KR20240072893A - Data acquisition apparatus and method for disgnosing a robot failure - Google Patents

Abstract

A method and apparatus for extracting a region of interest are disclosed. The region of interest extraction device includes a processor. The processor generates an input image by distorting an original image containing at least one object, refers to the original image, and scores the quality of the input image using a machine learning model learned based on the MOS (mean opinion score) dataset. Determine , generate a class activation map for the input image based on the quality score of the input image, and extract the region of interest from the original image based on the class activation map.

Description

Data acquisition device and method for diagnosing robot failure {DATA ACQUISITION APPARATUS AND METHOD FOR DISGNOSING A ROBOT FAILURE}

The disclosure below relates to a data acquisition device and method for robot failure diagnosis.

This invention is the result of support for the following research and development project.

- Research project number: 2022L43051

- Detailed project number: GRRC Korea National University of Technology 2020-B02/GRRCTUKorea2020-B02

- Research project title: Development of robot application technology for automation of manufacturing process for joining different materials

- Research support project name: Gyeonggi-do Regional Cooperation Research Center (GRRC) project

- Name of principal investigator: Kim Ki-hyun

- Project period: 2022-07-01~2023-06-30

- Research support organization: Gyeonggi Provincial Office

In general, if a robot used in an industrial field breaks down, it can result in significant opportunity loss due to the production of the machine being stopped. Such robot failures may occur due to motor failure, bearing failure, reducer failure, stator failure such as insulation damage, rotor failure, or mechanical defect. Various methods are being developed and implemented to diagnose robot failures by continuously monitoring the status of the parts that make up the robot.

A data acquisition device for robot failure diagnosis according to an embodiment includes a motor, a reducer for controlling the output rotation speed of the motor, a drive pulley connected to the motor, and a driven pulley connected to the reducer. , and a simulator robot that includes a bearing and is driven in either a normal mode or an abnormal mode according to user control, a temperature sensor that acquires temperature information of the simulator robot, and a torque that acquires torque information of the simulator robot. A sensor module including a sensor, a vibration sensor for acquiring vibration information of the simulation robot, and an encoder for obtaining position information of a drive shaft of the motor, and the temperature information and the torque according to the operation mode of the simulation robot. It may include a control module that stores a data set including information, the vibration information, and the location information, and transmits the data set to a server through a communication module.

The temperature sensor is disposed on one side of the motor and obtains temperature information of the motor, and the torque sensor is disposed on one side of the reducer and measures the torque of the reducer to obtain torque information, The vibration sensor may measure vibration occurring in the bearing to obtain vibration information, and the encoder may obtain position information of the driving pulley and the driven pulley.

The data acquisition device according to one embodiment may further include a precision stage disposed below the motor and controlling the position of the motor.

The data acquisition device according to one embodiment may further include a weight that is connected to the reducer and adds a load to the reducer.

The control module may provide the data set to the server through an EtherCAT network.

The vibration sensor includes a signal amplifier, a low-pass filter, and an analog-to-digital converter (ADC), and can convert the vibration signal included in the vibration information into a voltage signal using the analog-to-digital converter.

The control module may include a digital signal processor (DSP) that converts the voltage signal included in the vibration information into a frequency signal through fast Fourier transform.

The temperature sensor may be an infrared temperature sensor.

The abnormal mode of the simulation robot may correspond to at least one of the following: the motor is broken, the reducer is broken, the bearing is broken, and the pulley is broken.

A data acquisition method performed by a data acquisition device for robot failure diagnosis according to an embodiment includes a temperature sensor, a torque sensor acquiring torque information, a vibration sensor acquiring vibration information, and an encoder acquiring position information. Using a sensor module, a motor, a reducer for controlling the output rotation speed of the motor, a pulley including a driving pulley connected to the motor and a driven pulley connected to the reducer, and a bearing are controlled by the user. Obtaining temperature information, torque information, vibration information, and position information of the drive shaft of the motor of the simulation robot driven in one of the normal or abnormal operation modes according to the operation mode, the temperature information according to the operation mode of the simulation robot , storing a data set including the torque information, the vibration information, and the location information, and transmitting the data set to a server through a communication module.

The temperature sensor is disposed on one side of the motor and obtains temperature information of the motor, and the torque sensor is disposed on one side of the reducer and measures the torque of the reducer to obtain torque information, The vibration sensor may measure vibration occurring in the bearing to obtain vibration information, and the encoder may obtain position information of the driving pulley and the driven pulley.

The data acquisition method according to one embodiment may further include adjusting the position of the motor using a precision stage disposed below the motor.

The data acquisition method according to one embodiment may further include adding a load to the reducer using a weight connected to the reducer.

The operation of providing the data set to the server may include providing the data set to the server through an EtherCAT network.

The vibration sensor includes a signal amplifier, a low-pass filter, and an analog-to-digital converter, and the operation of acquiring the vibration information converts the vibration signal included in the vibration information into a voltage signal using the analog-to-digital converter. It may include a conversion operation.

It may further include converting the voltage signal included in the vibration information into a frequency signal through fast Fourier transform using a digital processor.

The temperature sensor may be an infrared temperature sensor.

The abnormal mode of the simulation robot may correspond to at least one of the following: the motor is broken, the reducer is broken, the bearing is broken, and the pulley is broken.

FIG. 1 is a diagram illustrating a data acquisition device for diagnosing a robot failure according to an embodiment.
Figure 2 is a diagram for explaining the operation of a data acquisition device according to an embodiment.
Figure 3 is a diagram for explaining the configuration of a simulation robot according to an embodiment.
Figure 4 is a graph showing data values obtained from a sensor module according to an embodiment.
5A to 5C are graphs showing examples of data values obtained from a sensor module according to an embodiment.
Figure 6 is a flowchart explaining a data acquisition method according to an embodiment.

Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be changed and implemented in various forms. Accordingly, the actual implementation form is not limited to the specific disclosed embodiments, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical idea described in the embodiments.

Terms such as first or second may be used to describe various components, but these terms should be interpreted only for the purpose of distinguishing one component from another component. For example, a first component may be named a second component, and similarly, the second component may also be named a first component.

When a component is referred to as being “connected” to another component, it should be understood that it may be directly connected or connected to the other component, but that other components may exist in between.

Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate the presence of the described features, numbers, steps, operations, components, parts, or combinations thereof, but are not intended to indicate the presence of one or more other features or numbers, It should be understood that this does not exclude in advance the possibility of the presence or addition of steps, operations, components, parts, or combinations thereof.

As used herein, “A or B”, “at least one of A and B”, “at least one of A or B”, “A, B or C”, “at least one of A, B and C”, and “A Each of phrases such as “at least one of , B, or C” may include any one of the items listed together in the corresponding phrase, or any possible combination thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art. Terms as defined in commonly used dictionaries should be interpreted as having meanings consistent with the meanings they have in the context of the related technology, and unless clearly defined in this specification, should not be interpreted in an idealized or overly formal sense. No.

Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the accompanying drawings, identical components will be assigned the same reference numerals regardless of the reference numerals, and overlapping descriptions thereof will be omitted.

FIG. 1 is a diagram illustrating a data acquisition device for diagnosing a robot failure according to an embodiment.

Referring to FIG. 1 , the data acquisition device 100 may include a simulation robot 110, a sensor module 120, and a control module 130. The data acquisition device 100 can acquire data for diagnosing a robot failure. The data acquisition device 100 may acquire data or sensor values that affect the driving ability of the simulation robot 110 using the sensor module 120. The control module 130 may transmit data received from the sensor module 120 to the server 140 through a communication module (not shown).

In one embodiment, the simulation robot 110 is a multi-spindle robot and may be a robot that replicates a part of a general robot having joints that are motion axes. The simulation robot 110 may include, for example, a motor, a reducer that adjusts the output rotation speed of the motor, a pulley including a driving pulley connected to the motor and a driven pulley connected to the reducer, and a bearing. However, the components included in the simulation robot 110 are not limited to the above components, and depending on the embodiment, at least one of the above components may be omitted or one or more other components may be added to the simulation robot 110. .

The sensor module 120 may acquire data that affects the driving ability of the simulation robot 110. The sensor module 120 includes, for example, a temperature sensor that acquires temperature information of the simulation robot 110, a torque sensor that acquires torque information of the simulation robot 110, and a vibration sensor that acquires vibration information of the simulation robot 110. , and may include an encoder that obtains position information of the drive shaft of the motor. The encoder may vary depending on the type of sensing signal. For example, if the sensing signal is a digital pulse train signal, the encoder may be implemented as an incremental encoder or absolute encoder. However, the components included in the simulation robot 110 are not limited to the above components, and depending on the embodiment, at least one of the above components may be omitted or one or more other components may be added to the simulation robot 110. . The sensor module 120 may obtain various data from the simulation robot 110 according to the operation mode of the simulation robot 110.

A typical robot containing joints may break down due to aging due to long-term use, continuous repetitive movements, or overload. Here, failure may mean a case where a component does not move properly or a case where the performance of the component does not meet the required performance according to the user's purpose. For example, the torque value applied to the joint axis may be detected, compared with a preset threshold value, and if the torque value is higher than the threshold value, the robot may be diagnosed as abnormal or malfunctioning.

In the case of motors, if used continuously for a long period of time, performance may deteriorate due to overcurrent or overheating, and the motor may deviate from its designated position. In the case of reducers, poor lubrication or performance degradation may occur due to constant friction. In the case of pulleys, vibration and noise may occur due to positional errors, deflection, backlash, etc. In the case of bearings, poor lubrication, cracks, and damage may occur. As mentioned above, the components that make up the robot can fail due to various reasons.

The user can set the simulation robot 110 to operate in normal mode or abnormal mode. The fact that the simulation robot 110 is driven in a normal mode may mean that the component parts included in the simulation robot 110 do not fail, meet the user's required performance, and operate normally. Driving the simulation robot 110 in an abnormal mode may mean that the simulation robot 110 is driven while at least one of the component parts included in the simulation robot 110 is broken. For example, the abnormal mode of the simulation robot 110 may correspond to a mode in which the simulation robot 110 is driven in at least one of the following cases: a motor failure, a reducer failure, a bearing failure, and a pulley failure. there is.

The user can set the normal mode or abnormal mode of the simulation robot 110 in various ways by controlling each of the component parts included in the simulation robot 110 to operate under different conditions. The sensor module 120 may obtain temperature information, torque information, vibration information, and location information corresponding to different normal modes or abnormal modes from the simulation robot 110 using sensors. The sensor module 120 may transmit temperature information, torque information, vibration information, and location information obtained from the simulation robot 110 to the control module 130.

The control module 130 may include a memory (not shown) that stores data sets. The control module 130 may store a data set including temperature information, torque information, vibration information, and location information according to the operation mode of the simulation robot 110. Memory may be implemented as a volatile memory device or a non-volatile memory device.

Volatile memory devices include, for example, dynamic random access memory (DRAM), static random access memory (SRAM), thyristor RAM (T-RAM), zero capacitor RAM (Z-RAM), or twin transistor RAM (TTRAM). can do. Non-volatile memory devices include Electrically Erasable Programmable Read-Only Memory (EEPROM), Flash memory, Magnetic RAM (MRAM), Spin-Transfer Torque (STT)-MRAM (MRAM), and Conductive Bridging RAM (CBRAM). , FeRAM (Ferroelectric RAM), PRAM (Phase change RAM), Resistive RAM (RRAM), Nanotube RRAM (Nanotube RRAM), Polymer RAM (PoRAM), Nano Floating Gate Memory (NFGM)), holographic memory, molecular electronic memory device (Molecular Electronic Memory Device), or insulation resistance change memory.

The data acquisition device 100 may be connected to the server 140 using short-range wireless communication or cellular communication. The control module 130 may transmit the data set to the server 140 through a communication module (not shown). The server 140 may receive a data set corresponding to the operation mode of the simulation robot 110 obtained from the data acquisition device 100, and store and manage the received data set. Each of the data sets stored in the server 140 may be labeled with information about the normal mode or abnormal mode of the simulation robot set by the user to obtain the corresponding data set.

The user can control the simulation robot 110 to operate in a normal mode and obtain a data set corresponding to the normal mode of the simulation robot 110. The user can control the simulation robot 110 to operate in an abnormal mode and obtain a data set corresponding to the abnormal mode of the simulation robot 110. The user can set various abnormal modes by independently controlling each component included in the simulation robot 110. The user can set the simulation robot 110 to various abnormal modes and obtain a data set corresponding to each abnormal mode. The user can estimate the state of the actual robot corresponding to the simulation robot 110 using data acquired from the data acquisition device 100.

For example, a user may acquire data (e.g., torque information, vibration information, or position information) obtained from the joint axis of a robot used in an industrial field, and transfer the acquired data to the data acquisition device (100). ) can be compared with data obtained from . Through comparison, the user can check whether the sensor value (for example, torque value) included in the data obtained from the robot in the industrial field exceeds the threshold value and determine whether the robot is broken. If the sensor value included in the data obtained from the robot in the industrial field has a value close to the threshold value, the user can predict robot failure and prepare for robot failure in advance. Depending on the embodiment, the data set acquired from the data acquisition device may be used as learning data for a neural network-based machine learning model that determines whether the robot has a breakdown.

Figure 2 is a diagram for explaining the operation of a data acquisition device according to an embodiment.

Referring to FIG. 2, the data acquisition device 200 may include a sensor module 210 and a control module 220. Sensor module 210 may include a temperature sensor 212, a torque sensor 214, a vibration sensor 216, and an encoder 218. The temperature sensor 212 may obtain temperature information of the simulation robot (eg, the simulation robot 110 in FIG. 1) and transmit it to the control module 220. The torque sensor 214 may obtain torque information of the simulated robot and transmit it to the control module 220. The vibration sensor 216 may acquire vibration information of the simulated robot and transmit it to the control module 220. The encoder 218 may obtain position information of the drive shaft of the motor included in the simulation robot and transmit it to the control module 220.

The control module 220 can communicate with the server 240 using an EtherCAT network (230). The control module 220 can transmit data obtained from each sensor included in the sensor module 210 to the server 240 in real time using the EtherCAT network 230. By using the EtherCAT network 230, the control module 220 can transmit all data acquired from the sensor module 210 to the server 240 at the same cycle and implement fast and accurate data synchronization. Depending on the embodiment, the control module 220 may transmit data to the server 240 through a separate communication module.

Figure 3 is a diagram for explaining the configuration of a simulation robot according to an embodiment.

For example, the simulation robot may correspond to the simulation robot 110 of the data acquisition device 100 of FIG. 1 . Referring to FIG. 3, the simulation robot includes a motor 310, a reducer 320 that controls the output rotation speed of the motor 310, a drive pulley 342 connected to the motor 310 and the drive shaft 302, and a reducer. Pulley 340 including driven pulley 344 connected to 320 and driven shaft 304, timing belt 350 connecting drive pulley 342 and driven pulley 344, and bearing 380 ) may include. The motor 310 and the reducer 320 are connected through the timing belt 350 and the pulley 340, so that space for different sensors to be attached to the motor 310 and the reducer 320 can be secured. However, depending on the embodiment, the reducer 320 may be placed on one side of the motor 310.

Depending on the embodiment, the data acquisition device may include a precision stage (not shown) disposed below the motor 310 and adjusting the position of the motor 310. The position of the motor 310 can be changed by a precision stage, and the sensor module (e.g., the sensor module 120 in FIG. 1) can acquire position information of the motor 310 according to the change in position of the motor 310. there is.

Around the components of the simulated robot are a temperature sensor 360 that acquires temperature information of the simulated robot, a torque sensor 365 that acquires torque information of the simulated robot, a vibration sensor 370 that acquires vibration information of the simulated robot, And an encoder 475 that obtains location information of the simulated robot may be disposed. The temperature sensor 360 may be placed on one side of the motor 310 of the robot. The temperature sensor 360 may be, for example, an infrared temperature sensor, and may obtain temperature information of the motor 310 without directly contacting the motor 310. For example, if the temperature sensor 360 is an infrared sensor, it can be easily attached and detached. However, the type of temperature sensor 360 is not limited to an infrared sensor, and various types of sensors can be used as the temperature sensor 360. The torque sensor 365 may be placed on one side of the reducer 320. Depending on the embodiment, the data acquisition device may include a weight 306 that is connected to the reducer 320 and adds the load of the reducer 320. The user can adjust the strength of the torque acting on the reducer 320 by adjusting the weight of the weight 306. Torque information acquired by the torque sensor 365 may change depending on the weight of the weight 306.

The user operates the simulated robot in its normal mode in which the motor 310, reducer 320, bearing 380, and pulley 340 are each in a normal state, and then sends data (or sensor values) through the sensor module. can be obtained. The user can drive the simulated robot in an abnormal mode by breaking at least one of the motor 310, reducer 320, bearing 380, and pulley 340, and then obtain data through the sensor module. there is. For example, the user may gradually increase the output of the motor 310 and obtain temperature information that changes according to the output of the motor 310 through the temperature sensor 360.

The user can set the simulation robot to worsen the lubrication state of the reducer 320 and generate vibration and noise due to friction, and then drive the simulation robot. Alternatively, the user may increase the load on the reducer 320 by increasing the weight of the weight 306 connected to the reducer 320 and then drive the simulation robot. The user can cause a malfunction by making various changes to the reducer 320 and obtain torque information corresponding to the cause of the malfunction from the torque sensor 365.

Figure 4 is a graph showing data obtained from a sensor module according to an embodiment.

The vibration sensor of the sensor module (e.g., the sensor module 120 in FIG. 1) may obtain vibration information from the component parts of the simulation robot. The vibration sensor may include a signal amplifier, a low-pass filter, and an analog-to-digital converter (ADC). The signal amplifier can amplify the size of the first analog vibration signal that the vibration sensor acquires from the components of the simulated robot. The vibration signal initially acquired by the vibration sensor may include noise. Noise may include, for example, noise caused by vibration of a simulated robot or external noise such as floor vibration. A low pass filter can remove noise included in vibration signals and alleviate aliasing. The vibration sensor can convert the vibration signal included in the vibration information into a voltage signal using an analog-to-digital converter. The graph 410 represents the voltage signal value included in the vibration information over time. The graph 420 represents a value obtained by sampling a voltage signal included in vibration information over time at a constant period.

The control module (e.g., control module 130 in FIG. 1) may include a digital signal processor (DSP) that converts a voltage signal included in vibration information into a frequency signal through fast Fourier transform. The control module can store the maximum amplitude value and maximum frequency value of the converted frequency signal in memory, and can transmit a data set containing the maximum amplitude value and maximum frequency value to the server. The maximum amplitude value and maximum frequency value of the frequency signal included in the vibration information may change depending on the state of the component measured by the vibration sensor.

5A to 5C are graphs showing examples of data values obtained from a sensor module according to an embodiment.

The graph in FIG. 5A shows the simulation robot being driven while the components of the simulation robot (e.g., the simulation robot 110 in FIG. 1) measured by the vibration sensor included in the sensor module (e.g., the sensor module in FIG. 1) are normal. In this case, it represents the frequency signal of the vibration information obtained from the vibration sensor. The graph of FIG. 5B shows the frequency signal of vibration information obtained from the vibration sensor when the simulated robot is driven while a component (eg, bearing) of the simulated robot measured by the vibration sensor is broken. The graph of FIG. 5C shows the frequency signal of vibration information obtained from the vibration sensor when the simulation robot is driven while another component (eg, reducer) of the simulation robot measured by the vibration sensor is broken.

Referring to Figure 5a, when the component parts of the simulated robot operate normally, the maximum amplitude value and maximum frequency value of the frequency signal value of the vibration information measured from the component parts are compared to the graph in Figure 5b and the graph in Figure 5c. It may be relatively low.

Referring to Figures 5b and 5c, when the component parts of the simulated robot operate in a broken state, the maximum amplitude value and maximum frequency value of the frequency signal value of vibration information measured from the component parts are compared to the graph in Figure 5a. It can be relatively high. The user can estimate the status of the components of the simulation robot measured by the vibration sensor based on the frequency signal value of the vibration information obtained from the vibration sensor.

Figure 6 is a flowchart explaining a data acquisition method according to an embodiment.

For example, operations of the data acquisition method may be performed by the data acquisition device 100 of FIG. 1 . In one embodiment, at least one of the operations in FIG. 6 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. Additionally, at least one of the operations may be omitted, and another operation may be additionally performed.

Referring to FIG. 6, in operation 610, the data acquisition device may acquire temperature information, torque information, vibration information, and position information of the drive shaft of the motor of the simulation robot. The data acquisition device may include a sensor module including a temperature sensor, a torque sensor acquiring torque information, a vibration sensor acquiring vibration information, and an encoder acquiring position information. The data acquisition device uses a sensor module to provide various information (e.g., temperature information, torque information, vibration information, and driving shaft of the motor) about the simulated robot that is driven in either a normal mode or an abnormal mode according to the user's control. location information) can be obtained. The simulation robot may include a motor, a reducer that adjusts the output rotation speed of the motor, a pulley including a driving pulley connected to the motor and a driven pulley connected to the reducer, and a bearing. The abnormal mode of the simulation robot may correspond to a mode in which the simulation robot is driven in at least one of the following: a motor failure, a reducer failure, a bearing failure, and a pulley failure.

The temperature sensor is placed on one side of the motor and can obtain temperature information of the motor. The torque sensor is placed on one side of the reducer and can obtain torque information by measuring the torque of the reducer. A vibration sensor can obtain vibration information by measuring vibration occurring in a bearing. The encoder can obtain position information of the driving pulley and driven pulley. However, the location where each sensor of the sensor module is placed and the type of component component being sensed may vary depending on the embodiment, and is not limited to the above. The temperature sensor may be, for example, an infrared temperature sensor.

The data acquisition device can control the position of the motor using a precision stage disposed below the motor. The data acquisition device can acquire position information according to the changing position of the motor due to the precision stage. The data acquisition device can add the load of the reducer using a weight connected to the reducer. The user can adjust the strength of the torque acting on the reducer by adjusting the weight of the weight.

The vibration sensor may include a signal amplifier, low-pass filter, and analog-to-digital converter. The operation of acquiring vibration information may include converting the vibration signal included in the vibration information into a voltage signal using an analog-to-digital converter.

In operation 620, the data acquisition device may store in memory a data set including temperature information, torque information, vibration information, and position information according to the operation mode of the simulation robot. The data acquisition device can process data acquired from the sensor module and store it in memory as a data set. For example, the data acquisition device can convert the voltage signal included in the vibration information into a frequency signal through fast Fourier transform using a digital processor. The data acquisition device may store the maximum amplitude value and maximum frequency value of the converted frequency signal in memory and transmit them to the server. The maximum amplitude value and maximum frequency value of the frequency signal included in the vibration information may change depending on the operating state of the component measured by the vibration sensor. The user can estimate the state of the component measured by the vibration sensor based on the maximum amplitude value and maximum frequency value of the frequency signal included in the vibration information.

In operation 630, the data acquisition device may transmit the data set to a server (e.g., server 140 in FIG. 1) via a communication module. The operation of the data acquisition device providing the data set to the server may include providing the data set to the server through an EtherCAT network. The data acquisition device can transmit data sets to a server in real time using the EtherCAT network.

The embodiments described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, the devices, methods, and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, and a field programmable gate (FPGA). It may be implemented using a general-purpose computer or a special-purpose computer, such as an array, programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and software applications running on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used; however, those skilled in the art will understand that a processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used on any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. It can be saved in . Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on a computer-readable recording medium.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. A computer-readable medium may store program instructions, data files, data structures, etc., singly or in combination, and the program instructions recorded on the medium may be specially designed and constructed for the embodiment or may be known and available to those skilled in the art of computer software. there is. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

The hardware devices described above may be configured to operate as one or multiple software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with limited drawings, those skilled in the art can apply various technical modifications and variations based on this. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

Claims (19)

In the data acquisition device for robot failure diagnosis,
It includes a motor, a reducer that adjusts the output rotation speed of the motor, a pulley including a driving pulley connected to the motor and a driven pulley connected to the reducer, and a bearing, and can be operated in a normal mode or in a normal mode according to user control. A simulated robot driven in one of the abnormal modes of operation;
A temperature sensor that acquires temperature information of the simulated robot, a torque sensor that acquires torque information of the simulated robot, a vibration sensor that acquires vibration information of the simulated robot, and an encoder that acquires position information of the drive shaft of the motor (encoder ) a sensor module including; and
A control module that stores a data set including the temperature information, the torque information, the vibration information, and the location information according to the operation mode of the simulation robot, and transmits the data set to a server through a communication module.
A data acquisition device comprising a.
According to paragraph 1,
The temperature sensor is,
disposed on one side of the motor, and obtain temperature information of the motor,
The torque sensor is,
It is disposed on one side of the reducer and measures the torque of the reducer to obtain torque information,
The vibration sensor is,
Obtain vibration information by measuring vibration occurring in the bearing,
The encoder is,
Obtaining position information of the driving pulley and the driven pulley,
Data acquisition device.
According to paragraph 1,
A precision stage disposed below the motor and controlling the position of the motor
A data acquisition device further comprising:
According to paragraph 1,
A weight connected to the reducer and adding the load of the reducer
A data acquisition device further comprising:
According to paragraph 1,
The control module is,
Providing the data set to the server through an EtherCAT network,
Data acquisition device.
According to paragraph 1,
The vibration sensor is,
Comprising a signal amplifier, a low-pass filter, and an analog-to-digital converter (ADC), and converting the vibration signal included in the vibration information into a voltage signal using the analog-to-digital converter,
Data acquisition device.
According to clause 6,
The control module is,
Comprising a digital signal processor (DSP) that converts the voltage signal included in the vibration information into a frequency signal through fast Fourier transform,
Data acquisition device.
According to paragraph 1,
The temperature sensor is,
An infrared temperature sensor,
Data acquisition device.
According to paragraph 1,
The abnormal mode of the simulated robot is,
Corresponding to at least one of the following cases: when the motor fails, when the reducer fails, when the bearing fails, and when the pulley fails,
Data acquisition device.
In a data acquisition method performed by a data acquisition device for robot failure diagnosis,
Using a sensor module including a temperature sensor, a torque sensor for acquiring torque information, a vibration sensor for acquiring vibration information, and an encoder for obtaining position information, a motor, a reducer for controlling the output rotation speed of the motor, and the motor Temperature information and torque information of a simulated robot that includes a pulley including a driving pulley connected to and a driven pulley connected to the reducer, and a bearing, and is driven in one of the normal mode and abnormal mode according to the user's control. , vibration information, and an operation of acquiring position information of a drive shaft of the motor;
An operation of storing a data set including the temperature information, the torque information, the vibration information, and the location information according to the operation mode of the simulation robot; and
An operation of transmitting the data set to a server through a communication module
Data acquisition method including.
According to clause 10,
The temperature sensor is,
disposed on one side of the motor, and obtain temperature information of the motor,
The torque sensor is,
It is disposed on one side of the reducer and measures the torque of the reducer to obtain torque information,
The vibration sensor is,
Obtain vibration information by measuring vibration occurring in the bearing,
The encoder is,
Obtaining position information of the driving pulley and the driven pulley,
Data acquisition methods.
According to clause 10,
An operation to adjust the position of the motor using a precision stage disposed below the motor
A data acquisition method further comprising:
According to clause 10,
An operation of adding the load of the reducer using a weight connected to the reducer
A data acquisition method further comprising:
According to clause 10,
The operation of providing the data set to the server is:
An operation of providing the data set to the server through an EtherCAT network
Data acquisition method including.
According to clause 10,
The vibration sensor is,
Includes a signal amplifier, low-pass filter, and analog-to-digital converter,
The operation of acquiring the vibration information is,
An operation of converting a vibration signal included in the vibration information into a voltage signal using the analog-to-digital converter.
Data acquisition method including.
According to clause 10,
An operation of converting the voltage signal included in the vibration information into a frequency signal through fast Fourier transform using a digital processor.
A data acquisition method further comprising:
According to clause 10,
The temperature sensor is,
An infrared temperature sensor,
Data acquisition methods.
According to clause 10,
The abnormal mode of the simulated robot is,
Corresponding to at least one of the following cases: when the motor fails, when the reducer fails, when the bearing fails, and when the pulley fails,
Data acquisition methods.
A computer-readable recording medium storing one or more computer programs including instructions for performing the method of any one of claims 10 to 18.

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