阅读说明：本技术 使用设施诊断系统的设施诊断方法 (Facility diagnosis method using facility diagnosis system ) 是由 金德暻 于 2018-06-21 设计创作，主要内容包括：本发明涉及使用设施诊断系统的设施诊断方法,该设施诊断系统包括：成像模块(110),该图像模块通过拍摄装载有PLC的设施控制器被内置在其中的设施来收集图像数据；诊断模块(120),该诊断模块包括具有用于诊断设施正常或异常的软件的硬件；和多个IoT传感器单元(130),该多个IoT传感器单元监视待监视目标,因此用户可以基于在诊断模块针对用户根据设施情形指定的每种条件生成各种种类的事件时,通过PLC存储区域、图像文件和IoT传感器单元提供的目标数据,来迅速地诊断、识别并应对设施故障的特定原因。(The present invention relates to a facility diagnosis method using a facility diagnosis system including: an imaging module (110) that collects image data by photographing a facility in which a facility controller loaded with a PLC is built; a diagnostic module (120) comprising hardware having software for diagnosing whether the facility is normal or abnormal; and a plurality of IoT sensor units (130) that monitor the object to be monitored, so the user can quickly diagnose, identify and cope with a specific cause of a facility failure through the PLC storage area, the image file, and the IoT sensor unit based on the object data provided by the PLC storage area when the diagnosis module generates various kinds of events for each condition specified by the user according to the facility situation.)

1. A facility diagnosis method using a facility diagnosis system including an imaging module (110) and a diagnosis module (120), the imaging module (110) being configured to photograph a facility in which a facility controller installed with a PLC is built, the diagnosis module (120) including hardware installed with software for diagnosing a fault of the facility, the facility diagnosis method comprising the steps of:

a diagnostic event generation step (S11) of receiving and detecting, by the diagnostic module (120), a PLC memory map access signal (P) output by the facility controller, and generating a diagnostic event of a kind corresponding to a plurality of preset event conditions in the diagnostic module (120);

a storage range setting step (S12) of arbitrarily selecting, by the diagnostic module (120), a range of state information and data values of a PLC storage region to be stored at a diagnostic event generation time point, and setting a time region in a preceding/following range based on the diagnostic event generation time point; and

a file storing step (S13) of storing the status information and the data value of the PLC storage area within the range selected in the storage range setting step in real time through the diagnosis module (120),

wherein the diagnostic module (120) is configured to selectively perform:

a main storage mode setting step (S21) of installing storage mode recognition software during one cycle of normal state operation of the facility, storing state information and data values of the PLC storage area, and setting the stored state information and data values to a main storage mode; and

a storage mode notification step (S22) of reading the PLC storage area in real time during operation of the facility, comparing the read PLC storage area with the main storage mode, and displaying an area in which the read PLC storage area does not coincide with the main storage mode, and

wherein, in the file storing step (S13),

the state information and the data value of the PLC storage area are stored in the form of a data file of a diagnostic event type and a generation date and time, areas for input/output, internal relays, link relays are converted in units of bits to display an operation state thereof, areas for data registers and link registers are converted in units of decimal numbers after being read in units of words to be displayed and stored, and are provided to a user.

2. The facility diagnostic method according to claim 1, wherein an image recognition application is installed on the imaging module (110) of the facility diagnostic system, the facility diagnostic method comprising the steps of:

a main image setting step (S31) of accumulating edge features of a plurality of images in units of pixels and learning an averaged main image after setting an image area as a normal state of a monitoring target;

a matching rate setting step (S32) of storing a matching rate and a storage condition in which a boundary value is set as a normal state and an abnormal state of the monitoring target;

an image monitoring event generating step (S33) of receiving and detecting an image monitoring event signal output by the imaging module (110) through the diagnostic module (120), generating an image monitoring event in compliance with a preset image monitoring event condition in the diagnostic module (120), and transmitting a signal to the imaging module (110); and

an image file storing step (S34) of acquiring, by the imaging module (110), a current state image of the monitoring target at the image monitoring event generation time point, and if a storage condition is satisfied according to a matching rate after comparing the current state image with the main image, storing the current state image as an image file, and

wherein the image file storing step (S34) includes the steps of:

image data of the monitoring target captured by an imaging device in a time region ranging before/after the image monitoring event generation time point is acquired and edited, and the edited image data is stored as an image file.

3. The facility diagnostic method of claim 1, wherein the facility diagnostic system comprises a plurality of IoT sensor units (130) configured to monitor the monitoring target, the facility diagnostic method comprising the steps of:

an IoT event generating step (S41) of receiving and detecting an IoT monitoring event signal through hardware contact or wired/wireless communication of the diagnostic module (120) with the IoT sensor unit (130), generating an IoT monitoring event corresponding to a preset IoT monitoring event condition in the diagnostic module (120), and transmitting a signal to the imaging module (110);

an image file storing step (S42) of acquiring and editing image data of the monitoring target captured by an imaging device within a time area ranging before/after the IoT monitoring event generation time point and storing the edited image data as an image file; and

an IoT notification step (S43) that sends an IoT monitoring event generation notification to a user' S smartphone through the diagnostic module (120).

Technical Field

The present disclosure relates to a disclosure about a facility diagnosis method using a facility diagnosis system, and more particularly, to the following facility diagnosis method: when managing a facility in which a facility controller mounted with a PLC is built, a user is allowed to quickly and accurately identify a cause of a facility failure at an event generation time point under a condition specified by the user, based on a PLC storage area, an image file, and target data provided by an IoT sensor unit, by using a facility diagnosis system provided with a diagnosis module, an imaging module, and an IoT sensor unit, whereby it is possible to effectively cope with a failure of a facility that is not difficult to identify.

Background

Generally, a facility generally refers to a machine or apparatus used to produce or manufacture a product throughout the industry or all combinations thereof.

In recent years, facilities for automated control, management, and overall operation of product production have been realized by factory automation using machine tools, robots, and computers, and in addition, not only has apparatus automation been performed, but also automated control of apparatus control processes has been performed by computers in a programmable state.

Accordingly, industrial facilities such as automated component mounters, various testers, and processing equipment are equipped with PCBs installed with PLCs, computers, and microprocessors, and with end-user dedicated programming controllers.

For example, in a brief description of the configuration of a vehicle assembly facility known in korean patent No.10-0867773, the vehicle assembly facility includes: a central management server that stores and manages vehicle information necessary for assembling a vehicle; a plurality of assembly facilities that assemble a vehicle according to vehicle information; a plurality of facility control units that are connected to the assembly facility and control the assembly facility; and a plurality of control PCs connected to the plurality of facility control units and communicating with the central management server, and the facility control units include PLC devices of different models.

Further, an industrial facility may cause errors such as facility failure due to various unpredictable problems in its operation. When the facility repeatedly experiences errors, the production efficiency is significantly reduced.

Therefore, although engineers always stay around the facility to identify the cause of the facility failure, it is difficult to more accurately and quickly cope with the failure due to accumulation of labor fatigue, a monitoring system relying on naked eyes, and a scheme of simply estimating the cause, which is inefficient.

Accordingly, a facility diagnosis technology that accurately and rapidly identifies the causes of various failures occurring in the process of developing or managing facilities to cope with the failures has been developed and provided, and a schematic configuration thereof will be described by a diagnosis method of facility failures in a production line known in korean patent No. 10-0084195.

A method of diagnosing a facility fault in a production line that is sequentially controlled to execute a plurality of steps in operation blocks in a predetermined sequence thereof, comprising the steps of: classifying a plurality of operations performed by a facility in a production line into a plurality of operation blocks of a series of operation units independently performed from a start until an end of the operations in a normal state of the facility; classifying the plurality of operation frames into a plurality of operation steps; measuring an operation time from the start to the end of a series of operation steps in the operation block; storing the completion of the operation in the operation step in the operation box; comparing the reference operation time of the operation block with the measured operation time; and designating a faulty operating step in the block in response to the status of completion of the operation in the operating step and the time difference in the comparing step.

Further, korean patent application laid-open No.10-2013-0102278 discloses a facility device monitoring system and a facility device monitoring method, the facility device monitoring system including: a plurality of facility devices including a display section, an audio output section, and a tower light configured to display an operation state; and a monitoring device configured to transmit and receive signals indicating operation states of the plurality of facility devices by using the PLC module, wherein the PLC module includes a control program that monitors the operation states of the plurality of facility devices based on the transmitted and received signals, and outputs a result through at least one of the display section and the audio output section.

Disclosure of Invention

Technical problem

A method of diagnosing a facility fault in a production line to which the conventional technique is applied includes a fault diagnosing apparatus including: a vehicle assembly line (hereinafter, facility); a line fault diagnosis unit installed in the entire facility to diagnose a line fault; a zone fault diagnosis unit installed for the line zone to diagnose a fault of the zone; and an apparatus failure diagnosis unit installed for the apparatus installed for the region to diagnose a failure of the apparatus, wherein the failures of the line, the region, and the apparatus are sequentially diagnosed.

That is, according to the fault diagnosis apparatus of the conventional art, the fault diagnosis apparatus is installed for the entire line, area, and device, and if an abnormality is determined by measuring the operation times (i.e., the in-out times) of the line, area, and device and comparing them with the reference time, a fault diagnosis result is performed.

Therefore, since an abnormality is simply diagnosed by measuring the process progress time of each component of a facility, it is difficult to clearly identify whether the direct cause of a fault is in its facility or another external factor such as a material.

Further, since the entry-and-exit time is always normally maintained during the operation of the production line even if the facility substantially malfunctions, it is difficult to ensure the failure diagnosis accuracy with the method of the conventional art.

Further, a facility device monitoring system of another example performs monitoring by connecting a drive circuit of a tower lamp provided in a facility device and a PLC module in a one-to-one correspondence and collecting an operation signal of the tower lamp using the PLC module and outputting an operation state.

Therefore, the conventional technology has a limitation in that the facility device only recognizes its operation, but it is difficult to recognize a detailed cause and a generation time point of a device failure.

Technical solution

According to an aspect of the present disclosure, there is provided a facility diagnosis method using a facility diagnosis system including an imaging module 110 and a diagnosis module 120, the imaging module 110 being configured to photograph a facility in which a facility controller installed with a PLC is built, the diagnosis module 120 including hardware installed with software for diagnosing a fault of the facility, the facility diagnosis method including the steps of:

a diagnostic event generating step S11 of receiving and detecting, by the diagnostic module 120, a PLC memory map access signal P output by the facility controller, and generating a kind of diagnostic event corresponding to a plurality of preset event conditions in the diagnostic module 120;

a storage range setting step S12 of arbitrarily selecting a range of the state information and the data value of the PLC storage region to be stored at a diagnostic event generation time point, and setting a time region in a previous/subsequent range based on the diagnostic event generation time point; and

a file storing step S13 of storing the status information and the data value of the PLC storage area within the range selected in the storage range setting step in real time by the diagnosis module 120,

wherein the diagnostic module 120 is configured to selectively perform: a main storage mode setting step S21 of installing storage mode recognition software during one cycle of normal state operation of the facility, storing state information and data values of the PLC storage area, and setting the stored state information and data values to a main storage mode; and

a storage mode notification step S22 of reading the PLC storage area in real time during operation of the facility, comparing the read PLC storage area with the main storage mode, and displaying an area in which the read PLC storage area does not coincide with the main storage mode, and

wherein, in the file storing step S13,

the state information and the data value of the PLC storage area are stored in the form of a data file of a diagnostic event type and a generation date and time, areas for input/output, internal relays, link relays are converted in units of bits to display an operation state thereof, areas for data registers and link registers are converted in units of decimal numbers after being read in units of words to be displayed and stored, and are provided to a user.

Installing an image recognition application on the imaging module 110 of the facility diagnosis system, the facility diagnosis method comprising the steps of:

a main image setting step S31 of accumulating edge features of a plurality of images in units of pixels and learning an averaged main image after setting an image area as a normal state of a monitoring target;

a matching rate setting step S32 of storing a matching rate and a storage condition in which boundary values are set as a normal state and an abnormal state of the monitoring target;

an image monitoring event generating step S33 of receiving and detecting an image monitoring event signal output by the imaging module 110 through the diagnostic module 120, generating an image monitoring event in conformity with a preset image monitoring event condition in the diagnostic module 120, and transmitting a signal to the imaging module 110; and

an image file storing step S34 of acquiring, by the imaging module 110, a current state image of the monitoring target at the image monitoring event generation time point, and if a storage condition is satisfied according to a matching rate after comparing the current state image with the main image, storing the current state image as an image file, and

wherein the image file storing step S34 includes the steps of:

image data of the monitoring target captured by an imaging device in a time region ranging before/after the image monitoring event generation time point is acquired and edited, and the edited image data is stored as an image file.

The facility diagnosis system includes a plurality of IoT sensor units 130 configured to monitor the monitoring target, and the facility diagnosis method includes the steps of:

an IoT event generating step S41 of receiving and detecting an IoT monitoring event signal through the diagnostic module 120 in hardware contact or wired/wireless communication with the IoT sensor unit 130, generating an IoT monitoring event corresponding to a preset IoT monitoring event condition in the diagnostic module 120, and transmitting a signal to the imaging module 110;

an image file storing step S42 of acquiring and editing image data of the monitoring target captured by an imaging device in a time area ranging before/after the IoT monitoring event generation time point and storing the edited image data as an image file; and

an IoT notify step S43 that sends an IoT monitoring event generation notification to the user' S smartphone through the diagnostic module 120.

Thus, the following objectives are achieved: when an abnormal operation occurs within the facility, the user is allowed to more quickly and accurately identify the cause of the abnormal operation of the facility based on the target data analyzed by the diagnostic module, the imaging module, and the IoT sensor unit.

Advantageous effects

The present disclosure includes a facility diagnosis system including a diagnosis module, an imaging module, and an IoT sensor unit, and can more effectively cope with a facility fault whose cause cannot be easily recognized by generating various kinds of events according to a condition specified by a user.

In particular, the present disclosure may allow a user to precisely identify the cause of an abnormal operation of a facility in more detail by extracting target data from a PLC storage area at an event generation event point and converting the data into the form of a data file, according to which the user may more easily and conveniently identify the data with respect to the kind of event and generation date and time to provide the data to the user.

Further, since image data is acquired from a conventional imaging apparatus according to an event generation time point based on an image recognition algorithm using the OPEN CV technique and an image file is provided using matching by image processing, even in the case where a high-priced vision system is not introduced, the cause of an abnormal operation can be easily identified in a software manner.

In addition, since events can be generated by hardware contact or wired/wireless communication by applying IoT technology to the facility diagnosis system and notifications can be provided to the user in real time using a smartphone, immediate measures can be taken.

Drawings

Fig. 1 is a block diagram illustrating a schematic structure of a facility diagnosis system to which the present disclosure is applied; and

fig. 2 is a schematic process flow diagram of a facility diagnostic method using a facility diagnostic system according to the present disclosure.

Detailed Description

The facility diagnosis method using the facility diagnosis system to which the technology of the present disclosure is applied is the following technology: when an abnormal operation occurs during management of a facility in which a facility controller installed with a PLC is built, a user is allowed to more rapidly and accurately identify a detailed cause of the abnormal operation based on target data analyzed specifically via the diagnosis module 120, the imaging module 110, and the IoT sensor unit 130, thereby making it possible to more effectively diagnose a fault whose cause cannot be easily identified during operation of the facility to take measures.

To achieve this, the facility diagnosis method using the facility diagnosis system is a facility diagnosis method performed using a facility diagnosis system including an imaging module 110 and a diagnosis module 120 whose details are as follows, the imaging module 110 being configured to photograph a facility in which a facility controller having a PLC installed therein is built, the diagnosis module 120 including hardware in which software for diagnosing a facility fault is installed.

The facility diagnosis method of the present disclosure includes a diagnostic event generating step S11, a storage range setting step S12, and a file storing step S13.

The diagnostic event generation step (S11) is a step of: the PLC memory map access signal P output by the facility controller is received and detected by the diagnostic module 120, and a kind of diagnostic event corresponding to a plurality of preset event conditions is generated in the diagnostic module 120.

The facility controller is a device built in the facility to control the automation facility, and includes a Printed Circuit Board (PCB) mounted with a Programmable Logic Controller (PLC), a computer, and a microprocessor.

The PLC is a control unit that realizes program control of infrastructure operation sequence control, control by numerical calculation, communication function, and the like by replacing devices such as a relay, a timer, and the like built in a control panel mounted on a conventional facility with a semiconductor device.

The PLC includes hardware and PLC software including an input/output module, a power supply, a communication module, and peripheral devices including a CPU and a memory.

The PLC memory is divided into areas for user program memory, data memory and system memory.

The user program memory is an area in which the user-specific program is stored. The PLC allows a user-specific program to perform a control operation of a device connected to the PLC. The data storage is an area in which device information such as input/output, auxiliary relays, contact states and setting values of timers and counters are stored. The system memory is an area in which a system program such as an Operating System (OS) written by a PLC manufacturer is stored.

The user-specific program is a control program written by a user according to a facility to be controlled, and inputs and outputs signals through an input/output module of the PLC and accesses and communicates with the interface to perform various control functions.

The input/output module of the PLC directly connects an input/output circuit and devices constituting a facility, and basically includes a signal control scheme by a digital unit or an analog unit in which a converter is built. In addition, input/output communication is made possible by the PLC memory map access signal P. Since known techniques can be referred to for common technical problems of the PLC, a detailed description thereof will be omitted.

The diagnostic module 120 includes: a plurality of terminal members; a plurality of communication ports for communication of the PLC, which will be described below, with the imaging module 110; a PCB mounted with software for analyzing and processing input data and diagnosing facility faults; and a display device which sets and changes various parameters through a software interface and identifies the stored image data.

The diagnostic module 120 receives the PLC memory map access signal P from the PLC input/output module and generates an event. The user may designate a signal to be used as a PLC memory map access signal or a memory area signal on a PLC program according to a facility situation by using an input/output module of the PLC.

The diagnosis module 120 generates an event according to preset parameters. Based on the event generation time point, the diagnosis module 120 transmits a signal to the imaging module 110, which will be described below, and allows the captured image data to be edited and stored according to the setting of user conditions, and in particular, analyzes the state information and data values of the PLC storage region and provides the analyzed state information and data values such that the state information and data values are used to diagnose the facility fault.

The storage range setting step (S12) is a step of: the ranges of the state information and the data values of the PLC storage region to be stored at the diagnostic event generation time point are arbitrarily selected, and the time region in the previous/subsequent range based on the diagnostic event generation time point is set.

Since various kinds of device information and data values such as input/output, internal relays, and link relays are stored in the data storage area of the PLC memory, in the storage range setting step (S12), the user arbitrarily selects the ranges of input/output state information and data values to be read and stored, and sets the time range to be stored based on the diagnostic event generation time point.

The file storing step (S13) is a step of storing, by the diagnostic module 120, the state information and data values of the PLC storage area within the range selected in the storage range setting step (S12) in real time.

Specifically, in the file storing step (S13), the status information and the data value of the PLC storage area are stored and provided to the user in the form of a data file of the type of the diagnostic event and the generation date and time of the diagnostic event, so that the user can take measures based on the stored file quickly and accurately.

In addition, in the file storing step (S13), regions for input/output, internal relays, and link relays of the PLC storage region are converted in units of bits to display an operation state of the PLC storage region, and regions for the data register and the link register are stored as a data file to convert the data register and the link register in units of decimal numbers after reading the data register and the link register in units of words to display the data register and the link register.

The input/output area is a device that stores on/off data and CPU calculation result data for transmitting devices (e.g., switches, sensors, lamps, or solenoids) connected to an input/output module of the PLC, and displays status information of input/output contact points. The internal relay area is a means for storing ON/OFF contact point data of the CPU. The link relay is a device that shares data during communication between CPUs. The data register is a device that stores internal data in the CPU. A link register is a device that shares word data between CPUs during communication. As for the detailed functions of the device applied to the PLC, known techniques can be referred to.

The CPU of the PLC stores and processes all data as 1 or 0. Therefore, since numerical calculation is also processed by binary number, when data is stored in a file in such a state, it is difficult for a user to easily recognize the content of the data. Therefore, in the file storing step (S13), since the ON/OFF operation is displayed in units of bits according to the operation characteristics of the device and the data in units of 16 bits or 32 bits is converted into decimal numbers for display after being read in units of words, the user can more conveniently and quickly recognize the stored data file when reading the data file.

[ modes for carrying out the invention ]

Further, in the facility diagnosis method using the facility diagnosis system of the present disclosure, the storage pattern recognition software is installed on the diagnosis module 120, and the facility diagnosis method includes a main storage pattern setting step (S21) and a storage pattern notification step (S22).

The main memory mode setting step (S21) is a step of: storing the state information and the data value of the PLC storage area during one period of a normal state operation of the facility, and setting the stored state information and data value to a main storage mode.

That is, the diagnostic module 120 stores the state information and the data value of the PLC storage area within the range preset in the storage device of the diagnostic module 120 by the user while performing one cycle of the normal operation of the facility in conjunction with the communication module of the PLC, thus setting the main storage mode recognized by the storage mode recognition software.

The storage mode notification step (S22) is a step of: the method includes reading the PLC storage area in real time during facility operation, comparing the read PLC storage area with a main storage mode, and displaying an area in which the read PLC storage area does not coincide with the main storage mode.

Further, in the facility diagnosis method using the facility diagnosis system of the present disclosure, the image recognition application is installed on the imaging module 110, and the facility diagnosis method includes a main image setting step (S31), a matching rate setting step (S32), an image monitoring event generating step (S33), and an image file storing step (S34).

The imaging module 110 includes an imaging device that normally photographs a monitoring target and uniformly stores the latest image data of an appropriate capacity.

The imaging device includes a camera or CCTV that is included and built into the facility diagnostic system 100 or is remotely installed. One or more imaging devices are connected to a connection port provided in the diagnostic module 120 to transmit and receive signals.

The image recognition application is software that installs image recognition comparison algorithms based on OPEN CV technology and allows the storage and matching of master images using conventional imaging devices.

OPEN source computer vision (OPEN CV) is an OPEN library for real-time computer vision in software, and functions such as operation, recognition, tracking, and confirmation of a monitoring target can be realized by image processing.

Conventional automated production lines perform inspections such as inspecting material assemblies, inspecting different products, or inspecting sizes by using sensors or vision systems (machine vision), and CCTV in circulation employs a scheme of storing real-time images or complete images by a motion detection scheme. Further, the present disclosure uses an OPEN CV-based implementation of image recognition applications and conventional imaging devices, rather than constructing a conventional high-priced vision system.

The main image setting step (S31) is a step of: after the image area is set to the normal state of the monitoring target, edge features of a plurality of images are accumulated in units of pixels and an averaged main image is learned.

That is, the main image is generated by combining edge features of hundreds of images obtained by capturing a normal state using an edge (periphery or corner) feature detection algorithm of an image implemented in an image recognition application.

The matching rate setting step (S32) is a step of storing the matching rate and the storage condition in which the boundary value is set as the normal state and the abnormal state of the monitoring target. The user can arbitrarily set the matching rate.

The image monitoring event generating step (S33) is a step of: the image monitoring event signal output by the imaging module 110 is received and detected by the diagnostic module 120, an image monitoring event conforming to a preset image monitoring event condition is generated in the diagnostic module 120, and a signal is transmitted to the imaging module 110.

The image file storing step (S34) is a step of: a current state image of the monitoring target is acquired at an image monitoring event generation time point by the imaging module 110, and if a storage condition is satisfied according to a matching rate after the current state image is compared with the main image, the current state image is stored as an image file.

In addition, in the image file storing step (S34), image data of the monitoring target captured by the imaging device in a time area ranging before/after the image monitoring event generation time point is acquired and edited and stored in the image file.

Further, in the facility diagnosis method using the facility diagnosis system of the present disclosure, a plurality of IoT sensor units 130 monitoring a monitoring target are provided, and the facility diagnosis method includes an IoT event generating step (S41), an image file storing step (S41), and an IoT notifying step (S43).

That is, when the IoT sensor unit 130 satisfies a preset condition after assuming a situation in the monitoring area (e.g., a situation such as control entry/exit, detection of intrusion, or facility health) that is determined to require user monitoring, the diagnostic module 120 detects the IoT monitoring event signal to generate the IoT monitoring event.

The IoT event generating step (S41) is a step of: the IoT monitoring event signal is received and detected through hardware contact or wired/wireless communication of the diagnostic module 120 with the IoT sensor unit 130, an IoT monitoring event corresponding to a preset IoT monitoring event condition is generated in the diagnostic module 120, and a signal is transmitted to the imaging module 110.

The image file storing step (S42) is a step of: image data of a monitoring target captured by an imaging device in a time area ranging before/after an IoT monitoring event generation time point is acquired and edited and the edited image data is stored as an image file.

The IoT notifying step (S43) is a step of: an IoT monitoring event generation notification is sent to the user's smartphone through the diagnostic module 120.

The above-described facility diagnosis method using the facility diagnosis system according to the present disclosure uses the facility diagnosis system 100 including the diagnosis module 120 interworking with the PLC, the imaging module 110 interworking with the diagnosis module 120, and the IoT sensor unit 130, and can effectively diagnose a facility fault whose cause is difficult to identify by generating various kinds of events according to user conditions specified for a facility situation.

Therefore, according to the present disclosure, it is possible to quickly identify an accurate reason by converting the state information and the data values of the PLC storage area into a form of a data file that can be more easily and conveniently recognized by a user through the event generation step to the file storage step (S11 to S13) and providing the state information and the data values to the user for the event type and the generation date and time, and the user can more quickly cope with the failure diagnosis through the main storage mode setting step to the storage mode notification step (S21 to S22).

In addition, according to the present disclosure, with the main image setting step to the image file storing step (S31 to S34), even without introducing a high-priced vision system, it is possible to easily diagnose and recognize abnormal operations in a software manner by using a conventional imaging apparatus.

[ Industrial Applicability ]

The present disclosure can achieve various effects as follows: for example, with the IoT event generation step to the IoT notification step (S41 to S43), diagnosis and measures are rapidly performed by connecting the facility controller, the facility diagnosis system, and the user to apply the IoT technology to the facility diagnosis system 100 in real time.