Wear determination device

Abstract

To enhance determination accuracy of a wear state of a rotary tool.SOLUTION: A wear determination device 6 for a tap 7 that machines a workpiece 2 includes: an acquisition unit that acquires a plurality of pieces of machining waveform data indicating a time-series waveform during machining of a spindle current of a motor that drives the tap 7; a regression unit that calculates cubic curve information by regressing a time-series distribution based on each piece of the machining waveform data; a differentiation unit that calculates quadratic curve information by differentiating the cubic curve information; and a determination unit that determines the wear state of the tap 7 on the basis of the presence or absence of the 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 Art

[0002] For example, a workpiece is processed using a rotary tool such as a tap. For example, Patent Document 1 describes calculating an increase in power consumption of an electric motor that drives a rotary tool to determine the lifespan.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, when processing is performed using a rotary tool, operations that do not actually perform processing on the workpiece (non-processing operations) are included, such as the operation of moving the rotary tool to a predetermined position and the standby operation between processes. For example, the increase in power consumption in Patent Document 1 may include the power consumption generated by such non-processing operations, which may affect the accuracy of lifespan determination. Therefore, there is room for improving the accuracy of determining the wear state of the rotary tool.

[0005] In view of the above problems, an object of the present invention is to provide a wear determination device capable of improving the accuracy of determining the wear state of a rotary tool.

Means for Solving the Problems

[0006] In order to solve the above problems, a wear determination device according to the present invention is a wear determination device for a rotary tool that processes a workpiece, and includes an acquisition unit that acquires a plurality of pieces of machining waveform data in which a time-series waveform during machining of a parameter related to the operating state of a motor that drives the rotary tool is shown, a regression unit that calculates curve information of the third order or higher by regressing the time-series distribution based on each of the machining waveform data, a differentiation unit that calculates quadratic curve information by differentiating the curve information, and a determination unit that determines the wear state of the rotary tool based on the presence or absence of a minimum value of the quadratic curve information.

[0007] Further, in the wear determination device, when there is a minimum value of the quadratic curve information, the determination unit determines that the rotary tool is in an abnormal wear state.

[0008] Further, in the wear determination device, when there is a maximum value in the quadratic curve information, or when there is no extreme value in the quadratic curve information, the determination unit determines that the rotary tool is not in an abnormal wear state.

[0009] Further, in the wear determination device, when the minimum value of the quadratic curve information changes from a state where it does not exist to a state where it exists, the determination unit determines that the rotary tool has changed to an abnormal wear state.

[0010] Further, in the wear determination device, the rotary tool is a tap.

Advantages of the Invention

[0011] According to the wear determination device of the present invention, the determination accuracy of the wear state of the rotary tool can be improved.

Brief Description of the Drawings

[0012]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Embodiments for Carrying Out the Invention

[0013] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. For ease of understanding of the description, the same reference numerals are used for the same components in each drawing as much as possible, and overlapping descriptions are omitted as appropriate.

[0014] ===Embodiment=== <Overall Configuration> FIG. 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 the present embodiment. The machining system 1 performs machining on a workpiece 2.

[0015] As shown in FIG. 1, the machining system 1 mainly includes a machine tool 4, a measuring instrument 5, and a wear determination device 6.

[0016] The machine tool 4 is provided with a tap 7 as a rotary tool. The tap 7 is a type of machining tool and is a tool for machining a screw inside a hole of the workpiece 2. For example, by rotating the tap 7 forward and applying feed, a screw is machined on the workpiece 2, and by rotating it backward and applying feed in the opposite direction, the tap 7 is removed from the workpiece 2.

[0017] The processing machine 4 is a device that controls the rotation and feed of the tap 7. By controlling the processing machine 4, desired processing is performed on the workpiece 2 using the tap 7. The processing machine 4 is provided with a motor 8 that rotationally drives the tap 7 and a feed motor (not shown) that provides the feed. The tap 7 is rotated by the motor 8, and in synchronization therewith, the feed motor is rotated to provide the feed, thereby processing the workpiece 2.

[0018] The measuring instrument 5 measures parameters related to the operating states of the motor 8 and the feed motor. In the present embodiment, the measuring instrument 5 measures the currents in the motor 8 and the feed motor of the processing machine 4. That is, the measuring instrument 5 measures the currents flowing through the motor 8 and the feed motor as the tap 7 is driven. The current flowing through the motor 8 is referred to as the "main spindle current". The current flowing through the feed motor is referred to as the "feed axis current". Hereinafter, unless otherwise specified, the term "current" shall refer to the main spindle current.

[0019] The wear determination device 6 is an information processing device that determines the wear state of a rotary tool for machining a workpiece 2. The wear determination device 6 includes, for example, a control device 20, a communication device 21, a storage device 22, an operation device 23, and a display device 24. The control device 20 is mainly configured to include a CPU (Central Processing Unit) 26 and a memory 27. In the control device 20, the CPU 26 functions as various functional configurations described below by executing a predetermined program stored in the memory 27 or the storage device 22 or the like. The communication device 21 is configured by a communication interface or the like for communicating with an external device. The storage device 22 is configured by a hard disk or the like and stores various programs, various information, and information on processing results necessary for the execution of processing in the control device 20. The operation device 23 is a device for performing operations on the wear determination device 6, and is, for example, a keyboard, a mouse, or a touch panel. The display device 24 is a device for displaying various information and processing results, and is, for example, a display or a touch panel. Note that the wear determination device 6 may be configured by a single information processing device or may be configured by a plurality of information processing devices. Further, FIG. 1 only shows a part of the main hardware configuration of the wear determination device 6, and the wear determination device 6 may include other configurations. The wear determination device 6 can be configured using a CPU unit or an arithmetic unit such as a PC or a PLC.

[0020] <Functional configuration> FIG. 2 is a block diagram showing an example of various functions in the wear determination device 6. Waveform extraction processing is executed by the functions in each block.

[0021] The wear determination device 6 includes a first acquisition unit 31, a cutout unit 32, a count unit 33, a second acquisition unit 34, a calculation unit 35, a recording unit 36, a regression unit 37, a differentiation unit 38, a determination unit 39, and a display unit 40.

[0022] The first acquisition unit 31 acquires time-series waveform data A of parameters related to the operating state of the motor 8 that drives the rotary tool. Specifically, the first acquisition unit 31 acquires the spindle current of the motor 8 measured by the measuring instrument 5. That is, the first acquisition unit 31 acquires the time-series waveform data A of the spindle current of the motor 8. For example, the first acquisition unit 31 performs A / D conversion (analog-digital conversion) on the analog data to acquire the time-series data of the spindle current as digital data.

[0023] FIG. 3 is a diagram showing an example of the time-series waveform data A of the spindle current. In FIG. 3, the vertical axis represents the current value and the horizontal axis represents the time. As shown in FIG. 3, the spindle current changes greatly according to the machining operation. For example, at time T1, the tap 7 starts rotating forward, and accordingly, a large spindle current flows. Then, at time T2, the tap 7 is in the air cut state. Then, starting from time T3, the tap 7 begins to contact the workpiece 2, and accordingly, the spindle current increases. Then, at time T4, the forward rotation of the tap 7 begins to decelerate, and accordingly, the spindle current increases. Thus, the waveform data A includes each state associated with the machining by the tap 7.

[0024] Returning to FIG. 2, the cutout unit 32 performs a machining process on the waveform data A acquired by the first acquisition unit 31. The cutout unit 32 cuts out the waveform during the machining of the workpiece 2 by the tap 7 from the waveform data A as the machining waveform data C. "During machining" means the state in which the tap 7 is performing a machining process on the workpiece 2. That is, the state while the tap 7 is performing the female thread machining of the workpiece 2 is "during machining". The cutout unit 32 discards the waveforms corresponding to the operations of moving the tap 7 to a predetermined position and the standby operations between machinings, etc., which are operations that do not actually perform machining on the workpiece 2 (non-machining operations) from the waveform data A, and cuts out the waveform during machining as the machining waveform data C.

[0025] As shown in FIG. 3, the cut-out unit 32 extracts partial waveform data B in which the value of the spindle current is within a predetermined range R1. The predetermined range R1 is a range between a preset upper limit value and a lower limit value. The predetermined range R1 is preset as the range of the value of the spindle current in a state where the tap 7 is machining the workpiece 2. In the example of FIG. 3, the cut-out unit 32 extracts partial waveform data B1, partial waveform data B2, partial waveform data B3, partial waveform data B4, and partial waveform data B5 as partial waveform data B in which the value of the spindle current is within the predetermined range R1 from the waveform data A.

[0026] Then, the cut-out unit 32 selects partial waveform data B in which the time width is equal to or greater than a predetermined value R2 from the extracted partial waveform data B. The predetermined value R2 is preset according to the machining time of the workpiece 2 by the tap 7. In the example of FIG. 3, the cut-out unit 32 selects partial waveform data B3 from the partial waveform data B.

[0027] Further, the cut-out unit 32 extracts a waveform of a partial time width including the center from the waveforms of the entire time width of the partial waveform data B3. For example, when the entire time width of the partial waveform data B3 is set to 100%, the cut-out unit 32 truncates, for example, 20% from both ends (start side and end side) of the entire time width, and extracts a waveform with a time width of 60%. In this way, the time widths to be truncated at both ends are set according to the entire time width of the partial waveform data B3. The waveform portions with large fluctuations in the current values at both ends are truncated, and the net machining location (forward rotation machining location) by the tap 7 is extracted. The net machining location is the waveform of the spindle current during the execution of the machining process on the workpiece 2 by the tap 7 rotating in the forward direction. The cut-out unit 32 sets the net forward rotation machining location as the machining waveform data C. Note that the time widths to be truncated at the start side and the end side of the partial waveform data B3 may be set respectively.

[0028] Furthermore, the cut-out unit 32 corrects the machining waveform data C. Specifically, the cut-out unit 32 identifies the air-cut waveform data D corresponding to the machining waveform data C to be corrected. Air-cut means a state in which the tap 7 rotates without touching other members before contacting the work 2. The cut-out unit 32 identifies the waveform data A of the target period H2 that is a predetermined period H1 before the start point P1 and sets it as the air-cut waveform data D. The waveform data A of the predetermined period H1 indicates, for example, a transient state in which the tap 7 is pressed against the work 2 from the air-cut state. The air-cut waveform data D becomes the base state of the spindle current in the rotating state.

[0029] Then, the cut-out unit 32 calculates the average value of the spindle current of the waveform indicated by the air-cut waveform data D. Then, the cut-out unit 32 calculates the difference between the waveform of the machining waveform data C to be corrected and the calculated average value. That is, the corrected machining waveform data C becomes the net spindle current during machining.

[0030] The counting unit 33 counts the number of machining operations performed on the work 2 by the tap 7. For example, the counting unit 33 performs counting every time the machining waveform data C (or the partial waveform data B3), which is the net forward machining location in the cut-out unit 32, is cut out. That is, the number of machining operations (count value) counted in the counting unit 33 becomes the machining number. Note that the counting by the counting unit 33 is not limited to the above timing as long as the number of machining operations can be counted. Also, the count value of the counting unit 33 is reset to the initial value, for example, when the tap 7 is replaced.

[0031] The second acquisition unit 34 acquires the machining waveform data C showing the time-series waveform during machining of the parameter related to the operating state of the motor 8. Specifically, the second acquisition unit 34 acquires the machining waveform data C corrected by the cut-out unit 32 and outputs it to the calculation unit 35. In this embodiment, the machining waveform data C is acquired from the cut-out unit 32, but for example, the time-series waveform of the spindle current during machining may be acquired from other parts or another device.

[0032] The calculation unit 35 calculates the average value in the corrected processed waveform data C. That is, the calculation unit 35 obtains the average value of the spindle current related to the processing of the workpiece 2 by the tap 7. Then, the calculation unit 35 associates the calculated average value with the count value (processing number) of the counting unit 33 and outputs the result to the recording unit 36.

[0033] The recording unit 36 receives the average value and the count value from the calculation unit 35, associates the average value with the count value, and records the result in the storage device 22. That is, the average value of the spindle current related to the processing of the workpiece 2 by the tap 7 and the processing number of the processing are associated and recorded as the history information of the tap 7.

[0034] The regression unit 37 calculates cubic curve information from the time-series distribution of the average values of the plurality of processed waveform data C. The cubic curve information is information indicating the cubic curve L, for example, a cubic function (a cubic polynomial with the processing number as a variable). The cubic curve L is a regression curve with the processing number as an explanatory variable and the average value as a target variable. Note that the cubic curve information is not limited to the above as long as it is information indicating the cubic curve L, and table information indicating the cubic curve L may be used.

[0035] In this embodiment, the regression unit 37 regresses the time-series distribution of the average values with a cubic function (regression formula). Specifically, the regression unit 37 acquires the history information from the recording unit 36. Then, the regression unit 37 performs regression processing (approximation processing) on the time-series distribution K of the average values of the processed waveform data C. As a result, a cubic function indicating the cubic curve L is obtained from the distribution K of the average values.

[0036] FIG. 4 is a diagram showing an example of the time-series distribution of the average value of each of a plurality of machining waveform data C. As shown in FIG. 4, by arranging the respective average values according to the machining number, a distribution K1 can be obtained as the time-series distribution K of the average values. Tap 7 wears as it is used. The wear state progresses in the order of the initial wear state, the steady wear state, and the abnormal wear state. FIG. 4 shows an example of the distribution K1 when the wear state of tap 7 has progressed to the abnormal wear state. In the example of FIG. 4, period W1 is the initial wear state, period W2 is 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 initial stage of the use of tap 7. The steady wear state is a wear state that progresses after the initial wear state as tap 7 is used. The initial wear state and the steady wear state are wear states of tap 7 for which use is permitted. The abnormal wear state is a wear state that progresses after the steady wear state as tap 7 is used. The abnormal wear state is an abnormal wear state in which the wear of tap 7 has progressed significantly, and there is a possibility of machining defects, breakage of workpiece 2 or tap 7, etc. That is, the abnormal wear state is a wear state of tap 7 for which use is not permitted. Then, as shown in FIG. 4, by performing a regression process on the distribution K1, a cubic curve L1 is obtained as the cubic curve L.

[0037] Returning to FIG. 2, the differentiator 38 differentiates a cubic function to calculate quadratic curve information. The quadratic curve information is information in which a quadratic curve M is shown, and is, for example, a quadratic function (a quadratic polynomial with the machining number as a variable). The quadratic curve M is a differential curve and becomes a parabola. Note that the quadratic curve information is not limited to the above as long as it is information in which the quadratic curve M is shown, and table information or the like in which the quadratic curve M is shown may be used.

[0038] In the present embodiment, the differentiator 38 differentiates a cubic function to calculate a quadratic function (differential formula). Specifically, the differentiator 38 differentiates the cubic function indicating the cubic curve L calculated by the regression unit 37 to obtain a quadratic function indicating the quadratic curve M.

[0039] In the example of FIG. 4, by differentiating the cubic curve L1, the quadratic curve M1 is obtained as the quadratic curve M. The quadratic curve M1 is characterized by having a minimum value at the processing number N1. In the example of FIG. 4, the quadratic curve M1 with respect to the distribution K1 at a certain tap 7 is shown. However, for example, when a coating that is more wear-resistant than the coating of the tap 7 is applied, the minimum value is located at a processing number position higher than N1. Also, when a coating that is less wear-resistant than the coating of the tap 7 is applied, the minimum value is located at a processing number position lower than N1.

[0040] In addition, in this embodiment, although the case where the distribution K is regressed to the cubic curve L in the regression unit 37 has been described as an example, a curve of a degree higher than three may be used as the regression curve. In this case, the curve information regressed by the regression unit 37 is differentiated into the quadratic curve M in the differentiating unit 38.

[0041] Returning to FIG. 2, the determination unit 39 determines the wear state of the tap 7 based on the presence or absence of a minimum value in the quadratic function indicating the quadratic curve M. Specifically, the determination unit 39 determines the extreme value state of the quadratic curve M calculated by the differentiating unit 38. The determination unit 39 determines whether the extreme value of the quadratic curve M is a minimum value, a maximum value, or no extreme value.

[0042] Then, when the determination unit 39 determines that there is a minimum value in the quadratic curve M, it determines that the tap 7 is in an abnormal wear state. Also, when there is a maximum value or no extreme value in the quadratic curve M, the determination unit 39 determines that the tap 7 is not in an abnormal wear state. Not being in an abnormal wear state means that the tap 7 is in an initial wear state or a steady wear state. In this way, the determination unit 39 determines the wear state of the tap 7 based on the extreme value state of the quadratic curve M. In the example of FIG. 4, the quadratic curve M1 is in a state where it has a minimum value. Therefore, the determination unit 39 determines that the tap 7 is in an abnormal wear state.

[0043] FIG. 5 is a diagram excerpting a part of the distribution K1 in FIG. 4. Specifically, FIG. 5 shows, as the distribution K2, the initial wear state and a part of the steady wear state in the distribution K1 of FIG. 4. When regression processing is performed on the distribution K2, a cubic curve L2 is obtained as the cubic curve L. Then, when the cubic curve L2 is differentiated, a quadratic curve M2 is obtained as the quadratic curve M. The quadratic curve M2 is in a state with a maximum value (a state without a minimum value). Therefore, the determination unit 39 determines that the tap 7 is not in an abnormal wear state.

[0044] Since FIG. 4 includes the state of abnormal wear in the distribution K1, the determination unit 39 determines that it is in an abnormal wear state. On the other hand, since FIG. 5 does not include the state of abnormal wear in the distribution K2, the determination unit 39 determines that it is not in an abnormal wear state. Thus, the wear state of the tap 7 is determined according to the extreme value state of the quadratic curve M.

[0045] When the minimum value of the quadratic curve M changes from a state without a minimum value to a state with a minimum value, the determination unit 39 determines that the tap 7 has changed to an abnormal wear state. That is, when the minimum value of the quadratic curve M changes from a state without a minimum value to a state with a minimum value, the determination unit 39 determines that it is the starting point of the abnormal wear state.

[0046] FIG. 6 is a diagram showing an example of the distribution K3 when wear progresses from the distribution K2 in FIG. 5. Specifically, FIG. 6 is a diagram showing the distribution K3 of the average value when the tap 7 is used up to the processing number N2, which is the change point from the state of the distribution K2 in FIG. 5 to the abnormal wear state in FIG. 4. That is, the distribution K3 includes the average value of the processing number N2, which is the change point of the abnormal wear state. When regression processing is performed on the distribution K3, a cubic curve L3 is obtained. Then, when the cubic curve L3 is differentiated, a quadratic curve M3 is obtained. The quadratic curve M3 is in a state with a minimum value. Note that a distribution that does not include the average value of the processing number N2 (that is, a distribution up to the processing number N2 - 1) is in a state with a maximum value (a state without a minimum value), similar to the case of the distribution K2 in FIG. 5. Therefore, the example of the distribution K3 in FIG. 6 is a case where the quadratic curve M3 changes from a state without a minimum value to a state with a minimum value, and the determination unit 39 determines that it is the starting point of the abnormal wear state.

[0047] Returning to FIG. 2, the determination unit 39 outputs the determination result of the wear state of the tap 7 to the recording unit 36 for recording. For example, the recording unit 36 records by associating the average value, the processing number, and the determination result of the wear state based on the distribution K of the average values up to the processing number. Note that, by executing the above processing in real time for the processing by the tap 7, the determination result of the wear state of the tap 7 is recorded in real time.

[0048] The display unit 40 controls the display device 24 to perform display. Specifically, the display unit 40 causes the display device 24 to display information processed by the wear determination device 6 such as information recorded in the recording unit 36. In particular, the display unit 40 displays the determination result of the wear state of the tap 7. By checking the display of the determination result, the user can recognize the current wear state of the tap 7. Also, by checking the determination result that it is the starting point of the abnormal wear state, it can be recognized that the tap 7 has entered the abnormal wear state.

[0049] <Flow of processing> FIG. 7 is a flowchart showing an example of the flow of the wear state determination process according to the present embodiment. Each process of the following steps is started when the user gives an instruction to start the process after a new tap 7 is provided, for example, when the tap 7 is replaced. Note that the order and content of the following steps can be changed as appropriate.

[0050] (Step SP10) The count unit 33 initializes the count value indicating the number of processed items. That is, the count value becomes 0. Then, the process proceeds to step SP11.

[0051] (Step SP11) The first acquisition unit 31 acquires the time-series waveform data A of the spindle current of the tap 7. Then, the process proceeds to step SP12.

[0052] (Step SP12) The cut-out unit 32 cuts out the processed waveform data C from the acquired waveform data A. Note that the cut-out unit 32 corrects the processed waveform data C with the air-cut waveform data D. Then, it proceeds to step SP13.

[0053] (Step SP13) The counting unit 33 increments the count value. That is, the counting unit 33 adds 1 to the count value. Then, it proceeds to step SP14.

[0054] (Step SP14) The calculation unit 35 calculates the average value for the corrected processed waveform data C. Note that the calculated average value is sequentially accumulated in the storage device 22 in association with the count value. Then, it proceeds to step SP15.

[0055] (Step SP15) The regression unit 37 calculates a cubic function representing the cubic curve L from the distribution K of the average values. Note that the distribution K of the average values includes the average value calculated in the immediately preceding step SP14, and the cubic function in the latest state is calculated. Then, it proceeds to step SP16.

[0056] (Step SP16) The differentiation unit 38 differentiates the calculated cubic function to calculate the quadratic curve information. Specifically, the differentiation unit 38 differentiates the cubic function to calculate a quadratic function. Then, it proceeds to step SP17.

[0057] (Step SP17) The determination unit 39 determines the state of the extreme value in the calculated quadratic function. Specifically, the determination unit 39 determines whether the extreme value in the quadratic curve M represented by the quadratic function is a minimum value, a maximum value, or no extreme value. Then, it proceeds to step SP18.

[0058] (Step SP18) The determination unit 39 determines whether there is a minimum value in the quadratic curve M. The case where there is no minimum value includes the case where there is no minimum value but there is a maximum value, and the case where neither a minimum value nor a maximum value exists. If there is no minimum value, the process proceeds to step SP19. If there is a minimum value, the process proceeds to step SP20.

[0059] (Step SP19) The determination unit 39 determines that the wear state of the tap 7 is not an abnormal wear state. Specifically, the determination unit 39 determines that the wear state of the tap 7 is an initial wear state or a steady wear state. Then, the process proceeds to step SP23.

[0060] (Step SP20) The determination unit 39 determines that the wear state of the tap 7 is an abnormal wear state. Then, the process proceeds to step SP21.

[0061] (Step SP21) The determination unit 39 determines whether the result of the previous determination by the determination unit 39 was that there was an abnormal wear state. The result of the previous determination by the determination unit 39 is the determination result based on the distribution K up to the average value of the processing numbers before being incremented in step SP13. If the result of the previous determination by the determination unit 39 was that there was an abnormal wear state, the process proceeds to step SP23. If the result of the previous determination by the determination unit 39 was that there was no abnormal wear state, the process proceeds to step SP22.

[0062] (Step SP22) The determination unit 39 determines that it is the starting point of the abnormal wear state. Then, the process proceeds to step SP23.

[0063] (Step SP23) The recording unit 36 records the determination result by the determination unit 39. Then, the process proceeds to step SP24.

[0064] (Step SP24) The display unit 40 displays the determination result by the determination unit 39. Specifically, it displays whether the wear state of the tap 7 is an abnormal wear state or not (initial wear state or steady wear state). Further, when it is determined in step SP22 that it is the starting point of the abnormal wear state, it displays that it has become the starting point of the abnormal wear state.

[0065] (Step SP25) The determination unit 39 determines whether there is the following process. The presence or absence of the following process can be set by the user, for example. Also, for example, it may be possible for the user who has confirmed the display to select whether to continue or end. If there is the following process, return to step SP11 and repeat the process. If there is no following process, end the process.

[0066] By executing the process as described above, the wear state is determined according to the processing of the tap 7. Since the wear state is determined according to the processing, the user can confirm the determination result in real time each time the processing progresses.

[0067] <Operational Effect> As described above, in the present embodiment, the wear determination device 6 is a wear determination device 6 for a rotary tool (for example, tap 7) that processes the workpiece 2, and a second acquisition unit that acquires a plurality of processing waveform data C showing the time-series waveform during processing of parameters (for example, spindle current) related to the operating state of the motor 8 that drives the rotary tool, a regression unit 37 that calculates cubic curve information (curve information of the third degree or higher) by regressing the time-series distribution based on each of the average values of the processing waveform data C, a differentiation unit 38 that calculates quadratic curve information by differentiating the curve information, and a determination unit 39 that determines the wear state of the rotary tool based on the presence or absence of the minimum value of the quadratic curve information. According to this configuration, it is possible to determine the wear state based on the presence or absence of the minimum value from the time-series distribution based on parameters related to the operating state of the motor 8 such as the spindle current. Therefore, it is possible to stop the device early and perform tool replacement according to the determination result of the wear state. Therefore, it is possible to avoid workpiece loss. In addition, by using the machining waveform data C, which is a time-series waveform during machining, for regression and differentiation, the wear state can be determined, and the determination accuracy of the wear state can be improved.

[0068] In the wear determination device 6 according to the present embodiment, when the determination unit 39 has a minimum value in the quadratic curve information, it determines that the rotating tool is in an abnormal wear state. According to this configuration, it is possible to determine that the wear state is an abnormal wear state based on the presence or absence of the minimum value.

[0069] In the wear determination device 6 according to the present embodiment, when the determination unit 39 has a maximum value in the quadratic curve information, or when there is no extreme value in the quadratic curve information, it determines that the rotating tool is not in an abnormal wear state. According to this configuration, it is possible to determine that the wear state is not an abnormal wear state based on the state of the extreme value.

[0070] In the wear determination device 6 according to the present embodiment, when the minimum value of the quadratic curve information changes from a state without a minimum value to a state with a minimum value, the determination unit 39 determines that the rotating tool has changed to an abnormal wear state. According to this configuration, it is possible to determine that the wear state has changed from a state without abnormal wear to a state of abnormal wear.

[0071] In the wear determination device 6 according to the present embodiment, the rotating tool is a tap 7. According to this configuration, when the rotating tool is the tap 7, although there is a possibility that the tap 7 is in an abnormal wear state and the tap 7 may break or the female thread accuracy of the workpiece 2 may be poor, since the wear state of the tap 7 can be determined, accidents as described above can be prevented.

[0072] <Modification Example> Note that the present invention is not limited to the above-described embodiments. That is, even if those skilled in the art make appropriate design changes to the above-described specific examples, as long as they have the features of the present invention, they are included in the scope of the present invention. Also, each element included in the above-described embodiments and the following modified examples can be combined as far as technically possible, and as long as the combination includes the features of the present invention, it is included in the scope of the present invention.

[0073] For example, in the above-described embodiment, the case where the tap 7 is used as the rotary tool was described as an example, but it is not limited to the tap 7 as long as it is a tool that rotates during machining. For example, a drill or the like may be used as the rotary tool.

[0074] Also, in the above-described embodiment, the case where the current flowing through the motor 8 is used as a parameter related to the operating state of the motor 8 was described as an example, but it is not limited to the above as long as it is a parameter indicating the operating state of the motor 8. For example, the torque of the motor 8 may be used as a parameter related to the operating state of the motor 8. Note that the torque of the motor 8 has a correlation with the current of the motor 8. Also, voltage or power consumption may be used as a parameter related to the operating state of the motor 8.

[0075] Also, in the above-described embodiment, the cutout portion 32 corrects the machining waveform data C with the air cut waveform data D, but the correction process may be omitted.

[0076] Also, in the above-described embodiment, the case where the average value of each of the machining waveform data C is calculated and the time-series distribution is regressed was described, but for example, the median, minimum value, or maximum value of each of the machining waveform data C may be used, or each value included in the machining waveform data C may be used.

Explanation of Reference Numerals

[0077] 2: Workpiece 6: Wear Determination Device 7: Tap (Rotary Tool) 8: Motor 34: Second acquisition unit (acquisition unit) 37: Regression unit 38: Differentiation unit 39: Judgment unit C: Processed waveform data K: Distribution (time series distribution)

Claims

1. A wear determination device for a rotary tool that machines a workpiece, an acquisition unit that acquires a plurality of machining waveform data showing a time-series waveform during machining of a parameter related to the operating state of a motor that drives the rotary tool; a regression unit that calculates curve information of the third degree or higher by regressing a time-series distribution based on each of the machining waveform data; a differentiation unit that differentiates the curve information to calculate quadratic curve information; a determination unit that determines the wear state of the rotary tool based on the presence or absence of a minimum value of the quadratic curve information; and a wear determination device comprising the same.

2. The determination unit determines that the rotary tool is in an abnormal wear state when there is a minimum value in the quadratic curve information. The wear determination device according to claim 1.

3. The determination unit determines that the rotary tool is not in an abnormal wear state when there is a maximum value in the quadratic curve information or when there is no extreme value in the quadratic curve information. The wear determination device according to claim 1 or 2.

4. The determination unit determines that the rotary tool has changed to an abnormal wear state when the minimum value of the quadratic curve information changes from a state where it does not exist to a state where it exists. The wear determination device according to claim 1 or 2.

5. The rotary tool is a tap. The wear determination device according to claim 1 or 2.

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