tap 7 as machining waveform data C1, using the start point or end point as a reference. In this embodiment, the case where the start point is used as a reference will be described as an example. Specifically, as shown in FIG. 2, the extracting unit 33 sets the start point of the partial waveform data B1 as 0% and the end point as 100%. In other words, the entire time width of the partial waveform data B1 is set as 100%. The extracting unit 33 then sets the range from 55% to 85% (30%) of the partial waveform data B1 as the net machining portion (net forward machining portion). The net machining portion is the waveform of the spindle torque when the tap 7, rotating forward, is performing a machining process on the workpiece 2 (during female thread machining). The extracting unit 33 sets this net machining portion (55% to 85%) as machining waveform data C1. Note that 55% and 85% are just examples, and specific values ​​can be set appropriately according to the machining operation to be executed.

[0027] Furthermore, the extracting unit 33 sets the range from 25% to 45% (20%) in the partial waveform data B1 as the air cut portion. The air cut portion is the portion where the tap 7 is rotating without touching other components (air cut state) before the tap 7 is brought into contact with the workpiece 2. The extracting unit 33 sets this air cut portion (25% to 45%) as the air cut waveform data D1. Note that 25% and 45% are just examples, and specific values ​​can be set appropriately according to the machining operation to be executed.

[0028] In this way, the extracting unit 33 truncates the partial waveform data B1 from the start point (0%) to 25%, sets the portion from 25% to 45% (20%) as air-cut waveform data D1, and truncates the portion from 45% to 55% (10%). Furthermore, the extracting unit 33 sets the portion from 55% to 85% (30%) of the partial waveform data B1 as processed waveform data C1, and truncates the portion from 85% to the end point (100%) (15%). The positions (ranges) of the processed waveform data C1 and the air-cut waveform data D1 in the partial waveform data B1 can be set appropriately according to the processing operation to be executed.

[0029] The correction unit 34 performs correction on the machining waveform data C1. The air-cut waveform data D1 indicates the base state of the spindle torque in the rotating state. Therefore, the correction unit 34 calculates the average value of the air-cut waveform data D1 and subtracts it from the machining waveform data C1. As a result, the base state is removed from the machining waveform data C1.

[0030] The clipping unit 21 clips the processed waveform data C1 from the first waveform data A1 as described above. By acquiring the first waveform data A1 in time series, the first waveform data A1 becomes data including multiple processing operations. For example, the first waveform data A1 becomes data including multiple waveforms (corresponding to one processing operation) as shown in FIG. 2. Therefore, the clipping unit 21 clips the processed waveform data C1 corresponding to each processing operation. Note that the method for clipping the processed waveform data C1 from the first waveform data A1 is not limited to the above.

[0031] The counting unit 22 counts the number of machining operations, which is the number of times that machining has been performed on the workpiece 2 by the tap 7. For example, the counting unit 22 counts each time the cutting unit 21 cuts out the machining waveform data C1. In other words, the number of machining operations (count value) counted by the counting unit 22 becomes the machining number. The count value of the counting unit 22 is reset to an initial value, for example, when the tap 7 is replaced.

[0032] The acquisition unit 23 acquires machining waveform data C1 relating to a time-series waveform of the spindle torque during machining. Specifically, the acquisition unit 23 acquires the machining waveform data C1 from the clipping unit 21 and acquires the machining number from the counting unit 22. The acquisition unit 23 acquires the machining waveform data C1 for each machining by the tap 7 and associates it with the machining number. In this embodiment, the acquisition unit 23 acquires the machining waveform data C1 corrected by the correction unit 34.

[0033] The averaging unit 24 calculates the average value of each piece of machining waveform data C1. This provides the average value of the spindle torque involved in machining the workpiece 2 with the tap 7. By calculating the average value corresponding to each piece of machining waveform data C1, the average value of the spindle torque during machining for each machining is obtained and associated with the machining number. For example, the average value and the machining number are associated with each other and recorded as history information in a storage device.

[0034] The dispersion unit 25 calculates the dispersion of the average value for each predetermined number of processes. The number of processes is set in advance to, for example, 10 times. The dispersion unit 25 calculates the dispersion for the average value for 10 processes (every 10 processes). Specifically, the dispersion is calculated for the average value of 10 consecutive process numbers. The calculated dispersion is recorded in the history information.

[0035] Figure 3 shows an example of the relationship between the machining number and the variance. In Figure 3, the horizontal axis represents the machining number and the vertical axis represents the variance (variance value). In Figure 3, the variance is calculated for every 10 machining operations and plotted as a distribution K1. As shown in Figure 3, the wear state of the tap 7 progresses as it undergoes multiple machining operations. The wear state progresses in the order of initial wear, steady wear, and abnormal wear. In the example shown in Figure 3, period W1 corresponds to the initial wear state, period W2 corresponds to the steady wear state, and period W3 corresponds to the abnormal wear state. The initial wear state is a wear state that occurs in the early stages of use of the tap 7. The steady wear state is a wear state that progresses after the initial wear state as the tap 7 is used. The initial wear state and steady wear state are wear states of the tap 7 that are acceptable for use. The abnormal wear state is a wear state that progresses after the steady wear state as the tap 7 is used. The abnormal wear state is an abnormal wear state in which the wear of the tap 7 has progressed significantly, which may result in machining defects or damage to the workpiece 2 or the tap 7. In other words, the abnormal wear state is a wear state of the tap 7 that is not permitted for use.

[0036] The regression unit 26 calculates cubic curve information by regressing the time-series distribution information of variance with a cubic curve L1. The time-series distribution information of variance is, for example, the information of the distribution K1 in FIG. 3. The cubic curve information is information in which the cubic curve L1 is represented, for example, a cubic function (regression curve). Note that the cubic curve information is not limited to the above as long as it is information in which the cubic curve L1 is represented, and table information or the like may also be used. In the example of FIG. 3, the regression unit 26 performs regression processing on the variance distribution K1 to calculate the cubic curve L1. The cubic curve L1 is calculated within the range of the variance distribution K1 (the range of processing numbers).

[0037] The differentiation unit 27 differentiates the cubic curve information to calculate quadratic curve information. The quadratic curve information is information that indicates a quadratic curve L2, such as a quadratic function (parabola). Note that the quadratic curve information is not limited to the above as long as it indicates the quadratic curve L2, and table information or the like may also be used. The differentiation unit 27 differentiates the cubic curve L1 calculated by the regression unit 26 to calculate the quadratic curve L2. The quadratic curve L2 is calculated within the range of the variance distribution K1.

[0038] The determination unit 28 determines the wear state of the tap 7 based on the presence or absence of a minimum value in the quadratic curve information. Specifically, the determination unit 28 determines the wear state of the tap 7 based on the minimum value in the quadratic curve information, a first value S1 which is the value of the quadratic curve information corresponding to the first variance, and a second value S2 which is the value of the quadratic curve information corresponding to the last variance. The minimum value is the minimum value in the quadratic curve L2 calculated by the differentiation unit 27. The first variance is the variance calculated using the first average value of the processing number in the variance distribution K1. The value of the quadratic curve information corresponding to the first variance (first value S1) is the value of the quadratic curve L2 corresponding to the processing number of the first variance. In other words, the first value S1 can also be said to be the maximum value in the range in which the processing number in the quadratic curve L2 is smaller than the minimum value. The last variance is the variance calculated using the last (latest) average value of the processing number in the variance distribution K1. The value of the quadratic curve information corresponding to the last variance (second value S2) is the value of the quadratic curve L2 corresponding to the processing number of the last variance. In other words, the second value S2 can be said to be the maximum value in the range in which the processing number on the quadratic curve L2 is greater than the minimum value.

[0039] Specifically, the determination unit 28 determines that the tap 7 is in an abnormally worn state if a minimum value exists in the quadratic curve information and the second value S2 is equal to or greater than the first value S1. That is, the determination unit 28 first determines whether a minimum value exists in the quadratic curve L2. If a minimum value exists in the quadratic curve L2, the determination unit 28 compares the first value S1 and the second value S2 in the quadratic curve L2 to determine whether the second value S2 is equal to or greater than the first value S1. If the second value S2 is equal to or greater than the first value S1, the determination unit 28 determines that the tap 7 is in an abnormally worn state. Note that if a minimum value does not exist in the quadratic curve L2 (if a maximum value exists), the determination unit 28 determines that the tap 7 is not in an abnormally worn state. Furthermore, even if a minimum value exists in the quadratic curve L2, the determination unit 28 determines that the tap 7 is not in an abnormally worn state if the second value S2 is not equal to or greater than the first value S1.

[0040] FIG. 4 shows the cubic curve L1 and quadratic curve L2 obtained when machining is performed up to the initial stage of steady wear in FIG. 3. FIG. 4 shows the cubic curve L1 obtained by performing regression processing on the variance distribution K1 obtained up to the period Q1 in FIG. 3, and the quadratic curve L2 obtained by performing differentiation processing on the cubic curve L1. In the example of FIG. 4, the quadratic curve L2 does not have a minimum value. Therefore, the judgment unit 28 judges that the tap 7 is not in a state of abnormal wear.

[0041] Fig. 5 is a diagram showing a cubic curve L1 and a quadratic curve L2 obtained when machining is performed up to the later stage of steady wear (before abnormal wear) in Fig. 3. Fig. 5 shows a cubic curve L1 obtained by performing a regression process on the variance distribution K1 obtained up to period Q2 in Fig. 3, and a quadratic curve L2 obtained by performing a differentiation process on the cubic curve L1. In the example of Fig. 5, a minimum value exists on the quadratic curve L2 at position P1, but because the second value S2 is less than the first value S1, the determination unit 28 determines that the tap 7 is not in a state of abnormal wear.

[0042] Fig. 6 is a diagram showing a cubic curve L1 and a quadratic curve L2 obtained when machining is continued until abnormal wear occurs in Fig. 3. Fig. 6 shows a cubic curve L1 obtained by performing a regression process on the variance distribution K1 obtained up to the period Q3 in Fig. 3, and a quadratic curve L2 obtained by performing a differentiation process on the cubic curve L1. In the example of Fig. 6, the quadratic curve L2 has a minimum value at position P2, and the second value S2 is equal to or greater than the first value S1, so the determination unit 28 determines that the tap 7 is in a state of abnormal wear.

[0043] In this way, the determining unit 28 determines the wear state of the tap 7. The determination result is recorded in the history information.

[0044] Furthermore, when a minimum value exists in the quadratic curve L2 and the first value S1 becomes equal to the second value S2, the determination unit 28 may determine that the timing at which the first value S1 becomes equal to the second value S2 is the start point of abnormal wear. The timing at which the first value S1 becomes equal to the second value S2 is, for example, the last (latest) processing number in the distribution K1. The start point (processing number) of abnormal wear may be determined using the timing at which the first value S1 becomes equal to the second value S2.

[0045] In the above example, the determination unit 28 determines the wear state using the minimum value, the first value S1, and the second value S2, but the wear state may also be determined based on the presence or absence of a minimum value. For example, if there is a minimum value on the quadratic curve L2, the determination unit 28 determines that the state is abnormal wear or a state close to abnormal wear (from the middle stage of the steady wear state onwards).

[0046] The display unit 29 displays various information processed by the wear determination device 6 on a display device or the like. In particular, the display unit 29 displays the determination result of the wear state of the tap 7 (whether or not there is an abnormal wear state). The user can recognize the current wear state of the tap 7 by checking the display of the determination result.

[0047] <Processing flow> 7 is a flowchart showing an example of the flow of the wear state determination process according to this embodiment. The processes in the following steps are started when a user issues a command to start the process after a new tap 7 is installed, for example, after replacing the tap 7. Note that the order and content of the following steps can be changed as appropriate.

[0048] (Step SP10) The counting section 22 initializes the count value indicating the processing number, that is, the count value becomes 0. Then, the process proceeds to step SP11.

[0049] (Step SP11) The cutout unit 21 acquires the first waveform data A1 of the spindle torque and the second waveform data A2 of the feed shaft rotation speed, and cuts out the machining waveform data C1, which is the net machining location in the first waveform data A1, using the second waveform data A2. The machining waveform data C1 is corrected using the air-cut waveform data D1. Then, the process proceeds to step SP12.

[0050] (Step SP12) The counting section 22 counts up the count value. That is, the counting section 22 adds 1 to the count value. Then, the process proceeds to step SP13.

[0051] (Step SP13) The averaging unit 24 calculates the average value of the processed waveform data C1. The average value is stored in association with the processing number (count value). Then, the process proceeds to step SP14.

[0052] (Step SP14) The dispersion unit 25 calculates the dispersion using the average value of 10 processes. When the number of average values ​​of the most recent processes not used in the variance calculation process reaches 10 processes, the dispersion unit 25 calculates the dispersion using the average value of the 10 processes. When the number of average values ​​of the most recent processes not used in the variance calculation process is less than 10 processes, the dispersion unit 25 does not calculate the variance. Then, the process proceeds to step SP15.

[0053] (Step SP15) The regression unit 26 performs regression processing on the calculated variance distribution K1 to calculate a cubic curve L1 (cubic curve information), and then the process proceeds to step SP16.

[0054] (Step SP16) The differentiating section 27 differentiates the cubic curve L1 to calculate a quadratic curve L2 (quadratic curve information), and the process then proceeds to step SP17.

[0055] (Step SP17) The determining unit 28 determines the wear state of the tap 7 using the quadratic curve L2. Then, the process proceeds to step SP18.

[0056] (Step SP18) The display unit 29 displays the determination result of the wear state of the tap 7. Then, the process proceeds to step SP19.

[0057] (Step SP19) The determination unit 28 determines whether or not there is a next processing. Whether or not there is a next processing can be set by the user, for example. Also, for example, the user who has checked the display may be able to select whether to continue or end. If there is a next processing, the process returns to step SP11 and repeats the process. If there is no next processing, the process ends.

[0058] By executing the process as described above, the wear state is determined in accordance with the machining of the tap 7. Since the wear state is determined in accordance with the machining, the user can check the determination result in real time as the machining progresses. For example, if the wear state is determined to be abnormal wear, the user can stop the device. Note that if the wear determination device 6 determines that the wear state is abnormal wear, machining by the tap 7 may be stopped.

[0059] <Action and effect> As described above, in this embodiment, the wear determination device 6 is a wear determination device 6 for a tap 7 that processes a workpiece 2, and includes an acquisition unit 23 that acquires, for each machining, machining waveform data C1 related to the time series waveform during machining of a parameter (spindle torque) related to the operating state of the spindle motor 8a that rotates and drives the tap 7, an averaging unit 24 that calculates the average value of each of the machining waveform data C1, a dispersion unit 25 that calculates the variance of the average value for each predetermined number of machining operations, a regression unit 26 that calculates cubic curve information by regressing the time series distribution information of the variance with a cubic curve L1, a differentiation unit 27 that differentiates the cubic curve information to calculate quadratic curve information, and a determination unit 28 that determines the wear state of the tap 7 using the presence or absence of a minimum value in the quadratic curve information.

[0060] According to this configuration, the variance of the average value of the machining waveform data C1, which is a time-series waveform during machining, is regressed on a cubic curve L1, and the wear state of the tap 7 is determined using the minimum value of a quadratic curve L2 obtained by differentiating the cubic curve L1. Because the quadratic curve L2 is calculated using the variance of the average values ​​of the machining waveform data C1 relating to multiple machining processes, the wear state can be determined while suppressing the influence of variations due to the influence of noise on each average value. In other words, the accuracy of determining the wear state can be improved. Depending on the determination result of the wear state of the tap 7, it is possible to stop the device early and perform tool replacement, etc. This makes it possible to avoid work loss.

[0061] Furthermore, in the wear determination device 6 according to this embodiment, the determination unit 28 determines the wear state of the tap 7 based on the minimum value of the quadratic curve information, a first value S1 which is the value of the quadratic curve information corresponding to the first variance, and a second value S2 which is the value of the quadratic curve information corresponding to the last variance.

[0062] According to this configuration, by using the minimum value, the first value S1, and the second value S2, it is possible to accurately determine whether the tap 7 is in an abnormal wear state.

[0063] Furthermore, in the wear determination device 6 according to this embodiment, the determination unit 28 determines that the tap 7 is in a state of abnormal wear when a minimum value exists in the quadratic curve information and the second value S2 is greater than or equal to the first value S1.

[0064] According to this configuration, by using the case where the minimum value exists and the second value S2 is equal to or greater than the first value S1 as a reference, it becomes possible to accurately determine whether the tap 7 is in an abnormal wear state.

[0065] In addition, the wear determination device 6 according to this embodiment further includes a state acquisition unit 31 that acquires first waveform data A1, which is time-series waveform data of the parameters of the spindle motor 8a, and second waveform data A2, which is time-series waveform data of the rotation speed of the feed shaft motor 8b that provides feed to the tap 7 in response to the operation of the spindle motor 8a; an identification unit 32 that identifies a location in the second waveform data A2 where the rotation speed is within a predetermined range and the time width is equal to or greater than a predetermined value, and sets the first waveform data A1 corresponding to that location as partial waveform data B1; and an extraction unit 33 that extracts a location in the partial waveform data B1 where the workpiece 2 is being machined by the tap 7 based on the start point or end point as machining waveform data C1.

[0066] According to this configuration, the machining waveform data C1 in the first waveform data A1 related to the spindle motor 8a is identified using the second waveform data A2 indicating the rotation speed of the feed shaft motor 8b. As a result, the second waveform data A2 is less affected by noise, making it possible to accurately extract the machining waveform data C1.

[0067] In addition, the wear determination device 6 according to this embodiment further includes a correction unit 34 that corrects the processed waveform data C1 by subtracting the average value of the air cut waveform data D1 from the partial waveform data B1, which is the point where the tap 7 is in an air cut state based on the start point or end point.

[0068] According to this configuration, by correcting the machining waveform data C1 using the air-cut waveform data D1, the base component of the air-cut state before machining can be suppressed from the machining waveform data C1. In other words, the corrected machining waveform data C1 more accurately indicates the state change of the spindle motor 8a related to machining.

[0069] <Modification> The present invention is not limited to the above-described embodiments. In other words, designs that are produced by those skilled in the art with appropriate design modifications to the above-described specific examples are also included within the scope of the present invention as long as they include the features of the present invention. Furthermore, the elements of the above-described embodiments and the following modifications can be combined to the extent technically possible, and such combinations are also included within the scope of the present invention as long as they include the features of the present invention.

[0070] For example, in the above embodiment, the case where the tap 7 is used as the rotary tool has been described as an example, but the rotary tool is not limited to the tap 7 as long as it is a tool that rotates during processing. For example, a drill or the like may be used as the rotary tool.

[0071] Furthermore, in the above embodiment, the case where the torque of the spindle motor 8a is used as the parameter relating to the operating state of the spindle motor 8a has been described as an example, but the parameter is not limited to the above as long as it indicates the operating state of the spindle motor 8a. For example, the parameter relating to the operating state of the spindle motor 8a may be the spindle current. Note that the spindle current has a correlation with the spindle torque. Furthermore, the parameter relating to the operating state of the spindle motor 8a may be the voltage or power consumption.

[0072] Furthermore, in the above embodiment, the clipping unit 21 corrects the processed waveform data C1 using the air-cut waveform data D1, but the correction process may be omitted.

[0073] Furthermore, in the above embodiment, the determination unit 28 determines the wear state. However, the determination unit 28 may perform the determination process when the processing number is equal to or greater than a threshold value. In other words, the determination process is not executed when the processing number is less than the threshold value. The threshold value is set in advance as, for example, a processing number corresponding to the later stage of the steady wear state. This prevents, for example, a case in which a minimum value exists in the quadratic curve L2 due to the influence of noise or the like in the initial wear state, causing the second value S2 to be equal to or greater than the first value S1, resulting in an erroneous determination that the state is abnormally worn. [Explanation of symbols]

[0074] 2: Work 6: Wear detection device 7: Tap (rotary tool) 8a: Main shaft motor (rotation motor) 8b: Feed shaft motor 23: Acquisition part 24: Average part 25: Dispersion section 26: Return section 27: Differential part 28: Judgment section C1: Processed waveform data K1: Distribution (time series distribution information of variance) L1: Cubic curve (cubic curve information) L2: Quadratic curve (quadratic curve information)

Claims

1. A wear determination device for a rotary tool used to machine a workpiece, comprising: an acquisition unit that acquires, for each machining operation, machining waveform data relating to a time-series waveform during machining of a parameter relating to an operating state of a rotary motor that rotationally drives the rotary tool; an averaging unit that calculates an average value of each of the processed waveform data; a variance unit that calculates the variance of the average value for each predetermined number of processing operations; a regression unit that calculates cubic curve information by regressing the time series distribution information of the variance with a cubic curve; a differentiation unit that differentiates the cubic curve information to calculate quadratic curve information; a determination unit that determines a wear state of the rotary tool based on the presence or absence of a minimum value of the quadratic curve information; A wear determination device comprising:

2. the determination unit determines the wear state of the rotary tool based on the minimum value of the quadratic curve information, a first value which is a value of the quadratic curve information corresponding to the first variance, and a second value which is a value of the quadratic curve information corresponding to the last variance. The wear determination device according to claim 1 .

3. the determination unit determines that the rotary tool is in an abnormal wear state when the local minimum value exists in the quadratic curve information and the second value is equal to or greater than the first value. The wear determination device according to claim 2 .

4. a state acquisition unit that acquires first waveform data, which is time-series waveform data of the parameters of the rotary motor, and second waveform data, which is time-series waveform data of the rotation speed of a feed motor that provides feed to the rotary tool in response to an operation of the rotary motor; an identifying unit that identifies a portion in the second waveform data where the rotation speed is within a predetermined range and the time width is equal to or greater than a predetermined value, and sets the first waveform data corresponding to the identified portion as partial waveform data; an extracting unit that extracts, from the partial waveform data, a portion where the workpiece is being machined by the rotary tool based on a start point or an end point as the machining waveform data; The wear determination device according to claim 1 , further comprising:

5. a correction unit that corrects the machining waveform data by using a portion in the partial waveform data where the rotary tool is in an air-cut state with the start point or the end point as a reference as air-cut waveform data and subtracting an average value of the air-cut waveform data from the machining waveform data; The wear determination device according to claim 4, further comprising:

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