Cutting system, display system, processing device, processing method and processing program

Abstract

The present invention achieves excellent performance related to the cutting edge in a cutting tool. A cutting system includes a cutting tool for milling, a plurality of sensors, and a processing unit. The cutting tool performs cutting using two or more cutting edges, the plurality of sensors measuring physical quantities representing a state related to the load on the cutting tool during cutting. The processing unit generates two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at multiple measurement timings. The load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool. Each of the generated two-dimensional data is classified into any one of a plurality of unit areas within the plane, equal to or greater than the number of the cutting edges, and an abnormality of the cutting edge is detected based on the two-dimensional data of each unit area.

Description

Technical Field

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

[0002] Patent Document 1 (Japanese Patent Application Laid-Open No. 2015-77658) discloses a state measurement device for measuring the state of a cutting tool during cutting, wherein the cutting tool comprises a rotating body having one or more cutting edges and rotating while the cutting edges contact a workpiece to perform machining. The state measurement device comprises: a measuring unit mounted on or near the cutting edges for measuring the state of the cutting edges; an AD converter mounted on the cutting tool for acquiring a measurement value measured by the measuring unit at a predetermined sampling rate and performing AD conversion; a transmitting unit for transmitting the acquired measurement value using digital wireless communication each time the measurement value is acquired from the AD converter; and a monitoring device disposed externally to the cutting tool, the monitoring device comprising: a receiving unit for receiving the measurement value transmitted by the transmitting unit; and a data management unit for displaying the measurement value on a display unit and storing the measurement value in a storage unit each time the measurement value is received by the receiving unit.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Laid-Open No. 2015-77658

[0006] Patent Document 2: Japanese Patent Application Laid-Open No. 2013-132734

[0007] Patent Document 3: Japanese Patent Application Publication No. 2018-43317

[0008] Patent Document 4: Japanese Patent Application Laid-Open No. 2018-24086

[0009] Patent Document 5: Japanese Patent Application Laid-Open No. 2006-71485

[0010] Patent Document 6: Japanese Patent Application Laid-Open No. 11-118625

[0011] Patent Document 7: Japanese Patent Application Laid-Open No. 2016-40071

[0012] Patent Document 8: U.S. Patent Application Publication No. 2015 / 0261207

[0013] Patent Document 9: European Patent Application Publication No. 3486737

[0014] Patent Document 10: Japanese Patent Application Laid-Open No. 2018-24086 Summary of the Invention

[0015] (1) The cutting system disclosed in the present invention comprises a cutting tool for milling, a plurality of sensors and a processing unit, wherein the cutting tool performs cutting using two or more cutting edges, the plurality of sensors measure physical quantities representing a state related to a load of the cutting tool during cutting, the processing unit generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool, and classifies each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects abnormalities of the cutting edge based on the two-dimensional data of each of the unit areas.

[0016] (8) The processing device disclosed in the present invention comprises: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing a state related to the load during cutting in a cutting tool for milling, wherein the cutting tool for milling performs cutting using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a detection unit, which classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

[0017] (9) The processing method disclosed in the present invention is a processing method in a processing device, and the processing method includes the following steps: obtaining measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, wherein the cutting tool for milling performs cutting using more than two cutting edges; based on the measurement results of each of the sensors at the multiple measurement moments obtained, generating two-dimensional data related to the load at each of the measurement moments, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and classifying each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detecting an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

[0018] (10) The processing program disclosed in the present invention is a processing program used in a processing device, which is used to enable a computer to function as the following functional units: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a detection unit, which classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects abnormalities of the cutting edge based on the two-dimensional data of each of the unit areas.

[0019] (11) The display system disclosed in the present invention comprises a cutting tool for milling processing, a plurality of sensors and a processing device, wherein the cutting tool performs cutting processing using two or more cutting edges, the plurality of sensors measure physical quantities representing a state related to the load of the cutting tool during cutting processing, and the processing device performs the following processing: based on the measurement results of each of the sensors at a plurality of measurement moments, two-dimensional data related to the load at each of the measurement moments are generated respectively, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool, each of the generated two-dimensional data is classified into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and the classification result is displayed.

[0020] (14) The processing device disclosed in the present invention comprises: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing a state related to the load during cutting in a cutting tool for milling, wherein the cutting tool for milling performs cutting using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a display processing unit, which performs the following processing: classifying each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and displaying the classification result.

[0021] (15) The processing method disclosed in the present invention is a processing method in a processing device, and the processing method includes the following steps: obtaining measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, wherein the cutting tool for milling performs cutting using two or more cutting edges; based on the measurement results of each of the sensors at the multiple measurement times obtained, generating two-dimensional data related to the load at each of the measurement times, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and classifying each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane and displaying the classification results.

[0022] (16) The processing program disclosed in the present invention is a processing program used in a processing device, which is used to enable a computer to function as the following functional units: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a display processing unit, which performs the following processing: classifying each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and displaying the classification result.

[0023] One embodiment of the present disclosure can be implemented not only as a cutting system having such a characteristic processing unit, but also as a semiconductor integrated circuit that realizes part or all of the cutting system. In addition, one embodiment of the present disclosure can be implemented not only as a processing device having such a characteristic processing unit, but also as a semiconductor integrated circuit that realizes part or all of the processing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a diagram showing the configuration of a cutting system according to an embodiment of the present disclosure.

[0025] Figure 2 It is a cross-sectional view showing the structure of a cutting tool according to an embodiment of the present disclosure.

[0026] Figure 3 It is an arrow-point view showing the structure of a cutting tool according to an embodiment of the present disclosure.

[0027] Figure 4 This is a diagram showing an example of measurement results of a strain sensor acquired by a wireless communication unit in a processing device according to an embodiment of the present disclosure.

[0028] Figure 5 This is a diagram showing an example of measurement results of a strain sensor acquired by a wireless communication unit in a processing device according to an embodiment of the present disclosure.

[0029] Figure 6 This is a diagram showing an example of measurement results of a strain sensor acquired by a wireless communication unit in a processing device according to an embodiment of the present disclosure.

[0030] Figure 7 This is a diagram showing an example of measurement results of a strain sensor acquired by a wireless communication unit in a processing device according to an embodiment of the present disclosure.

[0031] Figure 8 It is a diagram showing the configuration of a processing device in a cutting system according to an embodiment of the present disclosure.

[0032] Figure 9 It is a perspective view schematically showing a cutting tool according to an embodiment of the present disclosure.

[0033] Figure 10 This is a diagram showing an example of two-dimensional data generated by a generating unit in the processing device according to the embodiment of the present disclosure.

[0034] Figure 11 This is a diagram showing another example of two-dimensional data generated by the generating unit in the processing device according to the embodiment of the present disclosure.

[0035] Figure 12 This is a diagram showing an example of a result of classification of two-dimensional data by a processing unit in the processing device according to the embodiment of the present disclosure.

[0036] Figure 13 This is a diagram showing an example of the moving standard deviation ms calculated by the processing unit in the processing device according to the embodiment of the present disclosure.

[0037] Figure 14 1 is a diagram showing an example of an average value Ams calculated by a processing unit in the processing device according to the embodiment of the present disclosure.

[0038] Figure 15 This is a diagram showing an example of the difference Dms calculated by the processing unit in the processing device according to the embodiment of the present disclosure.

[0039] Figure 161 is a diagram showing an example of a moving standard deviation MS calculated by a processing unit in the processing device according to the embodiment of the present disclosure.

[0040] Figure 17 This is a frequency distribution showing calculation results of the cutting resistance of the cutting edge in the cutting tool according to the embodiment of the present disclosure.

[0041] Figure 18 This is a frequency distribution showing calculation results of the cutting resistance of the cutting edge in the cutting tool according to the embodiment of the present disclosure.

[0042] Figure 19 This is a diagram showing an example of a display screen displayed on a display unit in a processing device according to an embodiment of the present disclosure.

[0043] Figure 20 This is a diagram illustrating a method for determining a unit area by a processing unit in a processing device according to an embodiment of the present disclosure.

[0044] Figure 21 This is a flowchart that defines an example of an operation procedure when a processing device in a cutting system according to an embodiment of the present disclosure determines the state of a cutting edge.

[0045] Figure 22 This is a diagram showing an example of the sequence of detection processing and display processing in the cutting system according to the embodiment of the present disclosure.

[0046] Figure 23 This is a diagram showing an example of the moving average ma calculated by the processing unit in the processing device according to Modification 7 of the embodiment of the present disclosure.

[0047] Figure 24 This is a diagram showing an example of the average value Ama calculated by the processing unit in the processing device according to Modification 7 of the embodiment of the present disclosure.

[0048] Figure 25 This is a diagram showing an example of the difference Dma calculated by the processing unit in the processing device according to the seventh modification of the embodiment of the present disclosure.

[0049] Figure 26 This is a diagram showing an example of a moving standard deviation MA calculated by a processing unit in a processing device according to Modification 7 of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] Conventionally, a technique has been proposed in which a sensor is mounted on a cutting tool and an abnormality of a cutting edge of the cutting tool is detected based on measurement results of the sensor during cutting.

[0051] [Problems to be Solved by the Present Disclosure]

[0052] A technology that can surpass the technology of Patent Document 1 and achieve excellent performance related to the cutting edge in a cutting tool is desired.

[0053] The present disclosure has been made to solve the above-mentioned problems, and an object thereof is to provide a cutting system, a display system, a processing device, a processing method, and a processing program that can achieve excellent performance related to the cutting edge of a cutting tool.

[0054] [Effects of the Present Disclosure]

[0055] According to the present disclosure, it is possible to achieve excellent performance related to the cutting edge in a cutting tool.

[0056] [Description of Embodiments of the Present Disclosure]

[0057] First, the contents of the embodiments of the present disclosure will be listed and described.

[0058] (1) The cutting system involved in the embodiment of the present disclosure includes a cutting tool for milling processing, a plurality of sensors and a processing unit, the cutting tool performs cutting processing using more than two cutting edges, the plurality of sensors measure physical quantities representing the state related to the load of the cutting tool during cutting processing, the processing unit generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times, the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool, and each of the generated two-dimensional data is classified into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and based on the two-dimensional data of each of the unit areas, an abnormality of the cutting edge is detected.

[0059] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any one of multiple unit areas within a plane perpendicular to the rotation axis and detecting cutting edge abnormalities based on the two-dimensional data of each unit area, it is possible to distinguish and detect changes in the two-dimensional data of only a portion of the unit areas caused by the occurrence of cutting edge abnormalities from changes in the two-dimensional data of all unit areas caused by changes in cutting conditions. This allows accurate detection of cutting edge abnormalities. Consequently, it is possible to achieve excellent cutting edge-related performance in cutting tools.

[0060] (2) Preferably, the processing unit classifies each of the two-dimensional data into any one of the unit areas, the number of which is the same as the number of the cutting edges.

[0061] According to such a structure, the cutting resistance applied to each cutting edge can be analyzed using the two-dimensional data in each unit area. Therefore, when the two-dimensional data in only a part of the unit area changes, the cutting edge corresponding to the unit area can be determined as the cutting edge with an abnormality, and the two-dimensional data in each unit area can be used for various analyses other than detecting abnormalities of the cutting edge.

[0062] (3) Preferably, the processing unit sequentially generates and classifies the two-dimensional data, and detects abnormality of the cutting edge based on the number of the unit areas in which a temporal change in the two-dimensional data is equal to or greater than a predetermined value.

[0063] According to such a configuration, minute changes in the two-dimensional data in each unit area can be detected more reliably, and thus abnormalities in the cutting edge can be detected more accurately.

[0064] (4) More preferably, the processing unit calculates the index values ​​based on the two-dimensional data of the multiple unit areas respectively, and calculates the standard deviation of the difference between the index value of each unit area and the average value of the index value of each unit area, and detects the abnormality of the cutting edge based on the calculated standard deviation.

[0065] In this way, by focusing on the standard deviation of the difference between the index value of each unit area and the average value of the index value of each unit area, changes in two-dimensional data due to abnormalities in the cutting edge can be detected more accurately, thereby more accurately detecting abnormalities in the cutting edge.

[0066] (5) More preferably, the cutting system includes the sensors in a number that is independent of the number of the cutting edges in the cutting tool.

[0067] According to such a configuration, regardless of the number of cutting edges, a cutting system can be constructed using a plurality of cutting tools and a predetermined number of sensors.

[0068] (6) More preferably, the cutting system includes a smaller number of the sensors than the number of the cutting edges in the cutting tool.

[0069] According to such a configuration, the number of required sensors can be reduced compared to a system including the same number of sensors as the number of cutting edges, for example, and thus the cutting system can be constructed at a lower cost.

[0070] (7) More preferably, the cutting tool includes a shank, and the plurality of sensors are provided on the shank.

[0071] According to such a configuration, the physical quantity indicating the state of each cutting edge can be measured more accurately, and thus an abnormality of the cutting edge can be detected more accurately.

[0072] (8) The processing device involved in the embodiment of the present disclosure comprises: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a detection unit, which classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects abnormalities of the cutting edge based on the two-dimensional data of each of the unit areas.

[0073] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any one of multiple unit areas within a plane perpendicular to the rotation axis and detecting cutting edge abnormalities based on the two-dimensional data of each unit area, it is possible to distinguish and detect changes in the two-dimensional data of only a portion of the unit areas caused by the occurrence of cutting edge abnormalities from changes in the two-dimensional data of all unit areas caused by changes in cutting conditions. This allows accurate detection of cutting edge abnormalities. Consequently, it is possible to achieve excellent cutting edge-related performance in cutting tools.

[0074] (9) The processing method involved in the embodiment of the present disclosure is a processing method in a processing device, and the processing method includes the following steps: obtaining measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; based on the measurement results of each of the sensors at the multiple measurement times obtained, generating two-dimensional data related to the load at each of the measurement times, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and classifying each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detecting an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

[0075] In this way, by classifying each 2D data point generated based on the measurement results of multiple sensors into any one of multiple unit areas within a plane perpendicular to the rotation axis and detecting cutting edge abnormalities based on the 2D data of each unit area, it is possible to distinguish and detect changes in the 2D data of only a portion of the unit areas associated with the occurrence of a cutting edge abnormality from changes in the 2D data of all the unit areas associated with changes in cutting conditions. This allows accurate detection of cutting edge abnormalities. Consequently, it is possible to achieve excellent cutting edge-related performance in a cutting tool.

[0076] (10) The processing program involved in the embodiment of the present disclosure is a processing program used in a processing device, which is used to enable a computer to function as the following functional units: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a detection unit, which classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects abnormalities of the cutting edge based on the two-dimensional data of each of the unit areas.

[0077] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any one of multiple unit areas within a plane perpendicular to the rotation axis and detecting cutting edge abnormalities based on the two-dimensional data of each unit area, it is possible to distinguish and detect changes in the two-dimensional data of only a portion of the unit areas caused by the occurrence of cutting edge abnormalities from changes in the two-dimensional data of all unit areas caused by changes in cutting conditions. This allows accurate detection of cutting edge abnormalities. Consequently, it is possible to achieve excellent cutting edge-related performance in cutting tools.

[0078] (11) The display system involved in the embodiment of the present disclosure includes a cutting tool for milling processing, a plurality of sensors and a processing device, the cutting tool performs cutting processing using more than two cutting edges, the plurality of sensors measure physical quantities representing the state related to the load of the cutting tool during cutting processing, and the processing device performs the following processing: based on the measurement results of each of the sensors at multiple measurement times, two-dimensional data related to the load at each measurement time is generated respectively, the load is the load in two directions within a plane perpendicular to the rotation axis of the cutting tool, each of the generated two-dimensional data is classified into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and the classification result is displayed.

[0079] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any of a plurality of unit areas within a plane perpendicular to the rotation axis and displaying the classification results, it is possible to display the status of each cutting edge, for example, as two-dimensional data for each unit area, thereby enabling the user to identify the status of each cutting edge. This allows for achieving superior performance related to the cutting edge of the cutting tool.

[0080] (12) Preferably, the processing device performs processing such that, as a result of the classification, the two-dimensional data is displayed in a manner that differs for each of the unit areas.

[0081] According to such a configuration, the classification result of the two-dimensional data can be displayed in a more easily visually recognizable form.

[0082] (13) Preferably, the processing device performs the following processing: sequentially generates and classifies the two-dimensional data, and further displays information representing the time change of the two-dimensional data for each of the unit areas.

[0083] According to such a configuration, for example, the user can recognize the temporal change in the state of the cutting edge as the temporal change in the two-dimensional data for each unit area.

[0084] (14) The processing device involved in the embodiment of the present disclosure comprises: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a display processing unit, which performs the following processing: classifying each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and displaying the classification result.

[0085] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any of a plurality of unit areas within a plane perpendicular to the rotation axis and displaying the classification results, it is possible to display the status of each cutting edge, for example, as two-dimensional data for each unit area, thereby enabling the user to identify the status of each cutting edge. This allows for achieving superior performance related to the cutting edge of the cutting tool.

[0086] (15) The processing method involved in the embodiment of the present disclosure is a processing method in a processing device, and the processing method includes the following steps: obtaining measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; based on the measurement results of each of the sensors at the multiple measurement times obtained, generating two-dimensional data related to the load at each of the measurement times, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and classifying each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane and displaying the classification results.

[0087] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any of a plurality of unit areas within a plane perpendicular to the rotation axis and displaying the classification results, it is possible to display the status of each cutting edge, for example, as two-dimensional data for each unit area, thereby enabling the user to identify the status of each cutting edge. This makes it possible to achieve excellent performance related to the cutting edge of the cutting tool.

[0088] (16) The processing program involved in the embodiment of the present disclosure is a processing program used in a processing device, which is used to enable a computer to function as the following functional units: an acquisition unit, which acquires measurement results of multiple sensors, wherein the measurement results are measurement results of physical quantities representing the state related to the load during cutting in a cutting tool for milling processing, and the cutting tool for milling processing performs cutting processing using more than two cutting edges; a generation unit, which generates two-dimensional data related to the load at each measurement time based on the measurement results of each of the sensors at multiple measurement times acquired by the acquisition unit, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; and a display processing unit, which performs the following processing: classifying each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges within the plane and displaying the classification results.

[0089] In this way, by classifying the two-dimensional data generated based on the measurement results of multiple sensors into any of a plurality of unit areas within a plane perpendicular to the rotation axis and displaying the classification results, it is possible to display the status of each cutting edge, for example, as two-dimensional data for each unit area, thereby enabling the user to identify the status of each cutting edge. This allows for achieving superior performance related to the cutting edge of the cutting tool.

[0090] The following describes the embodiments of the present disclosure using the accompanying drawings. It should be noted that the same or corresponding parts in the drawings are marked with the same reference numerals and their descriptions are not repeated. In addition, at least some of the embodiments described below can be arbitrarily combined.

[0091] [Cutting system]

[0092] Figure 1 It is a diagram showing the configuration of a cutting system according to an embodiment of the present disclosure.

[0093] Reference Figure 1 The cutting system 301 includes a cutting tool 101 for milling, a plurality of strain sensors 20, and a processing device 201. The cutting system 301 is an example of a display system. The processing device 201 is an example of a processing unit in the cutting system 301.

[0094] [Cutting tools]

[0095] Cutting tool 101 performs cutting using two or more cutting edges. Cutting tool 101 is, for example, an end mill used in machine tools such as milling machines, and is used for rotary cutting of objects made of metal or the like. Cutting tool 101 is, for example, an end mill with an indexable insert. Cutting tool 101 is used while held by a tool holder 210, such as a spindle.

[0096] The tool holder 210 is mounted on the spindle 220 of the machine tool. The spindle 220 is cylindrical and applies rotational force to the tool holder 210. The tool holder 210 is a cylindrical member arranged on an extension of the spindle 220. Specifically, the upper end of the tool holder 210 is held by the spindle 220. The lower end of the tool holder 210 holds the cutting tool 101.

[0097] The cutting tool 101 includes a shank 11, a housing 24, a battery 22, a wireless communication device 23, and a blade mounting portion 12. Figure 1 In FIG, the housing 24 is shown by a two-dot chain line as an imaginary line.

[0098] The blade mounting portion 12 is provided on the cutting tool 101 at a position closer to the front end side than the shank 11 .

[0099] The blade attachment portion 12 includes, for example, four blade fixing portions 13. A cutting blade 14 is attached to each blade fixing portion 13.

[0100] For example, the strain sensor 20 is provided on the shank 11 of the cutting tool 101. More specifically, the strain sensor 20 is attached to the peripheral surface of the shank 11 via an adhesive or a bonding agent, for example.

[0101] The housing 24 accommodates the strain sensor 20 attached to the handle 11. Specifically, the housing 24 includes a bottom plate and side walls (not shown). The housing 24 covers the strain sensor 20 from below and from the sides.

[0102] The battery 22 and the wireless communication device 23 are housed in the housing 24. For example, the battery 22 and the wireless communication device 23 are fixed to the bottom plate or side wall of the housing 24. The wireless communication device 23 includes a communication circuit such as a communication IC (Integrated Circuit).

[0103] The battery 22 is connected to the strain sensor 20 and the wireless communication device 23 via an electric wire (not shown). The battery 22 supplies power to the strain sensor 20 and the wireless communication device 23 via the electric wire. A switch for switching on and off the power supply is provided on the electric wire.

[0104] For example, the cutting system 301 includes a number of strain sensors 20 that is unrelated to the number of cutting edges 14 in the cutting tool 101. Alternatively, for example, the cutting system 301 includes a smaller number of strain sensors 20 than the number of cutting edges 14 in the cutting tool 101. More specifically, the cutting system 301 includes, for example, three strain sensors 20.

[0105] Figure 2It is a cross-sectional view showing the structure of a cutting tool according to an embodiment of the present disclosure. Figure 2 yes Figure 1 Sectional view along line II-II.

[0106] Reference Figure 2 As the strain sensors 20, strain sensors 20A, 20B, and 20C are provided on the handle 11. The strain sensor 20B is provided at a position offset by 90° from the position where the strain sensor 20C is provided in the circumferential direction of the handle 11. The strain sensor 20A is provided at a position offset by 90° from the position where the strain sensor 20B is provided in the circumferential direction of the handle 11. The strain sensors 20A and 20C are provided at positions that are point-symmetrical with respect to the rotation axis 17 of the handle 11. The strain sensors 20A, 20B, and 20C may be provided at the same position in the direction along the rotation axis 17 of the handle 11, for example, or may be provided at different positions.

[0107] It should be noted that the strain sensors 20A, 20B, and 20C are independent of the position of the blade mounting portion 12 and can be provided on the circumferential surface of the shank 11, for example, as described above. In other words, the strain sensors 20A, 20B, and 20C do not need to be provided on the circumferential surface of the shank 11 at positions extending from the blade fixing portion 13 along the rotation axis 17.

[0108] For the sake of description, the direction from the rotation axis 17 toward the position where the strain sensor 20A is provided in a plane perpendicular to the rotation axis 17 is referred to as the X direction, and the direction from the rotation axis 17 toward the position where the strain sensor 20B is provided is referred to as the Y direction.

[0109] Figure 3 It is an arrow-point view showing the structure of a cutting tool according to an embodiment of the present disclosure. Figure 3 It is from Figure 1 The forward view when observing from direction III.

[0110] Reference Figure 3 The blade mounting portion 12 includes a blade fixing portion 13A, a blade fixing portion 13B, a blade fixing portion 13C, and a blade fixing portion 13D as the blade fixing portion 13. The blade fixing portion 13A, the blade fixing portion 13B, the blade fixing portion 13C, and the blade fixing portion 13D are respectively provided at positions offset by 90 degrees in the clockwise direction in the circumferential direction of the blade mounting portion 12.

[0111] A cutting edge 14A, a cutting edge 14B, a cutting edge 14C, and a cutting edge 14D are attached to the blade fixing portion 13A, the blade fixing portion 13B, the blade fixing portion 13C, and the blade fixing portion 13D, respectively, as the cutting edges 14 .

[0112] The cutting edge 14 is, for example, a reground blade. The cutting edge 14 is attached to the blade fixing portion 13, for example, by screwing. It should be noted that the cutting edge 14 may be fixed to the blade fixing portion 13 by means other than screwing. Alternatively, the cutting tool 101 may be a so-called solid end mill, having a cutting edge 14 integral with the shank 11 in place of the blade fixing portion 12.

[0113] The strain sensor 20 measures a physical quantity representing 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 shank 11 in a direction parallel to the rotation axis 17 as a physical quantity representing a state related to the load on the cutting tool 101 during cutting.

[0114] Figures 4 to 7 This is a diagram showing an example of measurement results of a strain sensor acquired by a wireless communication unit in a processing device according to an embodiment of the present disclosure. Figure 4 is time series data indicating the measurement result of the strain ε by the strain sensor 20A, Figure 5 yes Figure 4 Magnified view of area A in FIG. Figure 6 is time series data indicating the measurement result of the strain ε by the strain sensor 20B, Figure 7 yes Figure 6 Magnified view of area B in . Figures 4 to 7 In the graph, the horizontal axis is time [seconds] and the vertical axis is strain [με].

[0115] Reference Figures 4 to 7 The strain sensor 20 measures the strain ε during the period from the start time ts to the end time te of the cutting process, 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).

[0116] Wireless communication device 23 performs analog-to-digital (A / D) conversion on analog signals received from strain sensor 20 at a predetermined sampling cycle, generating sensor measurement values ​​as converted digital values. More specifically, wireless communication device 23 generates sensor measurement value sx by A / D converting the analog signal representing strain ε received from strain sensor 20A, generates sensor measurement value sy by A / D converting the analog signal representing strain ε received from strain sensor 20B, and generates sensor measurement value sr by A / D converting the analog signal representing strain ε received from strain sensor 20C.

[0117] The wireless communication device 23 adds a time stamp indicating a sampling timing to the generated sensor measurement values ​​sx, sy, and sr, and stores the time stamped sensor measurement values ​​sx, sy, and sr in a storage unit (not shown).

[0118] The wireless communication device 23, for example, obtains one or more sets of sensor measurement values ​​sx, sensor measurement values ​​sy, and sensor measurement values ​​sr from the storage unit at a predetermined period, generates a wireless signal containing the obtained sensor measurement values ​​sx, sensor measurement values ​​sy, sensor measurement values ​​sr and the identification information of the corresponding strain sensor 20, and sends the generated wireless signal to the processing device 201.

[0119] [Processing device]

[0120] Figure 8 It is a diagram showing the configuration of a processing device in a cutting system according to an embodiment of the present disclosure.

[0121] Reference Figure 8 The processing device 201 includes a wireless communication unit 110, a generating unit 120, a processing unit 130, a storage unit 140, and a display unit 150. The wireless communication unit 110 is an example of an acquiring unit. The processing unit 130 is an example of a detecting unit and an example of a display processing unit.

[0122] The wireless communication unit 110 is implemented, for example, by a communication circuit such as a communication IC. The generation unit 120 and the processing unit 130 are implemented, for example, by processors such as a CPU (Central Processing Unit) and a DSP (Digital Signal Processor). The storage unit 140 is, for example, a nonvolatile memory. The display unit 150 is, for example, a display. It should be noted that the display unit 150 may also be provided external to the processing device 201.

[0123] (Wireless Communications Department)

[0124] The wireless communication unit 110 acquires a measurement result of the strain sensor 20 that measures a physical quantity indicating a state related to a load applied to the cutting tool 101 during cutting.

[0125] 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, for example, a communication protocol such as ZigBee in accordance with IEEE 802.15.4, Bluetooth (registered trademark) in accordance with IEEE 802.15.1, or UWB (Ultra WideBand) in accordance with IEEE 802.15.3a. It should be noted that communication protocols other than those listed above may also be used between the wireless communication device 23 and the wireless communication unit 110.

[0126] The wireless communication unit 110 obtains the sensor measurement values ​​sx, sy, and sr, as well as the identification information, based on the wireless signal received from the wireless communication device 23 in the cutting tool 101. The wireless communication unit 110 then stores the sensor measurement values ​​sx, sy, and sr in the storage unit 140 in association with the identification information.

[0127] (Generation Department)

[0128] The generation unit 120 generates two-dimensional data D related to the load at each measurement time based on the measurement results of each strain sensor 20 at multiple measurement times obtained by the wireless communication unit 110. The load is the load in two directions within the plane perpendicular to the rotation axis 17 of the shank 11 in the cutting tool 101.

[0129] When the sensor measurement values ​​sx, sy, and sr are stored in the storage unit 140 via the wireless communication unit 110 , the generation unit 120 generates two-dimensional data D based on the sensor measurement values ​​sx, sy, and sr stored in the storage unit 140 .

[0130] Figure 9 It is a perspective view schematically showing a cutting tool according to an embodiment of the present disclosure.

[0131] Reference Figure 9 When cutting is performed by the cutting tool 101 , a load, ie, a cutting resistance F [N], is applied to the cutting edge 14 from the cutting object.

[0132] For example, the generating unit 120 generates two-dimensional data D representing the moment Mx generated by the load in the X direction and the moment My generated by the load in the Y direction within the cutting resistance action surface 18 based on the sensor measurement value sx, the sensor measurement value sy, and the sensor measurement value sr. The cutting resistance action surface 18 is a plane perpendicular to the rotation axis 17 of the shank 11 and is a plane through which the cutting edge 14 passes.

[0133] More specifically, the storage unit 140 stores a conversion formula for converting the sensor measurement values ​​sx, sy, and sr into the moments Mx and My. For example, this conversion formula is pre-created using the techniques described in Patent Documents 5 and 6. More specifically, this conversion formula is a conversion matrix pre-created based on the sensor measurement values ​​sx, sy, and sr obtained when a known load is applied to the cutting tool 101.

[0134] The generator 120 generates two-dimensional data D representing the moment Mx and the moment My based on the sensor measurement value sx, the sensor measurement value sy, the sensor measurement value sr and the conversion matrix in the storage 140 .

[0135] The generator 120 sequentially generates two-dimensional data D. More specifically, each time the sensor measurement values ​​sx, sy, and sr are stored in the storage unit 140 via the wireless communication unit 110 , the generator 120 generates the two-dimensional data D and outputs the generated two-dimensional data D to the processing unit 130 .

[0136] It should be noted that the generation unit 120 can also be configured to generate two-dimensional data D representing the strain ε at the position where the strain sensor 20A is set and the strain ε at the position where the strain sensor 20B is set based on the sensor measurement value sx, the sensor measurement value sy, and the sensor measurement value sr without using the conversion matrix.

[0137] (Processing Department)

[0138] Figure 10 This is a diagram showing an example of two-dimensional data generated by a generating unit in the processing device according to the embodiment of the present disclosure. Figure 10 This is a graph in which approximately 8,000 two-dimensional data D generated based on the sensor measurement values ​​sx, sy, and sr during the period before the abnormality of the cutting edge 14 occurs are plotted on a two-dimensional coordinate C (C1) with the vertical axis being the moment Mx [Nm] and the horizontal axis being the moment My [Nm].

[0139] Figure 11 This is a diagram showing another example of two-dimensional data generated by the generating unit in the processing device according to the embodiment of the present disclosure. Figure 11 This is a graph in which approximately 8,000 two-dimensional data D generated based on the sensor measurement values ​​sx, sensor measurement values ​​sy, and sensor measurement values ​​sr during the period after a defect occurs on a certain cutting edge 14 are plotted on a two-dimensional coordinate C (C2) with the vertical axis being the moment Mx [Nm] and the horizontal axis being the moment My [Nm].

[0140] Reference Figure 10 as well as Figure 11 The two-dimensional data D generated by the generator 120 slightly changes before and after the chipping of the cutting edge 14. The processor 130 analyzes the two-dimensional data D generated by the generator 120 to detect abnormalities such as chipping of the cutting edge 14.

[0141] More specifically, the processing unit 130 performs classification processing to classify each two-dimensional data D generated by the generating unit 120 into any one of a plurality of unit areas A, which is greater than the number of cutting edges 14, within a plane perpendicular to the rotation axis 17. For example, as a classification process, the processing unit 130 classifies each two-dimensional data D into any one of a plurality of unit areas A at the two-dimensional coordinate C1. The processing unit 130 then performs detection processing to detect abnormalities in the cutting edge 14 based on the two-dimensional data D for each unit area.

[0142] Unit area A is each area obtained by dividing 360 degrees into n equal parts. Here, n is an integer greater than the number of cutting edges 14. For example, unit area A is each area obtained by dividing a plane perpendicular to rotation axis 17 into n equal parts around rotation axis 17 using a plurality of straight lines on the plane and passing through rotation axis 17. Alternatively, unit area A is each area obtained by dividing a two-dimensional coordinate C1 into n equal parts around the origin using a plurality of straight lines passing through the origin.

[0143] (Classification processing)

[0144] Figure 12 This is a diagram showing an example of a result of classification of two-dimensional data by a processing unit in the processing device according to the embodiment of the present disclosure.

[0145] Reference Figure 12 The two-dimensional data D generated by the generator 120 has a substantially cross shape on the two-dimensional coordinates C and can be classified into four data groups extending from the origin. Here, each data group corresponds to the cutting resistance F experienced by each cutting edge 14 of the cutting tool 101.

[0146] Therefore, for example, the processing unit 130 classifies the plurality of two-dimensional data D received from the generating unit 120 into any one of the unit areas A, the number of which is the same as the number of cutting edges 14. That is, the processing unit 130 classifies each two-dimensional data D into any one of the four unit areas A in the two-dimensional coordinate C, namely, unit area A1, unit area A2, unit area A3, and unit area A4. Unit area A1, unit area A2, unit area A3, and unit area A4 are the areas obtained by dividing the two-dimensional coordinate C1 into four equal parts around the origin using two straight lines passing through the origin of the two-dimensional coordinate C1.

[0147] More specifically, unit areas A1, A2, A3, and A4 are areas divided in two-dimensional coordinates C by boundary lines L1 and L2, which are two straight lines passing through the origin in two-dimensional coordinates C and are orthogonal to each other.

[0148] For example, storage unit 140 stores a quadratic function F1 representing boundary line L1 and a quadratic function F2 representing boundary line L2. For example, processing unit 130 pre-generates quadratic functions F1 and F2 based on a plurality of two-dimensional data D received from generating unit 120, and stores the generated quadratic functions F1 and F2 in storage unit 140. The process of generating quadratic functions F1 and F2 will be described later.

[0149] For example, the storage unit 140 stores correspondence information R indicating the correspondence between each unit area A and each cutting edge 14. For example, this correspondence information R is pre-generated based on two-dimensional data D, which is generated based on sensor measurement values ​​sx, sy, and sr acquired by the processing device 201 during cutting using the test cutting edge 14. Hereinafter, unit area A1 corresponds to the cutting edge 14A, unit area A2 corresponds to the cutting edge 14B, unit area A3 corresponds to the cutting edge 14C, and unit area A4 corresponds to the cutting edge 14D.

[0150] When the processing unit 130 receives the two-dimensional data D from the generating unit 120, it determines the unit area A to which the moment Mx and moment My belong based on the moment Mx and moment My shown in the received two-dimensional data D and the quadratic functions F1 and quadratic functions F2 in the storage unit 140, and classifies the two-dimensional data D into the determined unit area A.

[0151] For example, the processing unit 130 sequentially classifies the two-dimensional data D received from the generating unit 120. More specifically, each time the processing unit 130 receives the two-dimensional data D from the generating unit 120, the processing unit 130 classifies the received two-dimensional data D into any unit area A. When classifying the two-dimensional data D into any unit area A, the processing unit 130 assigns classification information indicating the unit area A to be classified to the two-dimensional data D and stores the two-dimensional data D, to which the classification information is assigned, in the storage unit 140.

[0152] Hereinafter, the two-dimensional data D classified into the unit area A1 will be referred to as "two-dimensional data D1", the two-dimensional data D classified into the unit area A2 will be referred to as "two-dimensional data D2", the two-dimensional data D classified into the unit area A3 will be referred to as "two-dimensional data D3", and the two-dimensional data D classified into the unit area A4 will be referred to as "two-dimensional data D4".

[0153] (Detection and processing)

[0154] For example, the processing unit 130 performs detection processing based on the number of unit areas A in which the temporal variation of the two-dimensional data D is equal to or greater than a predetermined value.

[0155] For example, the processing unit 130 calculates the index value based on the two-dimensional data D of each of the plurality of unit areas A. Then, the processing unit 130 performs detection processing based on the temporal change of the calculated index value.

[0156] More specifically, when classifying the two-dimensional data D received from the generating unit 120, the processing unit 130 calculates the moving standard deviation ms of the distance R from the origin of the two-dimensional data D in each unit area A as an index value for each unit area A. Specifically, the processing unit 130 calculates the moving standard deviation ms1 of the distance R1 of the two-dimensional data D1, the moving standard deviation ms2 of the distance R2 of the two-dimensional data D2, the moving standard deviation ms3 of the distance R3 of the two-dimensional data D3, and the moving standard deviation ms4 of the distance R4 of the two-dimensional data D4.

[0157] Figure 13 This is a diagram showing an example of the moving standard deviation ms calculated by the processing unit in the processing device according to the embodiment of the present disclosure. Figure 13 A graph G1 is shown with the horizontal axis representing time [seconds] and the vertical axis representing the standard deviation of movement in ms [Nm]. Figure 13 In the figure, the solid line represents the moving standard deviation ms1, the dotted line represents the moving standard deviation ms2, the single-dot chain line represents the moving standard deviation ms3, and the double-dot chain line represents the moving standard deviation ms4.

[0158] Reference Figure 13 The processing unit 130 performs detection processing based on the time change of the calculated moving standard deviation ms.

[0159] Here, each moving standard deviation ms is a value corresponding to the cutting resistance F experienced by each cutting edge 14 in the cutting tool 101. Furthermore, when cutting conditions such as the amount of cut change, the cutting resistance F experienced by all cutting edges 14 changes with the change in cutting conditions, causing the moving standard deviation ms in all unit areas A to change. On the other hand, when an abnormality occurs in a portion of the cutting edges 14, the cutting resistance F experienced by the abnormal cutting edge 14 changes, causing the moving standard deviation ms in the unit area A corresponding to only that cutting edge 14 to change.

[0160] Therefore, the processing unit 130 monitors the changes in each moving standard deviation ms. When all the moving standard deviations ms change by more than a predetermined value, it is judged that the change in the moving standard deviation ms is not caused by an abnormality in the cutting edge 14. On the other hand, when it is detected that a part of the moving standard deviations ms has changed by more than a predetermined value, it is judged that an abnormality has occurred in the cutting edge 14.

[0161] However, the change in the moving standard deviation ms caused by an abnormality in the cutting edge 14 is minute and sometimes cannot be easily detected. Therefore, for example, the processing unit 130 calculates the moving standard deviation MS as the difference Dms between the moving standard deviation ms of each unit area A and the average value Ams of the moving standard deviations ms of each unit area A.

[0162] More specifically, the processing unit 130 calculates the average value Ams of the moving standard deviations ms1 to ms4. The processing unit 130 then calculates the moving standard deviations MS, which are the differences Dms between each moving standard deviation ms and the average value Ams of the moving standard deviations ms. Specifically, the processing unit 130 calculates moving standard deviation MS1, which is the difference Dms1 between the moving standard deviation ms1 and the average value Ams; moving standard deviation MS2, which is the difference Dms2 between the moving standard deviation ms2 and the average value Ams; moving standard deviation MS3, which is the difference Dms3 between the moving standard deviation ms3 and the average value Ams; and moving standard deviation MS4, which is the difference Dms4 between the moving standard deviation ms4 and the average value Ams.

[0163] Figure 14 1 is a diagram showing an example of an average value Ams calculated by a processing unit in the processing device according to the embodiment of the present disclosure. Figure 14 A graph G2 is shown in which the horizontal axis represents time (seconds) and the vertical axis represents the average value Ams (Nm).

[0164] Figure 15 This is a diagram showing an example of the difference Dms calculated by the processing unit in the processing device according to the embodiment of the present disclosure. Figure 15 A graph G3 is shown with the horizontal axis representing time (seconds) and the vertical axis representing the difference Dms (Nm). Figure 15 In the figure, the solid line represents the differential Dms1, the dotted line represents the differential Dms2, the one-dot chain line represents the differential Dms3, and the two-dot chain line represents the differential Dms4.

[0165] Figure 16 1 is a diagram showing an example of a moving standard deviation MS calculated by a processing unit in the processing device according to the embodiment of the present disclosure. Figure 16 The graph G4 is shown with the horizontal axis representing time (seconds) and the vertical axis representing the moving standard deviation MS (Nm). Figure 16 In FIG. 1 , the solid line represents the moving standard deviation MS1 ​​, the dotted line represents the moving standard deviation MS2 , the one-dot chain line represents the moving standard deviation MS3 , and the two-dot chain line represents the moving standard deviation MS4 .

[0166] Reference Figure 16 For example, the processing unit 130 detects an abnormality in the cutting edge 14 based on the calculated moving standard deviation MS. More specifically, the processing unit 130 monitors changes in the moving standard deviations MS. If all moving standard deviations MS increase, the processing unit 130 determines that the increase in moving standard deviations MS is not caused by an abnormality in the cutting edge 14. On the other hand, if a portion of the moving standard deviations MS increases, the processing unit 130 determines that an abnormality has occurred in the cutting edge 14.

[0167] Specifically, the processing unit 130 determines that the moving standard deviations MS increase simultaneously at time ts, the start time, and time te, the end time of the cutting process, but the increase in the moving standard deviations MS is not caused by an abnormality in the cutting edge 14. On the other hand, when the processing unit 130 detects an increase in only the moving standard deviations MS2 and MS3 at time t1 and time t2, the processing unit 130 determines, based on the correspondence information R in the storage unit 140, that an abnormality has occurred in at least one of the cutting edges 14B and 14C corresponding to the unit areas A2 and A3, respectively.

[0168] Here, when a chip occurs on a cutting edge 14, the amount of cutting by that cutting edge 14 decreases, and the cutting resistance F increases at the cutting edge 14 next to that cutting edge 14 in contact with the object being cut. Specifically, when a chip occurs on cutting edge 14A, the cutting resistance F increases at cutting edge 14B next to cutting edge 14A in contact with the object being cut. As a result, in some cases, not only does the moving standard deviation MS1 ​​corresponding to the chipped cutting edge 14A increase, but the moving standard deviation MS2 corresponding to cutting edge 14B in contact with the object being cut may also increase.

[0169] Therefore, when the moving standard deviation MS2 and the moving standard deviation MS3 in the adjacent multiple unit areas A2 and unit areas A3 increase, the processing unit 130 determines that the cutting edge 14B that first contacts the cutting object among the cutting edges 14B and 14C that continuously contact the cutting object corresponding to the moving standard deviation MS2 and the moving standard deviation MS3 is defective.

[0170] according to Figure 13 as well as Figure 15It can be seen that the difference in the amount of change of the moving standard deviation MS per unit area A is larger than the difference in the amount of change of the moving standard deviation ms per unit area A. Therefore, by performing detection processing using the moving standard deviation MS, an abnormality in the cutting edge 14 can be more easily detected.

[0171] (About moving standard deviation MS)

[0172] The significance of calculating the difference Dms between the moving standard deviation ms and the average value Ams will be described in detail below.

[0173] After the start of cutting using the cutting tool 101 , the cutting resistance Fn applied to the cutting edge 14 that cuts into the object to be cut for the nth time is expressed by the following formula (1).

[0174] [Number 1]

[0175] Fn=K(ap+hn)×(fz+rn-r(n-1))···(1)

[0176] Here, K is the specific cutting resistance. ap is the depth of cut of the cutting edge 14 in the direction of the rotation axis 17. hn is the positional offset of the cutting edge 14, which engages the workpiece, in the direction of the rotation axis 17. fz is the feed rate per edge. rn is the positional offset of the cutting edge 14, which engages the workpiece, in the radial direction of the shank 11. It should be noted that the depth of cut ap and the feed rate fz are set values ​​as cutting conditions.

[0177] In the formula (1), if rn-r(n-1) is set as Δrn and the formula (1) is expanded, the cutting resistance Fn is expressed as the following formula (2).

[0178] [Number 2]

[0179] Fn=K(ap×fz+ap×Δrn+hn×fz+hn×Δrn)··, (2)

[0180] In the formula (2), the term hn×Δrn is a value so small as to be negligible, and therefore the cutting resistance force Fn can be expressed by the following formula (3).

[0181] [Number 3]

[0182] Fn=K(ap×fz+ap×Δrn+hn×fz)···(3)

[0183] In equation (3), for example, the term ap × Δrn is approximately three times the value of the term hn × fz, and the term ap × fz is approximately ten times the value of the term ap × Δrn. ap and fz are values ​​determined based on the settings in the machining conditions. On the other hand, hn and Δrn are values ​​that result from a misalignment in the mounting position of the cutting edge 14 when it is mounted on the blade fixing portion 13 or a defect in the cutting edge 14. Therefore, focusing on hn and Δrn allows for more accurate detection of a defect in the cutting edge 14.

[0184] Figure 17 as well as Figure 18 is a frequency distribution showing the calculation results of the cutting resistance of the cutting edge in the cutting tool according to the embodiment of the present disclosure. More specifically, Figure 17 as well as Figure 18 The frequency distribution obtained by numerically calculating the deviation of the cutting resistance of the cutting edge 14 by taking into account the deviation of the mounting position when the cutting edge 14 is mounted on the blade fixing portion 13 is shown. Figure 17 as well as Figure 18 In the graph, the horizontal axis represents the ratio P [%] of the cutting resistance F to the product apfz of the cutting depth ap and the feed rate fz, and the vertical axis represents the frequency. Figure 17 The ratio P of the cutting resistance F of one of the four cutting edges 14 mounted on the cutting tool 101, that is, the ratio Ps, is shown. Figure 18 The ratio P, ie, the ratio Pm, is shown as the ratio of the average value Fmean of the cutting resistance F of the four cutting edges 14 attached to the cutting tool 101 .

[0185] Reference Figure 17 It is considered that the deviation of the ratio Ps of the cutting resistance F of one cutting edge 14 is caused by the deviation of the mounting position when the cutting edge 14 is mounted on the blade fixing portion 13. Figure 18 The ratio Pm of the average value Fmean of the cutting resistance F of each cutting edge 14 has a smaller deviation than the ratio Ps, and the ratio Pm can be regarded as 100%. In other words, the average value Fmean can be assumed to be substantially equal to the value determined based on the set values ​​set as the cutting conditions, namely, the cutting depth ap and the feed rate fz. Specifically, it can be expressed by the following formula (4).

[0186] [Number 4]

[0187] Fmean=K×ap×fz···(4)

[0188] From the equations (3) and (4), the difference DF between the cutting resistance Fn and the average value Fmean can be expressed by the following equation (5).

[0189] [Number 5]

[0190] DF=Fn-Fmean=K(ap×Δrn+hn×fz)···(5)

[0191] As shown in equation (5), the difference DF is obtained by deleting the term ap×fz from equation (3) and is represented by only the term containing hn or Δrn. Therefore, by focusing on the difference DF between the cutting resistance Fn and the average value Fmean, accurate detection processing can be performed.

[0192] As described above, the moving standard deviation ms is a value corresponding to the cutting resistance F experienced by each cutting edge 14 in the cutting tool 101. Meanwhile, the average value Ams of the moving standard deviations ms1 to ms4 is a value corresponding to the average value Fmean of the cutting resistance F experienced by all cutting edges 14. Therefore, by calculating the difference Dms between the moving standard deviation ms and the average value Ams and focusing on the moving standard deviation MS of the difference Dms, changes in the two-dimensional data D, i.e., changes in the cutting resistance F, due to the occurrence of an abnormality in the cutting edge 14 can be more accurately detected, enabling more accurate detection processing.

[0193] It should be noted that the processing unit 130 is not limited to a structure for detecting abnormalities of the cutting edge 14 based on the moving standard deviation MS. For example, it can also be a structure for detecting abnormalities of the cutting edge 14 using other methods such as an autoregressive model (AR model), an autoregressive moving average model (ARMA model), and Bayesian Online Changepoint Detection.

[0194] (Display Processing)

[0195] After performing the classification process, the processing unit 130 performs a display process for displaying the classification result on the display unit 150 .

[0196] Figure 19 This is a diagram showing an example of a display screen displayed on a display unit in a processing device according to an embodiment of the present disclosure.

[0197] Reference Figure 19 For example, the processing unit 130 performs the following processing: as a result of the classification, the display screen DS including the drawing illustrating the two-dimensional data D and the two-dimensional coordinates C of the unit area A is displayed on the display unit 150.

[0198] For example, the processing unit 130 performs processing to display the two-dimensional data D in a manner that differs for each unit area A. More specifically, for example, the processing unit 130 performs processing such that the display unit 150 displays a display screen DS including two-dimensional coordinates C illustrating a drawing with a different color for each unit area A. Alternatively, the processing unit 130 performs processing such that the display unit 150 displays a display screen DS including two-dimensional coordinates C illustrating a drawing with a different shape for each unit area A. Alternatively, the processing unit 130 performs processing such that the display unit 150 displays a display screen DS including two-dimensional coordinates C illustrating a drawing with a different color and shape for each unit area A.

[0199] Furthermore, for example, the processing unit 130 performs processing for displaying the temporal changes in the two-dimensional data D for each unit area A. More specifically, the processing unit 130 performs processing for displaying a display screen DS including a graph G1 showing the temporal changes in the moving standard deviation ms and a graph G4 showing the temporal changes in the moving standard deviation MS, together with the two-dimensional coordinates C, on the display unit 150.

[0200] (Generation of quadratic functions F1 and F2)

[0201] The processing unit 130 generates the quadratic function F1 and the quadratic function F2 using the plurality of two-dimensional data D received from the generating unit 120 .

[0202] Figure 20 This is a diagram illustrating a method for determining a unit area by a processing unit in a processing device according to an embodiment of the present disclosure.

[0203] Reference Figure 20 For example, the processing unit 130 first converts each two-dimensional data D into a polar coordinate system. The processing unit 130 then classifies each two-dimensional data D into four tentative unit areas in the two-dimensional coordinate system C: tentative unit area Ap1, tentative unit area Ap2, tentative unit area Ap3, and tentative unit area Ap4, using two mutually orthogonal straight lines, namely, tentative boundary lines Lp1(θ) and Lp2(θ), which pass through the origin of the two-dimensional coordinate system C.

[0204] The processing unit 130 then calculates the angle sum Asum1(θ), which is the sum of the angles formed between the provisional boundary line Lp1(θ) defining the provisional unit area Ap1, the bisector Lb1 of the provisional boundary line Lp2(θ), and each piece of two-dimensional data D classified into the provisional unit area Ap1. Similarly, the processing unit 130 calculates the angle sum Asum2(θ), which is the sum of the angles formed between the provisional boundary line Lp1(θ) defining the provisional unit area Ap2, the bisector Lb2 of the provisional boundary line Lp2(θ), and each piece of two-dimensional data D classified into the provisional unit area Ap2. Furthermore, the processing unit 130 calculates the angle sum Asum3(θ), which is the sum of the angles formed between the provisional boundary line Lp1(θ) defining the provisional unit area Ap3, the bisector Lb1 of the provisional boundary line Lp2(θ), and each piece of two-dimensional data D classified into the provisional unit area Ap3. In addition, the processing unit 130 calculates the angle sum Asum4(θ), which is the sum of the angles formed by the provisional boundary line Lp1(θ) defining the provisional unit area Ap4, the bisector Lb2 of the provisional boundary line Lp2(θ), and each two-dimensional data D classified into the provisional unit area Ap4.

[0205] The processing unit 130 calculates the sum of the angle sum Asum1 (θ), the angle sum Asum2 (θ), the angle sum Asum3 (θ), and the angle sum Asum4 (θ) as the evaluation value V (θ).

[0206] The processing unit 130 then offsets the provisional boundary lines Lp1(θ) and Lp2(θ) by a small angle, such as 1°, around the origin. Using the provisional boundary lines Lp1(θ+1) and Lp2(θ+1) obtained by the 1° offset, the evaluation value V(θ+1) is calculated according to the above steps. The processing unit 130 repeatedly calculates the evaluation value V(θ+n) by offsetting the provisional boundary lines Lp1(θ) and Lp2(θ) by 1° each until the boundary line rotates 360° around the origin. Here, n is an integer greater than or equal to 1 and less than or equal to 360.

[0207] The processing unit 130 determines the provisional boundary line Lp1(θ+n) and the provisional boundary line Lp2(θ+n) when the evaluation value V(θ+n) is the smallest as the boundary line L1 and the boundary line L2, generates a quadratic function F1 representing the boundary line L1 and a quadratic function F2 representing the boundary line L2, and saves the generated quadratic function F1 and quadratic function F2 in the storage unit 140.

[0208] The processing unit 130 can generate the quadratic function F1 and the quadratic function F2 before each cutting process is started, or can generate the quadratic function F1 and the quadratic function F2 each time the positional relationship between the cutting edge 14 and the strain sensor 20 changes due to replacement of the cutting edge 14 or the strain sensor 20, etc.

[0209] [Flow of Action]

[0210] Each device in the cutting system involved in the embodiment of the present disclosure has a computer including a memory, and the CPU or other processing unit in the computer reads out and executes a program including part or all of the steps of the following flowchart and sequence from the memory. The programs of these multiple devices are circulated in a state of being stored in a recording medium such as an HDD (Hard Disk Drive), a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), and a semiconductor memory. The programs of these multiple devices can be installed from the outside. For example, the programs of these multiple devices can be installed from the above-mentioned recording medium. In addition, for example, the programs of these multiple devices can be downloaded and installed from a predetermined server or the like via an electric communication line, a wireless communication line, a wired communication line, and a network represented by the Internet. In addition, for example, the programs of these multiple devices can be downloaded and installed from a predetermined server or the like via data broadcasting or the like.

[0211] Figure 21 This is a flowchart that defines an example of an operation procedure when a processing device in a cutting system according to an embodiment of the present disclosure determines the state of a cutting edge.

[0212] Reference Figure 21 First, the processing device 201 waits for a wireless signal from the wireless communication device 23 in the cutting tool 101 ("No" in step S102). When the wireless signal is received ("Yes" in step S102), the sensor measurement value sx, the sensor measurement value sy, the sensor measurement value sr and the identification information are obtained from the received wireless signal (step S104).

[0213] Next, the processing device 201 generates two-dimensional data D representing the moment Mx and the moment My based on the acquired sensor measurement values ​​sx, sy, and sr and the conversion matrix in the storage unit 140 (step S106 ).

[0214] Next, the processing device 201 classifies the generated two-dimensional data D into any one of the unit areas A1 , A2 , A3 , and A4 (step S108 ).

[0215] Next, the processing device 201 calculates the moving standard deviation MS based on the two-dimensional data D for each unit area A (step S110 ).

[0216] Next, when only some of the moving standard deviations MS corresponding to the unit areas A increase (YES in step S112 ), the processing device 201 determines that an abnormality has occurred in the cutting edge 14 (step S114 ).

[0217] Next, the processing device 201 performs the following processing: a display screen DS is displayed on the display unit 150, wherein the display screen DS includes a drawing illustrating the two-dimensional data D and the two-dimensional coordinates C of the unit area A, a curve graph G1 representing the time change of the moving standard deviation ms, and a curve graph G3 representing the time change of the moving standard deviation MS (step S116).

[0218] Next, the processing device 201 waits for a new wireless signal from the wireless communication device 23 in the cutting tool 101 (No in step S102).

[0219] On the other hand, when all the moving standard deviations MS corresponding to the unit areas A do not increase or when all the moving standard deviations MS increase (No in step S112 ), the processing device 201 determines that no abnormality has occurred in the cutting edge 14 (step S118 ).

[0220] Next, the processing device 201 performs the following processing: a display screen DS is displayed on the display unit 150, wherein the display screen DS includes a drawing illustrating the two-dimensional data D and the two-dimensional coordinates C of the unit area A, a curve graph G1 representing the time change of the moving standard deviation ms, and a curve graph G4 representing the time change of the moving standard deviation MS (step S116).

[0221] Next, the processing device 201 waits for a new wireless signal from the wireless communication device 23 in the cutting tool 101 (No in step S102).

[0222] It should be noted that the order of steps S112, S114, S118, and S116 is not limited to the above order, and the order may be reversed. In addition, any of steps S112, S114, S118, and S116 may not be performed.

[0223] Figure 22 This is a diagram showing an example of the sequence of detection processing and display processing in the cutting system according to the embodiment of the present disclosure.

[0224] Reference Figure 22 First, the cutting tool 101 starts cutting processing using two or more cutting edges (step S202).

[0225] Next, the strain sensor 20 provided on the cutting tool 101 starts measuring the strain ε of the shank 11 (step S204 ).

[0226] Next, the cutting tool 101 includes the sensor measurement values ​​sx, sy, and sr based on the analog signal from the strain sensor 20 in a wireless signal and transmits the signal to the processing device 201 (step S206 ).

[0227] Next, the processing device 201 obtains the sensor measurement value sx, sensor measurement value sy, and sensor measurement value sr according to the wireless signal received from the cutting tool 101, and generates two-dimensional data D representing the moment Mx and moment My based on the obtained sensor measurement value sx, sensor measurement value sy, sensor measurement value sr and the conversion matrix in the storage unit 140 (step S208).

[0228] Next, the processing device 201 performs classification processing (step S210).

[0229] Next, the processing device 201 performs detection processing (step S212).

[0230] Next, the processing device 201 performs display processing (step S214).

[0231] Next, the cutting tool 101 includes new sensor measurement values ​​sx, sy, and sr based on the analog signal from the strain sensor 20 in a wireless signal and transmits the signal to the processing device 201 (step S216 ).

[0232] [Variation 1]

[0233] The cutting tool 101 according to the embodiment of the present disclosure is an end mill including four blade fixing portions 13, but is not limited thereto. The cutting tool 101 may also include two, three, or five or more blade fixing portions 13. Furthermore, the cutting tool 101 may be a tool other than an end mill, such as a face milling cutter.

[0234] [Variation 2]

[0235] The cutting system 301 according to the embodiment of the present disclosure is configured to include a number of strain sensors 20 that is not correlated with the number of cutting edges 14 in the cutting tool 101 , but the present invention is not limited thereto. The cutting system 301 may also be configured to include a number of strain sensors 20 that is correlated with the number of cutting edges 14 .

[0236] The cutting system 301 includes a smaller number of strain sensors 20 than the number of cutting edges 14 in the cutting tool 101 , but the present invention is not limited thereto. The cutting system 301 may include a greater number of strain sensors 20 than the number of cutting edges 14 in the cutting tool 101 .

[0237] [Variation 3]

[0238] In the cutting system 301 according to the embodiment of the present disclosure, the strain sensor 20 is configured to be installed on the shank 11 of the cutting tool 101, but the present invention is not limited to this. The strain sensor 20 may also be installed on the blade mounting portion 12 of the cutting tool 101. Alternatively, the strain sensor 20 may be installed on the tool holder 210, for example.

[0239] [Variation 4]

[0240] In the cutting system 301 according to the embodiment of the present disclosure, the strain sensor 20 is configured to measure the strain ε of the shank 11 in a direction parallel to the rotation axis 17 , but the present invention is not limited thereto. The strain sensor 20 may also be configured to measure the shear strain of the shank 11 .

[0241] In this case, for example, the generator 120 generates two-dimensional data D indicating the load Fx in the X direction and the load Fy in the Y direction received by the cutting tool 101 in the cutting resistance acting surface 18 based on the sensor measurement value indicating the shear strain measured by the strain sensor 20 .

[0242] Furthermore, the cutting system 301 may be configured to include other sensors such as an acceleration sensor, a velocity sensor, and a displacement sensor instead of the strain sensor 20 or in addition to the strain sensor 20 as a plurality of sensors.

[0243] In this case, the generation unit 120 generates two-dimensional data D representing the acceleration in the X direction and the acceleration in the Y direction of the cutting tool 101 within the cutting resistance action surface 18, two-dimensional data D representing the speed in the X direction and the speed in the Y direction of the cutting tool 101 within the cutting resistance action surface 18, or two-dimensional data D representing the displacement in the X direction and the displacement in the Y direction of the cutting tool 101 within the cutting resistance action surface 18 based on the measurement results of the sensor.

[0244] It should be noted that when using an acceleration sensor or a speed sensor, the two-dimensional data D generated by the generation unit 120 based on the measurement results, that is, the two-dimensional data D related to the cutting resistance F applied to a certain cutting edge 14, and the two-dimensional data D related to the cutting resistance F applied to another cutting edge 14 located at a point-symmetrical position relative to the rotation axis 17, appear at approximately the same position in the two-dimensional coordinate C, and it is sometimes difficult to classify each two-dimensional data D according to each cutting edge 14.

[0245] Therefore, when an acceleration sensor or a velocity sensor is used, it is preferable to use a cutting tool 101 that does not have a cutting edge 14 provided at a point-symmetrical position with respect to the rotation axis 17. Specifically, when an acceleration sensor or a velocity sensor is used, it is preferable to use a cutting tool 101 that has three blade fixing portions 13 provided at equal intervals around the rotation axis 17 in the blade mounting portion 12, or a cutting tool 101 that has five blade fixing portions 13 provided at equal intervals around the rotation axis 17 in the blade mounting portion 12.

[0246] [Variation 5]

[0247] In the processing device 201 according to the embodiment of the present disclosure, the processing unit 130 is configured to classify the plurality of two-dimensional data D received from the generating unit 120 into any one of four unit areas A, which are equal in number to the number of cutting edges 14, within a plane perpendicular to the rotation axis 17. However, the present invention is not limited thereto. The processing unit 130 may also be configured to classify the plurality of two-dimensional data D into any one of four unit areas A, which are greater in number than the number of cutting edges 14, within a plane perpendicular to the rotation axis 17.

[0248] For example, processing unit 130 performs classification processing to classify a plurality of two-dimensional data D into any one of twelve unit areas A within a plane perpendicular to rotation axis 17. In this case, unit areas A are each area obtained by dividing 360 degrees into 30-degree intervals. In other words, unit areas A are each area obtained by dividing the plane perpendicular to rotation axis 17 into twelve equal parts around rotation axis 17 using six straight lines on the plane, namely, six straight lines passing through rotation axis 17.

[0249] [Variation 6]

[0250] In the processing device 201 according to the embodiment of the present disclosure, the processing unit 130 is configured to detect an abnormality in the cutting edge 14 based on the temporal change of the index value based on the two-dimensional data D, but the present invention is not limited to this. The processing unit 130 may also be configured to detect an abnormality in the cutting edge 14 based on the absolute value of the index value based on the two-dimensional data D.

[0251] [Variation 7]

[0252] In the processing device 201 according to the embodiment of the present disclosure, the processing unit 130 is configured to calculate the moving standard deviation ms in each unit area A, but the present invention is not limited thereto. The processing unit 130 may be configured to calculate the moving maximum value in each unit area A as the index value for each unit area A, or may be configured to calculate the moving average ma in each unit area A as the index value for each unit area A.

[0253] For example, the processing unit 130 calculates the moving average ma of the distance R from the origin of the two-dimensional data D in each unit area A. Specifically, the processing unit 130 calculates the moving average ma1 of the distance R1 of the two-dimensional data D1, the moving average ma2 of the distance R2 of the two-dimensional data D2, the moving average ma3 of the distance R3 of the two-dimensional data D3, and the moving average ma4 of the distance R4 of the two-dimensional data D4.

[0254] Figure 23 This is a diagram showing an example of the moving average ma calculated by the processing unit in the processing device according to Modification 7 of the embodiment of the present disclosure. Figure 23 A graph G5 is shown with the horizontal axis representing time [seconds] and the vertical axis representing the moving average ma [Nm]. Figure 23 In the figure, the solid line represents the moving average ma1, the dotted line represents the moving average ma2, the single-dot chain line represents the moving average ma3, and the double-dot chain line represents the moving average ma4.

[0255] Reference Figure 23 The processing unit 130 performs detection processing based on the time change of the calculated moving average ma.

[0256] For example, the processing unit 130 calculates the moving standard deviation MA of the difference Dma between the moving average ma of each unit area A and the average value Ama of the moving average ma of each unit area A.

[0257] More specifically, the processing unit 130 calculates the average value Ama of the moving averages ma1 to ms4. The processing unit 130 then calculates the moving standard deviation MA of the difference Dma between each moving average ma and the average value Ama of the moving averages ma. Specifically, the processing unit 130 calculates the moving standard deviation MA1 of the difference Dma1 between the moving average ma1 and the average value Ama, the moving standard deviation MA2 of the difference Dma2 between the moving average ma2 and the average value Ama, the moving standard deviation MA3 of the difference Dma3 between the moving average ma3 and the average value Ama, and the moving standard deviation MA4 of the difference Dma4 between the moving average ma4 and the average value Ama.

[0258] Figure 24This is a diagram showing an example of the average value Ama calculated by the processing unit in the processing device according to Modification 7 of the embodiment of the present disclosure. Figure 24 A graph G6 is shown in which the horizontal axis represents time (seconds) and the vertical axis represents the average value Ama (Nm).

[0259] Figure 25 This is a diagram showing an example of the difference Dma calculated by the processing unit in the processing device according to the seventh modification of the embodiment of the present disclosure. Figure 25 A graph G7 is shown with the horizontal axis representing time (seconds) and the vertical axis representing the difference Dma (Nm). Figure 25 In the figure, the solid line represents the differential Dma1, the dotted line represents the differential Dma2, the single-dot chain line represents the differential Dma3, and the double-dot chain line represents the differential Dma4.

[0260] Figure 26 This is a diagram showing an example of a moving standard deviation MA calculated by a processing unit in a processing device according to Modification 7 of the embodiment of the present disclosure. Figure 26 A graph G8 is shown with the horizontal axis representing time (seconds) and the vertical axis representing the moving standard deviation MA (Nm). Figure 26 In the figure, the solid line represents the moving standard deviation MA1, the dotted line represents the moving standard deviation MA2, the one-dot chain line represents the moving standard deviation MA3, and the two-dot chain line represents the moving standard deviation MA4.

[0261] Reference Figure 26 For example, the processing unit 130 detects an abnormality in the cutting edge 14 based on the calculated moving standard deviation MA. More specifically, the processing unit 130 monitors changes in the moving standard deviations MA. If all moving standard deviations MA increase, the processing unit 130 determines that the increase in the moving standard deviation MA is not caused by an abnormality in the cutting edge 14. On the other hand, if a portion of the moving standard deviations MA increases, the processing unit 130 determines that an abnormality has occurred in the cutting edge 14.

[0262] [Variation 8]

[0263] In the cutting system 301 according to the embodiment of the present disclosure, the processing unit 130 is configured to calculate the moving standard deviation ms of the distance R from the origin of the two-dimensional data D in each unit area A when classifying the two-dimensional data D received from the generating unit 120, but the present invention is not limited to this. The processing unit 130 may also be configured to calculate the moving standard deviation ms using only the distance R above a predetermined threshold in each unit area A. In other words, the processing unit 130 may also be configured to filter the two-dimensional data D. Two-dimensional data with a distance R less than a predetermined threshold may be data before or after the cutting edge 14 contacts the cutting object. By filtering the two-dimensional data D in this manner, more accurate detection processing can be performed.

[0264] [Variation 9]

[0265] The cutting system 301 according to the embodiment of the present disclosure is configured to include a processing device 201 independent of the cutting tool 101, but is not limited to this. The processing device 201 may be configured to be installed on the cutting tool 101 or on the machine tool. Furthermore, the processing device 201 is configured to perform detection processing and display processing, but is not limited to this. The processing device 201 may also be configured not to perform either detection processing or display processing.

[0266] Incidentally, a technology capable of achieving excellent performance related to a cutting edge in a cutting tool is desired.

[0267] For example, Patent Document 1 describes a method for attaching a strain sensor to each cutting edge of a cutting tool, and detecting abnormalities in the corresponding cutting edge based on the measured values ​​of each strain sensor. However, in the technique described in Patent Document 1, when a cutting process is performed in which multiple cutting edges come into contact with the object being cut, the measured values ​​of each strain sensor are influenced by the cutting resistance applied to cutting edges other than the corresponding cutting edge, that is, by the cutting resistance applied to the multiple cutting edges in contact with the object being cut. In other words, the technique described in Patent Document 1 cannot obtain measurement values ​​related to the cutting resistance applied to only one cutting edge from the corresponding strain sensor. Consequently, it is sometimes impossible to accurately detect abnormalities in the cutting edge. Furthermore, the technique described in Patent Document 1 requires a number of sensors corresponding to the number of cutting edges, resulting in increased costs as the number of cutting edges increases.

[0268] In addition, in the technology described in Patent Document 2, if the sampling frequency when performing AD conversion on the measurement results of the sensor relative to cutting conditions such as the number of cutting edges and the rotational speed of the cutting tool is insufficient, it is sometimes impossible to accurately detect the peak value of the measurement value of the sensor and the abnormality of the cutting edge.

[0269] In addition, in the technologies described in Patent Documents 8 and 9, due to the influence of the positional offset of each cutting edge in the direction of the rotation axis and the radial direction of the shank, the two-dimensional projection image obtained from the measurement results of the sensor becomes asymmetric, and sometimes it is impossible to accurately detect abnormalities in the cutting edge.

[0270] Furthermore, the technology described in Patent Document 10 describes the use of a sensor that measures the driving force of the machine tool's spindle. However, detecting cutting edge anomalies based on the measurement results of such a sensor requires analyzing machining conditions such as the rotational speed of the cutting tool, which complicates the structure and processing. Furthermore, the technology described in Patent Document 10 does not classify the two-dimensional data D generated based on the sensor's measurement results into unit areas A. Therefore, for example, it is impossible to analyze the cutting resistance applied to the cutting edge for each cutting edge, and thus, it is sometimes impossible to accurately detect cutting edge anomalies.

[0271] In contrast, in the cutting system 301 according to the embodiment of the present disclosure, the cutting tool 101 performs cutting processing using two or more cutting edges 14. The strain sensor 20 measures a physical quantity representing a state related to the load on the cutting tool 101 during cutting processing. Based on the measurement results of the strain sensor 20 at multiple measurement times, the processing device 201 generates two-dimensional data D related to the load at each measurement time. The load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool 101. The generated two-dimensional data D is classified into any one of a plurality of unit areas A greater than the number of cutting edges 14 within the plane, and an abnormality of the cutting edge 14 is detected based on the two-dimensional data D of each unit area A.

[0272] In a processing device 201 according to an embodiment of the present disclosure, a wireless communication unit 110 acquires measurement results from strain sensors 20, which are physical quantities indicating the state of load associated with cutting in a milling cutting tool 101 that performs cutting using two or more cutting edges. Based on the measurement results from strain sensors 20 acquired by the wireless communication unit 110 at multiple measurement times, a generation unit 120 generates two-dimensional data D related to the load in two directions within a plane perpendicular to the rotation axis 17 of the cutting tool 101 at each measurement time. The processing unit 130 categorizes each two-dimensional data D generated by the generation unit 120 into any one of a plurality of unit areas A, equal to or greater than the number of cutting edges 14 within the plane, and detects abnormalities in the cutting edges 14 based on the two-dimensional data D for each unit area A.

[0273] The processing method according to the embodiments of the present disclosure is a processing method performed by a processing device 201. In this processing method, the processing device 201 first obtains measurement results from strain sensors 20, which are physical quantities indicating the state of load associated with cutting in a milling cutting tool 101 that performs cutting using two or more cutting edges 14. Next, based on the measurement results obtained from each strain sensor 20 at each of the multiple measurement times, the processing device 201 generates two-dimensional data D related to the load in two directions within a plane perpendicular to the rotation axis 17 of the cutting tool 101. The processing device 201 then classifies each generated two-dimensional data D into any one of a plurality of unit areas A, equal to or greater than the number of cutting edges 14 within the plane, and detects abnormalities in the cutting edges 14 based on the two-dimensional data D for each unit area A.

[0274] In this way, according to the structure and method of classifying each two-dimensional data D generated based on the measurement results of the strain sensor 20 into any one of a plurality of unit areas A in a plane perpendicular to the rotation axis 17 and detecting the abnormality of the cutting edge 14 based on the two-dimensional data D of each unit area A, the change of the two-dimensional data D in only a part of the unit areas caused by the occurrence of the abnormality of the cutting edge can be distinguished from the change of the two-dimensional data D in all the unit areas caused by the change of the cutting conditions, and thus the abnormality of the cutting edge can be accurately detected.

[0275] Therefore, in the cutting system, the processing apparatus, and the processing method according to the embodiment of the present disclosure, it is possible to achieve excellent performance related to the cutting edge of the cutting tool.

[0276] In the cutting system 101 according to the embodiment of the present disclosure, the cutting tool 101 performs cutting processing using two or more cutting edges 14. The strain sensor 20 measures a physical quantity representing a state related to the load on the cutting tool 101 during the cutting processing. The processing device 201 performs the following processing: based on the measurement results of the strain sensor 20 at multiple measurement times, the processing device 201 generates two-dimensional data D related to the load at each measurement time, where the load is the load in two directions within a plane perpendicular to the rotation axis of the cutting tool 101, classifies each generated two-dimensional data D into any one of a plurality of unit areas A greater than the number of cutting edges 14 within the plane, and displays the classification results.

[0277] In a processing device 201 according to an embodiment of the present disclosure, a wireless communication unit 110 acquires measurement results from strain sensors 20, which are physical quantities indicating the state of load associated with cutting in a milling cutting tool 101 that performs cutting using two or more cutting edges. Based on the measurement results from strain sensors 20 acquired by the wireless communication unit 110 at multiple measurement times, a generation unit 120 generates two-dimensional data D related to load in two directions within a plane perpendicular to the rotation axis 17 of the cutting tool 101 at each measurement time. The processing unit 130 classifies each two-dimensional data D generated by the generation unit 120 into any one of a plurality of unit areas A, equal to or greater than the number of cutting edges 14 within the plane, and displays the classification results.

[0278] The processing method according to the embodiment of the present disclosure is a processing method performed by a processing device 201. In this processing method, the processing device 201 first obtains measurement results from a strain sensor 20, which are measurement results of physical quantities indicating the state related to the load during cutting in a milling cutting tool 101 that performs cutting using two or more cutting edges 14. Next, based on the measurement results obtained from each strain sensor 20 at each of the multiple measurement times, the processing device 201 generates two-dimensional data D related to the load in two directions within a plane perpendicular to the rotation axis 17 of the cutting tool 101 at each measurement time. The processing device 201 then performs processing to classify each generated two-dimensional data D into one of a plurality of unit areas A, equal to or greater than the number of cutting edges 14 within the plane, and displays the classification results.

[0279] In this way, according to the structure and method of classifying each two-dimensional data D generated based on the measurement results of the strain sensor 20 into any one of a plurality of unit areas A within a plane perpendicular to the rotation axis 17 and displaying the classification results, it is possible, for example, to display the state of each cutting edge as two-dimensional data of each unit area A, thereby enabling the user to identify the state of each cutting edge 14.

[0280] Therefore, in the display system, processing device, and processing method according to the embodiment of the present disclosure, it is possible to realize excellent performance related to the cutting edge of the cutting tool.

[0281] The above embodiments should be considered in all respects as illustrative rather than restrictive. The scope of the present invention is indicated by the claims rather than the above description, and is intended to include all modifications within the meaning and scope of the claims and equivalents.

[0282] The above description includes the following additional features.

[0283] [Note 1]

[0284] A cutting system, wherein:

[0285] The cutting system comprises:

[0286] cutting tools for milling operations;

[0287] multiple sensors; and

[0288] Processing Department,

[0289] The cutting tool performs cutting using two or more cutting edges.

[0290] The plurality of sensors measure physical quantities indicating a state related to a load on the cutting tool during cutting.

[0291] The processing unit generates two-dimensional data related to the load at each measurement timing based on measurement results of each of the sensors at multiple measurement timings, wherein the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool, classifies each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and detects an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

[0292] The processing unit calculates index values ​​based on the two-dimensional data of the plurality of unit areas, calculates a standard deviation of a difference between the index value of each unit area and an average value of the index values ​​of the unit areas, and detects an abnormality of the cutting edge based on the calculated standard deviation.

[0293] The processing unit calculates a moving average or a moving standard deviation of the distance from the origin within the plane of the two-dimensional data in each of the unit areas as the index value.

[0294] [Note 2]

[0295] A display system, wherein

[0296] The display system comprises:

[0297] cutting tools for milling operations;

[0298] Multiple sensors;

[0299] and a processing device,

[0300] The cutting tool performs cutting using two or more cutting edges.

[0301] The plurality of sensors measure physical quantities indicating a state related to a load on the cutting tool during cutting.

[0302] The processing device performs the following processing: based on the measurement results of each of the sensors at multiple measurement times, generates two-dimensional data related to the load at each measurement time, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool, classifies each of the generated two-dimensional data into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and displays the classification result;

[0303] The processing device classifies each of the two-dimensional data into any one of the unit areas whose number is the same as the number of the cutting edges.

[0304] The processing device performs processing to display the two-dimensional data in a manner different for each of the unit areas as a result of the classification.

[0305] Description of Reference Numerals

[0306] 11: handle;

[0307] 12: blade mounting portion;

[0308] 13: blade fixing portion;

[0309] 17: Rotation axis;

[0310] 18: Cutting resistance action surface;

[0311] 20: strain sensor;

[0312] 22: Battery;

[0313] 23: Wireless communication device;

[0314] 24: shell;

[0315] 101: cutting tools;

[0316] 110: Wireless Communication Department;

[0317] 120: Generation Department;

[0318] 130: Processing Department;

[0319] 140: storage unit;

[0320] 150: display unit;

[0321] 201: processing device;

[0322] 210: tool holder;

[0323] 220: spindle;

[0324] 301: Cutting system.

Claims

1. A cutting system, wherein: The cutting system comprises: cutting tools for milling operations; multiple sensors; and Processing Department, The cutting tool performs cutting using two or more cutting edges. The plurality of sensors measure physical quantities indicating a state related to a load on the cutting tool during cutting. The processing unit generates two-dimensional data related to the load at each measurement time based on the measurement results of each sensor at multiple measurement times, and the load is a load in two directions within a plane perpendicular to the rotation axis of the cutting tool. The generated two-dimensional data is classified into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and an abnormality of the cutting edge is detected based on the two-dimensional data of each unit area.

2. The cutting system according to claim 1, wherein: The processing unit classifies each of the two-dimensional data into any one of the unit areas, the number of which is the same as the number of the cutting edges.

3. The cutting system according to claim 1 or 2, wherein: The processing unit sequentially generates and classifies the two-dimensional data, and detects abnormality of the cutting edge based on the number of the unit areas in which a temporal change in the two-dimensional data is equal to or greater than a predetermined value.

4. The cutting system according to claim 3, wherein: The processing unit calculates the index values ​​based on the two-dimensional data of the multiple unit areas respectively, and calculates the standard deviation of the difference between the index value of each unit area and the average value of the index value of each unit area, and detects the abnormality of the cutting edge based on the calculated standard deviation.

5. The cutting system according to claim 1 or 2, wherein: The cutting system includes the sensors in a number that is independent of the number of the cutting edges in the cutting tool.

6. The cutting system according to claim 1 or 2, wherein: The cutting system includes the sensors, the number of which is smaller than the number of the cutting edges in the cutting tool.

7. The cutting system according to claim 1 or 2, wherein: The cutting tool comprises a shank, The plurality of sensors are disposed on the handle.

8. A processing device, wherein: The processing device comprises: an acquisition unit that acquires measurement results from a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; a generating unit configured to generate two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at the plurality of measurement timings acquired by the acquiring unit, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as A detection unit classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges in the plane, and detects an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

9. A processing method, which is a processing method in a processing device, wherein: The processing method comprises the following steps: acquiring measurement results of a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; generating two-dimensional data related to the load at each measurement timing based on the measurement results of each sensor at the plurality of measurement timings, the load being loads in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as The generated two-dimensional data are classified into any one of a plurality of unit areas greater than the number of the cutting edges in the plane, and abnormality of the cutting edge is detected based on the two-dimensional data of each unit area.

10. A storage medium storing a processing program, which is a processing program used in a processing device, wherein: The processing program is used to make the computer function as the following functional unit: an acquisition unit that acquires measurement results from a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; a generating unit configured to generate two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at the plurality of measurement timings acquired by the acquiring unit, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as A detection unit classifies each of the two-dimensional data generated by the generation unit into any one of a plurality of unit areas greater than the number of the cutting edges in the plane, and detects an abnormality of the cutting edge based on the two-dimensional data of each of the unit areas.

11. A display system, wherein: The display system comprises: cutting tools for milling operations; multiple sensors; and processing device, The cutting tool performs cutting using two or more cutting edges. The plurality of sensors measure physical quantities indicating a state related to a load on the cutting tool during cutting. The processing device performs the following processing: based on the measurement results of each of the sensors at multiple measurement times, two-dimensional data related to the load at each measurement time is generated respectively, and the load is the load in two directions within the plane perpendicular to the rotation axis of the cutting tool, and each of the generated two-dimensional data is classified into any one of a plurality of unit areas greater than the number of the cutting edges within the plane, and the classification results are displayed.

12. The display system according to claim 11, wherein: The processing device performs processing to display the two-dimensional data in a manner different for each of the unit areas as a result of the classification.

13. The display system according to claim 11 or 12, wherein: The processing device performs the following processing: sequentially generates and classifies the two-dimensional data, and further displays information indicating a temporal change of the two-dimensional data for each of the unit areas.

14. A processing device, wherein: The processing device comprises: an acquisition unit that acquires measurement results from a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; a generating unit configured to generate two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at the plurality of measurement timings acquired by the acquiring unit, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as A display processing unit performs processing for classifying each of the two-dimensional data generated by the generating unit into any one of a plurality of unit areas equal to or greater than the number of the cutting edges in the plane, and displays a result of the classification.

15. A processing method, which is a processing method in a processing device, wherein: The processing method comprises the following steps: acquiring measurement results of a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; generating two-dimensional data related to the load at each measurement timing based on the measurement results of each sensor at the plurality of measurement timings, the load being loads in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as A process is performed to classify each of the generated two-dimensional data into any one of a plurality of unit areas equal to or greater than the number of the cutting edges in the plane and to display the classification result.

16. A storage medium storing a processing program, the processing program being used in a processing device, wherein: The processing program is used to make the computer function as the following functional unit: an acquisition unit that acquires measurement results from a plurality of sensors, the measurement results being measurement results of physical quantities representing a state related to a load during cutting in a cutting tool for milling, the cutting tool for milling performing cutting using two or more cutting edges; a generating unit configured to generate two-dimensional data related to the load at each measurement timing based on the measurement results of each of the sensors at the plurality of measurement timings acquired by the acquiring unit, the load being a load in two directions within a plane perpendicular to the rotation axis of the cutting tool; as well as A display processing unit performs processing for classifying each of the two-dimensional data generated by the generating unit into any one of a plurality of unit areas equal to or greater than the number of the cutting edges in the plane, and displays a result of the classification.

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