JP7427938B2 - Diagnostic device, diagnostic device control method and program - Google Patents

Description

The present invention relates to a diagnostic device, a method for controlling the diagnostic device, and a program.

2. Description of the Related Art As a method for detecting an abnormality in a machine, a method of detecting and outputting physical quantities such as information on a current value of a motor of a machine, vibration, or force is already known.

For example, Patent Document 1 discloses that when processing a workpiece with a machine tool, measurements are taken from multiple sensors to diagnose tool wear and machining accuracy of the workpiece, and the possibility of machining accuracy failure occurring before machining accuracy failure occurs. A technique for identifying the cause has been disclosed.

However, in the technology described in Patent Document 1, the degree of conformity (degree of abnormality) used for diagnosing tool wear and workpiece machining accuracy is a membership function linked to phenomena related to tool wear and workpiece machining accuracy. The weighting coefficient (parameter weight) used in the calculation is a fixed value. Therefore, the fitness value is a value that reflects multiple phenomena, and it may be difficult to focus on a specific phenomenon.

The present invention has been made in view of the above-mentioned problems, and after the parameters are displayed in a stacked manner on the display section with varying degree of abnormality, the reception section re-receives the input of parameter weight candidates. It is an object of the present invention to provide a diagnostic device, a control method for the diagnostic device, and a program that make it possible to input parameter weight candidates again .

In order to solve the above-mentioned problems and achieve the purpose, the present invention includes an acquisition section that acquires detection information indicating a physical quantity detected by a detection section that detects a physical quantity that changes depending on the operation of a target device; a calculation unit that calculates an abnormality degree based on information that associates operation information of the target device with the detection information acquired by the detection unit when the detection information is acquired by the acquisition unit; , an accumulation unit that accumulates the degree of abnormality calculated by the calculation unit; a reception unit that receives input of weight candidates for a plurality of parameters used to calculate the degree of abnormality; and a storage unit that stores the degree of abnormality calculated by the calculation unit; a display control unit that changes and displays the degree of abnormality accumulated by the accumulation unit by reflecting weight candidates of a plurality of parameters ; and a determination unit that finalizes the displayed weight candidates of the plurality of parameters. The display control unit changes the plurality of parameters, weight candidates for the plurality of parameters, and weight candidates for the plurality of parameters to reflect them, and displays the plurality of parameters in a stacked manner. and the degree of abnormality determined by the parameter is displayed on the display unit as a first screen; When the degree of abnormality is displayed, input of weight candidates for the plurality of parameters is accepted again.

According to the present invention, after the parameters are displayed in a stacked manner on the display section with varying degrees of abnormality, the receiving section receives the input of the parameter weight candidates again, thereby inputting the parameter weight candidates again. becomes possible .

FIG. 1 is a diagram schematically showing the configuration of a diagnostic system. FIG. 2 is a diagram schematically showing the configuration of the processing machine. FIG. 3 is a block diagram showing an example of the hardware configuration of the processing machine. FIG. 4 is a block diagram showing an example of the hardware configuration of the diagnostic device. FIG. 5 is a block diagram showing an example of the functional configuration of a processing machine and a diagnostic device. FIG. 6 is a diagram showing an example of processing machine detection information and ladder signals. FIG. 7 is a diagram illustrating an example of operation information of a processing machine. FIG. 8 is a diagram illustrating an example of the association between operating information and detection information. FIG. 9 is a diagram schematically illustrating feature information extracted from detection information by the diagnostic device using frequency components. FIG. 10A is a diagram showing an example of a custom score setting screen. FIG. 10B is a diagram showing an example of a custom score setting addition screen. FIG. 10C is a diagram illustrating an example of a process for reading registered custom score settings. FIG. 10D is a diagram illustrating an example of a custom score setting screen after adding custom score settings. FIG. 11 is a diagram showing an example of an abnormality degree display screen. FIG. 12 is a flowchart showing an example of processing data accumulation processing. FIG. 13 is a flowchart illustrating an example of custom score setting addition processing. FIG. 14 is a flowchart illustrating an example of abnormality degree display processing.

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of a diagnostic device, a control method for a diagnostic device, and a diagnostic program according to the present invention will be described in detail below with reference to the drawings.

(Overall configuration of diagnostic system)
FIG. 1 is a diagram schematically showing the configuration of a diagnostic system 1 according to an embodiment. The diagnostic system 1 includes a processing machine 200, a diagnostic device 100, and a cloud server CS. The processing machine 200 and the diagnostic device 100 are connected to each other via a communication line CM. Diagnostic device 100 is connected to cloud server CS via network NT.

(Schematic configuration of processing machine)
FIG. 2 is a diagram schematically showing the configuration of the processing machine. A processing machine is an example of a "target device." The processing machine 200 includes a plurality of holders 200h and a plurality of tools 200t. The tool 200t is attached to the holder 200h. In this embodiment, any tool 200t can be attached to any holder 200h.

The tool 200t performs various types of processing on the object to be processed. The tools 200t include, for example, a drill (5 mm in diameter, 10 mm in diameter), an end mill (5 mm in diameter, 10 mm in diameter), a reamer (5 mm in diameter), and the like. In this embodiment, cutting is performed on the workpiece using a plurality of tools 200t and a plurality of machining programs.

(Hardware configuration of processing machine)
Next, an example of the hardware configuration of the processing machine 200 according to the embodiment will be described. FIG. 3 is a diagram showing an example of the hardware configuration of the processing machine 200.

The processing machine 200 includes a CPU (Central Processing Unit) 20, a ROM (Read Only Memory) 20a, a RAM (Random Access Memory) 20b, a communication I/F (interface) 21, and a drive control circuit 23. . Further, each component is communicably connected via a bus 2B.

The CPU 20 is a calculation device that controls the entire processing machine 200. For example, the CPU 20 controls the operation of the entire processing machine 200 and realizes processing functions by executing a program stored in the ROM 20a or the like using the RAM 20b as a work area.

The communication I/F 21 is an interface used for communication with external devices such as the diagnostic device 100. The communication I/F 21 is, for example, a NIC (Network Interface Card) compatible with TCP (Transmission Control Protocol)/IP (Internet Protocol).

The drive control circuit 23 is a circuit that controls the drive of the drive section 24. The drive unit 24 is an actuator that drives a tool 200t used for machining. The tools 200t include a drill, an end mill, a cutting tip, a grindstone, etc., and a table on which a workpiece is placed and moved in accordance with the machining.

In addition, in this embodiment, although the drive part 24 is a motor, it is not limited to this. Any actuator may be used as long as it is used for processing and is subject to numerical control by a numerical control unit 201, which will be described later. Further, the processing machine 200 may include a plurality of drive units 24.

The sensor 25 is composed of, for example, a microphone device, a vibration sensor, an acceleration sensor, an AE (Acoustic Emission) sensor, or the like, and is installed near the tool 200t where it can detect vibrations, sounds, etc., for example. The sensor amplifier 25a to which the sensor 25 is connected is communicably connected to the diagnostic device 100. The sensor 25 and the sensor amplifier 25a are an example of a "detection section".

The sensor 25 and the sensor amplifier 25a detect vibrations or sounds generated when a tool 200t installed in the processing machine 200, such as a drill, an end mill, a cutting tip, or a grindstone, comes into contact with a workpiece during a machining operation, or the tool 200t. Alternatively, a physical quantity such as vibration or sound emitted by the processing machine 200 itself is detected, and information on the detected physical quantity is output to the diagnostic device 100 as detection information (sensor data).

Note that the number of sensors 25 and sensor amplifiers 25a is arbitrary. For example, it may be provided with a plurality of sensors 25 and sensor amplifiers 25a that detect the same physical quantity, or may be provided with a plurality of sensors 25 and sensor amplifiers 25a that detect mutually different physical quantities.

For example, if the blade of the tool 200t used for machining is broken or chipped, the sound during machining will change. Therefore, abnormality in the operation of the processing machine 200 can be detected by detecting acoustic data with the sensor 25 (microphone) and making a determination using a model or the like for determining normal sound.

The sensor 25 and the sensor amplifier 25a may be provided in the processing machine 200 in advance, or may be attached to the processing machine 200, which is a completed machine, afterwards. Further, the sensor amplifier 25a is not limited to being installed in the processing machine 200, but may be installed in the diagnostic device 100 side.

Note that the hardware configuration shown in FIG. 3 is an example, and the processing machine 200 does not need to include all the components, and may include other components.

(Hardware configuration of diagnostic equipment)
Next, an example of the hardware configuration of the diagnostic device 100 according to the embodiment will be described. FIG. 4 is a diagram showing an example of the hardware configuration of the diagnostic device 100.

The diagnostic device 100 includes a CPU 10, a ROM 10a, a RAM 10b, a communication I/F 11, a sensor I/F 12, a storage section 13, an input device 14, and a display section 15. Further, each component is communicably connected via a bus 1B.

The CPU 10 is an arithmetic unit that controls the entire diagnostic device 100. The CPU 10 controls the overall operation of the diagnostic device 100 and realizes the functions of the diagnostic device 100, for example, by executing programs stored in the ROM 10a or the like using the RAM 10b as a work area.

The communication I/F 11 is an interface used for communication with external devices such as the processing machine 200. The communication I/F 11 is, for example, a NIC compatible with TCP/IP.

The sensor I/F 12 is an interface that receives detection information from the sensor 25 installed in the processing machine 200 via the sensor amplifier 25a.

The storage unit 13 stores various data such as setting information of the diagnostic device 100, detection information received from the processing machine 200, operating information (described later), an OS (Operating System), and application programs.

The storage unit 13 is, for example, a nonvolatile storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an EEPROM (Electrically Erasable Programmable Read-Only Memory). .

The input device 14 performs operations such as inputting characters and numbers, selecting various instructions, and moving a cursor. The input device 14 is, for example, an input device such as a mouse or a keyboard.

The display unit 15 displays letters, numbers, various screens, operation icons, and the like. The display unit 15 is, for example, a display device such as a CRT (Cathode Ray Tube) display, an LCD (Liquid Crystal Display), or an organic EL (Electro-Luminescence) display.

Note that the hardware configuration shown in FIG. 4 is an example, and the diagnostic device 100 does not need to include all of the component devices, and may include other component devices.

(Functional configuration of processing machine and diagnostic device)
Next, the functional configurations of the processing machine 200 and the diagnostic device 100 will be explained. FIG. 5 is a block diagram showing an example of the functional configuration of a processing machine and a diagnostic device.

First, the functional configuration of the processing machine 200 will be explained. The processing machine 200 includes a numerical control section 201, a communication control section 202, and a drive control section 203.

The numerical control unit 201 executes processing by the drive unit 24 using numerical control (NC). For example, the numerical control unit 201 generates and outputs numerical control data for controlling the operation of the drive unit 24. Further, the numerical control section 201 outputs operating information to the communication control section 202.

Here, the operating information is information indicating the operating state of the target device. In this embodiment, it refers to information indicating the operating state of the processing machine 200. The operation information includes, for example, an ON/OFF signal (hereinafter referred to as a "ladder signal") for indicating the interval from the feed operation of the tool 200t to the workpiece to the end of the actual machining process.

For example, the numerical control unit 201 sequentially transmits operation information corresponding to the current operation of the processing machine 200 to the diagnostic device 100 via the communication control unit 202. When processing an object to be processed, the numerical control unit 201 changes the type of drive unit 24 to be driven or the driving state (number of rotations, rotation speed, etc.) of the drive unit 24 depending on the process of processing.

Each time the numerical control unit 201 changes the type of operation, it sequentially transmits operation information corresponding to the changed type of operation to the diagnostic device 100 via the communication control unit 202. For example, when the type of the tool 200t is changed or when the machining program is changed, the numerical control unit 201 transmits corresponding operation information to the diagnostic device 100.

The communication control unit 202 controls communication with external devices such as the diagnostic device 100. For example, the communication control unit 202 transmits operation information corresponding to the current operation to the diagnostic device 100.

The drive control section 203 drives and controls the drive section 24 based on the numerical control data obtained by the numerical control section 201. In this embodiment, the drive control section 203 controls the drive control circuit 55 shown in FIG. 3 to drive the drive section 24.

In this embodiment, the functions of the numerical control section 201, communication control section 202, and drive control section 203 described above are realized by the CPU 20 executing a program stored in the ROM 20a or the like. It is not limited. For example, at least some of the functions of the numerical control section 201, communication control section 202, and drive control section 203 described above may be realized by a dedicated hardware circuit.

The program executed by the processing machine 200 of this embodiment is a file in an installable or executable format and can be stored on a computer such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk). It may be configured to be recorded on a readable recording medium and provided.

Furthermore, the program executed by the processing machine 200 of this embodiment may be stored on a computer connected to a network such as the Internet, and may be provided by being downloaded via the network. Further, the program executed by the processing machine 200 of this embodiment may be provided or distributed via a network such as the Internet.

Next, the functional configuration of the diagnostic device 100 will be explained. The diagnostic device 100 includes a communication control section 101, a detection information acquisition section 102, an operation information acquisition section 103, a processing section 104, a feature extraction section 105, a model generation section 106, an abnormality degree calculation section 107, an abnormality determination section 108, and an accumulation section 109. , a reception section 110, a confirmation section 111, a management section 112, a setting section 113, and a display control section 114.

The communication control unit 101 controls communication with the processing machine 200. For example, the communication control unit 101 receives operation information from the numerical control unit 201 of the processing machine 200 via the communication control unit 202.

The detection information acquisition unit 102 acquires detection information indicating a physical quantity detected by a detection unit that detects a physical quantity that changes depending on the operation of the target device. The detection information acquisition unit 102 is an example of an “acquisition unit”.

In this embodiment, the detection information acquisition unit 102 acquires detection information from the sensor 25 and sensor amplifier 25a installed in the processing machine 200. The detection information acquisition unit 102 acquires information on vibrations of the processing machine 200 as detection information. The vibration information is, for example, waveform data.

The operation information acquisition unit 103 acquires operation information indicating the operation state of the target device. In this embodiment, the operation information acquisition unit 103 acquires operation information received by the communication control unit 101 from the processing machine 200.

The operation information acquired by the operation information acquisition unit 103 includes the spindle rotation speed, feed rate, spindle coordinate value, spindle current value, etc. during machining. Further, by accepting user input, information such as tool type, tool manufacturer, tool diameter, etc. can also be acquired.

Here, the detection information acquired by the detection information acquisition unit 102 and the operation information acquired by the operation information acquisition unit 103 will be explained in detail. FIG. 6 is a diagram showing an example of processing machine detection information and ladder signals. As mentioned above, the ladder signal is an example of "operation information."

The detection information includes a waveform portion indicating a non-processing section and a waveform portion indicating a processing section. The non-machining section is a section before and after the tool 200t starts feeding the object to be machined. The machining section is a section in which the tool 200t is in contact with the object to be processed to perform processing such as cutting. In other words, the machining section is the period during which machining is actually performed.

On the other hand, the processing machine 200, for example, turns on the ladder signal when starting a machining operation using the tool 200t, performs a feed operation to send the tool 200t to the workpiece, and turns the ladder signal OFF when the actual machining process is finished. .

In other words, the period in which the ladder signal is in the ON state in FIG. 6 is the time when machining is performed. The machining execution time includes a non-machining section in which the tool 200t is not in contact with the machining object, and a machining period in which the tool 200t is in contact with the machining object and performing machining.

When manufacturing a plurality of predetermined processed products, the processing machine 200 may repeatedly perform a cycle including a plurality of processing steps P1 to P3. At this time, the operation information acquisition unit 103 acquires operation information such as a ladder signal, and at the same time, the detection information acquisition unit 102 acquires detection information such as vibrations and sounds in the processing machine 200.

When the detection information is acquired by the detection information acquisition unit 102, the processing unit 104 performs a process of associating the detection information with operating information corresponding to a processing step to be monitored set by the user.

In this embodiment, when detection information is acquired by the detection information acquisition unit 102, the processing unit 104 acquires operating information corresponding to a processing step to be monitored set by a setting unit 113, which will be described later, and the detection information acquisition unit 104. Among the detection information acquired by the unit 102, the detection information corresponding to the operation information corresponding to the processing step to be monitored is associated with the detection information.

Furthermore, the processing unit 104 performs preprocessing of the detection information associated with the operation information. Examples of the preprocessing include filtering to remove noise.

The process of associating operating information and detection information by the processing unit 104 will be described in detail. First, operation information assumed in the diagnostic system 1 of this embodiment will be explained. FIG. 7 is a diagram showing an example of operation information of a processing machine.

In FIG. 7, 1-1 etc. indicate programs for performing general cutting processing. In this example, machining is performed on the workpiece using tool A using programs 1-1 and 1-2, machining is performed using tool B using program 1-3, and machining is performed using program 1-4 to 1-4. Machining is performed using tool C using a program 1-6, and machining is performed using tool D using programs 1-7 to 1-9, thereby completing the machining of object 1.

When focusing on the number of machining operations as the operating information acquired from the processing machine 200, 1-1 to 1-9 can be considered to be the same operating information. Furthermore, when focusing on the type of tool 200t as the operating information acquired from the processing machine 200, 1-1 and 1-2, 2-1 and 2-2, N-1 and N-2 have the same operating information. You can think about it.

Furthermore, when focusing on the machining program as information acquired from the machining machine 200, 1-1, 2-1, and N-1 can be considered to be the same operating information. In this way, operation information can be grouped from various viewpoints. Information for grouping operation information includes, in addition to tool type and machining program, the number of machining operations, machining cycles, spindle rotation speed, and sequence numbers.

Next, a process of associating operating information and detection information by the processing unit 104 will be specifically described. FIG. 8 is a diagram illustrating an example of the association between operating information and detection information.

In this example, it is assumed that the processing step to be monitored set by the user is the processing step performed by tool B. In this embodiment, the processing unit 104 groups 1-3, 2-3, and N-3 as the same operating information. Further, the processing unit 104 associates the grouped operation information with the detection information corresponding to 1-3, 2-3, and N-3. By performing such processing, it becomes possible to observe changes in the characteristic information of a specific process.

The feature extraction unit 105 extracts feature information indicating the characteristics of the detection information from the detection information that has been associated with the operation information and preprocessed by the processing unit 104.

The characteristic information may be any information as long as it indicates the characteristics of the detected information. For example, when the detection information is acoustic data collected by a microphone, the feature extraction unit 105 may extract energy, frequency spectrum, MFCC (Mel frequency cepstral coefficient), etc. as the feature information.

Here, extraction of feature information by the feature extraction unit 105 will be explained in detail. Here, the description will be made assuming that the extracted feature information is a frequency spectrum. FIG. 9 is a diagram schematically illustrating feature information extracted from detection information by the diagnostic device using frequency components. In this example, it is assumed that the processing step P2 shown in FIG. 6 has been set as a monitoring target by the user. The section shown in FIG. 9 is the processing implementation time corresponding to the processing step P2.

In this embodiment, the feature extraction unit 105 extracts feature information by performing Fourier transform on the detection information for each frame.

Here, a frame refers to the amount of data for a predetermined period of time, such as 20 [ms], 40 [ms], etc., of detection information, and the feature information is a frequency spectrum obtained by Fourier transforming the detection information. This corresponds to the amount of data for the window length in a certain case. The feature information shown in FIG. 9 is associated with the time of the corresponding detection information frame.

The model generation unit 106 generates a model used to determine whether processing has been performed normally. A model is generated for each operation information, for example. Note that when the model is generated by an external device, the model generation unit 106 may not be provided.

In this embodiment, the model generation unit 106 generates a model for each operation information by performing a correlation analysis for each processing step of the feature information extracted by the feature extraction unit 105 from the detection information during normal operation of the processing machine 200. Note that the model generation unit 106 may generate the model by machine learning, deep learning, or the like using feature information.

When the detection information is acquired by the detection information acquisition unit 102, the abnormality degree calculation unit 107 calculates the degree of abnormality based on information that associates the operation information of the target device with the detection information acquired by the detection unit. Calculate. The abnormality degree calculation unit 107 is an example of a “calculation unit”.

In this embodiment, the abnormality degree calculation unit 107 first uses the feature information extracted by the feature extraction unit 105 and the model for each operation information generated by the model generation unit 106 to calculate the extracted feature information. A sub-score is calculated, which is a score value in which abnormalities are accumulated. Here, the sub-score indicates how much the extracted feature information deviates from the model. A subscore is an example of a "parameter."

Note that the abnormality degree calculation unit 107 calculates the sub-score by comparing the characteristic information obtained during normal operation of the processing machine 200 and the characteristic information obtained from the detection information of the abnormality determination target, without using a model. It may be calculated. Alternatively, the abnormality degree calculation unit 107 calculates the sub-score by comparing the detection information obtained during normal operation of the processing machine 200 and the detection information corresponding to the processing process to be monitored set by the user. You may.

The abnormality degree calculation unit 107 calculates a plurality of sub-scores according to abnormality detection targets such as the workpiece, the tool 200t, the drive unit 24 of the processing machine 200, and the main shaft of the drive unit 24.

The abnormality degree calculation unit 107 calculates the abnormality degree by combining the plurality of calculated sub-scores. Specifically, the abnormality degree calculation unit 107 calculates the abnormality degree by summing the numerical values obtained by multiplying each sub-score by a weight.

Note that the weight can also be adjusted by the user. In this embodiment, the degree of abnormality calculated using unadjusted weights will be referred to as a comprehensive score, and the degree of abnormality calculated using weights adjusted by the user will be referred to as a custom score. Settings for displaying custom scores will be described later.

The abnormality determination unit 108 determines whether or not there is an abnormality in the target device based on the abnormality degree calculated by the abnormality degree calculation unit 107. In this embodiment, the abnormality determination unit 108 performs threshold processing on the abnormality degree calculated by the abnormality degree calculation unit 107 to determine whether or not there is an abnormality in the processing machine 200. The abnormality determination unit 108 determines that an abnormality has occurred in the processing machine 200 when the degree of abnormality exceeds a preset threshold, and determines that no abnormality has occurred in the processing machine 200 when the degree of abnormality is equal to or less than the threshold.

Note that the method of determining an abnormality by the abnormality determining unit 108 is not limited to this. For example, abnormalities may be determined using learning means such as machine learning or deep learning.

The storage unit 109 stores the abnormality degree calculated by the abnormality degree calculation unit 107. In the present embodiment, the storage unit 109 stores the operation information associated with the detection information by the processing unit 104, the abnormality degree calculated by the abnormality degree calculation unit 107, and the abnormality determination of the processing machine 200 by the abnormality determination unit 108. The results are associated with each other, a monitoring range number is attached, and processed data is stored in the storage unit 13. The monitoring range number is a number assigned to manage processed data.

In this embodiment, the storage unit 109 stores the processed data in the storage unit 13, but it may also store the processed data in a storage device or the like provided in the cloud server CS (see FIG. 1).

The reception unit 110 receives input from the user. The receiving unit 110 receives, for example, an input of weight candidates indicating weight candidates for a plurality of parameters used to calculate the degree of abnormality.

In the present embodiment, the receiving unit 110 receives input of numerical values that are candidates for sub-score weights on a custom score setting addition screen that will be described later. The receiving unit 110 also receives an instruction to determine the weight of the sub-score from the user.

Further, the receiving unit 110 receives a selection of one custom score setting from the user in a dialog that is displayed when the user presses the "load registered score" button on the custom score setting addition screen. Note that the weight of the sub-score is an example of "parameter weight" used to calculate the degree of abnormality.

The determining unit 111 determines the weight candidate accepted by the accepting unit 110 as the weight of the parameter. In this embodiment, when the reception unit 110 receives an instruction to confirm the weight of a sub-score from the user, the determining unit 111 determines the input numerical value as the weight of the sub-score.

The management unit 112 stores the parameters and the weights of the parameters determined by the determination unit 111 in association with each other as calculation information in the storage unit 13, and reads the calculation information from the storage unit 13. Note that the calculation information is information for calculating the degree of abnormality.

In this embodiment, the management unit 112 stores the name of the custom score setting, the sub-score, and the weight of the sub-score determined by the determining unit 111 in the storage unit 13 as the custom score setting. Furthermore, the management unit 112 reads out the custom score settings stored in the storage unit 13 according to the user's selection. Custom score settings are an example of "calculation information."

The setting unit 113 performs various settings of the diagnostic device 100. In this embodiment, the setting unit 113 sets a specific processing step as a processing step to be monitored by the user. Furthermore, the setting unit 113 can also set a specific tool 200t as the tool 200t that is to be monitored by the user. Furthermore, the setting unit 113 can also set a threshold value for determining an abnormality in the processing machine 200 by the abnormality determining unit 108.

The display control unit 114 changes and displays the degree of abnormality accumulated by the accumulation unit 109, reflecting the weight candidate accepted by the reception unit 110. Furthermore, the display control unit 114 causes the display unit 15 to simultaneously display the parameters, the weight candidates, and the degree of abnormality that is changed to reflect the weight candidates.

The display control unit 114 causes the display unit 15 to display the degree of abnormality that has been changed to reflect the weight of the parameter determined by the determination unit 111.

The display control unit 114 refers to calculation information that associates, for each of the plurality of abnormal items, a parameter for calculating the degree of abnormality of the abnormal item with a weight of the parameter determined by the determining unit 111. Then, the parameters and weights of the parameters associated with the abnormality items specified by the user are extracted, and the weights of the parameters are used as weight candidates, and the weights are changed to reflect the parameters, weight candidates, and weight candidates. The degree of abnormality and the degree of abnormality are simultaneously displayed on the display unit 15.

Note that the display control section 114 is an example of an "output control section."

In the present embodiment, the display control unit 114 displays arbitrary past processed data accumulated by the accumulation unit 109 by reflecting the numerical value input by the user as a candidate for the weight of the sub-score on the custom score setting addition screen. It is displayed on the display unit 15. Further, the display control unit 114 causes the display unit 15 to display arbitrary past processed data that reflects the custom score settings read by the user on the abnormality degree display screen.

Here, custom score settings will be explained in detail. FIGS. 10A to 10D are diagrams illustrating an example of custom score settings. FIG. 10A is a diagram showing an example of a custom score setting screen.

In this figure, "Drill Abnormality Score," "End Mill Abnormality Score," and "Reamer Abnormality Score" represent the names of custom score settings that have already been registered. “Drill abnormality score”, “end mill abnormality score”, and “reamer abnormality score” are examples of “abnormality items”.

By selecting the name of the custom score setting, such as "drill abnormal score", the user can read the custom score setting and perform operations such as editing. "Subscore 1", "Subscore 2", and "Subscore 3" are parameter sets for calculating the degree of abnormality. The “drill abnormality score,” “end mill abnormality score,” and “reamer abnormality score” have “subscore 1,” “subscore 2,” and “subscore 3” as setting items.

Note that "subscore 1," "subscore 2," and "subscore 3" are calculated from vibration information, and are index values with different calculation methods and characteristics. The numerical value to the right of each sub-score represents the weight of the sub-score. Buttons such as "Add" and "Edit" at the bottom right are buttons for performing various operations.

The "Add" button is a button for adding custom score settings. When the user presses the "Add" button, the reception unit 110 receives an instruction to add custom score settings. When the receiving unit 110 receives an instruction to add custom score settings, the display control unit 114 causes the display unit 15 to display a custom score setting addition screen.

FIG. 10B is a diagram showing an example of a custom score setting addition screen. In this figure, "display name" is the name of the custom score setting. The display name can be changed to any name. In this example, the name "Custom Score 1" is input as the display name. The custom score setting addition screen is an example of a "first screen."

The weight of a subscore such as "subscore 1" can be incremented/decremented by using the up and down buttons on the screen. Note that the user can also directly input numerical values using the input device 14. The accepting unit 110 accepts numerical values input by the user that are candidates for sub-score weights.

When the reception unit 110 accepts the numerical value input, the display control unit 114 reflects the received numerical value, changes the degree of abnormality included in the past processed data, and displays it in real time on the preview display unit at the bottom of the screen. In the preview display section, the degree of abnormality is displayed in the form of stacked sub-scores so that the breakdown of the sub-scores can be seen. Note that in the preview display section, the vertical axis indicates the degree of abnormality, and the horizontal axis indicates the number of processing times.

The "Read registered score" button is a button for reading out custom score settings that have already been registered. A detailed explanation of "reading registered scores" will be given later. The "monitoring range number" is a button for specifying processed data to be displayed on the preview display section. The user can preview any past processed data.

The "OK" button is a button for confirming the numerical value accepted by the reception unit 110 as the weight of the sub-score. The "Cancel" button is a button for canceling the custom score setting addition process.

When the user presses the "OK" button, the receiving unit 110 receives an instruction to confirm the weight of the sub-score. When the reception unit 110 receives the confirmation instruction, the confirmation unit 111 confirms the currently input numerical value as the weight of the sub-score. The weight of the sub-score determined by the determining section 111 is stored by the managing section 112 in the storage section 13 as a custom score setting.

Here, the concept of weight adjustment of sub-scores will be explained. For example, suppose a user wants to monitor machining performed with an end mill. In general, end mills are known to have a relatively long machining time, so in this case, the user pays attention to abnormalities in the time direction. Then, if there is a sub-score representing an abnormality in the time direction, the user increases the weight of that sub-score.

Further, the numerical value input by the user as a weight candidate for the sub-score is reflected in the preview display section in real time. Furthermore, since the degree of abnormality is displayed in a form that shows the breakdown of sub-scores, the user may notice a sudden increase in a particular sub-score from the display in the preview display section.

For example, in the example of FIG. 10B, it can be seen that the sub-score 3 increases rapidly in the first processing. Therefore, the user increases the weight of "sub-score 3" in order to pay attention to the abnormality represented by "sub-score 3".

Next, "reading registered scores" will be explained in detail. FIG. 10C is a diagram illustrating an example of a process for reading registered sub-score settings. When the user presses the "Read registered score" button, the registered custom score settings can be read.

For example, assume that the user wants to monitor the machining performed by the end mill because the end mill is used frequently. In this case, if a custom score setting called "end mill abnormality score" is registered to focus on machining by end mills, the weights of sub-scores can be adjusted using this custom score setting as a template, improving work efficiency. can be expected.

When the user presses the "Read Registered Score" button, the reception unit 110 receives an instruction to read the custom score settings. When the reception unit 110 receives the read instruction, the display control unit 114 causes the display unit 15 to display the dialog shown in FIG. 10C.

In this example, three buttons are displayed on the dialog: "Drill Abnormality Score," "End Mill Abnormality Score," and "Reamer Abnormality Score."

When the user presses the "end mill abnormality score" button in the displayed dialog, the reception unit 110 receives a selection of custom score settings from the user. When the reception unit 110 accepts the selection, the management unit 112 reads the custom score settings accepted by the reception unit 110 from the storage unit 13. The display control unit 114 redisplays the custom score setting addition screen.

The weight of the sub-score set in the "end mill abnormality score" is entered in the weight of the sub-score on the redisplayed custom score setting addition screen, and this weight of the sub-score is also reflected in the preview display area. , the displayed degree of abnormality changes. The user adjusts the weight of the sub-scores with reference to the display on the preview display section.

When a custom score setting is added on the custom score setting addition screen, the display control unit 114 causes the display unit 15 to display the custom score setting screen. The added custom score settings are displayed on the custom score settings screen.

FIG. 10D is a diagram illustrating an example of a custom score setting screen after adding custom score settings. In this example, "Custom Score 1" added to the row below "Reamer Abnormality Score" is displayed. Note that the custom score displayed when "custom score 1" in this figure is used is "10*subscore 1+5*subscore 2+4*subscore 3".

Next, the abnormality degree display screen will be explained. FIG. 11 is a diagram showing an example of an abnormality degree display screen. On the abnormality level display screen, the display control unit 114 changes and displays past processed data stored in the storage unit 13 to reflect the custom score settings. The abnormality degree display screen is an example of a "second screen."

Specifically, the degree of abnormality and determination results included in past processed data are changed and displayed. The user can arbitrarily specify the processed data to be displayed. Selection of processed data is performed on a processed data selection screen (not shown). The monitoring range number of the processed data selected by the user is displayed on the abnormality degree display screen.

The "display content" button is a button for changing custom score settings. When the user presses the "display content" button, the reception unit 110 receives an instruction to change the custom score settings.

When the receiving unit 110 receives the change instruction, a dialog similar to the dialog that is displayed when the "load registered score" button is pressed on the custom score setting addition screen is displayed. When the user selects one custom score setting, the receiving unit 110 receives a custom score setting selection instruction.

When the reception unit 110 receives the selection instruction, the display control unit 114 causes the display unit 15 to display the processed data, reflecting the selected custom score settings. It is also possible to select the overall score using the "Display Contents" button. The currently selected custom score settings are displayed below the "Display Contents" button.

In the abnormality degree display screen, the vertical axis represents the abnormality degree, and the horizontal axis represents the number of machining operations. The values on the horizontal and vertical axes change depending on the processing data to be displayed. Although not shown, if the degree of abnormality exceeds a set threshold, an alert is displayed at the top of the screen. By pressing the "alert setting" button, a threshold value for determining an abnormality in the processing machine 200 can be set.

Note that the display control unit 114 can switch between the custom score setting addition screen and the abnormality degree display screen to display them on the display unit 15. In this embodiment, the display control unit 114 switches and displays a custom score setting addition screen and an abnormality degree display screen via the custom score setting screen.

In this embodiment, the above communication control unit 101, detection information acquisition unit 102, operation information acquisition unit 103, processing unit 104, feature extraction unit 105, model generation unit 106, abnormality degree calculation unit 107, abnormality determination unit 108, storage The functions of the unit 109, reception unit 110, confirmation unit 111, management unit 112, setting unit 113, and display control unit 114 are realized by the CPU 10 executing a program stored in the ROM 10a or the like. It is not limited to this.

For example, the above-mentioned communication control unit 101, detection information acquisition unit 102, operation information acquisition unit 103, processing unit 104, feature extraction unit 105, model generation unit 106, abnormality degree calculation unit 107, abnormality determination unit 108, storage unit 109, Even if at least some of the functions of the reception unit 110, confirmation unit 111, management unit 112, setting unit 113, and display control unit 114 are realized by a dedicated hardware circuit, good.

The program executed by the diagnostic device 100 of this embodiment is a file in an installable or executable format that can be stored on a computer such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk). It may be configured to be recorded on a readable recording medium and provided.

Furthermore, the program executed by the diagnostic apparatus 100 of this embodiment may be stored on a computer connected to a network such as the Internet, and may be provided by being downloaded via the network. Further, the program executed by the diagnostic device 100 of this embodiment may be provided or distributed via a network such as the Internet.

Each function of the embodiments described above can be realized by one or more processing circuits. Here, the term "processing circuit" as used herein refers to a processor programmed to execute each function by software, such as a processor implemented by an electronic circuit, or a processor designed to execute each function explained above. This includes devices such as ASICs, DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays), and conventional circuit modules.

(Diagnostic system processing)
Next, the processing of the diagnostic system 1 will be explained. First, processing for accumulating processed data will be explained. FIG. 12 is a flowchart showing an example of processing data accumulation processing. Note that it is assumed that the setting unit 113 has set a processing step to be monitored.

First, the receiving unit 110 receives an instruction to record processed data from a user (step S101). Note that the recording instruction is input by the user pressing the "ON/OFF" button displayed at the upper right end of the screen to turn the display "ON" (for example, in Figures 10A and 11). reference).

The detection information acquisition unit 102 acquires the physical quantities detected by the sensor 25 and the sensor amplifier 25a of the processing machine 200 as detection information (step S102). The operation information acquisition unit 103 acquires operation information from the processing machine 200 (step S103).

The processing unit 104 selects the operation information corresponding to the processing process to be monitored set by the setting unit 113 from among the operation information acquired by the operation information acquisition unit 103 and the detection information acquired by the detection information acquisition unit 102. , performs a process of associating the operation information corresponding to the processing step to be monitored set by the setting unit 113 with the corresponding detection information (step S104). Also, at this time, the processing unit 104 performs preprocessing of the detection information associated with the operation information.

The feature extraction unit 105 extracts feature information from the preprocessed detection information that is associated with the operation information corresponding to the processing step to be monitored set by the setting unit 113 (step S105). The abnormality degree calculation unit 107 calculates a sub-score from the feature information extracted by the feature extraction unit 105 (step S106). The abnormality degree calculation unit 107 calculates the abnormality degree from the calculated sub-scores (step S107).

The abnormality determination unit 108 determines whether or not there is an abnormality in the processing machine 200 based on the abnormality degree calculated by the abnormality degree calculation unit 107 (step S108). The storage unit 109 stores operation information corresponding to the processing process to be monitored set by the setting unit 113, the degree of abnormality calculated by the abnormality degree calculation unit 107, and the determination result of the presence or absence of an abnormality by the abnormality determination unit 108. , are associated with each other as processed data, are stored in the storage unit 13, and this processing is ended (step S109).

Next, the custom score setting addition process will be explained. FIG. 13 is a flowchart illustrating an example of custom score setting addition processing.

First, as a premise, in order to perform additional processing of custom score settings, it is necessary to display the custom score settings screen. When the custom score setting screen is not displayed (for example, see FIG. 11), when the user presses the "score setting" button for switching views, the reception unit 110 accepts the custom score setting screen display instruction and controls the display. The unit 114 causes the display unit 15 to display a custom score setting screen.

When the user presses the "Add" button on the custom score setting screen, the reception unit 110 receives an instruction to add custom score settings (step S201). When the reception unit 110 receives the addition instruction, the display control unit 114 displays a custom score setting addition screen (step S202).

The receiving unit 110 receives a designation of a monitoring range number from the user (step S203). As a result, the processed data to which the monitoring range number specified by the user is attached is displayed as a preview. The accepting unit 110 accepts numerical values input by the user as weight candidates for the sub-scores (step S204).

When the reception unit 110 receives a numerical value that is a weight candidate for a sub-score, the display control unit 114 displays a preview of the processed data that reflects the input weight candidate for the sub-score (step S205).

The accepting unit 110 accepts from the user again an input of a numerical value as a candidate weight for a sub-score, or an input for an instruction to confirm the weight of a sub-score (step S206). When the reception unit 110 receives an input from the user of an instruction to determine the weight of the sub-score (step S206: Yes), the determination unit 111 determines the input numerical value as the weight of the sub-score.

When the weight of the sub-score is determined by the determining section 111, the management section 112 stores the determined weight of the sub-score as a custom score setting in the storage section 13, and ends this process (step S207).

In addition, in step S206, when the receiving unit 110 receives from the user a numerical value as a sub-score weight candidate again (step S206: No), steps S204 and S205 continue until the input of an instruction to confirm the sub-score weight is received. Repeat the process.

Next, the abnormality degree display processing will be explained. FIG. 14 is a flowchart illustrating an example of abnormality degree display processing. As a premise, it is assumed that the process starts from a state where the custom score setting screen is displayed (for example, see FIG. 10D).

The receiving unit 110 receives an instruction to display the abnormality degree display screen (step S301). A display instruction for the abnormality degree display screen is input by the user pressing a view switching "details" button. When the reception unit 110 receives the display instruction, a monitoring range number designation screen is displayed. The receiving unit 110 receives the designation of a monitoring range number from the user (step S302).

When the reception unit 110 accepts the designation of the monitoring range number, the display control unit 114 displays an abnormality degree display screen (step S303).

When the user presses the "display content" button on the abnormality level display screen, the display control unit 114 displays the dialog that is displayed when the user presses the "load registered score" button on the custom score setting addition screen described above. Display a similar dialog.

The user selects any custom score setting, and the receiving unit 110 receives the user's selection of display content (step S304). By selecting display content, the user can display past processed data that reflects arbitrary custom score settings.

The display control unit 114 displays processed data that reflects the selected display content, and ends this process (step S305).

(Effects of diagnostic system)
In conventional diagnostic systems, the degree of abnormality calculated is a composite of a plurality of subscores, and the weights of the subscores used to calculate the degree of abnormality are fixed values. Fluctuations in subscores are associated with specific phenomena, but since the degree of abnormality is a composite of multiple subscores, it comprehensively represents multiple phenomena. Therefore, even if attention is paid to the degree of abnormality, it may be difficult to understand a specific phenomenon.

In the diagnostic device 100 of the present embodiment, the reception unit 110 receives numerical values that are candidates for sub-score weights, and the display control unit 114 displays past processed data on the display unit 15 in which the numerical values that are candidates for sub-score weights are reflected. to be displayed. At this time, the degree of abnormality is displayed so that the breakdown of the sub-scores can be understood.

This allows the user to notice that ``a certain phenomenon seems to be occurring'' from the fluctuations in the sub-scores. Once you realize this, you will be able to adjust the weights of subscores to be more appropriate. Therefore, the diagnostic device 100 of this embodiment can make it easier to understand a specific phenomenon by adjusting the parameters.

Further, the determining unit 111 determines the numerical value of the sub-score weight candidate input by the user as the sub-score weight, and the management unit 112 stores the determined sub-score weight in the storage unit 13 as a custom score setting. . The display control unit 114 causes the display unit 15 to display past processed data accumulated by the accumulation unit 109, reflecting the custom score settings read by the management unit 112.

Thereby, even if a new custom score setting is registered, the custom score setting can be immediately reflected and past processed data can be displayed.

(Modified example)
In the above embodiment, the device to be diagnosed is, for example, the processing machine 200, but the target device may also be other machine tools such as assembly machines, measuring machines, inspection machines, or machines such as cleaning machines. .

In the above-described embodiment, the sensor 25 was described as being composed of, for example, a microphone device, a vibration sensor, an acceleration sensor, or an AE (Acoustic Emission) sensor, but it is also possible to use a camera (image) sensor in conjunction with these. You can. This makes it possible to check the progress of processing, etc.

In the embodiment described above, the detection information is, for example, vibration data or acoustic data, but other data such as the current value of the motor, load, torque, etc. can also be used as the detection information.

In the embodiment described above, the display control unit 114 of the diagnostic device 100 causes the display unit 15 to display various data, but the data output method is not limited to this. Various data may be printed out to a printer or the like connected to the diagnostic device 100. Various data may be output as audio data through a speaker or the like connected to the diagnostic device 100, such as when an alarm is issued when an alert threshold is exceeded.

Although the embodiments of the present invention have been described above, the above embodiments are presented as examples and are not intended to limit the scope of the invention. The novel embodiment described above can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. The above-mentioned embodiments and their modifications are included within the scope and gist of the invention, and are also included within the scope of the invention described in the claims and its equivalents.

1 Diagnostic system 1B bus 10 CPU
10a ROM
10b RAM
11 Communication I/F
12 Sensor I/F
13 Storage section 14 Input device 15 Display section 2B Bus 20 CPU
20a ROM
20b RAM
21 Communication I/F
23 Drive control circuit 24 Drive unit 25 Sensor 25a Sensor amplifier 100 Diagnosis device 101 Communication control unit 102 Detection information acquisition unit 103 Operation information acquisition unit 104 Processing unit 105 Feature extraction unit 106 Model generation unit 107 Abnormality degree calculation unit 108 Abnormality determination unit 109 Accumulation section 110 Reception section 111 Determination section 112 Management section 113 Setting section 114 Display control section 200 Processing machine 200h Holder 200t Tool 201 Numerical control section 202 Communication control section 203 Drive control section

Japanese Patent Application Publication No. 9-204219

Claims (5)

an acquisition unit that acquires detection information indicating a physical quantity that changes depending on the operation of the target device;
a calculation unit that calculates an abnormality degree based on information that associates operation information of the target device with the acquired detection information ;
a reception unit that receives input of parameter weight candidates used to calculate the degree of abnormality;
a display control unit that changes the degree of abnormality and displays it on a display unit in a stacked form of the parameters, reflecting the weight candidates of the parameters input by the reception unit ;
a determining unit that determines the parameter weight candidates input by the accepting unit as parameter weights;
Equipped with
After displaying the abnormality degree in a stacked manner on the display unit while changing the degree of abnormality, the accepting unit receives an input of a weight candidate for the parameter again.
Diagnostic equipment. The display control unit causes the display unit to display the degree of abnormality that has been changed to reflect the weight of the parameter determined by the determination unit.
The diagnostic device according to claim 1 . The display control unit generates, for each of the plurality of abnormal items, calculation information that associates the parameters for calculating the degree of abnormality of the abnormal item with the weights of the parameters determined by the determining unit. The parameter and the weight of the parameter associated with the abnormality item specified by the user are extracted by referring to displaying the candidate and the abnormality degree changed by reflecting the weight candidate of the parameter on the display unit;
The diagnostic device according to claim 2 . A method for controlling a diagnostic device, the method comprising:
an acquisition step of acquiring detection information indicating a physical quantity that changes according to the operation of the target device;
a calculation step of calculating an abnormality degree based on information that associates operation information of the target device with the acquired detection information ;
a reception step of accepting input of candidate weights of parameters used to calculate the degree of abnormality;
a display control step of changing the degree of abnormality and displaying it on a display unit in a stacked form of the parameters, reflecting the weight candidates of the parameters input in the reception step;
including;
In the receiving step, after displaying the abnormality degree in a stacked manner on the display unit while changing the degree of abnormality, the receiving unit again receives an input of a weight candidate for the parameter.
How to control diagnostic equipment. In the computer of the diagnostic equipment,
an acquisition step of acquiring detection information indicating a physical quantity that changes according to the operation of the target device;
a calculation step of calculating an abnormality degree based on information that associates operation information of the target device with the detection information acquired by the detection unit ;
a reception step of accepting input of candidate weights of parameters used to calculate the degree of abnormality;
a display control step of changing the degree of abnormality and displaying it on a display unit in a stacked form of the parameters, reflecting the weight candidates of the parameters input in the reception step;
In addition to executing
In the receiving step, after displaying the abnormality degree in a stacked manner on the display unit while changing the degree of abnormality, the receiving unit again receives an input of a weight candidate for the parameter.
program .

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