Processing system, processing device, processing method, and processing program

Abstract

The present invention provides a processing system comprising a cutting tool, a sensor, and a processing unit, wherein the sensor measures a physical quantity that indicates a state related to a load on the cutting tool at the time of cutting machining and the processing unit creates, on the basis of a measurement result of the sensor at a plurality of measurement times, a graph containing a plurality of plots indicating data relating to the load at each of the measurement times and detects a state of the cutting machining through use of the cutting tool on the basis of an area occupied by the plurality of plots on the created graph.

Description

Processing system, processing device, processing method, and processing program

[0001] The present disclosure relates to a processing system, a processing device, a processing method, and a processing program.

[0002] Patent Document 1 (US Patent Application Publication No. 2015 / 0261207) discloses a method for setting or monitoring operating parameters of a workpiece processing machine having a tool holder and means for moving the workpiece and the tool holder relative to each other along at least a first axis, wherein during a processing operation of the tool holder to which the workpiece is attached and during application of the tool to the workpiece, a value of at least one of the following measurement variables (a) to (c) generated at the tool during interaction between the tool and the workpiece and transmitted to the tool holder is detected and recorded for a processing sequence, and the ascertained value of the at least one measurement variable is used to set operating parameters for an extended service life of the tools used, in conjunction with processing times below the maximum processing time, for monitoring the processing operation with regard to its reproducibility, or for monitoring tool wear or machine errors of the workpiece processing machine: (a) an axial force acting in a direction parallel to the first axis; (b) a torque present about the first axis or an axis parallel to the first axis; and (c) a bending torque or bending torque component depending on the direction and amount.

[0003] US Patent Application Publication No. 2015 / 0261207 JP 2006-71485 A JP 11-118625 A

[0004] The processing system of the present disclosure comprises a cutting tool, a sensor, and a processing unit, wherein the sensor measures a physical quantity indicating the state of the load on the cutting tool during cutting processing, and the processing unit creates a graph including multiple plots showing data regarding the load at each measurement time point based on the measurement results of the sensor at the multiple measurement time points, and detects the state of cutting processing using the cutting tool based on the area occupied by the multiple plots in the created graph.

[0005] One aspect of the present disclosure can be realized not only as a processing system including such a characteristic processing unit, but also as a semiconductor integrated circuit that realizes part or all of the processing system.

[0006] FIG. 1 is a diagram illustrating a configuration of a processing system according to an embodiment of the present disclosure. FIG. 2 is a cross-sectional view illustrating a configuration of a cutting tool according to an embodiment of the present disclosure. FIG. 3 is a diagram illustrating a configuration of a processing device in a cutting system according to an embodiment of the present disclosure. FIG. 4 is a perspective view schematically illustrating a cutting tool according to an embodiment of the present disclosure. FIG. 5 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 6 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 7 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 8 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 9 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 10 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 11 is a diagram illustrating another example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 12 is a diagram illustrating another example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 13 is a diagram illustrating another example of a graph created by the creation unit in the processing device according to the embodiment of the present disclosure. FIG. 14 is a diagram illustrating another example of a graph created by the creation unit in the processing device according to the embodiment of the present disclosure. FIG. 15 is a diagram illustrating an example of detection processing by the detection unit in the processing device according to the embodiment of the present disclosure. FIG. 16 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibration by the processing device according to the embodiment of the present disclosure. FIG. 17 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibration by the processing device according to the embodiment of the present disclosure. FIG. 18 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibration by the processing device according to the embodiment of the present disclosure. FIG. 19 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibration by the processing device according to the embodiment of the present disclosure. FIG. 20 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibration by the processing device according to the embodiment of the present disclosure.FIG. 21 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibrations by a processing device according to an embodiment of the present disclosure. FIG. 22 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibrations by a processing device according to an embodiment of the present disclosure. FIG. 23 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibrations by a processing device according to an embodiment of the present disclosure. FIG. 24 is a diagram illustrating a simulation result for explaining the detection accuracy of abnormal vibrations by a processing device according to an embodiment of the present disclosure. FIG. 25 is a schematic diagram of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 26 is a schematic diagram illustrating the positional relationship of plots in a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 27 is a schematic diagram illustrating the positional relationship of plots in a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 28 is a diagram illustrating a simulation result for explaining the relationship between the pitch of plots included in a graph created by a processing device according to an embodiment of the present disclosure and detection accuracy. FIG. 29 is a diagram illustrating the simulation result for explaining the relationship between the pitch of plots included in a graph created by a processing device according to an embodiment of the present disclosure and detection accuracy. FIG. 30 is a diagram illustrating simulation results for explaining the relationship between the pitch of plots included in a graph created by a processing device according to an embodiment of the present disclosure and detection accuracy. FIG. 31 is a flowchart defining an example of an operational procedure when a processing device according to an embodiment of the present disclosure acquires sensor measurement values. FIG. 32 is a flowchart defining an example of an operational procedure when a processing device according to an embodiment of the present disclosure performs detection processing. FIG. 33 is a diagram illustrating a configuration of a processing system according to a modified embodiment of the present disclosure. FIG. 34 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. FIG. 35 is a diagram illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure.

[0007] Conventionally, a technique has been proposed in which a sensor is attached to a cutting tool and an abnormality in the cutting edge of the cutting tool is detected based on the measurement results of the sensor during cutting processing.

[0008] [Problem to be Solved by the Present Disclosure] There is a need for a technology that goes beyond the technology of Patent Document 1 and that is capable of more accurately detecting the state of cutting processing using a cutting tool.

[0009] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a processing system, processing device, processing method, and processing program that are capable of more accurately detecting the state of cutting processing using a cutting tool.

[0010] Effect of the Present Disclosure The state of cutting work using a cutting tool can be detected more accurately.

[0011] [Description of Embodiments of the Present Disclosure] First, the contents of the embodiments of the present disclosure will be listed and described.

[0012] (1) A processing system according to an embodiment of the present disclosure includes a cutting tool, a sensor, and a processing unit. The sensor measures a physical quantity indicating a state related to the load on the cutting tool during cutting processing. The processing unit creates a graph including multiple plots indicating data related to the load at each measurement time point based on the measurement results of the sensor at multiple measurement time points. The processing unit detects the state of cutting processing using the cutting tool based on the area occupied by the multiple plots in the created graph.

[0013] In this way, by configuring the cutting state to be detected based on the area occupied by multiple plots in a graph created based on the sensor measurement results, a change in the position of the plots due to the occurrence of abnormal vibrations can be detected as a change in the area occupied by the multiple plots in the graph, and abnormal vibrations can be detected based on this change in area. Furthermore, since the area occupied by multiple plots in a graph is more likely to reflect changes in the amplitude of abnormal vibrations than the standard deviation of the sensor measurement results, etc., this area can be used as an evaluation value to detect changes in the amplitude of abnormal vibrations with higher sensitivity. Therefore, the state of cutting using a cutting tool can be detected more accurately.

[0014] (2) In the above (1), the processing unit may create the graph in which the size of the plots is set according to the pitch of the plots.

[0015] With this configuration, it is possible to create a graph in which the change in amplitude of abnormal vibration is more easily reflected by the area occupied by multiple plots.

[0016] (3) In (2) above, the processing unit may create the graph including the plot having a diameter that is 5% or more of the maximum value of the data based on the measurement results of the sensor obtained in advance before the operation of the processing system and that is 20% or less of the maximum value of the data.

[0017] With this configuration, it is possible to ensure an area where the plots overlap when no abnormal vibrations are occurring, and when abnormal vibrations occur, the plots do not go beyond the graph and the overlap of the plots is more reliably eliminated. Therefore, the area occupied by multiple plots can be used as an evaluation value, making it possible to detect abnormal vibrations with higher sensitivity.

[0018] (4) In any of (1) to (3) above, the processing unit may create the graph based on the measurement results of the sensor at the multiple measurement points during the period required for the cutting tool or the workpiece to be cut to make multiple rotations.

[0019] With this configuration, it is possible to obtain the measurement results necessary for creating a graph while keeping the sampling period for obtaining the measurement results of the sensor low.

[0020] (5) In any one of (1) to (4) above, the processing unit may create a plurality of the graphs in which the plot sizes are different.

[0021] With this configuration, it is possible to create a plurality of graphs according to the purpose, such as graphs for analysis and graphs for display.

[0022] (6) In the above (5), the processing unit may perform a process of selectively displaying at least one of the plurality of graphs.

[0023] With this configuration, for example, it is possible to display a display graph that allows the user to recognize the state of cutting while detecting the state of cutting using an analysis graph.

[0024] (7) In the above (5) or (6), the processing unit may detect a state of cutting using the cutting tool based on an area occupied by the plurality of plots in each of the plurality of graphs.

[0025] With such a configuration, for example, it is possible to detect a variety of abnormal vibrations with different amplitudes with higher sensitivity.

[0026] (8) In any one of (1) to (7) above, the processing unit may create the graph of time series including the plurality of plots showing the correspondence between the measurement time points and the data.

[0027] With this configuration, it is possible to detect the state of various cutting processes such as milling and turning, based on the area occupied by multiple plots in a time series graph.

[0028] (9) In any of (1) to (7) above, the processing system may include a plurality of the sensors, and the processing unit may create the graph including the plurality of plots showing the correspondence of the data regarding the load in two directions in a plane perpendicular to the rotation axis of the cutting tool for each measurement time point based on the measurement results of each of the sensors at the plurality of measurement time points.

[0029] With this configuration, it is possible to detect changes in the amplitude of abnormal vibrations with higher sensitivity than with a configuration that detects the state of cutting processing using a time-series graph.

[0030] (10) In any of the above (1) to (9), the sensor may be a strain sensor or an acceleration sensor.

[0031] With this configuration, if the sensor is a strain sensor, it can more accurately detect deformation of the cutting tool that affects machining accuracy, and if the sensor is an acceleration sensor, it can detect smaller vibrations of the cutting tool.

[0032] (11) A processing device according to an embodiment of the present disclosure includes a measurement result acquisition unit that acquires measurement results of a physical quantity that indicates the state of the load on the cutting tool during cutting processing, which are measurement results of a sensor; a creation unit that creates a graph including multiple plots that indicate data on the load for each measurement time point based on the measurement results of the sensor at multiple measurement time points acquired by the measurement result acquisition unit; and a detection unit that detects the state of cutting processing using the cutting tool based on the area occupied by the multiple plots in the graph created by the creation unit.

[0033] (12) A processing method according to an embodiment of the present disclosure is a processing method in a processing device, and includes the steps of: acquiring measurement results of a sensor, the measurement results being of a physical quantity that indicates a state related to the load on a cutting tool during cutting processing; creating a graph including a plurality of plots that indicate data related to the load at each of the measurement points based on the acquired measurement results of the sensor at the plurality of measurement points; and detecting the state of cutting processing using the cutting tool based on the area occupied by the plurality of plots in the created graph.

[0034] In this way, by configuring the cutting state to be detected based on the area occupied by multiple plots in a graph created based on the sensor measurement results, a change in the position of the plots due to the occurrence of abnormal vibrations can be detected as a change in the area occupied by the multiple plots in the graph, and abnormal vibrations can be detected based on this change in area. Furthermore, since the area occupied by multiple plots in a graph is more likely to reflect changes in the amplitude of abnormal vibrations than the standard deviation of the sensor measurement results, etc., this area can be used as an evaluation value to detect changes in the amplitude of abnormal vibrations with higher sensitivity. Therefore, the state of cutting using a cutting tool can be detected more accurately.

[0035] (13) A processing program according to an embodiment of the present disclosure is a processing program used in a processing device, and causes a computer to function as: a measurement result acquisition unit that acquires measurement results of physical quantities from a sensor that indicate the state of the load on the cutting tool during cutting processing; a creation unit that creates a graph including multiple plots that indicate data on the load for each measurement time point based on the measurement results of the sensor at multiple measurement time points acquired by the measurement result acquisition unit; and a detection unit that detects the state of cutting processing using the cutting tool based on the area occupied by the multiple plots in the graph created by the creation unit.

[0036] In this way, by using a method for detecting the state of cutting processing based on the area occupied by multiple plots in a graph created based on the measurement results of the sensor, changes in the position of the plots due to the occurrence of abnormal vibrations can be detected as changes in the area occupied by the multiple plots in the graph, and abnormal vibrations can be detected based on this change in area. Furthermore, since the area occupied by multiple plots in a graph is more likely to reflect changes in the amplitude of abnormal vibrations than the standard deviation of the measurement results of the sensor, this area can be used as an evaluation value to detect changes in the amplitude of abnormal vibrations with higher sensitivity. Therefore, the state of cutting processing using a cutting tool can be detected more accurately.

[0037] In this way, by configuring the cutting state to be detected based on the area occupied by multiple plots in a graph created based on the sensor measurement results, a change in the position of the plots due to the occurrence of abnormal vibrations can be detected as a change in the area occupied by the multiple plots in the graph, and abnormal vibrations can be detected based on this change in area. Furthermore, since the area occupied by multiple plots in a graph is more likely to reflect changes in the amplitude of abnormal vibrations than the standard deviation of the sensor measurement results, etc., this area can be used as an evaluation value to detect changes in the amplitude of abnormal vibrations with higher sensitivity. Therefore, the state of cutting using a cutting tool can be detected more accurately.

[0038] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, identical or corresponding parts are designated by the same reference numerals, and their description will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any manner.

[0039] [Configuration and Basic Operation] <Processing System> Fig. 1 is a diagram showing the configuration of a processing system according to an embodiment of the present disclosure. Referring to Fig. 1, the processing system 301 includes a cutting tool 101, a plurality of strain sensors 20, and a processing device 201. The processing device 201 is an example of a processing unit in the processing system 301.

[0040] <Cutting Tool> The cutting tool 101 is, for example, an end mill used in a machine tool such as a milling machine, and is used for milling an object to be cut, such as a metal. The cutting tool 101 is, for example, an indexable end mill. The cutting tool 101 is used while held in a tool holder 210 such as an arbor.

[0041] The cutting tool 101 includes a shaft portion 10, a housing 24, a battery 22, a wireless communication device 23, and a blade attachment portion 12. The shaft portion 10 includes a shank portion 11. In Fig. 1, the housing 24 is indicated by an imaginary two-dot chain line.

[0042] The blade mounting portion 12 is provided closer to the tip of the cutting tool 101 than the shaft portion 10. The blade mounting portion 12 includes, for example, four blade fixing portions 13. A tip 14 is attached to each blade fixing portion 13. The blade mounting portion 12 may include one, two, three, five or more blade fixing portions 13.

[0043] The tip 14 is, for example, a throw-away tip. The tip 14 is attached to the blade fixing portion 13 by, for example, screwing. The tip 14 may be fixed to the blade fixing portion 13 by means other than screwing. The cutting tool 101 may also be a so-called solid end mill that has a cutting blade integrated with the shaft portion 10 instead of the blade mounting portion 12.

[0044] The tool holder 210 is attached to a spindle 220 of a machine tool. The spindle 220 is columnar and applies a rotational force to the tool holder 210. The tool holder 210 is a columnar member arranged on an extension of the spindle 220. Specifically, the upper end of the tool holder 210 is held by the spindle 220. Furthermore, the lower end of the tool holder 210 holds the shank portion 11 of the cutting tool 101.

[0045] For example, the strain sensor 20 is attached to the circumferential surface of the shaft portion 10 via an adhesive or a pressure-sensitive adhesive. The strain sensor 20 may also be attached to the circumferential surface of the tool holder 210.

[0046] The housing 24 houses the strain sensor 20. Specifically, the housing 24 includes a bottom plate portion and a side wall portion (not shown). The housing 24 covers the strain sensor 20 from below and from the sides.

[0047] The battery 22 and the wireless communication device 23 are stored in a housing 24. For example, the battery 22 and the wireless communication device 23 are fixed to a bottom plate or a side wall of the housing 24. The wireless communication device 23 includes a communication circuit such as a communication integrated circuit (IC). The battery 22 is connected to the strain sensor 20 and the wireless communication device 23 via a power line (not shown). The battery 22 supplies power to the strain sensor 20 and the wireless communication device 23 via the power line.

[0048] For example, the processing system 301 includes three strain sensors 20. The processing system 301 may be configured to include a smaller number of strain sensors 20 than the number of tips 14 in the cutting tool 101, or may be configured to include a larger number of strain sensors 20 than the number of tips 14 in the cutting tool 101. The processing system 301 may also be configured to include a number of strain sensors 20 that is not correlated with the number of tips 14 in the cutting tool 101.

[0049] FIG. 2 is a cross-sectional view showing a configuration of a cutting tool according to an embodiment of the present disclosure. FIG. 2 is a cross-sectional view taken along line II-II in FIG. 1 . Referring to FIG. 2 , strain sensors 20A, 20B, and 20C are provided on the shaft portion 10 as strain sensors 20. Strain sensor 20B is provided at a position 90° offset from the position at which strain sensor 20C is provided in the circumferential direction of the shaft portion 10. Strain sensor 20A is provided at a position 90° offset from the position at which strain sensor 20B is provided in the circumferential direction of the shaft portion 10. Strain sensors 20A and 20C are provided at positions that are point-symmetric with respect to the rotation axis 17 of the shaft portion 10. Strain sensors 20A, 20B, and 20C may be provided at the same position or at different positions, for example, in the direction along the rotation axis 17 of the shaft portion 10.

[0050] The strain sensors 20A, 20B, and 20C may be provided, for example, on the circumferential surface of the shaft portion 10 or the tool holder 210 as described above, regardless of the position of the blade mounting portion 12. In other words, the strain sensors 20A, 20B, and 20C do not need to be provided at positions along the rotation axis 17 from the blade fixing portion 13 on the circumferential surface of the shaft portion 10 or the tool holder 210.

[0051] For the sake of explanation, in the plane perpendicular to the rotation axis 17, the direction from the rotation axis 17 to the position where the strain sensor 20A is provided will be referred to as the X direction, and the direction from the rotation axis 17 to the position where the strain sensor 20B is provided will be referred to as the Y direction.

[0052] The strain sensor 20 measures a physical quantity that indicates a state related to the load on the cutting tool 101 during cutting. More specifically, the strain sensor 20 measures the strain ε of the shaft portion 10 as a physical quantity that indicates a state related to the load on the cutting tool 101 during cutting. The strain sensor 20 may be configured to measure shear strain as the strain ε, or may be configured to measure normal strain, or may be configured to measure both shear strain and normal strain.

[0053] The strain sensor 20 measures the strain ε, for example, during the period from time ts, which is the start time of the cutting process, to time te, which is the end time, and transmits an analog signal of a level corresponding to the strain ε to the wireless communication device 23 via a signal line not shown.

[0054] The wireless communication device 23 performs AD (Analog-Digital) conversion on the analog signals received from the strain sensors 20 at a predetermined sampling period to generate sensor measurement values ​​that are converted digital values. More specifically, the wireless communication device 23 performs AD conversion on the analog signal of the strain ε received from the strain sensor 20A to generate a sensor measurement value sx, performs AD conversion on the analog signal of the strain ε received from the strain sensor 20B to generate a sensor measurement value sy, and performs AD conversion on the analog signal of the strain ε received from the strain sensor 20C to generate a sensor measurement value sr.

[0055] The wireless communication device 23 assigns a timestamp indicating the sampling timing to the generated sensor measurement values ​​sx, sy, sr and stores the timestamp-assigned sensor measurement values ​​sx, sy, sr in a storage unit (not shown). The wireless communication device 23 acquires one or more sets of sensor measurement values ​​sx, sy, sr from the storage unit, for example at a predetermined interval, generates a wireless signal including the acquired sensor measurement values ​​sx, sy, sr and identification information of the corresponding strain sensor 20, and transmits the generated wireless signal to the processing device 201.

[0056] [Processing Device] Fig. 3 is a diagram showing the configuration of a processing device in a cutting system according to an embodiment of the present disclosure. Referring to Fig. 3, the processing device 201 includes a wireless communication unit 110, a creation unit 120, a detection unit 130, and a storage unit 140. The wireless communication unit 110 is an example of a measurement result acquisition unit. Some or all of the wireless communication unit 110, the creation unit 120, and the detection unit 130 are realized, for example, by a processing circuit including one or more processors. The storage unit 140 is, for example, a non-volatile memory included in the processing circuit. The processing device 201 performs a detection process to detect the state of cutting processing using the cutting tool 101.

[0057] <Wireless Communication Unit> The wireless communication unit 110 acquires the measurement results of the strain sensor 20, which are physical quantity measurement results that indicate the state related to the load on the cutting tool 101 during cutting processing.

[0058] More specifically, the wireless communication unit 110 communicates wirelessly with the wireless communication device 23 in the cutting tool 101. The wireless communication device 23 and the wireless communication unit 110 communicate wirelessly using a communication protocol such as ZigBee (registered trademark) conforming to IEEE 802.15.4, Bluetooth (registered trademark) conforming to IEEE 802.15.1, or UWB (Ultra Wide Band) conforming to IEEE 802.15.3a. Note that a communication protocol other than those described above may also be used between the wireless communication device 23 and the wireless communication unit 110.

[0059] The wireless communication unit 110 acquires the sensor measurement values ​​sx, sy, sr and the identification information from the wireless signal received from the wireless communication device 23 in the cutting tool 101. Then, the wireless communication unit 110 stores the sensor measurement values ​​sx, sy, sr in the storage unit 140 in association with the identification information.

[0060] <Creation Unit> The creation unit 120 creates a graph G including a plurality of plots P showing data related to the load on the cutting tool 101 at each measurement time point, based on the measurement results of the strain sensor 20 at each measurement time point acquired by the wireless communication unit 110. More specifically, the creation unit 120 creates the graph G based on the sensor measurement values ​​sx, sy, and sr stored in the storage unit 140 by the wireless communication unit 110. The graph G is used in the detection process in the detection unit 130, which will be described later.

[0061] 4 is a perspective view schematically illustrating a cutting tool according to an embodiment of the present disclosure. Referring to FIG. 4, when cutting is performed by cutting tool 101, a load, i.e., cutting resistance F [N], is applied from the workpiece to the cutting edge within cutting resistance acting surface 18, which is a plane perpendicular to rotation axis 17 and passing through the cutting edge of tip 14.

[0062] For example, based on the sensor measurement values ​​sx, sy, and sr, the creation unit 120 calculates cutting resistance Fx, which is the cutting resistance F in the X direction that the cutting tool 101 receives on the cutting resistance acting surface 18, and cutting resistance Fy, which is the cutting resistance F in the Y direction that the cutting tool 101 receives on the cutting resistance acting surface 18.

[0063] More specifically, the storage unit 140 stores a conversion formula Fm1 for converting the sensor measurement values ​​sx, sy, and sr into cutting resistances Fx and Fy. For example, the conversion formula Fm1 is created in advance using the techniques described in Patent Documents 2 and 3. More specifically, the conversion formula Fm1 is a conversion matrix created in advance based on the sensor measurement values ​​sx, sy, and sr obtained when a known load is applied to the cutting tool 101.

[0064] The creation unit 120 calculates the cutting resistances Fx and Fy based on the sensor measurement values ​​sx, sy, and sr and the conversion formula Fm1 in the storage unit 140. The sensor measurement values ​​sx, sy, and sr and the cutting resistances Fx and Fy are an example of data related to the load.

[0065] 5 and 6 are diagrams showing examples of graphs created by the creation unit in the processing device according to the embodiment of the present disclosure. Figures 5 and 6 show graph Ga created by creation unit 120 when cutting is performed using cutting tool 101 under predetermined machining conditions Wc1. In graph Ga, the horizontal axis represents time [seconds] and the vertical axis represents cutting resistance Fx [N]. Figure 5 shows graph Ga in a state where no chatter vibration is occurring in cutting tool 101, and Figure 6 shows graph Ga in a state where chatter vibration is occurring in cutting tool 101.

[0066] 5 and 6 , the creation unit 120 creates a graph Ga, which is a time-series graph G including a plurality of plots Pa indicating the correspondence between measurement times and cutting resistance Fx. The plots Pa are an example of plots P. For example, the shape of the plots Pa is circular. Note that the shape of the plots Pa may be a shape other than a circle, such as a rectangle or a triangle. The creation unit 120 may be configured to create a graph Ga including plots Pa indicating the correspondence between measurement times and cutting resistance Fy, or may be configured to create a graph Ga including plots Pa indicating the correspondence between measurement times and sensor measurement values ​​sx or sy.

[0067] 7 and 8 are diagrams showing examples of graphs created by the creation unit in the processing device according to the embodiment of the present disclosure. Figures 7 and 8 show graph Gb of cutting resistances Fx and Fy created by creation unit 120 when cutting is performed using cutting tool 101 under machining conditions Wc1. In graph Gb, the horizontal axis represents cutting resistance Fx [N] and the vertical axis represents cutting resistance Fy [N]. Figure 7 shows graph Gb in a state where chatter vibration is not occurring, and Figure 8 shows graph Gb in a state where chatter vibration is occurring.

[0068] 7 and 8, the creation unit 120 creates a graph Gb, which is a graph G including a plurality of plots Pb showing the correspondence between the cutting resistances Fx and Fy on the cutting resistance acting surface 18 for each measurement time point, based on the measurement results of each strain sensor 20 at each measurement time point. The plots Pb are an example of plots P. For example, the shape of the plots Pb is a circle. Note that the shape of the plots Pb may be a shape other than a circle, such as a rectangle or a triangle.

[0069] 9 and 10 are diagrams illustrating an example of a graph created by a creation unit in a processing device according to an embodiment of the present disclosure, in which the diameter of the plot Pb is larger than that of the graph Gb illustrated in FIGS.

[0070] 9 and 10 , for example, the creation unit 120 creates a plurality of graphs G having plots P of different sizes. More specifically, the creation unit 120 creates a plurality of graphs Gb having plots Pb of different diameters using the same cutting resistances Fx and Fy calculated based on the same sensor measurement values ​​sx, sy, and sr. As an example, the creation unit 120 creates two graphs Gb having plots Pb of different diameters and a display graph Gdis having plots Pb of smaller diameters than the two graphs Gb using the same cutting resistances Fx and Fy calculated based on the same sensor measurement values ​​sx, sy, and sr.

[0071] For example, the creation unit 120 calculates the cutting resistances Fx and Fy at each measurement time point in a predetermined target period T starting from time (Pg×m) based on multiple sensor measurement values ​​sx, sy, and sr at creation timing according to a creation period Pg. The creation unit 120 then creates graphs Ga and Gb and a display graph Gdis using the calculated cutting resistances Fx and Fy. Here, m is a positive integer. Note that the creation period Pg may be the same as the target period T, so that the target periods T are continuous. Alternatively, the creation period Pg may be shorter than the target period T, so that the target periods T partially overlap. Alternatively, the creation period gP may be longer than the target period T, so that the target periods T are intermittently provided.

[0072] For example, the creation unit 120 creates the graph G based on the measurement results of the strain sensor 20 at multiple measurement points in a period required for the cutting tool 101 to make multiple rotations. Here, the target period T is the period required for the cutting tool 101 to make multiple rotations.

[0073] The creation unit 120 creates graphs Ga, Gb and a display graph Gdis for each target period T at a creation timing according to the creation period Pg, and stores the graph information including the created graphs Ga, Gb and display graph Gdis in the memory unit 140 in association with the target period T.

[0074] In addition, the creation unit 120 may be configured to calculate a moment Mx, which is the moment M generated by a load in the X direction, and a moment My, which is the moment M generated by a load in the Y direction, within the cutting resistance acting surface 18, instead of or in addition to the cutting resistances Fx and Fy.

[0075] More specifically, the storage unit 140 stores a transformation formula Fm2 for transforming the sensor measurement values ​​sx, sy, and sr into moments Mx and My. For example, the transformation formula Fm2 is created in advance using the techniques described in Patent Documents 2 and 3. More specifically, the transformation formula Fm2 is a transformation matrix created in advance based on the sensor measurement values ​​sx, sy, and sr obtained when a known load is applied to the cutting tool 101.

[0076] The generating unit 120 calculates the moments Mx and My based on the sensor measurement values ​​sx, sy, and sr and the conversion formula Fm2 stored in the storage unit 140. The moments Mx and My are an example of data related to the load.

[0077] The creation unit 120 creates a graph Gc, which is a time-series graph G including a plurality of plots Pc showing the correspondence between measurement times and the calculated moments Mx. The plots Pc are an example of the plots P. For example, the shape of the plots Pc is circular. Note that the shape of the plots Pc may be a shape other than a circle, such as a rectangle or a triangle.

[0078] 11 and 12 are diagrams showing other examples of graphs created by the creation unit in the processing device according to the embodiment of the present disclosure. Figures 11 and 12 show graph Gd of moments Mx and My created by the creation unit 120 when cutting is performed using cutting tool 101 under predetermined machining conditions Wc2. In graph Gd, the horizontal axis represents moment Mx [Nm] and the vertical axis represents moment My [Nm]. Figure 11 shows graph Gd for the first cutting pass, and Figure 12 shows graph Gd for the 150th cutting pass.

[0079] 13 and 14 are diagrams showing other examples of graphs created by the creation unit in the processing device according to the embodiment of the present disclosure. Figures 13 and 14 show graph Gd of moments Mx and My created by creation unit 120 when cutting is performed under predetermined cutting conditions Wc3 using cutting tool 101. Figure 13 shows graph Gd for the first cutting pass, and Figure 14 shows graph Gd for the 50th cutting pass.

[0080] 11 to 14 , the creation unit 120 creates a graph Gd, which is a graph G including a plurality of plots Pd showing the correspondence between the moments Mx and My on the cutting resistance acting surface 18 for each measurement time point, based on the measurement results of each strain sensor 20 at each measurement time point. The plots Pd are an example of plots P. For example, the shape of the plots Pd is circular. Note that the shape of the plots Pd may be a shape other than a circle, such as a rectangle or a triangle.

[0081] 5 and 6 , the graph Ga in the state where chatter vibration is occurring has a larger absolute value of cutting resistance Fx than the graph Ga in the state where chatter vibration is not occurring. This is because, when chatter vibration is occurring, abnormal chatter vibration is added to fundamental vibration, which is normal vibration caused by the cutting edge biting into and separating from the workpiece. Chatter vibration has a higher frequency than fundamental vibration and a smaller amplitude in the early stages of chatter vibration occurrence. Furthermore, the area Ag occupied by plot Pa in the graph Ga in the state where chatter vibration is occurring is larger than that in the graph Ga in the state where chatter vibration is not occurring. This is because the range of possible values ​​of cutting resistance Fx is wider in the graph Ga in the state where chatter vibration is occurring than in the graph Ga in the state where chatter vibration is not occurring, resulting in less overlap between multiple plots Pa.

[0082] 7 to 10, the absolute values ​​of the cutting resistances Fx and Fy are larger in the graph Gb when chatter vibration is occurring than in the graph Gb when chatter vibration is not occurring. This is because, when chatter vibration is occurring, abnormal chatter vibration is added to the fundamental vibration. Furthermore, the area Ag occupied by the plots Pb in the graph Gb when chatter vibration is occurring is larger than in the graph Gb when chatter vibration is not occurring. This is because, when chatter vibration is occurring, the absolute values ​​of the cutting resistances Fx and Fy are larger, resulting in a smaller area where multiple plots Pb overlap than in the graph Gb when chatter vibration is not occurring.

[0083] 11 and 12 , the absolute values ​​of the moments Mx and My are larger in the graph Gd for the 150th cutting operation than in the graph Gd for the first cutting operation. This is because, when using a tip 14 that has been used for 150 cutting operations, not only does the fundamental vibration increase due to wear on the cutting edge, but abnormal vibration due to wear on the cutting edge is also added to the fundamental vibration. The abnormal vibration due to wear on the cutting edge has a higher frequency and a smaller amplitude than the fundamental vibration. Furthermore, the area Ag occupied by the plot Pd is larger in the graph Gd for the 150th cutting operation than in the graph Gd for the first cutting operation. This is because the absolute values ​​of the moments Mx and My are larger in the graph Gd for the 150th cutting operation than in the graph Gd for the first cutting operation, resulting in a smaller area where multiple plots Pd overlap.

[0084] <Detection Unit> The detection unit 130 performs a detection process to detect the state of cutting using the cutting tool 101 based on the area Ag occupied by the plurality of plots P in the graph G created by the creation unit 120 .

[0085] More specifically, when the creation unit 120 stores the graph G for the target period T in the storage unit 140, the detection unit 130 acquires the graph G from the storage unit 140. The detection unit 130 generates a binary image in which areas of the acquired graph G occupied by the plot P are colored black and areas of the graph G in which the plot P is not present are colored white. The detection unit 130 calculates the number of pixels of the black area in the generated binary image as the area Ag.

[0086] After calculating the area Ag, the detection unit 130 performs a detection process using the calculated area Ag as an evaluation value. More specifically, the detection unit 130 compares the calculated area Ag with a predetermined threshold value ThA and detects abnormal vibration based on the comparison result. The threshold value ThA is set in advance based on the area Ag occupied by the plot P in the graph G created by the creation unit 120 when normal cutting is being performed.

[0087] 15 is a diagram illustrating an example of a detection process performed by a detection unit in a processing device according to an embodiment of the present disclosure, in which the horizontal axis represents the number of times of processing and the vertical axis represents the area Ag [pixels].

[0088] 15 , each time the detection unit 130 calculates the area Ag, it compares the calculated area Ag with a threshold value ThA1, which is an example of the threshold value ThA. If the area Ag is equal to or smaller than the threshold value ThA1, the detection unit 130 determines that the state of the cutting process using the cutting tool 101 is normal. On the other hand, if the area Ag is larger than the threshold value ThA1, the detection unit 130 determines that abnormal vibration due to wear of the cutting edge is occurring.

[0089] Furthermore, the detection unit 130 may perform the detection process using a threshold value ThA2, which is an example of the threshold value ThA, instead of or in addition to the threshold value ThA1. More specifically, each time the detection unit 130 calculates the area Ag, the detection unit 130 compares the calculated area Ag with the threshold value ThA2. If the area Ag is equal to or smaller than the threshold value ThA2, the detection unit 130 determines that the state of the cutting process using the cutting tool 101 is normal. On the other hand, if the area Ag is larger than the threshold value ThA2, the detection unit 130 determines that chatter vibration, which is an abnormal vibration, is occurring. The threshold value ThA2 may be a value different from or the same as the threshold value ThA1.

[0090] In addition to or instead of chatter vibration and abnormal vibration due to wear of the cutting edge, the detection unit 130 may detect other abnormal vibrations that may cause a change in the plot P in the graph G, such as abnormal vibration due to chipping of the cutting edge. Furthermore, instead of or in addition to detecting abnormal vibrations, the detection unit 130 may determine the life of the cutting tool 101 based on the area Ag. As described above, wear of the cutting edge may increase the fundamental vibration. Therefore, the life of the cutting tool 101 can be determined based on the change in the area Ag that accompanies an increase in the fundamental vibration.

[0091] For example, the detection unit 130 detects the state of cutting using the cutting tool 101 based on the area Ag occupied by multiple plots P in each of multiple graphs G, each of which has different sizes of plot P. More specifically, the detection unit 130 calculates the area Ag occupied by each plot P in multiple graphs G, each of which has different sizes of plot P and which were created by the creation unit 120 using the same cutting resistances Fx and Fy. After calculating the area Ag for each graph G, the detection unit 130 compares the calculated area Ag for each graph G with multiple thresholds ThA that vary depending on the size of the plot P. For example, if at least one of the multiple areas Ag calculated for each graph G is larger than a corresponding threshold ThA1, the detection unit 130 determines that abnormal vibration due to wear of the cutting edge is occurring. Furthermore, for example, if at least one of the multiple areas Ag calculated for each graph G is larger than a corresponding threshold ThA2, the detection unit 130 determines that chatter vibration is occurring.

[0092] When the detection unit 130 determines that abnormal vibration is occurring, it performs a notification process to notify the user of the processing system 301 of the determination result. For example, the user receives the notification of the determination result and stops the cutting process using the cutting tool 101. Here, chatter vibration has a small amplitude in the early stages of occurrence, but as the chatter vibration grows, the amplitude increases, which may affect machining accuracy and tool life. The processing device 201 according to the embodiment of the present disclosure can detect chatter vibration with a small amplitude in the early stages of occurrence, and therefore can urge the user to stop cutting before it affects machining accuracy and tool life.

[0093] For example, the detection unit 130 performs a process of selectively displaying at least one of a plurality of graphs G having different sizes of plots P. More specifically, when the creation unit 120 stores graph information in the storage unit 140, the detection unit 130 performs a process of displaying the display graph Gdis included in the graph information on a display (not shown). Furthermore, the detection unit 130 performs a process of displaying, in accordance with a user operation, graphs G other than the display graph Gdis out of the plurality of graphs G having different sizes of plots P on a display (not shown).

[0094] The detection unit 130 may be configured to perform the detection process using, as an evaluation value, an area ratio Rg, which is the ratio of the area Ag to the area of ​​the entire region of the graph G, instead of or in addition to the area Ag. More specifically, the detection unit 130 calculates the area ratio Rg as the ratio of the number of pixels in the black region in the binary image to the number of pixels in the entire region of the graph G. After calculating the area ratio Rg, the detection unit 130 compares the calculated area ratio Rg with a predetermined threshold value ThB and detects abnormal vibration based on the comparison result. The threshold value ThB is set in advance based on the area ratio Rg of the area Ag to the area of ​​the entire region of the graph G created by the creation unit 120 when normal cutting is being performed.

[0095] (Simulation Results) FIGS. 16 to 18 are diagrams illustrating simulation results for explaining the abnormal vibration detection accuracy of a processing device according to an embodiment of the present disclosure. FIGS. 16 to 18 show simulation results for abnormal vibration detection accuracy when the frequency of the abnormal vibration is set to 20 times the frequency of the fundamental vibration and the amplitude of the abnormal vibration is changed from 0 to 0.5 times the amplitude of the fundamental vibration. In FIGS. 16 to 18, the horizontal axis represents the amplitude ratio of the abnormal vibration to the amplitude of the fundamental vibration. In FIG. 16, the vertical axis represents the standard deviation Ssd1 of the vibration amplitude. In FIG. 17, the vertical axis represents the area Ag. FIG. 17 shows simulation results for the area Ag in graph G, where the maximum value of the data related to the load of the cutting tool 101 corresponds to 169 pixels and the diameter of plot P is 11 pixels. In FIG. 18, the vertical axis represents the rate of change of the evaluation value relative to when the amplitude of the abnormal vibration is zero. The dashed line in Fig. 18 indicates the rate of change in the standard deviation Ssd1 when the amplitude of the abnormal vibration is zero as a reference. The solid line in Fig. 18 indicates the rate of change in the area Ag when the amplitude of the abnormal vibration is zero as a reference.

[0096] 16 to 18 , the rate of change of the area Ag, relative to when the amplitude of the abnormal vibration is zero, is greater than the rate of change of the standard deviation Ssd1, relative to when the amplitude of the abnormal vibration is zero. Therefore, by using the area Ag as the evaluation value, changes in the amplitude of the abnormal vibration can be detected with higher sensitivity than when the standard deviation Ssd1 is used as the evaluation value. Similarly, when the area ratio Rg is used as the evaluation value, changes in the amplitude of the abnormal vibration can be detected with higher sensitivity than when the standard deviation Ssd1 is used as the evaluation value.

[0097] 19 to 21 are diagrams illustrating simulation results for explaining the abnormal vibration detection accuracy of a processing device according to an embodiment of the present disclosure. FIGS. 19 to 21 show simulation results for abnormal vibration detection accuracy when the amplitude of the abnormal vibration is set to 0.05 times the amplitude of the fundamental vibration and the frequency of the abnormal vibration is changed from 2 to 100 times the frequency of the fundamental vibration. In FIGS. 19 to 21 , the horizontal axis represents the frequency ratio of the abnormal vibration frequency to the fundamental vibration frequency. In FIG. 19 , the vertical axis represents the standard deviation Ssd2 of the vibration amplitude. In FIG. 20 , the vertical axis represents the area Ag. FIG. 20 shows simulation results for the area Ag in graph G, where the maximum value of the data related to the load of the cutting tool 101 corresponds to 169 pixels and the diameter of plot P is 11 pixels. In FIG. 21 , the vertical axis represents the rate of change of the evaluation value relative to when the frequency of the abnormal vibration is twice the fundamental vibration. The dashed line in Fig. 21 indicates the rate of change of the standard deviation Ssd2 when the frequency of the abnormal vibration is twice that of the fundamental vibration, and the solid line in Fig. 21 indicates the rate of change of the area Ag when the frequency of the abnormal vibration is twice that of the fundamental vibration.

[0098] 19 to 21 , the rate of change of the area Ag, relative to when the frequency of the abnormal vibration is twice that of the fundamental vibration, is greater than the rate of change of the standard deviation Ssd2, relative to when the frequency of the abnormal vibration is twice that of the fundamental vibration. Therefore, by using the area Ag as the evaluation value, changes in the frequency of the abnormal vibration can be detected with higher sensitivity than when the standard deviation Ssd2 is used as the evaluation value. Similarly, when the area ratio Rg is used as the evaluation value, changes in the frequency of the abnormal vibration can be detected with higher sensitivity than when the standard deviation Ssd2 is used as the evaluation value.

[0099] 22 to 24 are diagrams illustrating simulation results for explaining the abnormal vibration detection accuracy of the processing device according to the embodiment of the present disclosure. In FIGS. 22 to 24 , the horizontal axis represents the radial depth of cut [mm]. In FIG. 22 , the vertical axis represents the standard deviation of the cutting resistances Fx and Fy. In FIG. 23 , the vertical axis represents the area Ag. FIG. 23 shows simulation results for the area Ag in graph G, where the maximum value of the load data on the cutting tool 101 corresponds to 175 pixels and the diameter of the plot P is 11 pixels. In FIG. 24 , the vertical axis represents the rate of change of the evaluation value. The dashed lines in FIGS. 22 and 23 represent simulation results for the evaluation value when only the fundamental vibration due to the cutting resistances Fx and Fy is generated. The solid lines in FIGS. 22 and 23 represent simulation results for the evaluation value when the fundamental vibration is subjected to abnormal vibration, the amplitude of which is 5% of the maximum value of the fundamental vibration and the frequency of which is 40 times the fundamental vibration. The dashed line in Fig. 24 indicates the rate of change in the standard deviation of the cutting forces Fx and Fy due to the application of abnormal vibrations, and the solid line in Fig. 24 indicates the rate of change in the area Ag due to the application of abnormal vibrations.

[0100] 22 and 24, when the radial depth of cut is 9 mm or more, the rate of change in the standard deviation of the cutting resistances Fx and Fy due to the application of abnormal vibration is large, so abnormal vibration can be detected by using the standard deviation of the cutting resistances Fx and Fy as the evaluation value. On the other hand, when the radial depth of cut is less than 9 mm, the rate of change in the standard deviation of the cutting resistances Fx and Fy due to the application of abnormal vibration is small and close to 1, so it is difficult to detect abnormal vibration when the standard deviation of the cutting resistances Fx and Fy is used as the evaluation value.

[0101] 23 and 24 , in contrast, the area Ag has a large rate of change in standard deviation due to the application of abnormal vibration, regardless of the amount of radial cutting. Specifically, the area Ag increases by 12% or more when abnormal vibration occurs whose amplitude is 5% of the maximum value of the fundamental vibration. Therefore, regardless of the amount of radial cutting, abnormal vibration can be detected by using the area Ag as an evaluation value. Note that, like the area Ag, the area ratio Rg has a large rate of change in standard deviation due to the application of abnormal vibration, and therefore abnormal vibration can be detected by using the area ratio Rg as an evaluation value.

[0102] (Size and Pitch PT of Plots P) Fig. 25 is a schematic diagram of a graph created by the creation unit in the processing device according to the embodiment of the present disclosure. Fig. 25 shows a graph G in a state where no abnormal vibration is occurring. With reference to Fig. 25, for example, the creation unit 120 creates the graph G including a plurality of plots P arranged on the periphery of a circle C1 of radius R based on the sensor measurement values ​​sx, sy, and sr.

[0103] Fig. 26 is a schematic diagram showing the positional relationship of plots in a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. Fig. 26 shows the positional relationship of two adjacent plots in Fig. 25. Referring to Fig. 26, the creation unit 120 creates a graph G in which at least some plots P are arranged so as to overlap with other plots P in a state in which no abnormal vibration is occurring, i.e., a state in which only fundamental vibration is occurring. Here, it is assumed that the diameter of the plots P is d, and the plots P are arranged at a constant pitch PT.

[0104] 27 is a schematic diagram showing the positional relationship of plots in a graph created by a creation unit in a processing device according to an embodiment of the present disclosure. Fig. 27 shows the positional relationship of plots P when abnormal vibration is occurring. Referring to Fig. 27, if the position of one of two adjacent plots P changes along the radial direction of circle C1 due to the occurrence of abnormal vibration, the overlapping area of ​​the two plots P becomes smaller, and therefore the area Ag occupied by plot P in graph G becomes larger. Therefore, by using the area Ag as an evaluation value, the occurrence of abnormal vibration can be detected.

[0105] 28 to 30 are diagrams illustrating simulation results for explaining the relationship between the pitch of plots included in graphs created by a processing device according to an embodiment of the present disclosure and detection accuracy. In FIGS. 28 to 30 , the horizontal axis represents the ratio Prt_pt [%] of the pitch PT to the diameter D of the circle C1, and the vertical axis represents the rate of change CRg of the area Ag relative to a zero amplitude of the abnormal vibration. The solid lines in FIGS. 28 to 30 represent the rate of change CRg in a state where a random abnormal vibration with a normal distribution having a standard deviation of 4% of the diameter D of the circle C1 is occurring. The dashed lines in FIGS. 28 to 30 represent the rate of change CRg in a state where a random abnormal vibration with a normal distribution having a standard deviation of 12% of the diameter D of the circle C1 is occurring. The dashed lines in FIGS. 28 to 30 represent the rate of change CRg in a state where a random abnormal vibration with a normal distribution having a standard deviation of 20% of the diameter D of the circle C1 is occurring.

[0106] Fig. 28 shows the relationship between the ratio Prt_pt and the rate of change CRg when the ratio Prt_d of the diameter d of the plot P to the diameter D of the circle C1 is 40%. Fig. 29 shows the relationship between the ratio Prt_pt and the rate of change CRg when the ratio Prt_d of the diameter d of the plot P to the diameter D of the circle C1 is 10%. Fig. 30 shows the relationship between the ratio Prt_pt and the rate of change CRg when the ratio Prt_d of the diameter d of the plot P to the diameter D of the circle C1 is 5%.

[0107] 28 to 30 , the smaller the diameter d of the plot P, the larger the rate of change CRg in the region where the ratio Prt_pt of the pitch PT is small. Therefore, by setting the diameter d of the plot P to a smaller value and setting the pitch PT of the plot P to a smaller value, abnormal vibration can be detected with higher sensitivity. However, the smaller the pitch PT, the greater the number of plots P required for detection processing.

[0108] On the other hand, the larger the diameter d of the plot P, the smaller the rate of decrease in the rate of change CRg with respect to an increase in the ratio Prt_pt. Therefore, when the diameter d of the plot P is set to a larger value, the degree of freedom in setting the pitch PT for detecting abnormal vibration is increased. Therefore, by setting the pitch PT to a larger value, abnormal vibration can be detected while reducing the number of plots P required for detection processing.

[0109] For example, the creation unit 120 creates a graph G in which the size of the plots P is set according to the pitch PT of the plots P. More specifically, the creation unit 120 acquires in advance the magnitude of the fundamental vibration that occurs when cutting is performed using the cutting tool 101. Next, the creation unit 120 acquires the magnitude of abnormal vibration that may occur when cutting is performed using the cutting tool 101, expressed as a ratio to the magnitude of the fundamental vibration. Next, the creation unit 120 determines the ratio Prt_pt of the pitch PT and the ratio Prt_d of the diameter d, which are capable of detecting abnormal vibration that may occur, based on, for example, the simulation results of FIGS. 28 to 30 . Note that instead of determining the ratio Prt_pt of the pitch PT, the creation unit 120 may acquire a ratio Prt_pt of the pitch PT that is preset based on the processing conditions, etc.

[0110] For example, the creation unit 120 creates a graph G including a plot P having a diameter d that is 5% or more and 20% or less of the maximum value of data based on measurement results of the strain sensor 20 acquired in advance before operation of the processing system 301. More specifically, in a state where no abnormal vibration is occurring, the creation unit 120 generates a graph G including a plurality of plots P arranged on the circumference of a circle C1 having a radius R, for example, and sets a ratio Prt_d of the diameter d of the plot P to the diameter D of the circle C1 in a numerical range of 5% or more and 20% or less. By setting the ratio Prt_d within such a numerical range, it is possible to ensure an overlapping area between the plots P in a state where no abnormal vibration is occurring, and in the event of abnormal vibration, the plots P do not extend beyond the graph G, and the overlapping of the plots P is more reliably resolved, thereby enabling abnormal vibration to be detected with higher sensitivity using an evaluation value such as the area Ag.

[0111] [Operation Flow] FIG. 31 is a flowchart defining an example of an operation procedure when a processing device according to an embodiment of the present disclosure acquires a sensor measurement value.

[0112] Referring to Figure 31, first, after starting cutting processing, the processing device 201 waits for a wireless signal from the wireless communication device 23 in the cutting tool 101 (NO in step S11), and when it receives a wireless signal (YES in step S11), it acquires the sensor measurement values ​​sx, sy, sr and identification information from the received wireless signal (step S12).

[0113] Next, the processing device 201 stores the acquired sensor measurement values ​​sx, sy, sr and identification information in the memory unit 140 (step S13), and waits for a new wireless signal from the wireless communication device 23 in the cutting tool 101 (NO in step S11).

[0114] FIG. 32 is a flowchart illustrating an example of an operation procedure when a processing device according to an embodiment of the present disclosure performs a detection process.

[0115] 32, first, the processing device 201 waits for the creation timing according to the creation period Pg (NO in step S21), and when the creation timing arrives (YES in step S21), it calculates the cutting resistances Fx and Fy at each measurement time point in the target period T based on the multiple sensor measurement values ​​sx, sy, sr in the target period T. Note that the processing device 201 may calculate moments Mx and My instead of or in addition to the cutting resistances Fx and Fy (step S22).

[0116] Next, the processing device 201 creates a graph G using the calculated cutting resistances Fx and Fy (step S23).

[0117] Next, the processing device 201 performs processing to display the display graph Gdis of the created graph G on a display (not shown) (step S24).

[0118] Next, the processing device 201 calculates the area Ag occupied by the plurality of plots P in the created graph G (step S25).

[0119] Next, the processing device 201 performs a detection process using the calculated area Ag as an evaluation value. More specifically, the processing device 201 compares the area Ag with a threshold value ThA and detects abnormal vibration based on the comparison result (step S26).

[0120] Next, when the processing device 201 determines that abnormal vibration or chatter vibration due to wear of the cutting blade is occurring, it performs a notification process to notify the user of the processing system 301 of the determination result (step S27).

[0121] Next, the processing device 201 waits for a new generation timing (NO in step S21).

[0122] Although the processing system 301 according to the embodiment of the present disclosure is configured to include the strain sensor 20, this is not limiting. The processing system 301 may also be configured to include an acceleration sensor instead of the strain sensor 20. The acceleration sensor measures the acceleration of the vibration of the shaft portion 10 as a physical quantity indicating the state of the load on the cutting tool 101 during cutting. In this case, the creation unit 120 in the processing device 201 creates a graph G based on the measurement results from the acceleration sensor. Compared to the acceleration sensor, the strain sensor 20 can detect deformation of the cutting tool 101 that affects machining accuracy. On the other hand, compared to the strain sensor 20, the acceleration sensor can detect smaller vibrations of the cutting tool 101.

[0123] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the creation unit 120 is configured to create a graph G in which the size of the plots P is set according to the pitch PT of the plots P, but this is not limited to this. The creation unit 120 may be configured to create a graph G including plots P having a size that is set regardless of the pitch PT.

[0124] In addition, in the processing device 201 according to the embodiment of the present disclosure, the creation unit 120 is configured to set the ratio Prt_d of the diameter d of the plot P to the diameter D of the circle C1 within a range of 5% to 20%, but this is not limiting. The creation unit 120 may be configured to set the ratio Prt_d to a value outside this range.

[0125] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the creation unit 120 is configured to create the graph G based on the measurement results of the strain sensor 20 at multiple measurement points in the period required for the cutting tool 101 to make multiple revolutions, but this is not limited to this. The creation unit 120 may be configured to create the graph G based on the measurement results of the strain sensor 20 at multiple measurement points in the period required for the cutting tool 101 to make one revolution.

[0126] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the creation unit 120 is configured to create multiple graphs Gb each having a different diameter of the plot Pb using the same cutting resistances Fx and Fy calculated based on the same sensor measurement values ​​sx, sy, and sr, but this is not limited thereto. The creation unit 120 may be configured to create only one graph G using the same cutting resistances Fx and Fy calculated based on the same sensor measurement values ​​sx, sy, and sr.

[0127] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the detection unit 130 is configured to perform processing to display the display graph Gdis included in the graph information on a display (not shown) when the creation unit 120 saves the graph information in the storage unit 140, but this is not limiting. The detection unit 130 may also be configured not to perform processing to display the graph G such as the display graph Gdis.

[0128] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the detection unit 130 is configured to detect the state of cutting using the cutting tool 101 based on the area Ag occupied by multiple plots P in each of multiple graphs G in which the plots P are different in size, but this is not limited to this. The detection unit 130 may also be configured to detect the state of cutting using the cutting tool 101 based on the area Ag occupied by multiple plots P in one graph G.

[0129] Furthermore, in the processing device 201 according to the embodiment of the present disclosure, the creation unit 120 is configured to create time-series graphs Ga and Gc and graphs Gb and Gd, but this is not limited to this. The creation unit 120 may be configured to create graphs Ga and Gc but not create graphs Gb and Gd. Furthermore, the creation unit 120 may be configured to create graphs Gb and Gd but not create graphs Ga and Gc.

[0130] Furthermore, although the processing system 301 according to the embodiment of the present disclosure is configured to include the cutting tool 101 used in milling, the present disclosure is not limited to this. The processing system 301 may be configured to include a generating tool used in generating tool machining instead of the cutting tool 101.

[0131] FIG. 33 is a diagram illustrating the configuration of a processing system according to a modified example of the embodiment of the present disclosure. Referring to FIG. 33 , compared to processing system 301, processing system 302 includes cutting tool 102 instead of cutting tool 101. Cutting tool 102 is used for turning a workpiece WK. For example, the workpiece WK is a cylindrical metal having a groove on its outer circumferential surface. A tip 14s is attached to cutting tool 102. Cutting tool 102 performs intermittent machining of the outer circumferential surface of the rotating workpiece WK.

[0132] The wireless communication unit 110 in the processing device 201 acquires the sensor measurement values ​​sx, sy, sr and the identification information from the wireless signal received from the wireless communication device 23 in the cutting tool 102. Then, the wireless communication unit 110 stores the sensor measurement values ​​sx, sy, sr in the storage unit 140 in association with the identification information.

[0133] 34 and 35 are diagrams showing examples of graphs created by the creation unit in the processing device according to the embodiment of the present disclosure. FIGS. 34 and 35 show graph Ge created by creation unit 120 when cutting is performed using cutting tool 103 under predetermined machining conditions Wc4. In graph Ge, the horizontal axis represents time [seconds] and the vertical axis represents strain ε [με]. Strain ε correlates with cutting resistance F. FIG. 34 shows graph Ge when no chatter vibration is occurring in cutting tool 102, and FIG. 35 shows graph Ge when chatter vibration is occurring in cutting tool 102.

[0134] 34 and 35 , the creation unit 120 creates a graph Ge, which is a time-series graph G including a plurality of plots Pe showing the correspondence between measurement time points and strain ε. The plots Pe are an example of plots P. For example, the shape of the plots Pe is circular. Note that the shape of the plots Pe may be a shape other than a circle, such as a rectangle or a triangle. For example, the creation unit 120 creates the graph Ge based on the measurement results of the strain sensor 20 at a plurality of measurement time points during a period required for the cutting workpiece WK to make a plurality of rotations.

[0135] Here, the absolute value of the strain ε in the graph Ge when chatter vibration is occurring is larger than that in the graph Ge when chatter vibration is not occurring. This is because, when chatter vibration is occurring, abnormal chatter vibration is added to the fundamental vibration, which is a normal vibration caused by the cutting edge biting into and separating from the workpiece. Chatter vibration has a higher frequency than the fundamental vibration and a smaller amplitude in the early stages of chatter vibration occurrence. Furthermore, the area Ag occupied by the plot Pe in the graph Ge when chatter vibration is occurring is larger than that in the graph Ge when chatter vibration is not occurring. This is because the range of possible values ​​of the strain ε in the graph Ge when chatter vibration is occurring is larger than that in the graph Ge when chatter vibration is not occurring, resulting in less overlap between multiple plots Pe.

[0136] When the creation unit 120 saves the graph Ge for the target period T in the storage unit 140, the detection unit 130 acquires the graph Ge from the storage unit 140. The detection unit 130 generates a binary image in which areas of the acquired graph Ge occupied by the plot Pe are colored black and areas of the graph Ge where the plot Pe is not present are colored white. The detection unit 130 calculates the number of pixels of the black area in the generated binary image as an area Ag. After calculating the area Ag, the detection unit 130 performs detection processing using the calculated area Ag as an evaluation value.

[0137] However, there is a demand for technology that can more accurately detect the state of cutting processing using a cutting tool. More specifically, normal vibrations are generally larger than abnormal vibrations, and the magnitude of abnormal vibrations is difficult to reflect in the standard deviation of the sensor measurement results. Therefore, it is not easy to detect the state of cutting processing using the standard deviation as an evaluation value. Furthermore, extracting the vibration components of abnormal vibrations using Fourier transform requires a processing device with a high sampling frequency. Furthermore, it is difficult to detect abnormal vibrations using a method that analyzes the envelope of a graph.

[0138] In contrast, the processing system 301 according to an embodiment of the present disclosure comprises a cutting tool, a strain sensor 20, and a processing device 201, wherein the strain sensor 20 measures a physical quantity indicating the load state of the cutting tool 101 during cutting processing, and the processing device 201 creates a graph G including multiple plots P indicating data regarding the load at each measurement time point based on the measurement results of the strain sensor 20 at multiple measurement time points, and detects the state of cutting processing using the cutting tool 101 based on the area occupied by the multiple plots P in the created G graph.

[0139] In this way, with a configuration for detecting the state of cutting processing based on the area Ag occupied by multiple plots P in graph G created based on the measurement results of strain sensor 20, a change in the position of plot P due to the occurrence of abnormal vibration is detected as a change in the area Ag occupied by multiple plots P in graph G, and abnormal vibration can be detected based on this change in area Ag. Furthermore, since the area Ag occupied by multiple plots P in graph G is more likely to reflect changes in the amplitude of abnormal vibration than the standard deviation of the measurement results of strain sensor 20, this area Ag can be used as an evaluation value to detect changes in the amplitude of abnormal vibration with higher sensitivity. Therefore, the state of cutting processing using cutting tool 101 can be detected more accurately.

[0140] The above-described embodiments should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims.

[0141] Each process (each function) in the above-described embodiments is realized by a processing circuit (circuitry) including one or more processors. The processing circuit may be configured as an integrated circuit or the like that combines one or more memories, various analog circuits, and various digital circuits in addition to the one or more processors. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the processes. The one or more processors may execute each of the processes according to the program read from the one or more memories, or may execute each of the processes according to a logic circuit designed in advance to execute each of the processes. The processor may be any of various processors suitable for computer control, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and an ASIC (Application Specific Integrated Circuit). Note that the physically separated processors may cooperate with each other to execute the processes. For example, the processors installed in the physically separated computers may cooperate with each other via a network such as a LAN (Local Area Network), a WAN (Wide Area Network), or the Internet to execute the processes. The program may be installed into the memory from an external server device or the like via the network, or may be distributed in a state stored on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a semiconductor memory, and then installed into the memory from the recording medium.

[0142] The above description includes the following additional features: [Supplementary Note 1] A processing system comprising: a cutting tool; a sensor; and a processing unit, wherein the sensor measures a physical quantity indicating a state related to a load on the cutting tool during cutting processing, the processing unit creates a graph including a plurality of plots indicating data related to the load at each measurement time point based on measurement results of the sensor at the plurality of measurement time points, and performs a detection process to detect a state of cutting processing using the cutting tool based on an area occupied by the plurality of plots in the created graph, and the processing unit performs at least one of detecting abnormal vibrations due to wear of a cutting edge of the cutting tool, detecting chatter vibrations, detecting abnormal vibrations due to chipping of the cutting edge, and determining the life of the cutting tool in the detection process.

[0143] DESCRIPTION OF SYMBOLS 10 Shaft portion 11 Shank portion 12 Blade mounting portion 13 Blade fixing portion 14, 14s Tip 17 Rotating shaft 18 Cutting resistance acting surface 20, 20A, 20B, 20C Strain sensor 22 Battery 23 Wireless communication device 24 Housing 101, 102 Cutting tool 110 Wireless communication unit 120 Creation unit 130 Detection unit 140 Storage unit 201 Processing device 210 Tool holder 220 Spindle 301, 302 Processing system G, Ga, Gb, Gd, Ge Graph P, Pa, Pb, Pd, Pe Plot ThA1 Threshold value C1 Circle R Radius d Diameter PT Pitch WK Cutting object

Claims

1. A processing system comprising: a cutting tool; a sensor; and a processing unit, wherein the sensor measures a physical quantity indicating a state related to the load on the cutting tool during cutting processing; the processing unit creates a graph including a plurality of plots showing data related to the load for each measurement time point based on measurement results of the sensor at the plurality of measurement time points; and detects the state of cutting processing using the cutting tool based on the area occupied by the plurality of plots in the created graph.

2. The processing system according to claim 1, wherein the processing unit creates the graph in which the size of the plots is set according to the pitch of the plots.

3. The processing system of claim 2, wherein the processing unit creates the graph including the plot having a diameter that is 5% or more of the maximum value of the data based on the measurement results of the sensor obtained in advance before operation of the processing system and that is 20% or less of the maximum value of the data.

4. A processing system according to any one of claims 1 to 3, wherein the processing unit creates the graph based on the measurement results of the sensor at the multiple measurement points during the period required for the cutting tool or the workpiece to be cut to rotate multiple times.

5. The processing system according to any one of claims 1 to 4, wherein the processing unit creates a plurality of the graphs in which the plot sizes are different.

6. The processing system according to claim 5, wherein the processing unit performs processing for selectively displaying at least one of the plurality of graphs.

7. The processing system according to claim 5 or 6, wherein the processing unit detects a state of cutting using the cutting tool based on an area occupied by the plurality of plots in each of the plurality of graphs.

8. A processing system according to any one of claims 1 to 7, wherein the processing unit creates the graph of a time series including the plurality of plots showing the correspondence between the measurement time points and the data.

9. A processing system as described in any one of claims 1 to 7, wherein the processing system is provided with a plurality of the sensors, and the processing unit creates the graph including the plurality of plots showing the correspondence of the data regarding the load in two directions in a plane perpendicular to the rotation axis of the cutting tool for each of the measurement points based on the measurement results of each of the sensors at the plurality of measurement points.

10. The processing system according to any one of claims 1 to 9, wherein the sensor is a strain sensor or an acceleration sensor.

11. A processing device comprising: a measurement result acquisition unit that acquires measurement results of physical quantities from a sensor that indicate a state related to the load on a cutting tool during cutting processing; a creation unit that creates a graph including a plurality of plots that indicate data related to the load for each measurement time point based on the measurement results of the sensor at multiple measurement time points acquired by the measurement result acquisition unit; and a detection unit that detects the state of cutting processing using the cutting tool based on the area occupied by the plurality of plots in the graph created by the creation unit.

12. A processing method in a processing device, comprising the steps of: acquiring a measurement result of a physical quantity from a sensor that indicates a state related to the load on a cutting tool during cutting processing; creating a graph including a plurality of plots showing data related to the load at each of the measurement points based on the acquired measurement results of the sensor at the plurality of measurement points; and detecting a state of cutting processing using the cutting tool based on the area occupied by the plurality of plots in the created graph.

13. A processing program used in a processing device, which causes a computer to function as: a measurement result acquisition unit that acquires measurement results of physical quantities that indicate a state related to the load on a cutting tool during cutting processing, which are measurement results of a sensor; a creation unit that creates a graph including a plurality of plots that indicate data related to the load for each measurement time point based on the measurement results of the sensor at multiple measurement time points acquired by the measurement result acquisition unit; and a detection unit that detects the state of cutting processing using the cutting tool based on the area occupied by the plurality of plots in the graph created by the creation unit.

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