JP2021086588A - Diagnosis device, diagnosis device control method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a diagnostic device, a control method and a program of the diagnostic device capable of easily grasping a specific phenomenon by adjusting the weight of a parameter. SOLUTION: A acquisition unit 102 that acquires detection information indicating a physical quantity detected by a detection unit that detects a physical quantity that changes according to an operation of a target device 200, and a case where the detection information is acquired by the acquisition unit. , The calculation unit 107 that calculates the degree of abnormality based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other, and the degree of abnormality calculated by the calculation unit. The storage unit 109 that stores the information, the reception unit 110 that receives the input of the weight candidate of the parameter used to calculate the abnormality degree, and the storage unit that reflects the weight candidate received by the reception unit. An output control unit (display control unit) 114 for changing and outputting the accumulated abnormality degree is provided. [Selection diagram] Fig. 5

Description

The present invention relates to a diagnostic device, a control method and a program of the diagnostic device.

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

For example, in Patent Document 1, when a workpiece is machined by a machine tool, measured values are taken from a plurality of sensors to diagnose tool wear and workpiece machining accuracy, and there is a possibility that machining accuracy failure may occur before machining accuracy failure occurs. Techniques for identifying the cause are disclosed.

However, in the technique described in Patent Document 1, the degree of conformity (abnormality) used for diagnosing tool wear and workpiece machining accuracy is a membership function associated with phenomena related to tool wear and workpiece machining accuracy. The weighting coefficient (parameter weight) used in the calculation is a fixed value. Therefore, the goodness of fit is a value that reflects a plurality of phenomena, and it may be difficult to pay attention to a specific phenomenon.

The present invention has been made in view of the above, and an object of the present invention is to provide a diagnostic device, a control method and a program of the diagnostic device, which can make it easier to grasp a specific phenomenon by adjusting the weights of parameters. And.

In order to solve the above-mentioned problems and achieve the object, the present invention includes an acquisition unit that acquires detection information indicating a physical quantity detected by a detection unit that detects a physical quantity that changes according to the operation of the target device, and the above-mentioned acquisition unit. When the detection information is acquired by the acquisition unit, the calculation unit that calculates the degree of abnormality based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other. , The storage unit that accumulates the anomaly degree calculated by the calculation unit, the reception unit that accepts the input of the weight candidate of the parameter used for calculating the anomaly degree, and the weight candidate that is accepted by the reception unit. Is provided, and an output control unit for changing and outputting the abnormality degree accumulated by the storage unit is provided.

According to the present invention, it is possible to easily grasp a specific phenomenon by adjusting the parameters.

FIG. 1 is a diagram schematically showing the configuration of a diagnostic system. FIG. 2 is a diagram schematically showing the configuration of a 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 the processing machine and the diagnostic apparatus. FIG. 6 is a diagram showing an example of detection information and a ladder signal of the processing machine. FIG. 7 is a diagram illustrating an example of operation information of the processing machine. FIG. 8 is a diagram illustrating an example of associating operation information with detection information. FIG. 9 is a diagram schematically exemplifying the feature information extracted from the detection information by the diagnostic apparatus in terms of 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 showing an example of the reading process of the registered custom score setting. FIG. 10D is a diagram showing an example of a custom score setting screen after adding the custom score setting. FIG. 11 is a diagram showing an example of an abnormality degree display screen. FIG. 12 is a flowchart showing an example of processing for accumulating processing data. FIG. 13 is a flowchart showing an example of the custom score setting addition process. FIG. 14 is a flowchart showing an example of the abnormality degree display processing.

Hereinafter, the diagnostic apparatus according to the present invention, the control method of the diagnostic apparatus, and the embodiment of the diagnostic program will be described in detail with reference to the drawings.

(Overall configuration of diagnostic system)
FIG. 1 is a diagram schematically showing a 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. The diagnostic device 100 is connected to the cloud server CS via the network NT.

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

The tool 200t performs various machining on the machining target. The tool 200t includes, for example, a drill (diameter 5 mm, diameter 10 mm), an end mill (diameter 5 mm, diameter 10 mm), a reamer (diameter 5 mm), and the like. In this embodiment, cutting is performed on a machining target with a plurality of tools 200t and a plurality of machining programs.

(Hardware configuration of processing machine)
Next, a hardware configuration example of the processing machine 200 of 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 connected so as to be communicable by bus 2B.

The CPU 20 is an arithmetic unit that controls the entire processing machine 200. For example, the CPU 20 controls the operation of the entire processing machine 200 and realizes a processing function by executing a program stored in the ROM 20a or the like with the RAM 20b as a work area (work area).

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

The drive control circuit 23 is a circuit that controls the drive of the drive unit 24. The drive unit 24 is an actuator that drives a tool 200t used for machining. The tool 200t includes a drill, an end mill, a tool tip, a grindstone, etc., and a table on which a machining object is placed and moved according to the machining.

In the present embodiment, the drive unit 24 is a motor, but the present invention 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 the numerical control unit 201 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 in the vicinity of, for example, a tool 200t capable of detecting vibration or sound. 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 examples of the “detection unit”.

The sensor 25 and the sensor amplifier 25a include vibrations or sounds generated when a tool 200t such as a drill, an end mill, a tool tip or a grindstone installed in the processing machine 200 and a processing target come into contact with each other during a machining operation, or a tool 200t. Alternatively, the physical quantity such as vibration or sound generated by the processing machine 200 itself is detected, and the information of the detected physical quantity is output to the diagnostic apparatus 100 as detection information (sensor data).

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

For example, when the blade of the tool 200t used for machining is broken or chipping of the blade occurs, the sound during machining changes. Therefore, by detecting the acoustic data with the sensor 25 (microphone) and making a judgment using a model or the like for judging the normal sound, it is possible to detect an abnormality in the operation of the processing machine 200.

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 later. Further, the sensor amplifier 25a is not limited to being installed in the processing machine 200, and may be installed on the diagnostic device 100 side.

The hardware configuration shown in FIG. 3 is an example, and the processing machine 200 does not have to be equipped with all the constituent devices, and may be provided with other constituent devices.

(Hardware configuration of diagnostic device)
Next, a hardware configuration example of the diagnostic device 100 of 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 unit 13, an input device 14, and a display unit 15. Further, each component is connected so as to be communicable by bus 1B.

The CPU 10 is an arithmetic unit that controls the entire diagnostic device 100. For example, the CPU 10 controls the operation of the entire diagnostic device 100 by executing a program stored in the ROM 10a or the like with the RAM 10b as a work area (work area), and realizes the functions of the diagnostic device 100.

The communication I / F 11 is an interface used for communication with an external device such as a processing machine 200. The communication I / F 11 is, for example, a NIC or the like corresponding to TCP / IP.

The sensor I / F 12 is an interface for receiving 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, operation information described later, an OS (Operating System), and an application program.

The storage unit 13 is, for example, a non-volatile storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or an EEPROM (Electrically Elegant Program 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 characters, 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-Luminence) display.

The hardware configuration shown in FIG. 4 is an example, and the diagnostic device 100 does not have to include all the constituent devices, and may include other constituent devices.

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

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

The numerical control unit 201 executes machining by the drive unit 24 by numerical control (NC: Numerical Control). 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 unit 201 outputs operation information to the communication control unit 202.

Here, the operation information is information indicating the operation state of the target device. In the present embodiment, it refers to information indicating an 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 a section from the feed operation of the tool 200t to the machining target 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 apparatus 100 via the communication control unit 202. When machining an object to be machined, the numerical control unit 201 changes the type of drive unit 24 to be driven or the drive state (rotation speed, rotation speed, etc.) of the drive unit 24 according to the machining process.

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

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

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

In the present embodiment, the functions of the numerical control unit 201, the communication control unit 202, and the drive control unit 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 a part of the functions of the numerical control unit 201, the communication control unit 202, and the drive control unit 203 described above may be realized by a dedicated hardware circuit.

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

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

Next, the functional configuration of the diagnostic apparatus 100 will be described. The diagnostic device 100 includes a communication control unit 101, a detection information acquisition unit 102, an operation information acquisition unit 103, a processing unit 104, a feature extraction unit 105, a model generation unit 106, an abnormality degree calculation unit 107, an abnormality determination unit 108, and a storage unit 109. , A reception unit 110, a confirmation unit 111, a management unit 112, a setting unit 113, and a display control unit 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 the physical quantity detected by the detection unit that detects the physical quantity that changes according to the operation of the target device. The detection information acquisition unit 102 is an example of the “acquisition unit”.

In the present embodiment, the detection information acquisition unit 102 acquires detection information from the sensor 25 and the sensor amplifier 25a installed in the processing machine 200. The detection information acquisition unit 102 acquires vibration information 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 the present embodiment, the operation information acquisition unit 103 acquires the operation information received by the communication control unit 101 from the processing machine 200.

Examples of the operation information acquired by the operation information acquisition unit 103 include the spindle rotation speed at the time of machining, the feed rate, the spindle coordinate value, the current value of the spindle, and the like. In addition, by accepting user input, it is possible to acquire information such as a tool type, a tool maker, and a tool diameter.

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 described in detail. FIG. 6 is a diagram showing an example of detection information and a ladder signal of the processing machine. As described above, the ladder signal is an example of "operation information".

The detection information includes a waveform portion indicating a non-processed section and a waveform portion indicating a processed section. The non-machining section is a section before and after the tool 200t starts the feed operation with respect to the machining target. The machining section is a section in which the tool 200t is in contact with the machining target to perform machining processing such as cutting. That is, the processing section is the period during which processing is actually performed.

On the other hand, the machining machine 200 turns on the ladder signal at the start of the machining operation by the tool 200t, causes the feed operation to send the tool 200t to the machining target, and turns off the ladder signal when the actual machining process is completed. ..

That is, the section in FIG. 6 in which the ladder signal is in the ON state is the processing execution time. The machining execution time includes a non-machining section in which the tool 200t is not in contact with the machining target and a machining section in which the tool 200t is in contact with the machining target to perform machining processing.

When a plurality of predetermined processed products are produced, 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 vibration and sound in the processing machine 200.

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

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

In addition, the processing unit 104 performs preprocessing of the detection information associated with the operation information. Examples of the pretreatment include filtering for removing noise.

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

In FIG. 7, 1-1 and the like show a program for performing a general cutting process. In this example, the machining target is machined by the tool A using the program 1-1 and 1-2, and the tool B is machined by using the program 1-3. Machining by the tool C is performed using the program 1-6, machining is performed by the tool D using the programs 1-7 to 1-9, and machining for the machining target of 1 is completed.

When focusing on the number of times of processing as the operation information acquired from the processing machine 200, 1-1 to 1-9 can be considered to be the same operation information. Further, when paying attention to the type of the tool 200t as the operation 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 operation information. Can be considered.

Further, when paying attention to the machining program as the information acquired from the machining machine 200, 1-1, 2-1 and N-1 can be considered to be the same operation information. In this way, operation information can be grouped from various viewpoints. In addition to the tool type and machining program, the information for grouping the operation information includes the number of machining, the machining cycle, the spindle speed, the sequence number, and the like.

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

In this example, it is assumed that the processing process to be monitored set by the user is the processing process performed by the tool B. In the present embodiment, the processing unit 104 groups 1-3, 2-3, and N-3 as the same operation 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 feature information of a specific process.

The feature extraction unit 105 is associated with the operation information by the processing unit 104, and extracts the feature information indicating the feature of the detection information from the preprocessed detection information.

The feature information may be any information as long as it indicates the features of the detection 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 cepstrum coefficient), and the like as feature information.

Here, the extraction of the feature information by the feature extraction unit 105 will be described in detail. Here, it is assumed that the extracted feature information is a frequency spectrum. FIG. 9 is a diagram schematically exemplifying the feature information extracted from the detection information by the diagnostic apparatus in terms of frequency components. In this example, it is assumed that the processing process P2 shown in FIG. 6 is set as a monitoring target by the user. The section shown in FIG. 9 is the processing execution time corresponding to the processing step P2.

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

Here, the frame is a frequency spectrum obtained by indicating a predetermined time of detection information, for example, a data amount of 20 [ms], 40 [ms], etc., and the feature information is Fourier transformed with respect to the detection information. It corresponds to the amount of data of the window length in a certain case. The feature information shown in FIG. 9 is associated with a frame time of the corresponding detection information.

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

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

When the detection information acquisition unit 102 acquires the detection information, the abnormality degree calculation unit 107 has an abnormality degree based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other. Is calculated. The abnormality degree calculation unit 107 is an example of the “calculation unit”.

In the present 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 extract the feature information. Calculate the sub-score, which is the accumulated score value of the abnormalities of. Here, the subscore indicates how much the extracted feature information deviates from the model. The subscore is an example of a "parameter".

The abnormality degree calculation unit 107 determines the subscore by comparing the feature information obtained during normal operation of the processing machine 200 with the feature 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 subscore by comparing the detection information obtained during the normal operation of the processing machine 200 with 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 subscores according to an abnormality detection target such as a workpiece, a tool 200t, a drive unit 24 of the processing machine 200, and a spindle of the drive unit 24.

The abnormality degree calculation unit 107 calculates the abnormality degree by synthesizing a plurality of calculated subscores. Specifically, the abnormality degree calculation unit 107 calculates the abnormality degree by multiplying each subscore by a weight and summing the numerical values obtained.

The weight can also be adjusted by the user. In the present embodiment, the degree of abnormality calculated by the weight adjusted by the user is referred to as a total score, and the degree of abnormality calculated by the weight adjusted by the user is referred to as a custom score. The settings for displaying the custom score 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 the present embodiment, the abnormality determination unit 108 determines the presence or absence of an abnormality in the processing machine 200 by performing threshold processing on the abnormality degree calculated by the abnormality degree calculation unit 107. 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 value, and determines that an abnormality has not occurred in the processing machine 200 when the degree of abnormality exceeds the threshold value.

The method for determining an abnormality by the abnormality determination unit 108 is not limited to this. For example, the abnormality may be determined by using a learning means such as machine learning or deep learning.

The storage unit 109 stores the degree of abnormality calculated by the degree of abnormality calculation unit 107. In the present embodiment, the storage unit 109 determines 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 of the processing machine 200 by the abnormality determination unit 108. The result is associated with the monitoring range number to be processed data, which is stored in the storage unit 13. The monitoring range number is a number assigned to manage the machining data.

In the present embodiment, the storage unit 109 stores the processing data in the storage unit 13, but the processing data may be stored in a storage device or the like provided in the cloud server CS (see FIG. 1).

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

In the present embodiment, the reception unit 110 accepts the input of a numerical value that is a candidate for the weight of the subscore on the custom score setting addition screen described later. In addition, the reception unit 110 receives an instruction to confirm the weight of the subscore from the user.

Further, the reception unit 110 accepts the selection of 1 custom score setting from the user in the dialog displayed when the user presses the "read registered score" button on the custom score setting addition screen. The subscore weight is an example of the "parameter weight" used to calculate the degree of abnormality.

The confirmation unit 111 determines the weight candidates received by the reception unit 110 as parameter weights. In the present embodiment, when the reception unit 110 receives the confirmation instruction of the subscore weight from the user, the confirmation unit 111 determines the input numerical value as the subscore weight.

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

In the present embodiment, the management unit 112 stores the name of the custom score setting, the subscore, and the weight of the subscore confirmed by the confirmation unit 111 as the custom score setting in the storage unit 13. Further, the management unit 112 reads out the custom score setting stored in the storage unit 13 according to the user's selection. The custom score setting is an example of "calculation information".

The setting unit 113 makes various settings for the diagnostic device 100. In the present embodiment, the setting unit 113 sets a specific processing process as a processing process to be monitored by the user. Further, the setting unit 113 can also set a specific tool 200t as a tool 200t to be monitored by the user. Further, the setting unit 113 can also set a threshold value for determining the abnormality of the processing machine 200 by the abnormality determination unit 108.

The display control unit 114 reflects the weight candidates received by the reception unit 110, and changes and displays the degree of abnormality accumulated by the storage unit 109. Further, the display control unit 114 simultaneously displays the parameters, the weight candidates, and the degree of abnormality changed by reflecting the weight candidates on the display unit 15.

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

The display control unit 114 refers to the calculation information in which the parameter for calculating the abnormality degree of the abnormality item and the weight of the parameter determined by the confirmation unit 111 are associated with each of the plurality of abnormality items. Then, the parameter associated with the abnormal item specified by the user and the parameter weight were extracted, and the parameter weight was used as the weight candidate, and the parameter, the weight candidate, and the weight candidate were reflected and changed. The degree of abnormality is displayed on the display unit 15 at the same time.

The display control unit 114 is an example of an “output control unit”.

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

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

In this figure, "drill anomaly score", "end mill anomaly score", and "reamer anomaly score" represent the names of custom score settings that have already been registered. The "drill abnormal score", "end mill abnormal score", and "reamer abnormal score" are examples of "abnormal items".

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

The "subscore 1", "subscore 2", and "subscore 3" are calculated from vibration information, and are index values having different calculation methods and characteristics. The number to the right of each subscore represents the weight of the subscore. The buttons such as "Add" and "Edit" at the lower right are buttons for performing various operations and the like.

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

FIG. 10B is a diagram showing an example of a custom score setting addition screen. In this figure, the "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 entered as the display name. The custom score setting addition screen is an example of the "first screen".

The weight of the subscore such as "subscore 1" can be incremented / decremented by the up / down buttons on the screen. The user can also directly input the numerical value by the input device 14. The reception unit 110 receives a numerical value that is a candidate for the weight of the subscore input by the user.

When the reception unit 110 accepts the input of the numerical value, the display control unit 114 reflects the received numerical value, changes the degree of abnormality included in the past processing data, and displays it in the preview display unit at the bottom of the screen in real time. In the preview display unit, the degree of abnormality is displayed in the form of stacking each subscore so that the breakdown of the subscores can be understood. In the preview display unit, the vertical axis indicates the degree of abnormality and the horizontal axis indicates the number of times of machining.

The "Read registered score" button is a button for reading the already registered custom score setting. A detailed explanation of "reading the registered score" will be described later. The "monitoring range number" is a button for designating the processing data to be displayed on the preview display unit. The user can preview any past machining data.

The "OK" button is a button for determining the numerical value received by the reception unit 110 as the weight of the subscore. The "Cancel" button is a button for canceling the additional processing of the custom score setting.

When the "OK" button is pressed by the user, the reception unit 110 receives an instruction to confirm the weight of the subscore. When the reception unit 110 receives the confirmation instruction, the confirmation unit 111 confirms the currently input numerical value as the weight of the subscore. The weight of the subscore confirmed by the confirmation unit 111 is stored in the storage unit 13 as a custom score setting by the management unit 112.

Here, the concept of weight adjustment of subscores will be described. For example, suppose a user wants to monitor the machining performed on an end mill. Since it is generally known that an end mill has a relatively long machining time, in this case, the user pays attention to an abnormality in the time direction. Then, if there is a subscore indicating an abnormality in the time direction, the user will increase the weight of the subscore.

In addition, the numerical value input by the user as a weight candidate for the subscore is reflected in the preview display unit in real time. Further, since the degree of abnormality is displayed in a form in which the breakdown of the subscore can be understood, the user may notice a sudden rise in a specific subscore from the display of the preview display unit.

For example, in the example of FIG. 10B, it can be seen that the subscore 3 soars in the initial processing. Therefore, the user increases the weight of the "subscore 3" in order to pay attention to the abnormality represented by the "subscore 3".

Next, "reading the registered score" will be described in detail. FIG. 10C is a diagram showing an example of the reading process of the registered subscore setting. When the user presses the "Read registered score" button, the registered custom score setting can be read.

For example, suppose a user wants to monitor machining with an end mill because the end mill is used frequently. In this case, if a custom score setting called "end mill abnormal score" is registered to pay attention to the machining by the end mill, the weight of the subscore can be adjusted using this custom score setting as a template, so that the work efficiency is improved. Can be expected.

When the user presses the "read registered score" button, the reception unit 110 receives the instruction to read the custom score setting. 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 of "drill abnormal score", "end mill abnormal score", and "reamer abnormal score" are displayed in the dialog.

When the user presses the "end mill abnormal score" button in the displayed dialog, the reception unit 110 accepts the user to select the custom score setting. When the reception unit 110 accepts the selection, the management unit 112 reads the custom score setting received 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 subscore set in "End mill abnormal score" is input to the weight of the subscore on the redisplayed custom score setting addition screen, and the weight of this subscore is also reflected in the preview display section. , The displayed anomaly changes. The user adjusts the weight of the subscore with reference to the display of the preview display unit.

When the 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 custom score setting screen displays the added custom score setting.

FIG. 10D is a diagram showing an example of a custom score setting screen after adding the custom score setting. In this example, the "custom score 1" added to the bottom of the "reamer abnormal score" is displayed. 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 described. FIG. 11 is a diagram showing an example of an abnormality degree display screen. On the abnormality degree display screen, the display control unit 114 changes and displays the past processing data stored in the storage unit 13 by reflecting the custom score setting. The abnormality degree display screen is an example of the “second screen”.

Specifically, the degree of abnormality and the determination result included in the past processing data are changed and displayed. The processing data to be displayed can be arbitrarily specified by the user. The processing data is selected on the processing data selection screen (not shown). The monitoring range number of the machining data selected by the user is displayed on the abnormality degree display screen.

The "Display content" button is a button for changing the custom score setting. When the user presses the "display content" button, the reception unit 110 accepts the custom score setting change instruction.

When the reception unit 110 accepts the change instruction, a dialog similar to the dialog displayed when the "read registered score" button is pressed on the custom score setting addition screen is displayed. When the user selects the custom score setting of 1, the reception unit 110 accepts the custom score setting selection instruction.

When the reception unit 110 receives the selection instruction, the display control unit 114 reflects the selected custom score setting and displays the processing data on the display unit 15. You can also select the total score with the "Display content" button. Below the "Display Contents" button, the currently selected custom score setting is displayed.

On the abnormality degree display screen, the vertical axis represents the abnormality degree and the horizontal axis represents the number of times of machining. The numerical values on the horizontal axis and the vertical axis change according to the processing data to be displayed. Although not shown, an alert is displayed at the upper part of the screen when the degree of abnormality exceeds the set threshold value. When the "alert setting" button is pressed, a threshold value for determining an abnormality of the processing machine 200 can be set.

The display control unit 114 can switch between the custom score setting addition screen and the abnormality degree display screen and display them on the display unit 15. In the present embodiment, the display control unit 114 switches and displays the custom score setting addition screen and the abnormality degree display screen via the custom score setting screen.

In the present embodiment, 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, and accumulation. The functions of the unit 109, the reception unit 110, the confirmation unit 111, the management unit 112, the setting unit 113, and the 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 a part of the functions of the reception unit 110, the confirmation unit 111, the management unit 112, the setting unit 113, and the display control unit 114 is realized by a dedicated hardware circuit. Good.

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

Further, the program executed by the diagnostic apparatus 100 of the present embodiment may be stored on a computer connected to a network such as the Internet and provided by downloading via the network. Further, the program executed by the diagnostic apparatus 100 of the present embodiment may be configured to be provided or distributed via a network such as the Internet.

Each function of the above-described embodiment can be realized by one or more processing circuits. Here, the "processing circuit" in the present specification is 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 described above. It shall include devices such as ASICs, DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays) and conventional circuit modules.

(Processing of diagnostic system)
Next, the processing of the diagnostic system 1 will be described. First, the processing of accumulating processing data will be described. FIG. 12 is a flowchart showing an example of processing for accumulating processing data. As a premise, it is assumed that the processing process to be monitored is set by the setting unit 113.

First, the reception unit 110 receives a processing data recording instruction from the user (step S101). 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, FIGS. 10A and 11). reference).

The detection information acquisition unit 102 acquires the physical quantity 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).

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

The feature extraction unit 105 is associated with the operation information corresponding to the processing process to be monitored set by the setting unit 113, and extracts the feature information from the preprocessed detection information (step S105). The abnormality degree calculation unit 107 calculates a subscore 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 subscore (step S107).

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

Next, the custom score setting addition process will be described. FIG. 13 is a flowchart showing an example of the custom score setting addition process.

First, as a premise, it is necessary to display the custom score setting screen in order to perform the additional processing of the custom score setting. When the custom score setting screen is not displayed (see, for example, FIG. 11), when the user presses the "score setting" button for view switching, 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 the custom score setting screen.

When the "Add" button is pressed by the user on the custom score setting screen, the reception unit 110 receives the custom score setting addition instruction (step S201). When the reception unit 110 receives the additional instruction, the display control unit 114 displays the custom score setting addition screen (step S202).

The reception unit 110 receives the designation of the monitoring range number from the user (step S203). As a result, the machining data with the monitoring range number specified by the user is displayed as a preview. The reception unit 110 receives a numerical value as a weight candidate for the subscore input by the user (step S204).

When the reception unit 110 receives a numerical value as a weight candidate for the subscore, the display control unit 114 displays a preview of the processing data reflecting the input weight candidate for the subscore (step S205).

The reception unit 110 again accepts the input of the numerical value as the subscore weight candidate or the input of the subscore weight determination instruction from the user (step S206). When the reception unit 110 receives the input of the subscore weight confirmation instruction from the user (step S206: Yes), the confirmation unit 111 confirms the input numerical value as the subscore weight.

When the confirmation unit 111 determines the weight of the subscore, the management unit 112 saves the confirmed weight of the subscore in the storage unit 13 as a custom score setting, and ends this process (step S207).

In step S206, when the input of the numerical value which is the weight candidate of the subscore is received again from the reception unit 110 user (step S206: No), step S204 and step S205 until the input of the confirmation instruction of the weight of the subscore is accepted. Repeat the process of.

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

The reception unit 110 receives a display instruction on the abnormality degree display screen (step S301). The display instruction of the abnormality degree display screen is input by the user pressing the view switching "details" button. When the reception unit 110 receives the display instruction, the monitoring range number designation screen is displayed. The reception unit 110 receives the designation of the 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 the abnormality degree display screen (step S303).

When the user presses the "display content" button on the abnormality degree display screen, the display control unit 114 displays a dialog displayed when the user presses the "registered score read" button on the above-mentioned custom score setting addition screen. Display a similar dialog.

The user selects an arbitrary custom score setting, and the reception unit 110 accepts the user's selection of display contents (step S304). The user can display the past processing data reflecting any custom score setting by selecting the display content.

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

(Effect of diagnostic system)
In the conventional diagnostic system, the calculated degree of abnormality is a combination of a plurality of subscores, and the weight of the subscore used for calculating the degree of abnormality is a fixed value. Fluctuations in subscores are associated with specific phenomena, but since the degree of anomaly is a combination of multiple subscores, it is a comprehensive representation of multiple phenomena. Therefore, it may be difficult to grasp a specific phenomenon even if attention is paid to the degree of abnormality.

In the diagnostic device 100 of the present embodiment, the reception unit 110 receives a numerical value that is a candidate for the weight of the subscore, and the display control unit 114 reflects the past processing data that reflects the numerical value that is a candidate for the weight of the subscore. To display. At this time, the degree of abnormality is displayed so that the breakdown of the subscore can be understood.

This allows the user to be aware that "a certain phenomenon seems to be occurring" from the fluctuation of the subscore. With this awareness, it will be possible to adjust the weight of the subscore to a more suitable state. Therefore, the diagnostic device 100 of the present embodiment can easily grasp a specific phenomenon by adjusting the parameters.

Further, the confirmation unit 111 determines the numerical value of the subscore weight candidate input by the user as the subscore weight, and the management unit 112 stores the confirmed subscore weight as a custom score setting in the storage unit 13. .. The display control unit 114 reflects the custom score setting read by the management unit 112, and causes the display unit 15 to display the past machining data accumulated by the storage unit 109.

As a result, even when a new custom score setting is registered, the custom score setting can be immediately reflected and the past processing data can be displayed.

(Modification example)
In the above-described embodiment, the device to be diagnosed is, for example, a processing machine 200, but other machine tools such as an assembly machine, a measuring machine, an inspection machine, or a machine such as a washing machine may be the target device. ..

In the above-described embodiment, it has been described that 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, but a camera (image) sensor is used in combination with these. You may. This makes it possible to check the progress of processing.

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

In the above-described embodiment, the display control unit 114 of the diagnostic apparatus 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 on a printer or the like connected to the diagnostic apparatus 100. Various data may be output as voice data, such as an alarm being issued when the alert threshold is exceeded by a speaker or the like connected to the diagnostic device 100.

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

1 Diagnostic system 1B bus 10 CPU
10a ROM
10b RAM
11 Communication I / F
12 Sensor I / F
13 Storage unit 14 Input device 15 Display unit 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 Diagnostic 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 calculation unit 108 Abnormality determination unit 109 Storage unit 110 Reception unit 111 Confirmation unit 112 Management unit 113 Setting unit 114 Display control unit 200 Machining machine 200h Holder 200t Tool 201 Numerical control unit 202 Communication control unit 203 Drive control unit

Japanese Unexamined Patent Publication No. 9-20421

Claims (7)

An acquisition unit that acquires detection information indicating the physical quantity detected by the detection unit that detects the physical quantity that changes according to the operation of the target device, and an acquisition unit.
When the detection information is acquired by the acquisition unit, the calculation unit calculates the degree of abnormality based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other. When,
A storage unit that accumulates the degree of abnormality calculated by the calculation unit, and a storage unit that accumulates the degree of abnormality.
A reception unit that accepts input of parameter weight candidates used to calculate the degree of abnormality, and
An output control unit that reflects the weight candidates received by the reception unit and changes and outputs the degree of abnormality accumulated by the storage unit.
A diagnostic device. The first aspect of claim 1, wherein the output control unit simultaneously displays the parameter, the weight candidate, and the abnormality degree changed by reflecting the weight candidate on the display unit as a first screen. Diagnostic device. A confirmation unit for determining the weight candidate received by the reception unit is further provided.
The output control unit causes the display unit to display the degree of abnormality changed by reflecting the weight of the parameter determined by the determination unit as a second screen.
The diagnostic device according to claim 2. The diagnostic device according to claim 3, wherein the output control unit switches between the first screen and the second screen and displays them on the display unit. The output control unit provides calculation information in which the parameter for calculating the degree of abnormality of the abnormality item and the weight of the parameter determined by the confirmation unit are associated with each of the plurality of abnormality items. With reference to, the parameter associated with the abnormal item specified by the user and the weight of the parameter are extracted, and the weight of the parameter is used as the weight candidate, and the parameter, the weight candidate, and the above are used. The degree of abnormality changed by reflecting the weight candidate is simultaneously displayed on the display unit as the first screen.
The diagnostic device according to claim 3 or 4. It is a control method for diagnostic equipment.
An acquisition step of acquiring detection information indicating the physical quantity detected by the detection unit that detects the physical quantity that changes according to the operation of the target device, and
When the detection information is acquired by the acquisition step, a calculation step of calculating the degree of abnormality based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other. When,
An accumulation step for accumulating the degree of abnormality calculated by the calculation step, and
A reception step that accepts input of parameter weight candidates used to calculate the degree of anomaly, and
An output control step that reflects the weight candidate received by the reception step and changes and outputs the abnormality degree accumulated by the accumulation step, and an output control step.
Diagnostic device control methods, including. On the computer of the diagnostic device,
An acquisition step of acquiring detection information indicating the physical quantity detected by the detection unit that detects the physical quantity that changes according to the operation of the target device, and
When the detection information is acquired by the acquisition step, a calculation step of calculating the degree of abnormality based on the information in which the operation information of the target device and the detection information acquired by the detection unit are associated with each other. When,
An accumulation step for accumulating the degree of abnormality calculated by the calculation step, and
A reception step that accepts input of parameter weight candidates used to calculate the degree of anomaly, and
An output control step that reflects the weight candidate received by the reception step and changes and outputs the abnormality degree accumulated by the accumulation step, and an output control step.
A program that executes.

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