Control system for instrumentation device with artificial intelligence

Abstract

The artificial intelligence-type instrumentation control device management system according to the present invention comprises: an equipment data measurement unit disposed in a controlled equipment and generating measurement data from the equipment; an equipment power detection unit for detecting power data supplied to the equipment; a control panel unit for receiving measurement data from the data measurement unit and generating a control signal for the equipment; a control panel data measurement unit disposed in the control panel unit and generating measurement data from the control panel unit; a control panel power detection unit for detecting power data supplied to the control panel unit; a central control server unit configured to be connected to the control panel unit via communication; a data storage unit for storing data; a management interface unit connected to the central control server unit for inputting and outputting information; and a manager terminal unit configured to be connected to the central control server unit via communication. An artificial intelligence module is configured to be linked to the central control server unit. When the data detected by the equipment data measurement unit, the equipment power detection unit, the control panel data measurement unit, and the control panel power detection unit during the operation of the equipment is in an abnormal state that deviates from a predetermined standard range, the system displays this on the management interface unit. It is characterized by being configured to notify the administrator terminal. According to the present invention, abnormal conditions of equipment under control can be monitored remotely, monitoring efficiency can be increased, and the risk of data loss that may occur during system operation can be reduced. In addition, it improves the accuracy of abnormal condition monitoring, enabling timely necessary measures; enhances data security during overall system operation to prevent data alteration caused by external hacking; and allows for the prediction of equipment abnormalities and modification of operating conditions through artificial intelligence.

Description

Technology Field

[0001] The present invention relates to an instrumentation control device management system, and more specifically, to an artificial intelligence-type instrumentation control device management system configured to remotely monitor abnormal conditions of controlled equipment using artificial intelligence, reduce the risk of data loss that may occur during system operation, and increase the accuracy of abnormal condition monitoring to take necessary measures in a timely manner. Background Technology

[0002] Instrumentation control systems are primarily used in water supply and sewage treatment plants, power generation facilities, and transmission and distribution facilities, and are also currently utilized for the management of various buildings, lighting management of facilities, and power management.

[0003] The above instrumentation control system analyzes and processes data such as flow rate, pressure, temperature, and humidity measured by various measuring devices installed in the controlled equipment through programs stored in the central processing unit.

[0004] And, the control signal generated as a result of processing as described above is transmitted to the devices to be controlled connected through the control unit (PLC: Programmable Logic Controller) to control the equipment.

[0005] Meanwhile, due to the rapid advancement of artificial intelligence technology in recent years, there is a trend of using the aforementioned AI technology to solve most intellectual activities performed by humans.

[0006] However, conventional instrumentation control systems have limitations in that they are ineffective for integrated monitoring of the entire facility, as they monitor abnormal conditions only for individual control targets included in the system. The problem to be solved

[0007] The objective of the present invention is to provide an artificial intelligence-type instrumentation control device management system configured to remotely monitor abnormal conditions of equipment under control.

[0008] Another objective of the present invention is to provide an artificial intelligence-type instrumentation control device management system configured to prevent data loss.

[0009] Another objective of the present invention is to provide an artificial intelligence-type instrumentation control device management system configured to improve the accuracy of abnormal condition monitoring.

[0010] Another objective of the present invention is to provide an artificial intelligence-type instrumentation control device management system configured to enhance data security during the operation of the entire system.

[0011] Another objective of the present invention is to provide an artificial intelligence-type instrumentation control device management system configured to predict abnormal conditions through artificial intelligence and change the operating conditions of equipment to be controlled. means of solving the problem

[0012] An artificial intelligence-type instrumentation control device management system according to the present invention for achieving the above objective comprises: an equipment data measurement unit disposed in a controlled equipment and generating measurement data from the equipment; an equipment power detection unit for detecting power data supplied to the equipment; a control panel unit for receiving measurement data from the equipment data measurement unit and generating a control signal for the equipment; a control panel data measurement unit disposed in the control panel unit and generating measurement data from the control panel unit; a control panel power detection unit for detecting power data supplied to the control panel unit; a central control server unit configured to be connected to the control panel unit via communication; a data storage unit for storing data; a management interface unit connected to the central control server unit for inputting and outputting information; and a manager terminal unit configured to be connected to the central control server unit via communication. An artificial intelligence module is configured to be linked to the central control server unit. When the data detected by the equipment data measurement unit, the equipment power detection unit, the control panel data measurement unit, and the control panel power detection unit during the operation of the equipment is in an abnormal state that deviates from a predetermined standard range, the management interface unit It is characterized by being configured to display and notify the above-mentioned administrator terminal.

[0013] Preferably, when the equipment is not in operation, if the data detected by the equipment data measurement unit, equipment power detection unit, control panel data measurement unit, and control panel power detection unit is in an abnormal state that deviates from a predetermined standard range, it may be configured to display this on the management interface unit and notify the manager terminal unit.

[0014] Here, the data storage unit includes a first data storage unit and a second data storage unit, and data detected by the equipment data measurement unit, equipment power detection unit, control panel data measurement unit, and control panel power detection unit is stored in the first data storage unit and the second data storage unit, and may be configured to be stored in the first data storage unit or the second data storage unit by being classified according to the time when the data was measured.

[0015] In addition, the period during which the data is stored in the first data storage unit and the second data storage unit may be configured to be different from each other.

[0016] In addition, the central control server unit includes a data encryption module, and the data stored in the second data storage unit may be configured to be encrypted and stored by the data encryption module.

[0017] Preferably, it can be configured so that the identity of the data stored in the first data storage unit and the data stored in the second data storage unit is compared at predetermined intervals.

[0018] In addition, the second data storage unit may be configured as a WORM (Write Once Read Many) memory.

[0019] In addition, the artificial intelligence module includes a first artificial intelligence module and a second artificial intelligence module, wherein the first artificial intelligence module learns first data collected during a predetermined first period, and the second artificial intelligence module is configured to learn second data collected during a second period shorter than the first period.

[0020] Preferably, the artificial intelligence module is configured to learn normal state data and abnormal state data during a predetermined period.

[0021] In addition, if the artificial intelligence module determines that the state of the control target equipment and the control panel is approaching an abnormal state, it may be configured to display this on the management interface.

[0022] In addition, if it is determined by the artificial intelligence module that it is approaching an abnormal state, the artificial intelligence module may be configured to learn the final confirmation result of a human regarding that determination.

[0023] Here, if the artificial intelligence module determines that the equipment to be controlled is approaching an abnormal state, the drive control signal of the equipment to be controlled included in the equipment may be configured to be changed.

[0024] Preferably, the system may be configured to calculate the efficient operating conditions of the control target device included in the facility relative to the power supplied to the facility through the artificial intelligence module and display them on the management interface. Effects of the invention

[0025] According to the present invention, abnormal conditions of equipment under control can be monitored remotely, and monitoring efficiency can be increased.

[0026] In addition, it can reduce the risk of data loss that may occur during system operation.

[0027] In addition, the accuracy of abnormal condition monitoring can be improved, allowing necessary measures to be taken in a timely manner.

[0028] In addition, data security is enhanced during the operation of the entire system, preventing data alteration caused by external hacking.

[0029] In addition, artificial intelligence can predict abnormal conditions of the equipment and change operating conditions. Brief explanation of the drawing

[0030] The attached drawings below are intended to facilitate an understanding of the technical concept of the present invention in conjunction with the detailed description of the invention; therefore, the present invention should not be interpreted as being limited to the matters illustrated in the drawings below. FIG. 1 is a configuration diagram of an artificial intelligence-type instrumentation control device management system according to the present invention, and FIG. 2 is a configuration diagram of an artificial intelligence-type instrumentation control device management system according to another embodiment of the present invention. Specific details for implementing the invention

[0031] Hereinafter, the configuration of the present invention will be described in detail with reference to the attached drawings.

[0032] Prior to this, the terms used in this specification and claims shall not be interpreted as being limited to their dictionary meanings; rather, based on the principle that the inventor may appropriately define the concepts of the terms to best describe their invention, they shall be interpreted in a meaning and concept consistent with the technical spirit of the invention.

[0033] Therefore, it should be understood that the embodiments described in this specification and the configurations illustrated in the drawings are merely preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention, and that various equivalents and modifications that can replace them may exist at the time of filing this application.

[0034] FIG. 1 is a configuration diagram of an artificial intelligence-type instrumentation control device management system according to the present invention, and FIG. 2 is a configuration diagram of an artificial intelligence-type instrumentation control device management system according to another embodiment of the present invention.

[0036] Referring to FIG. 1, the artificial intelligence-type instrumentation control device management system according to the present invention comprises: an equipment data measurement unit (10) disposed in a controlled equipment and generating measurement data from the equipment; an equipment power detection unit (20) for detecting power data supplied to the equipment; a control panel unit (30) for receiving measurement data from the equipment data measurement unit (10) and generating a control signal for the equipment; a control panel data measurement unit (40) disposed in the control panel unit (30) and generating measurement data from the control panel unit (30); a control panel power detection unit (50) for detecting power data supplied to the control panel unit (30); a central control server unit (60) configured to be connected to the control panel unit (30) by communication; a data storage unit (70) for storing data; a management interface unit (80) connected to the central control server unit (60) for inputting and outputting information; and a central control server unit (60) connected by communication It is characterized by including a manager terminal unit (90) configured to be connected, and an artificial intelligence module is configured to be linked to the central control server unit (60), and when the data detected by the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) during the operation of the equipment is in an abnormal state that deviates from a predetermined standard range, it is configured to display on the management interface unit (80) and notify the manager terminal unit (90).

[0037] The instrumentation control device management system according to the present invention can be used, for example, in water supply or sewage treatment facilities, transmission / distribution facilities, or power management facilities.

[0038] The above-mentioned facility data measurement unit (10) is configured to be placed in various facilities included in the above-mentioned water and sewage treatment facilities, etc., and to generate measurement data from the facilities.

[0039] The above measurement data may be, for example, data such as temperature, pressure, and flow rate, and the above equipment data measurement unit (10) may preferably be configured to include various sensors placed in various element devices such as pumps, motors, pipes, and valves included in the above equipment.

[0040] Preferably, the equipment or component devices are configured to be assigned unique identification information (ID) to clearly distinguish and manage data detected from the equipment or component devices.

[0041] And, at this time, it is configured to provide a detailed data view so that status data of a specific facility or element device can be viewed through the administrator interface unit (80) connected to the central control server unit (60).

[0042] In addition, it is configured to store status data history for each piece of equipment or component device, so that it can be utilized as data for cause analysis in the event of a failure.

[0043] The above-mentioned equipment power detection unit (20) is positioned to detect power data supplied to the equipment, and the power data may be data regarding the voltage and current of the power supplied to the equipment.

[0044] The above-mentioned equipment power detection unit (20) is preferably configured to be placed in various element devices included in the equipment and to detect the voltage and current of the power supplied to the element devices.

[0045] The above equipment power detection unit (20) may be configured to detect the voltage and current supplied to the equipment or element devices included therein (e.g., pump, motor, fan) and to check whether they fall outside the reference range.

[0046] In addition, the above-mentioned equipment power detection unit (20) may be configured to detect an overload condition exceeding the rated current of the equipment or element devices included therein, or to detect abnormal power consumption and power factor reduction by detecting the power consumption and power factor of power consuming devices such as motors.

[0047] The control unit (30) receives data such as temperature, pressure, and flow rate from the equipment data measurement unit (10) and generates control signals for various element devices included in the equipment.

[0048] The above control unit (30) may be configured in multiple units and distributed according to the type of equipment to be controlled or the installation site.

[0049] For data transmission between the above-mentioned equipment data measurement unit (10) and equipment power detection unit (20) and the control unit (30), wired analog / digital communication methods such as RS-485 or 4-20 mA standards, or wireless communication methods such as LoRa, Zigbee, and Wi-Fi may be used.

[0050] The above control panel data measurement unit (40) is positioned in the control panel (30) and configured to generate measurement data from the components included in the control panel (30).

[0051] The above measurement data may be, for example, data such as temperature, humidity, vibration, and whether an arc has occurred, and the control panel data measurement unit (40) may preferably be configured to include various sensors placed on the component parts or exterior of the control panel unit (30).

[0052] The above control panel data measurement unit (40) may be configured to detect whether an arc is generated in a power switch, circuit breaker, cable connection part, etc. inside the control panel (30), for example, by including an arc detection sensor.

[0053] In addition, it can be configured to prevent fire and equipment damage by linking with a system that immediately notifies the central control server (60) when an arc is detected and automatically trips the main circuit breaker or the circuit breaker of the corresponding component as needed.

[0054] Additionally, the control panel data measurement unit (40) may be configured to include a temperature / humidity detection sensor to detect temperature and humidity at various points inside the control panel (30), and to notify the central control server unit (60) if the detected temperature and humidity fall outside the reference range.

[0055] In addition, when the internal temperature of the control unit (30) reaches a dangerous level, it may be configured to operate a cooling fan installed inside the control unit (30) or to be linked with an external air conditioning / dehumidification system to maintain an appropriate environment.

[0056] Alternatively, a vibration detection sensor may be placed near components that can cause vibration, such as a cooling fan, relay, or contactor inside the control panel (30), and configured to notify the central control server (60) when an abnormal vibration pattern is detected.

[0057] The above control panel power detection unit (50) is positioned to detect power data supplied to the control panel (30), and the power data may be data regarding the voltage and current of the power supplied to the control panel (30).

[0058] The above control panel power sensing unit (50) is preferably configured to be placed in various component parts included in the control panel (30) to sense the voltage and current of the power supplied to the component parts.

[0059] The above control panel power detection unit (50) may be configured to detect, for example, the voltage, current, and frequency of the main power supply entering the control panel unit (30), and to notify the central control server unit (60) if the voltage is outside the reference range or if an abnormal pattern is detected.

[0060] Additionally, the control panel power detection unit (50) may be configured to individually measure the voltage and current distributed to each module (relay, power supply, etc.) inside the control panel (30) to detect overload, short circuit, or abnormal power consumption of a specific module.

[0061] The above control unit (30) is configured to be connected to the above central control server unit (60) via wired or wireless communication.

[0062] The above control panel (30) and the above central control server (60) can be connected by, for example, wired or wireless internet communication, Ethernet, or communication methods such as MQTT, Modbus / TCP, OPC UA.

[0063] The data detected by the above equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) and transmitted to the above central control server unit (60) is stored in the above data storage unit (70).

[0064] The data storage unit (70) may be configured as a designated area for data storage in the central control server unit (60), or it may be configured as a data storage device separate from the central control server unit (60).

[0065] The central control server unit (60) is configured to have an administrator interface unit (80) connected to it to input and output information.

[0066] The above administrator interface unit (80) may be configured to include a monitor for displaying information and a personal computer for inputting and outputting information.

[0067] And, the above-mentioned administrator terminal (90) is configured to be connected to the above-mentioned central control server (60) by communication.

[0068] Preferably, the administrator terminal (90) is configured as a mobile communication device such as a smartphone and is configured to be connected to the central control server (60) via wireless communication.

[0069] The above central control server unit (60) is configured to have an artificial intelligence module linked to it.

[0070] The above artificial intelligence module may be developed by the applicant of the present invention, but preferably, it may be an artificial intelligence algorithm developed and distributed by multinational corporations, and may be configured to be connected to the central control server unit (60) to provide artificial intelligence functions.

[0071] The artificial intelligence module is configured to learn and analyze data flowing in from the detection sensors.

[0072] In the management system according to the present invention, when power is supplied to the equipment and the equipment is in operation, the system is configured to determine that the equipment is in an abnormal state if the data detected by the equipment data measurement unit (10), the equipment power detection unit (20), the control panel data measurement unit (40), and the control panel power detection unit (50) deviates from a predetermined standard range.

[0073] Thus, it is configured to determine whether the equipment to be controlled is operating normally.

[0074] In addition, if an abnormal condition as described above occurs, it is configured to be displayed on the management interface unit (80) so that necessary measures can be taken.

[0075] In addition, in the event of an abnormal condition as described above, it is configured to notify the administrator terminal (90) so that immediate action can be taken at the site where the equipment is located.

[0076] Preferably, the equipment is configured to detect data by the equipment data measurement unit (10), the equipment power detection unit (20), the control panel data measurement unit (40), and the control panel power detection unit (50) even when the equipment is not in operation, for example, when power is not supplied to the equipment, or when the operation of the included element devices is stopped even when power is supplied to the equipment.

[0077] In addition, even if the data detected as described above is in an abnormal state that deviates from a predetermined standard range, it can be configured to be displayed on the management interface unit (80) and notified to the administrator terminal unit (90).

[0078] Thus, it is configured to monitor the status of the equipment even when the equipment to be controlled is not in operation.

[0079] And, as described above, when the equipment is not in operation, it is configured to detect whether the various detection sensors included in the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) output normal output values.

[0080] Thus, it is configured to check for malfunctions or defects in the detection sensors.

[0081] In addition, the system is configured to check at predetermined intervals whether the various detection sensors included in the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) are properly transmitting data to the control panel unit (30) and the central control server unit (60), and if there is no data transmission, it is determined that there is a sensor communication failure or a power cutoff, and a warning signal is generated through the central control server unit (60).

[0082] In addition, if the above detection sensors transmit an abnormal output value that is outside the maximum / minimum range of the detected value, it is determined that there is a sensor failure or data contamination, and a warning signal is generated through the central control server unit (60).

[0083] Meanwhile, as in another embodiment of the present invention illustrated in FIG. 2, the data storage unit (70) may be configured to include a first data storage unit (72) and a second data storage unit (74).

[0084] In addition, the data detected by the equipment data measurement unit (10), the equipment power detection unit (20), the control panel data measurement unit (40), and the control panel power detection unit (50) can be configured to be stored in the second data storage unit (74) along with the first data storage unit (72).

[0085] Here, the data may be configured to be classified according to the time at which they were measured and stored in the first data storage unit (72) or the second data storage unit (74).

[0086] The first data storage unit (72) is configured to be a high-performance SSD memory device so that data measured within the last few months is stored, thereby enabling efficient and rapid access, and the second data storage unit (74) is configured to be a storage device of a different type from the first data storage unit (72) so that data measured more than one year ago is stored.

[0087] Preferably, the second data storage unit (74) may be configured as a WORM (Write Once Read Many) memory.

[0088] The above WORM memory is a memory that cannot be changed or deleted once data is written, and can fundamentally prevent tampering with stored data.

[0089] By using the above WORM memory, tampering with long-term preserved data caused by hacking can be prevented.

[0090] In addition, the data storage cycle in the first data storage unit (72) and the second data storage unit (74) can be configured to be set differently from each other.

[0091] For example, the period for storing data in the second data storage unit (74) may be configured to be longer than the period for storing data in the first data storage unit (72), and the first data storage unit (72) may be configured to store data at every moment, while the second data storage unit (74) may be configured to store data at a period of 0.1 to 1 second.

[0092] Thus, it is configured so that the total data capacity stored in the second data storage unit (74) is significantly reduced while still being able to identify the fluctuation trends of the data.

[0093] In addition, the central control server unit (60) is configured to include a data encryption module (62), and the data stored in the second data storage unit (74) can be configured to be encrypted by the data encryption module (62) and stored.

[0094] The above data encryption module (62) can be configured to encrypt the measured data and generate a hash function value.

[0095] A hash function or hash algorithm is a function that maps data of arbitrary length to data of fixed length, and the value obtained by said hash function is called the hash function value.

[0096] The above hash function is widely used in computer software for very fast data retrieval. While conventional encryption algorithms use keys, this hash function does not use keys, so the same input always produces the same output.

[0097] The above hash function is used to provide integrity capable of detecting errors or tampering with the message.

[0098] As described above, the data encrypted by the data encryption module (60) and its hash function value are stored in the second data storage unit (74), thereby ensuring the confidentiality of the data while simultaneously preventing data tampering through integrity verification using the hash function value.

[0099] Preferably, the data stored in the first data storage unit (72) and the data stored in the second data storage unit (74) may be configured to be compared for identity at predetermined intervals.

[0100] Thus, the first data storage unit (72) is configured to be protected by a firewall with very high security, and the data stored in the second data storage unit (74), which is configured as WORM memory, is compared for identity at predetermined intervals to monitor hacking or data alteration.

[0101] In addition to configuring the second data storage unit (74) as a WORM memory, the firewall is designed economically and efficiently by comparing the identity of the data stored in the first and second data storage units (72, 74) at predetermined intervals, thereby enhancing data security performance and enabling monitoring of hacking or data alteration situations.

[0102] In addition, the artificial intelligence module may be configured to include a first artificial intelligence module and a second artificial intelligence module.

[0103] Here, the first artificial intelligence module may be configured to learn first data collected during a predetermined first period, and the second artificial intelligence module may be configured to learn second data collected during a second period shorter than the first period.

[0104] The first period above may be set as a period in units of months, quarters, or seasons, for example, and the second period above may be set as a period in units of hours during the day, for example.

[0105] Thus, it can be configured to learn the influence of external environmental factors, such as season or weather, on the data through the first data, and to learn the influence of external environmental factors, such as sunlight or temperature, on the data through the second data.

[0106] An LSTM model may be used for the above first data processing.

[0107] The above LSTM (Long Short-term Memory) model is an algorithm used for predicting time series data. It has the advantage of processing data by remembering previous information for a long period, allowing for efficient identification of data change patterns over long periods or seasonal influences.

[0108] And, the XGBoost model can be used for the above second data processing.

[0109] The above XGBoost model is a scalable distributed model that is robust for high-speed short-term forecasting and outlier handling, and can efficiently process various data at the current time.

[0110] Thus, the artificial intelligence module is configured to learn the influence of data caused by long-term and short-term external environmental factors by collecting and learning the first data and the second data.

[0111] In addition, the artificial intelligence module is configured to learn normal state data and abnormal state data during a predetermined period.

[0112] The above normal state data refers to data measured by the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) while the equipment or control panel (30) is operating normally without any abnormal state occurring.

[0113] And, the above abnormal state data refers to data measured by the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) when an abnormal state occurs in the equipment or control panel unit (30).

[0114] Thus, it is configured to identify and learn all the data when all the data measured by the equipment data measurement unit (10), equipment power detection unit (20), control panel data measurement unit (40), and control panel power detection unit (50) are within a reference range, and all the remaining data when any one of the data falls outside the reference range.

[0115] The learning of normal and abnormal state data as described above can be performed within a period of, for example, 3 months to 1 year, and thereafter, when the artificial intelligence module determines that the state of the control target equipment and the control panel (30) is close to an abnormal state, it can be configured to display this on the management interface (80).

[0116] And, when it is determined by the artificial intelligence module that it is approaching an abnormal state and displayed on the management interface unit (80), the artificial intelligence module may be configured to learn the final confirmation result of a person regarding that determination again.

[0117] Alternatively, when the artificial intelligence module determines that the state is close to an abnormal state as described above and the state displayed on the management interface unit (80) is such that the artificial intelligence module is configured to learn the operating state or measurement data after a predetermined time.

[0118] Thus, the AI ​​module is configured to learn through trial and error the judgments made by the AI ​​module and the final human verification results thereof, or the operating status or measurement data after a predetermined period, over time, thereby gradually increasing the accuracy of the AI ​​module's judgment regarding whether it is approaching an abnormal state.

[0119] In addition, if the artificial intelligence module determines that the control target equipment is approaching an abnormal state, it may be configured to display this on the manager interface unit (80) and change the drive control signals of the element devices included in the equipment.

[0120] Thus, for example, when multiple motors are included as the control target element devices, the motor determined to be approaching an abnormal state may be displayed on the manager interface unit (80), and at the same time, the load of the motor may be reduced or its operation stopped, and the load of other motors operating in a normal state may be increased to replace it.

[0121] With the above configuration, the element device that is judged to be close to an abnormal state can be displayed on the administrator interface section (80) to allow for action to be taken, while also being configured to temporarily supplement functions through other element devices.

[0122] Preferably, the artificial intelligence module is configured to measure the power supplied to the element devices of the equipment through the equipment power detection unit (20) and to measure the operating status of element devices, such as motors included in the equipment, through the equipment data measurement unit (10).

[0123] In addition, the artificial intelligence module can be configured to calculate the power-efficient operating conditions of the element devices included in the facility based on the supply power and operating conditions measured as above and display them on the management interface unit (80).

[0125] For the above, the terms used in the embodiments of the present invention have the same meaning as generally understood by those skilled in the art to which the present invention pertains.

[0126] Although the present invention has been described by limited embodiments and drawings, the above embodiments are intended to explain, not to limit, the technical concept of the present invention, and therefore the technical concept of the present invention is not limited to these, and various modifications and variations may be made by a person skilled in the art within the scope of the technical concept of the present invention and the equivalent scope of the following claims.

[0127] Accordingly, the scope of protection of the present invention shall be interpreted by the claims, and all technical ideas within an equivalent scope shall be interpreted as being included within the scope of rights of the present invention.

[0128] In addition, within the scope of the purpose of the present invention, one or more of the components may be optionally combined.

[0129] The terms "included" or "composed" mentioned above mean that the relevant component may be included, and should be interpreted as meaning that other components may additionally be included. Explanation of the symbols

[0130] 10: Equipment Data Measurement Unit 20: Equipment Power Detection Unit 30: Control panel 40: Control panel data measurement unit 50: Control panel power detection unit 60: Central Control Server Department 70: Data storage unit 80: Administrator Interface Section 90: Administrator Terminal

Claims

Claim 1 The system comprises: an equipment data measurement unit positioned at the equipment to be controlled and generating measurement data from the equipment; an equipment power detection unit for detecting power data supplied to the equipment; a control panel unit for receiving measurement data from the equipment data measurement unit and generating a control signal for the equipment; a control panel data measurement unit positioned at the control panel unit and generating measurement data from the control panel unit; a control panel power detection unit for detecting power data supplied to the control panel unit; a central control server unit configured to be connected to the control panel unit via communication; a data storage unit for storing data; a management interface unit connected to the central control server unit for inputting and outputting information; and a manager terminal unit configured to be connected to the central control server unit via communication, wherein an artificial intelligence module is configured to be linked to the central control server unit, and if, during the operation of the equipment, the data detected by the equipment data measurement unit, the equipment power detection unit, the control panel data measurement unit, and the control panel power detection unit is in an abnormal state that deviates from a predetermined standard range, it is displayed on the management interface unit and notified to the manager terminal unit. An artificial intelligence-type instrumentation control device management system characterized by being configured such that, when the equipment is not in operation, if the data detected by the equipment data measurement unit, equipment power detection unit, control panel data measurement unit, and control panel power detection unit is in an abnormal state that deviates from a predetermined standard range, it is displayed on the management interface unit and notified to the administrator terminal unit; the data storage unit includes a first data storage unit and a second data storage unit; the data detected by the equipment data measurement unit, equipment power detection unit, control panel data measurement unit, and control panel power detection unit is stored in the first data storage unit and the second data storage unit, and is configured to be stored in the first data storage unit or the second data storage unit by being classified according to the time when the data was measured. Claim 2 An artificial intelligence-type instrumentation control device management system according to claim 1, characterized in that the period during which data is stored in the first data storage unit and the second data storage unit is set differently from each other. Claim 3 An artificial intelligence-type instrumentation control device management system according to claim 1, wherein the central control server unit includes a data encryption module, and the data stored in the second data storage unit is encrypted and stored by the data encryption module. Claim 4 An artificial intelligence-type instrumentation control device management system according to claim 3, characterized in that the identity of data stored in the first data storage unit and data stored in the second data storage unit is compared at predetermined intervals. Claim 5 An artificial intelligence-type instrumentation control device management system according to claim 1, characterized in that the second data storage unit is composed of WORM (Write Once Read Many) memory. Claim 6 An artificial intelligence-type instrumentation control device management system according to claim 1, wherein the artificial intelligence module includes a first artificial intelligence module and a second artificial intelligence module, wherein the first artificial intelligence module learns first data collected during a predetermined first period, and the second artificial intelligence module is configured to learn second data collected during a second period shorter than the first period. Claim 7 An artificial intelligence-type instrumentation control device management system according to claim 6, characterized in that the artificial intelligence module is configured to learn normal state data and abnormal state data during a predetermined period. Claim 8 An artificial intelligence-type instrumentation control device management system according to claim 7, characterized in that when the artificial intelligence module determines that the state of the equipment to be controlled and the control panel is approaching an abnormal state, it is configured to be displayed on the management interface. Claim 9 An artificial intelligence-type instrumentation control device management system according to claim 8, characterized in that when the artificial intelligence module determines that the device is approaching an abnormal state, the artificial intelligence module is configured to learn the operating state or measurement data after a predetermined time. Claim 10 An artificial intelligence-type instrumentation control device management system according to claim 7, characterized in that when the artificial intelligence module determines that the equipment to be controlled is approaching an abnormal state, the driving control signal of the equipment to be controlled is changed. Claim 11 An artificial intelligence-type instrumentation control device management system according to claim 10, characterized in that it is configured to calculate the efficient operating conditions of a control target device included in the facility relative to the power supplied to the facility through the artificial intelligence module and display them in the management interface section. Claim 12 delete Claim 13 delete

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