KR20210021832A - Intelligent diagnosing system available of facility and equipment operation by dynamic simulator of marine structure - Google Patents

Abstract

The present invention relates to an intelligent diagnosis system for a facility and an equipment operation by a dynamic simulator of an offshore structure, which combines a dynamic simulator with an automation controller to compare and analyze a simulation process value and an actual process value using preventive check result data to diagnose whether the facility and equipment are abnormal and whether the sensor is abnormal. The intelligent diagnosis system of the present invention includes: an operator station which forms operation data according to on-site operating conditions of facilities and equipment of a ship or offshore plant; an operating condition storage server which stores the operation data formed in the operator station in real time; a dynamic simulator which builds a virtual model of facilities and equipment using operation data and analyzes the simulated process value by performing a simulation operation; an automation controller which actually operates the facility and equipment according to the operation data from the operating condition storage server, and receives the actual process value according to the actual operation through a sensor which monitors the facility and equipment; and an AMS which compares the simulated process value with the actual process value and diagnoses the abnormality of facilities and equipment and the abnormality of the sensor according to the mutual gap. The operator station forms operation data based on the result data of the preventive inspection of the facility and equipment.

Description

Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures {INTELLIGENT DIAGNOSING SYSTEM AVAILABLE OF FACILITY AND EQUIPMENT OPERATION BY DYNAMIC SIMULATOR OF MARINE STRUCTURE}

The present invention relates to an intelligent diagnosis system for offshore structures, and more particularly, by combining a dynamic simulator with an automated controller to compare and analyze simulation process values and actual process values using preventive inspection result data of facilities and equipment. It relates to an intelligent diagnosis system of equipment and equipment operation by dynamic simulator of offshore structures, capable of diagnosing abnormality of abnormality and sensor abnormality.

Usually, the facilities and equipment of offshore structures such as ships operating at sea or offshore plants drilling offshore underground resources of crude oil and gas consist of specialized facilities and equipment of large offshore structures. It requires skilled maneuvering and requires the ability to actively and accurately respond to various events under various weather conditions, and predicts the design life and maintenance cycle during actual operation in addition to the design life of the original manufacturer of equipment and equipment. There is a need to cope with it.

Operating facilities or equipment of offshore structures in actual operating conditions inevitably entails occurrence of unexpected alarms or malfunctions.It is inefficient for unskilled persons to accumulate operating experience for equipment and equipment through actual operation. Even if facilities and equipment are built under stable operating conditions, unexpected alarms or malfunctions according to various operating conditions are identified and coped with only through actual operation, which is quite inefficient.

In addition, operating a facility or equipment under actual operating conditions is when an unexpected alarm or malfunction occurs, whether the occurrence of an alarm or malfunction is due to exceeding the actual operating threshold of the facility or equipment, or a malfunction of the corresponding sensor of the facility and equipment. There is a problem that is difficult to judge.

Accordingly, based on the various result data obtained during the preventive inspection of facilities and equipment, a virtual model of the same or similar facilities and equipment is constructed under the same situation as the actual operating conditions, and comparative analysis with the actual process values detected by the corresponding sensor is performed. There is a need for a technology capable of clarifying the cause of defects or abnormalities by performing simulation operation so as to be possible, predicting the design life during actual operation, and performing optimal maintenance.

Korean Patent Application Publication No. 10-2015-0118340 (published on October 22, 2015) Korean Patent Application Publication No. 10-2016-0042673 (published on April 20, 2016) Korean Patent Application Publication No. 10-2015-0124241 (published on November 5, 2015)

The present invention combines a dynamic simulator with an automation controller to compare and analyze the simulated process value and the actual process value using the preventive inspection result data of facilities and equipment to diagnose the abnormality of the facility and equipment and the sensor. It provides an intelligent diagnosis system for facility and equipment operation by a dynamic simulator of a structure.

An intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator of an offshore structure according to an embodiment of the present invention comprises: a driver station for forming operation data according to on-site operation conditions of equipment and equipment of a ship or offshore plant; A driving condition storage server for storing the driving data formed in the driver station in real time; A dynamic simulator for constructing a virtual model of the facility and equipment using the operation data, and analyzing a simulated process value by performing a simulated operation; An automation controller that actually operates the equipment and equipment according to operation data from the operation condition storage server, and receives an actual process value according to the actual operation through a sensor that monitors the equipment and equipment; And an Alarm Monitoring System (AMS) that compares the simulated process value with the actual process value and diagnoses whether the facility or equipment is abnormal and whether the sensor is abnormal, according to a mutual gap, wherein the driver station comprises: And the operation data may be formed based on the result data of the preventive inspection of the equipment.

As an example, the preventive inspection result data may include bearing wear, crank deflection, shaft wear, cylinder liner obtained during preventive inspection through disassembly of the facility and equipment. It may include at least one of the wear and the information on the piston ring groove (Piston Ring Groove).

As an embodiment, the AMS analyzes the change trend of the actual process value, and provides information on the next preventive inspection cycle based on the increase or decrease of the operating time of the facility and equipment and the preventive inspection result data obtained during the last preventive inspection. Can be formed.

As an embodiment, the dynamic simulator calculates an allowable simulated process value within the normal operation range of the facility and equipment, and the AMS analyzes whether the actual process value exceeds the simulated process value within the normal operation range. , It is possible to diagnose whether the facility and equipment are operating normally, whether mechanical coupling has occurred, and whether the sensor is normally measured.

As an embodiment, the dynamic simulator performs operation simulation for a specific period of time for equipment, fittings, or transmitters including any one or more of field devices, compressors, pumps, heat exchangers, expanders, gas turbines, valves, and pipes. Meanwhile, through mathematical analysis and heat and mass balance analysis according to the fluctuation of the operating conditions, the performance of the equipment and equipment in operation can be measured.

As an example, the dynamic simulator analyzes the possibility of normal control of the process temperature, pressure, flow rate, power consumption, motor RPM, and control valve position of the facility and equipment, and whether an alarm occurs and whether a shutdown occurs. Can be measured.

As an embodiment, the automation controller may include at least one of an Integrated Control and Safety System (ICSS), an Integrated Automation System (IAS), and an Alarm Monitoring System (AMS).

As an embodiment, the dynamic simulator performs a simulation operation in which a stress test is applied to the virtual model under various environmental conditions by applying possible environmental condition data of a vessel operating sea or an offshore plant installation sea, By analyzing the design life and depreciation, the maintenance cycle can be predicted.

As an embodiment, the dynamic simulator may measure an amount of power consumed during a simulated operation of the facility and equipment modeled and constructed to calculate an optimized energy consumption power and apply it to the automation controller.

According to the present invention, by combining a dynamic simulator with an automated controller, the simulation process value using the preventive inspection result data of the facility and equipment and the actual process value can be compared and analyzed to diagnose the abnormality of the facility and equipment and whether the sensor is abnormal. , Before actual operation of equipment and equipment, performance can be simulated to test performance, and stress test under various environmental conditions is applied to predict maintenance cycles to maintain optimal performance of equipment and equipment. It is possible to increase the time available for normal operation. In addition, the reliability of the inspection result can be improved by utilizing the results obtained during the preventive inspection of the facility and equipment to diagnose the abnormality of the facility and equipment.

1 is a schematic configuration diagram of an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator of an offshore structure according to an embodiment of the present invention.
2 is a flowchart showing a procedure of a diagnosis method by an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator according to an embodiment of the present invention.
3 is a diagram illustrating a modification of the intelligent diagnosis system for operation of facilities and equipment by the dynamic simulator of the offshore structure of FIG. 1.
4 is a flowchart showing a procedure of a diagnosis method by an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present invention. The present invention may be implemented in various different forms and is not limited to the embodiments described herein.

1 is a schematic configuration diagram of an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator of an offshore structure according to an embodiment of the present invention.

Referring to FIG. 1, an intelligent diagnosis system of equipment and equipment operation by a dynamic simulator of an offshore structure such as a ship operating at sea or an offshore plant drilling underground resources of crude oil and gas according to an embodiment of the present invention, A driver station 110 that generates actual driving data, a driving condition storage server 120 that stores driving data in real time, and a dynamic simulator 130 that measures the performance of facilities and equipment (151, 152, 153) by simulating a virtual model. ), the automation controller 140 that actually operates the facilities and equipment (151, 152, 153) and receives the actual process value through the sensor 160, and the facility and equipment ( 151, 152, 153) or an AMS 170 that diagnoses the abnormality of the sensor 160, and the driver station 110, based on the preventive inspection result data of the facilities and equipment (151, 152, 153) By forming operation data, by combining the dynamic simulator with the automation controller, the simulation process value and the actual process value can be compared and analyzed to diagnose the abnormality of the facilities and equipment (151, 152, 153) and the sensor 160. Before the actual operation of facilities and equipment (151, 152, 153), performance can be simulated to test performance, and maintenance cycles are predicted to maintain optimal performance of facilities and equipment (151, 152, 153). By doing so, the available time for normal operation can be increased. In addition, the results obtained during preventive checks (overhaul) of facilities and equipment (151, 152, 153) are used to diagnose abnormalities of facilities and equipment (151, 152, 153). ) Can improve the reliability of the results of preventive checks.

The operator station 110 is the actual operation data according to the actual field and local operating conditions of facilities and equipment of offshore structures such as ships or offshore plants. Can be generated and transmitted to the driving condition storage server 120 at a later stage. As an embodiment, the driver station 110 may form operation data based on the preventive inspection result data of the facilities and equipment 151, 152, and 153, wherein the preventive inspection result data is the facility and equipment 151 , 152, 153), obtained during preventive inspection through disassembly of the bearing, crank deflection, shaft wear, cylinder liner wear, and piston ring groove. It may include at least one of the information about, but the preventive check result data is not limited thereto.

For example, the operator station 110 is a control and control system of facilities and equipment (151, 152, 153) installed in a ship or land control room, or facilities and equipment (151, 152) operated by the operator 111 , 153).

The driving condition storage server 120 may store driving data transmitted from the driver station 110 in real time and transmit it to the dynamic simulator 130 and the automation controller 140 at the rear stage.

The dynamic simulator 130 may receive operation data from the operation condition storage server 120 and perform a simulation operation of the facilities and equipment 151, 152, and 153 constructed as a virtual model to analyze the simulation process value.

As an embodiment, the dynamic simulator 130 is the same or similar to the actual process of the facilities and equipment (151, 152, 153), the degree of plugging of the pipe, the degree of contamination of the heat exchanger, the degree of cavitation of the centrifugal pump, A virtual model can be built by simulating the degree of valve leakage.

For example, the dynamic simulator 130 includes facilities and equipment, that is, a field device 151, a compressor, a pump, a heat exchanger, an expander, a gas turbine, a valve, Mathematical analysis and thermal balance and mass balance according to fluctuations in operating conditions while performing operation simulation for a specific period of time for equipment such as vessels 152, fittings or transmitters 153 Through (heat and mass balance) analysis, the performance of operating facilities and equipment 151, 152, and 153 can be measured (S151).

The automation controller 140 actually operates the facilities and equipment 151, 152, 153 according to the operation data from the operation condition storage server 120, and monitors the facilities and equipments 151, 152, 153, respectively. Through 160), actual process values of facilities and equipment 151, 152, and 153 according to actual operation may be received, and the received actual process values may be transmitted to the AMS 170.

As an embodiment, the automation controller 140 may include at least one of an Integrated Control and Safety System (ICSS), an Integrated Automation System (IAS), and an Alarm Monitoring System (AMS). have. For example, the AMS 170 may be configured to be integrated with the automation controller 140, or may be configured to be separated from the automation controller 140 as a separate configuration.

For example, the automation controller 140 determines whether the process temperature, pressure, or flow rate of the facilities and equipment 151, 152, 153 is normally controlled, whether an alarm is generated, and the possibility of a shutdown It may be transmitted to the station 110 so that the operator 111 can recognize it.

As an embodiment, the AMS (Alarm Monitoring System) 170 is detected by the simulation process value calculated by the simulation operation of the dynamic simulator 130 and the sensor 160 of the facilities and equipment 151, 152, 153 By comparing the actual process values obtained, the gap is analyzed to diagnose whether the facility and equipment 151, 152, 153 is abnormal, and whether the sensor 160 is abnormal.

In addition, the AMS 170 analyzes the change trend of the actual process value accumulated over a long period of time, and based on the increase or decrease of the operating time of the facilities and equipment (151, 152, 153) and the preventive inspection result data acquired during the last preventive inspection. Information can be formed for the next preventive inspection cycle. As an embodiment, the AMS 170 may set the next preventive inspection period ahead of the initially expected preventive inspection period when the operating time of the facilities and equipment 151, 152, 153 increases, and the facility and equipment If the operating time of (151, 152, 153) decreases, the next preventive inspection period can be set to be delayed compared to the originally expected preventive inspection period. However, the method of setting the next preventive inspection period of the AMS 170 is not limited thereto, and the next preventive inspection period of the facilities and equipment 151, 152, and 153 may be set in various ways.

As an embodiment, the dynamic simulator 130 calculates an allowable simulation process value within the normal operation range of the facilities and equipment 151, 152, and 153 under a specific condition, and the AMS 170 calculates a normal process value of the actual process value. By analyzing whether the operation range exceeds the simulation process value, it is possible to diagnose whether the facilities and equipment 151, 152, 153 operate normally, whether mechanical coupling has occurred, and whether the sensor 160 is normally measured.

The dynamic simulator 130 includes a process temperature of a heat exchanger, a compressor, a pressure of a pump and a pipe, a flow rate of a pipe and a valve, an amount of power consumption, a motor RPM (rate per minute) of a gas turbine, whether the control valve position is normally controlled, and an alarm. It is possible to measure the performance of the facilities and equipments 151, 152, 153 and the sensor 160 by analyzing the possibility of occurrence and whether a shutdown has occurred.

2 is a flowchart showing a procedure of a diagnosis method by an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator according to an embodiment of the present invention. Although process steps, method steps, algorithms, and the like have been described in a sequential order in the flowchart of FIG. 2, such processes, methods, and algorithms may be configured to operate in any suitable order. In other words, the steps of the processes, methods and algorithms described in the various embodiments of the present invention need not be performed in the order described in the present invention. Further, although some steps are described as being performed asynchronously, in other embodiments, some of these steps may be performed simultaneously. Further, the illustration of the process by depiction in the drawings does not imply that the illustrated process excludes other changes and modifications thereto, and the illustrated process or any of its steps are among the various embodiments of the present invention. It does not imply that it is essential to one or more, and does not imply that the illustrated process is desirable.

As shown in Fig. 2, in step S210, actual driving data is generated. For example, referring to Figure 1, the driver station 110, the actual operation data according to the actual site and local operating conditions of the facilities and equipment (151, 152, 153) of an offshore structure such as a ship or offshore plant. Can be generated.

In step S215, operation data is formed based on the preventive inspection result data of facilities and equipment. For example, referring to FIG. 1, the driver station 110 may form driving data based on the preventive inspection result data of the facilities and equipment 151, 152, and 153, where the preventive inspection result data is, Bearing wear, crank deflection, shaft wear, cylinder liner wear, and piston ring grooves acquired during preventive inspection through disassembly of facilities and equipment (151, 152, 153) Piston Ring Groove) may include at least one of the information, but is not limited thereto.

In step S220, the driving data is stored in real time. For example, referring to FIG. 1, the driving condition storage server 120 may store driving data transmitted from the driver station 110 in real time and transmit it to the dynamic simulator 130 and the automation controller 140 at the rear stage. have.

In step S230, a virtual model is built. For example, referring to FIG. 1, the dynamic simulator 130 receives operation data from the operation condition storage server 120 to form a virtual model for the operation conditions of the facilities and equipment (151, 152, 153). I can. As an embodiment, the dynamic simulator 130 determines the degree of pipe plugging, the degree of contamination of the heat exchanger, the degree of cavitation of the centrifugal pump, and the degree of leakage of the valve, which is the same or similar to the actual process of the facilities and equipment 151, 152, and 153. It can be simulated to build a virtual model. However, information used by the dynamic simulator 130 when constructing a virtual model is not limited thereto.

In step S240, facilities and equipment are operated in a simulation. For example, referring to FIG. 1, the dynamic simulator 130 can simulate a virtual model of facilities and equipment 151, 152, and 153 formed using operation data transmitted from the operation condition storage server 120. have.

In step S250, the simulation process value according to the simulation operation of the virtual model is analyzed. For example, referring to FIG. 1, the dynamic simulator 130 may analyze a simulation process value formed by a simulation operation of a virtual model of the facilities and equipment 151, 152, and 153. As an embodiment, in step S255, the dynamic simulator 130 includes equipment and equipment, that is, field devices 151, equipment 152 such as compressors, pumps, heat exchangers, expanders, gas turbines, valves, and piping, Measuring the performance of operating facilities and equipment (151, 152, 153) through mathematical analysis and thermal balance and mass balance analysis according to fluctuations in operating conditions while performing operation simulation for fittings or transmitters 153 for a specific time. can do.

In step S260, an actual process value is received. For example, referring to FIG. 1, the automation controller 140 actually operates the facilities and equipment 151, 152, and 153 according to the operation data from the operation condition storage server 120, and The actual process values of the facilities and equipment 151, 152, and 153 according to actual operation may be received through the sensor 160 that monitors the 152, 153, respectively, and transmitted to the AMS 170.

In step S270, the simulated process value and the actual process value are compared. For example, referring to FIG. 1, the AMS 170 includes a simulation process value calculated by the simulation operation of the dynamic simulator 130 in step S250, and the sensors of the facilities and equipment 151, 152, and 153 in step S260. The actual process value detected by 160 can be compared.

In step S280, it is diagnosed whether there is an abnormality in the facility and equipment and whether the sensor is abnormal. For example, referring to FIG. 1, the AMS 170 compares the simulated process value and the actual process value, analyzes the gap, and determines whether the facility and equipment 151, 152, 153 are abnormal, and the sensor 160 ) Can be diagnosed.

3 is a diagram illustrating a modification of the intelligent diagnosis system for operation of facilities and equipment by the dynamic simulator of the offshore structure of FIG. 1.

2 and 3, the dynamic simulator 130 receives and applies the possible environmental condition data of the ship operating area or the offshore plant installation area from the Meteorological Administration server 180, and applies it to a virtual model under various environmental conditions. By performing a simulation operation to which a stress test is applied, analyzing the design life of facilities and equipment (151, 152, 153) and analyzing depreciation, predicting the maintenance cycle at the time of need for maintenance, and optimal performance of facilities and equipment. You can try to keep it.

In addition, the dynamic simulator 130 may measure the amount of power consumed during the simulation operation of the modeled and constructed facilities and equipment 151, 152, and 153 to calculate the optimized energy consumption and apply it to the automation controller 140. .

4 is a flowchart showing a procedure of a diagnosis method by an intelligent diagnosis system for operation of equipment and equipment by a dynamic simulator according to an embodiment of the present invention. As an embodiment, the procedure of the diagnosis method by the intelligent diagnosis system of equipment and equipment operation by the dynamic simulator shown in the flow chart of FIG. 4 may be performed after step S280 of the diagnosis method shown in the flow chart of FIG. 2.

As shown in FIG. 4, in step S290, the change trend of the actual process value is analyzed. For example, referring to FIGS. 1 to 3, the AMS 170 is an actual field accumulated over a long period of time at the actual site and local of the facilities and equipment 151, 152, and 153 of an offshore structure such as a ship or an offshore plant. It is possible to analyze the trend of the process value change. That is, the automation controller 140 actually operates the facilities and equipment (151, 152, 153) according to the operation data from the operation condition storage server 120, and monitors the facilities and equipment (151, 152, 153), respectively. The actual process values of facilities and equipment (151, 152, 153) according to actual operation are received through the sensor 160 and transmitted to the AMS 170, and the AMS 170 accumulates and stores these actual process values. Data for analysis of the change trend of the process value can be provided.

In step S300, information on the next preventive inspection cycle is formed based on the increase or decrease of the operating time of the facility and equipment and the preventive inspection result data acquired during the last preventive inspection. For example, referring to FIGS. 1 to 3, the AMS 170 includes data on an increase or decrease in operating time of facilities and equipment, and a preventive check result obtained during the last preventive check based on the change trend analysis result of the actual process value. Based on the data, information about the next preventive maintenance cycle can be formed. As an embodiment, the AMS 170 may set the next preventive inspection period ahead of the initially predicted preventive inspection period when the operating time of the facility and equipment increases, and when the operating time of the facility and equipment decreases The next preventive inspection cycle can be set to be delayed compared to the initially predicted preventive inspection cycle.

Although the method has been described through specific embodiments, the method can also be implemented as computer-readable code on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tapes, floppy disks, and optical data storage devices. Further, the computer-readable recording medium is distributed over a computer system connected through a network, so that computer-readable codes can be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing the above embodiments can be easily inferred by programmers in the technical field to which the present invention belongs.

In the above, the present invention has been described with reference to the embodiments shown in the drawings. However, the present invention is not limited thereto, and various modifications or other embodiments falling within the scope equivalent to the present invention are possible by those of ordinary skill in the art. Therefore, the true scope of protection of the present invention should be determined by the claims that follow.

111: operator 110: operator station
120: operation condition storage server 130: dynamic simulator
140: automation controller 151: field device
152: equipment 153: transmitter
160: sensor 170: AMS
180: Meteorological Administration server

Claims (9)

A driver station for forming operation data according to on-site operating conditions of equipment and equipment of a ship or offshore plant;
A driving condition storage server for storing the driving data formed in the driver station in real time;
A dynamic simulator for constructing a virtual model of the facility and equipment using the operation data, and analyzing a simulated process value by performing a simulated operation;
An automation controller that actually operates the equipment and equipment according to operation data from the operation condition storage server, and receives an actual process value according to the actual operation through a sensor that monitors the equipment and equipment; And
Comprising an Alarm Monitoring System (AMS) that compares the simulated process value with the actual process value and diagnoses whether the facility or equipment is abnormal and whether the sensor is abnormal according to mutual differences,
The driver station forms the driving data based on the preventive inspection result data of the facility and equipment,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The above preventive check result data,
Bearing wear, crank deflection, shaft wear, cylinder liner wear, and piston ring grooves acquired during preventive inspection through disassembly of the above facilities and equipment Containing at least one of the information,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The AMS is,
Analyzing the change trend of the actual process value, and forming information on the next preventive inspection cycle based on the increase or decrease of the operating time of the facility and equipment and the preventive inspection result data obtained during the last preventive inspection,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The dynamic simulator,
Calculates the allowable simulated process value within the normal operation range of the facility and equipment, and the AMS analyzes whether the actual process value exceeds the simulated process value of the normal operation range, Diagnosing whether mechanical coupling has occurred and whether the sensor is normally measured,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The dynamic simulator,
Mathematical analysis and fluctuations in the above operating conditions while performing operation simulation for a specific period of time for equipment, fittings, or transmitters including any one or more of field devices, compressors and pumps, heat exchangers, expanders, gas turbines, valves, and piping. Through analysis of the heat and mass balance according to the following, the performance of facilities and equipment in operation is measured,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 5,
The dynamic simulator,
To measure the performance by analyzing the possibility of normal control of the process temperature, pressure, flow rate, power consumption, motor RPM, and control valve position of the facility and equipment, whether an alarm occurs, and whether a shutdown occurs.
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The automation controller,
Including at least one of ICSS (Integrated Control and Safety System), IAS (Integrated Automation System) and AMS (Alarm Monitoring System),
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 1,
The dynamic simulator,
By applying the possible environmental condition data of the vessel operating sea or the offshore plant installation sea, a simulated operation with stress tests applied to the virtual model under various environmental conditions is performed, analyzing the design life of facilities and equipment, and analyzing the depreciation. , To predict the maintenance cycle,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures. The method of claim 8,
The dynamic simulator,
By measuring the amount of power consumed during the simulated operation of the facility and equipment that has been modeled and constructed, the optimized energy consumption power is calculated and applied to the automation controller,
Intelligent diagnosis system for facility and equipment operation by dynamic simulator of offshore structures.

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