WO2019171777A1 - プラント監視システムのシミュレーション装置 - Google Patents

プラント監視システムのシミュレーション装置 Download PDF

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Publication number
WO2019171777A1
WO2019171777A1 PCT/JP2019/001451 JP2019001451W WO2019171777A1 WO 2019171777 A1 WO2019171777 A1 WO 2019171777A1 JP 2019001451 W JP2019001451 W JP 2019001451W WO 2019171777 A1 WO2019171777 A1 WO 2019171777A1
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WIPO (PCT)
Prior art keywords
area
gas cloud
camera
unit
monitoring
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Ceased
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PCT/JP2019/001451
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English (en)
French (fr)
Japanese (ja)
Inventor
紗織 平田
橋野　弘義
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Konica Minolta Inc
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Konica Minolta Inc
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Priority to JP2020504833A priority Critical patent/JP7255583B2/ja
Publication of WO2019171777A1 publication Critical patent/WO2019171777A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T19/00—Manipulating three-dimensional [3D] models or images for computer graphics
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • the present invention relates to a simulation apparatus for a plant monitoring system.
  • Patent Document 1 discloses a three-dimensional display system capable of displaying wide-area map information and information on structures included in the map information.
  • Patent Document 2 an actual device constituting a plant facility is displayed as a three-dimensional image in accordance with the shape and arrangement of the actual device, so that an operator can easily grasp the state of the plant.
  • a display system that can be used is disclosed.
  • Patent Documents 1 and 2 have a problem that an image of a structure model that takes into account environmental information in which the structure is provided is not displayed.
  • An object of the present invention is to provide a plant monitoring system simulation apparatus capable of presenting monitoring information suitable for customer needs.
  • a simulation apparatus for a plant monitoring system includes: An environment model generation unit that generates an environment model including display data for schematically displaying an environment that changes over time; A structure model generation unit that generates a structure model including display data for schematically displaying the structure of the plant provided in the environment; A display unit configured to display the environment model generated by the environment model generation unit and the structure model generated by the structure model generation unit.
  • monitoring information suitable for customer needs can be presented.
  • the figure which shows roughly an example of the structure model imitating the structure of a plant The figure which shows schematically the structure of the simulation apparatus of the plant monitoring system in embodiment of this invention.
  • Diagram for explaining the principle of gas cloud detection Diagram showing an example of a false detection factor model Diagram showing an example of a false detection factor model
  • Flow chart showing processing of environmental model etc. in simulation device The figure which shows schematically a part of structure of the simulation apparatus of the plant monitoring system in a modification. Flow chart showing processing of environmental model etc. in simulation device
  • FIG. 1 is a diagram schematically showing an example of a structure model 120 simulating a plant structure.
  • the structure model 120 includes display data for schematically displaying a structure of a plant for purifying and liquefying natural gas, for example.
  • the structure model 120 includes, for example, a receiver tank 121, a service tank 122, a molecular sieve tower 123, an activated carbon tower 124, a regeneration gas heater 125, a regeneration gas cooling tower 126, and a plurality of pipes 127 connecting them. ing.
  • the pipes 127 are represented by different line types (solid lines and broken lines) in FIG.
  • FIG. 1 shows a camera 10 provided at a virtual position.
  • FIG. 2 is a diagram schematically showing a configuration of the simulation apparatus 100 of the plant monitoring system in the embodiment of the present invention.
  • the simulation apparatus 100 includes a structure model generation unit 101, an environment model generation unit 102, a storage unit 110, an input unit 140 (corresponding to the “camera position input unit” of the present invention), a display unit 150, A setting calculation unit 160, a structure information acquisition unit 171, and an environment information acquisition unit 172 are provided.
  • the setting calculation unit 160 includes a gas cloud generation area setting unit 161, a risk level setting unit 162, a monitoring area creation unit 163, and a calculation unit 164.
  • the simulation apparatus 100 includes a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a touch panel, a display, and a speaker, which are connected to each other via a bus.
  • the CPU is a control circuit composed of a microprocessor or the like that executes control of each unit and various arithmetic processes according to a program.
  • the functions of the above-described units of the simulation apparatus 100 are exhibited when the CPU executes a corresponding program.
  • the ROM includes, for example, a nonvolatile semiconductor memory and a large-capacity magnetic disk device, and stores three-dimensional data, content data, and a control processing program.
  • the structure information acquisition unit 171 acquires information (for example, photographs and map information) regarding the plant structure.
  • the environmental information acquisition unit 172 acquires on-site inspections, aerial photography / satellite images, and environmental information from local people.
  • Environmental information is year-round information.
  • the environmental information includes environmental information that affects detection of a gas cloud that can be generated (leaked) from the structure.
  • the environmental information includes the surrounding environment of the structure and the natural environment.
  • the surrounding environment includes the sea, roads, railways, surrounding factories, miscellaneous forests, mountains, trees and ground in the plant site (asphalt, lawn, soil, sand (dust)).
  • the natural environment includes sunlight (luminance, temperature), climate, and weather information (fog, rain, snow, wind).
  • the structure model generation unit 101 generates a structure model 120 based on information related to plant structures.
  • the structure model generation unit 101 extracts parameters (photographing position and photographing direction) of the camera 10 (visible light camera 10A and infrared camera 10B shown in FIG. 1) used for photographing from the photograph information.
  • the structure model generation unit 101 generates a three-dimensional structure model 120 from photographs taken from different directions and parameters of the camera 10.
  • the storage unit 110 stores the structure model 120.
  • the environment model generation unit 102 generates an environment model 130 including display data for schematically displaying the environment of the structure based on the environment information.
  • the storage unit 110 stores the environment model 130.
  • the environmental model 130 in order to make the following explanation easy to understand, as an example of the environmental model 130, explanation will be given by taking sunlight, the ground, and the climate.
  • the environmental model generation unit 102 includes a false detection factor model generation unit 103.
  • the false detection factor model generation unit 103 generates a false detection factor model 131 that affects the detection of a gas cloud that can be generated (leaked) from the structure.
  • the storage unit 110 stores a false detection factor model 131.
  • the erroneous detection factor model 131 includes the luminance of the visible image of the background of the gas leakage source (gas generating unit, for example, the pipe 127).
  • the luminance of the visible image of the background of the gas leakage source is sunlight, artificial light source, sea, reflected light from buildings, phenomena similar to gas (water vapor, clouds), dust, swaying trees and lawn.
  • Each includes the luminance of the visible image that is the background of the gas leak source.
  • the gas cloud to be detected such as methane cannot be seen. Therefore, the visible image is used by being superimposed with the infrared image in order to make the gas leakage source easy to understand.
  • the visible image of the gas leakage source (gas generating unit) is a visible image of a predetermined gas leakage source model.
  • the luminance of the visible image of the gas leakage source is a predetermined luminance.
  • the infrared camera 10B for detecting the gas cloud is not provided.
  • the infrared camera 10B is provided at a virtual position.
  • the principle of gas cloud detection by the infrared camera 10B will be described with reference to FIG.
  • the gas cloud absorbs part of the emitted infrared light depending on the background temperature.
  • FIG. 3 shows an infrared ray amount V (Tb) emitted from the background, an infrared ray amount absorbed by the gas cloud as ⁇ V (Tb), and an infrared ray amount V (Tg) emitted from the gas cloud.
  • V (T) is the black body radiance at the absolute temperature T (K).
  • the gas cloud has an infrared ray amount V (Tb) emitted from the background, an infrared ray amount (1- ⁇ ) V (Tb) emitted from the background and transmitted through the gas cloud, and an infrared ray amount V (Tg) emitted from the gas cloud. ) Is detected based on the difference from the total amount. Therefore, the range of the gas cloud detection includes a background temperature image that is an image based on the infrared amount V (Tb) and a gas cloud that is an image based on the infrared amount ((1 ⁇ ) V (Tb) + V (Tg)). It is defined as an image obtained by extracting a difference from the image.
  • the false detection factor model 131 includes the brightness (thermal information) of the infrared image of the background of the gas cloud.
  • the brightness (thermal information) of the infrared image of the background of the gas cloud is the brightness (thermal information) of sunlight, the artificial light source, the infrared image with the artificial heat source as the background, and the background whose temperature changes due to the wind. Infrared image brightness (thermal information) is included. If the difference between the brightness (thermal information) of the infrared image of the background of the gas cloud and the brightness (thermal information) of the infrared image of the gas cloud is equal to or less than a predetermined threshold, the gas cloud may be erroneously detected. .
  • the infrared image of the gas cloud is an infrared image of a predetermined gas cloud model. Further, the luminance (thermal information) of the infrared image of the gas cloud is a predetermined luminance (temperature).
  • the gas cloud generation area setting unit 161 sets a gas cloud generation possibility area which is a region where there is a possibility that a gas cloud is generated. Specifically, the gas cloud generation area setting unit 161 sets the pipe 127 as a gas cloud generation possibility area.
  • the input unit 140 is used for setting the gas cloud generation possibility area.
  • the storage unit 110 stores a gas cloud generation possibility area.
  • the pipe 127 will be described as an example of the gas cloud generation possibility area.
  • the risk level setting unit 162 sets a risk level indicating the high possibility that a gas cloud is generated in the gas cloud generation possibility area (plurality of pipes 127) based on a predetermined condition.
  • the input unit 140 is used to set the risk level.
  • the predetermined conditions include, for example, the service life (life), actual service life, material (material of piping 127), purpose of use (type of gas), installation status of piping 127 (outdoor, indoor), corrosion status, And a deterioration state is included.
  • the storage unit 110 stores the degree of risk.
  • the monitoring area creation unit 163 creates a monitoring setting area for monitoring the gas cloud based on the misdetection factor model 131, the gas cloud generation possibility area (plurality of pipes 127), and the risk level.
  • the risk level setting unit 162 sets the gas cloud generation possibility area (plurality of pipes 127) to the same risk level.
  • the monitoring area creation unit 163 creates a monitoring setting area based on the pipes 127 having a high risk level.
  • FIG. 4 An example of the erroneous detection factor model 131 shown in FIG. 4 includes a building wall 128A in the background of a gas cloud.
  • FIG. 4 shows an infrared camera 10B provided at a virtual position.
  • the wall surface 128A of the building is shown as a place where sunlight does not hit.
  • the difference in luminance (thermal information) between the infrared image of the gas cloud and the infrared image of the wall 128A becomes slight. . Thereby, it becomes difficult to detect the gas cloud, and the gas cloud may be erroneously detected.
  • the monitoring area creation unit 163 When the difference in luminance (thermal information) between the infrared image of the gas cloud and the infrared image of the wall surface 128A is equal to or less than a predetermined threshold, the monitoring area creation unit 163 has a gas leakage source whose background is the wall surface 128A. As a misdetection area 128 (see FIG. 1).
  • FIG. 5 is an example in which the tree 128B is included in the background of the gas cloud.
  • FIG. 5 shows an infrared camera 10B provided at a virtual position.
  • the difference in luminance (thermal information) between the infrared image of the gas cloud and the infrared image of the tree 128B is slight, It is difficult to detect.
  • a method of extracting a gas cloud region from a background region as a moving body region is used (for example, a frame difference method). In this method, when the background tree 128B is shaken by a wind or the like, it is difficult to extract the gas cloud region, so that it becomes more difficult to detect the gas cloud.
  • the monitoring area creation unit 163 excludes the pipe 127 as a gas leakage source with the tree 128B as a background from the monitoring setting area as the erroneous detection area 128 (see FIG. 1).
  • the calculation unit 164 calculates a change in the display data of the background of the gas cloud in the effective monitoring area that is the monitoring setting area that can be seen from the camera 10 based on the false detection factor model 131.
  • the false detection factor model 131 is environmental information (sun position, ground, climate) that changes with the passage of time.
  • the change in the display data of the background of the gas leakage source is a change in the visible image that becomes the background of the gas leakage source.
  • the change in the display data of the gas cloud background is a change in the infrared image that becomes the background of the gas cloud.
  • the operator uses the input unit 140 for the installation location, the number of cameras 10 installed, the model (fixed type, pan-tilt type), the operation schedule, the monitoring direction, and the like of the camera 10 (visible light camera 10A, infrared camera 10B). Is input.
  • FIG. 6 is a diagram showing an image of the background of the gas cloud in the effective monitoring area as seen from the left camera 10 in FIG.
  • FIG. 7 is a diagram showing an image of the background of the gas cloud in the effective monitoring area as seen from the right camera 10 in FIG.
  • the display unit 150 displays changes in the background image (visible image) of the gas leakage source and the background image (infrared image) of the gas cloud in the effective monitoring area visible from the camera 10 provided at the installation position (FIG. 6). And FIG. 7). Further, the display unit 150 displays a gas leak source image (visible image of a predetermined gas leak source model) and a gas cloud image 129 (preliminary) in the gas cloud generation possibility area (pipe 127) in the effective monitoring area. An infrared image of a defined gas cloud model) is displayed. Moreover, the display part 150 displays the misdetection area 128, as shown in FIG. 6 and FIG. By displaying the erroneous detection area 128, it can be shown to the customer that it is meaningful to consider the necessity of installing a monitoring device other than the camera 10.
  • FIG. 8 is a flowchart showing processing of the environment model 130 and the like in the simulation apparatus 100.
  • This process includes the process of generating the structure model 120 and the environment model 130. If the structure model 120 and the environment model 130 are stored in the storage unit 110 in advance, the structure model 120 is stored. And the like. The generation process may not be included.
  • step S100 the structure model generation unit 101 generates a structure model 120 based on information related to the plant structure.
  • the storage unit 110 stores the structure model 120.
  • step S110 the environment model generation unit 102 generates the environment model 130 based on the environment information of the structure.
  • the storage unit 110 stores the environment model 130.
  • step S120 the erroneous detection factor model generation unit 103 generates an erroneous detection factor model 131 that affects the detection of the gas cloud.
  • the storage unit 110 stores a false detection factor model 131.
  • step S130 the gas cloud generation area setting unit 161 uses the input unit 140 to set a gas cloud generation possibility area (a plurality of pipes 127).
  • the storage unit 110 stores a gas cloud generation possibility area.
  • step S140 the operator uses the input unit 140 to set the degree of danger that a gas cloud is generated.
  • step S150 the monitoring area creation unit 163 creates a monitoring setting area based on the erroneous detection factor model 131, the gas cloud generation possibility area, and the risk level.
  • step S160 the operator uses the input unit 140 to input the installation position of the camera 10 (visible light camera 10A, infrared camera 10B).
  • the camera 10 visible light camera 10A, infrared camera 10B.
  • step S170 the display unit 150 displays an effective monitoring area that can be seen from the camera 10 provided at the installation position. At this time, the display unit 150 displays the gas cloud in the gas cloud generation possibility area.
  • the environment model 130 including display data for schematically displaying the environment that changes with the passage of time is stored, and the plant structure provided in the environment is schematically illustrated.
  • a gas cloud generation area setting unit 161 that sets a gas cloud generation possibility area (pipe 127), which is an area where gas clouds may be generated, and an error that affects detection of gas clouds that can be generated from a structure.
  • a monitoring area creation unit 163 that creates a monitoring setting area based on the detection factor model 131 and the gas cloud generation possibility area. Accordingly, it is possible to increase the effectiveness of monitoring by intentionally removing areas that are erroneously detected from the monitoring target.
  • the monitoring area creation unit 163 creates a monitoring setting area based on the risk level. This makes it possible to preferentially monitor an area with a high degree of risk, thereby further enhancing the effectiveness of monitoring.
  • an input unit 140 for inputting the installation position of the camera 10 is provided, and the display unit 150 displays an effective monitoring area visible from the camera 10 provided at the installation position.
  • the effective monitoring area includes a gas cloud generation possibility area (pipe 127), an erroneous detection area 128, and a gas cloud image 129. Thereby, it becomes possible to examine how the gas cloud looks with the camera 10. In addition, it is possible to examine the presence or absence of the influence of the surrounding environment or the like in the detection of the gas cloud.
  • the operator determines the installation position of the camera 10 (visible light camera 10A, infrared camera 10B) using the input unit 140.
  • the simulation apparatus 100A in the modified example automatically Stipulated in
  • FIG. 9 is a diagram schematically showing a part of the simulation apparatus 100A.
  • the setting calculation unit 160A in the simulation apparatus 100A includes a camera position setting unit 165, a position candidate extraction unit 166, and an effective position calculation unit 167.
  • the camera position setting unit 165 sets the installation position of the camera 10 based on a predetermined condition.
  • the predetermined condition is that the installation position of the camera 10 is provided at a predetermined interval (for example, 1 m) along the pipe 127.
  • the position candidate extraction unit 166 extracts an installation position candidate of the camera 10 from the installation position of the camera 10 based on the effective monitoring area and the blind spot area that can be seen from the camera 10 provided at the installation position.
  • the blind spot area is an area that cannot be seen from the camera 10 and is obstructed by the structure model 120 on the near side of the optical axis direction of the camera 10 (the lower side in the drawing shown in FIG. 1). This is an area where a gas cloud on the back side (upper side of the paper shown in FIG. 1) cannot be detected.
  • the position candidate extraction unit 166 extracts the installation position candidates in the order of the size of the effective monitoring area excluding the blind spot area.
  • the effective position calculation unit 167 calculates an effective position from among the installation position candidates so that the cost effectiveness is high and the coverage of the monitoring setting area is high.
  • the display unit 150 displays an effective monitoring area that is visible from the camera 10 (visible light camera 10A, infrared camera 10B) provided at the effective position.
  • cost effectiveness refers to the size of the effective monitoring area with respect to the installation cost of the camera 10.
  • coverage ratio of the monitoring setting area refers to the ratio of the effective monitoring area that can be seen from the camera 10 provided in the installation position candidate to all the planned monitoring setting areas (for example, the length of the pipe 127).
  • FIG. 10 is a flowchart showing processing of the environment model 130 and the like in the simulation apparatus 100A according to the modification.
  • processing different from the above embodiment will be mainly described, and description of the same processing will be omitted.
  • step S200 to step S250 is the same as step S100 to step S150 in the above embodiment.
  • step S260 the camera position setting unit 165 sets the installation position of the camera 10.
  • step S270 the position candidate extraction unit 166 extracts the installation position candidates of the camera 10 based on the monitoring setting area and the blind spot area.
  • step S280 the effective position calculation unit 167 calculates the effective position based on the cost effectiveness and the coverage of the monitoring setting area.
  • step S290 the display unit 150 displays an effective monitoring area that can be seen from the camera 10 provided at the effective position.
  • a camera position setting unit 165 that sets the installation position of the camera 10, an effective monitoring area that can be seen from the camera 10 provided at the installation position, and a gas cloud that is seen from the camera 10 are detected.
  • a position candidate extraction unit 166 that extracts the installation position candidate of the camera 10 from the installation position of the camera 10, and an effective position calculation that calculates a cost-effective effective position from the installation position candidates Part 167.
  • the monitoring area creation unit 163 creates the monitoring setting area based on the erroneous detection factor model 131, the gas cloud generation possibility area (pipe 127), and the risk level.
  • the monitoring area creation unit 163 replaces the error detection factor model 131 or the like, or in addition to the error detection factor model 131 or the like, a difference between the temperature of the gas cloud and the background temperature (detectability). ),
  • the monitoring setting area may be created by giving priority to the magnitude of the difference. The greater the difference between the temperature of the gas cloud and the background temperature, the lower the possibility of erroneous detection of the gas cloud, so that the detection accuracy of the gas cloud can be increased.
  • the infrared image used while being superimposed on the visible image is acquired from, for example, environment information, but the present invention is not limited to this.
  • an image corresponding to an infrared image (equivalent to an infrared image) may be acquired from a visible image.
  • a color image obtained from a visible light camera is converted into a monochrome image (luminance information).
  • temperature information from the heat source is added to the monochrome image as luminance information, such as increasing the brightness where the temperature rises when the heat source such as the sun hits, and lowering the brightness where the temperature does not rise without being hit by the heat source.
  • Reference temperature information suitable for the environmental model 130 is added to the added monochrome image as luminance information.
  • a histogram indicating the luminance distribution of the monochrome image is adjusted.
  • liquefied natural gas is vaporized.
  • the plant can be applied to any plant as long as it has a possibility of gas leakage, such as a plant that performs gas leakage.

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PCT/JP2019/001451 2018-03-08 2019-01-18 プラント監視システムのシミュレーション装置 Ceased WO2019171777A1 (ja)

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Cited By (4)

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KR102618412B1 (ko) * 2023-06-07 2023-12-28 주식회사 포커스에이치엔에스 공간의 디지털 안전품질 평가정보 제공 플랫폼 시스템 및 그 방법
WO2024105951A1 (ja) * 2022-11-15 2024-05-23 コニカミノルタ株式会社 監視カメラシステム、マスク補正方法、及び、プログラム
JP2024160604A (ja) * 2023-05-01 2024-11-14 トヨタ自動車株式会社 情報処理装置
KR102929235B1 (ko) 2023-03-28 2026-02-23 ㈜케이더블유티솔루션 플랜트 시뮬레이션 방법 및 이를 위한 컴퓨터 프로그램

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JP7800154B2 (ja) * 2022-01-25 2026-01-16 コニカミノルタ株式会社 表示システム、赤外線カメラ、および表示制御方法

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JPH07282299A (ja) * 1994-04-13 1995-10-27 Toshiba Corp 表示方法及び表示装置
JP2003066825A (ja) * 2001-08-24 2003-03-05 Mitsubishi Heavy Ind Ltd 擬似体感装置

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH07282299A (ja) * 1994-04-13 1995-10-27 Toshiba Corp 表示方法及び表示装置
JP2003066825A (ja) * 2001-08-24 2003-03-05 Mitsubishi Heavy Ind Ltd 擬似体感装置

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2024105951A1 (ja) * 2022-11-15 2024-05-23 コニカミノルタ株式会社 監視カメラシステム、マスク補正方法、及び、プログラム
KR102929235B1 (ko) 2023-03-28 2026-02-23 ㈜케이더블유티솔루션 플랜트 시뮬레이션 방법 및 이를 위한 컴퓨터 프로그램
JP2024160604A (ja) * 2023-05-01 2024-11-14 トヨタ自動車株式会社 情報処理装置
JP7827006B2 (ja) 2023-05-01 2026-03-10 トヨタ自動車株式会社 情報処理装置
KR102618412B1 (ko) * 2023-06-07 2023-12-28 주식회사 포커스에이치엔에스 공간의 디지털 안전품질 평가정보 제공 플랫폼 시스템 및 그 방법

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