Human error prevention training equipment, software architecture, building method and training method

Abstract

The invention provides a human error prevention training device, a software architecture, a building method and a training method. The human error prevention training device comprises a plurality of training panels. Each training panel comprises a panel and a plurality of training assemblies. And the plurality of training components are integrated with digital display screens for displaying codes or names. An arithmetic unit is mounted on the panel. The panel is provided with a plurality of input and output ports supporting hot plugging. The plurality of input and output ports are respectively used for the connection between different training panels, the connection between the panel and the training assembly, the connection between the panel and the computer console, and the connection between the panel and the output device. And the panel is connected with the computer console through a data bus connected with the input / output port. According to the application, the extensible panel carrying the arithmetic unit is used to connect various training components, so as to solve the technical problems that the existing equipment or system is designed only for the specific training function of a single scene, and only new training equipment can be developed for other training requirements.

Description

Technical Field

[0001] The present application belongs to the field of nuclear power technology, and specifically relates to a human error prevention training device, software architecture, construction method and training method. Background Art

[0002] Safety is the lifeline of the nuclear industry, and mistakes made by nuclear power plant staff may lead to significant losses. In other words, human error is one of the important causes of nuclear power plant accidents. Effective prevention of human error is of great significance to the efficient and safe operation of nuclear power. Training on preventing human error is an effective way to improve the awareness, understanding and mastery of human error prevention skills of nuclear power plant personnel.

[0003] Traditional human error prevention training equipment is mostly based on actual equipment restoration, which is costly and has great limitations. In order to reduce training costs and improve training efficiency, many new types of human error prevention training equipment or systems have been used in actual training, such as behavioral standard training teaching aids for preventing human errors using valve matrix (CN201520071094.1), behavioral standard training teaching aids for preventing human errors using electric switch matrix (CN201520071126.8), electrical training device for preventing human errors (CN201810605489.3), a nuclear power plant instrumentation and control training device for preventing human errors (CN201810524733.3), and some scenario-based and automated training systems, such as a VR-based nuclear power plant human error prevention training system, platform and method (CN202111475481.8, CN202223292763.7), and a human error prevention training system based on lidar and projection technology (CN202311690950.7).

[0004] However, the above-mentioned equipment or system is only designed for a specific training function in a single scenario, and new training equipment can only be developed separately for other training needs in nuclear power plants. Although the equipment based on VR technology disclosed in CN202223292763.7 can develop various training scenarios and functions, neither CN202111475481.8 nor CN202223292763.7 discloses corresponding rapid development methods. Although there are technical inventions that have achieved the scalability of training scenarios and functions based on VR, new scenarios and functions still require time-consuming and labor-intensive development, and VR technology cannot achieve the realism of the operating experience in actual applications, and has certain limitations. Summary of the invention

[0005] In view of this, the present application is committed to providing a human error prevention training device, software architecture, construction method and training method, by using an expandable panel equipped with a computing unit to connect various training components, so as to solve the technical problem that existing equipment or systems are only designed for specific training functions of a single scenario, and new training equipment can only be developed separately for other training needs in nuclear power plants.

[0006] The first aspect of the present application provides a human error prevention training device, which includes multiple training panels, each of which includes a panel and multiple training components connected to the panel. Multiple training components are integrated with a digital display screen for code or name display. The panel is equipped with a computing unit. The panel has multiple input and output ports that support hot plugging. The multiple input and output ports are respectively used for connections between different training panels, between panels and training components, between panels and computer consoles, and between panels and output devices. The panel and the computer console are connected via a data bus connected to the input and output ports. The computer console is used to issue instructions and input training programs to the human error prevention training device through the input and output ports, and collect training process information for analysis and interactive operation processing. The output device is used to output simulation scenario information.

[0007] In a specific implementation of the present application, multiple training components are divided into three types, including display components, collection components and operation components. The display component is used to simulate the actual display. The collection component is used to collect the user's action and sound information. The operation component is used to simulate the actual operation mode.

[0008] The second aspect of the present application provides a software architecture of a human error prevention training device, and the software architecture of the human error prevention training device is applicable to the human error prevention training device of the first aspect of the present application. The software architecture of the human error prevention training device includes a basic layer, a service layer, a functional layer and an application layer. The basic layer includes a system scenario library, a device model library, a virtual component library, a panel / component driver library, a module program library and a sound and picture recognition model library. The service layer includes system scenario call definition, device model call definition, component hot plugging, component automatic identification, logic diagram programming and sound and picture data identification. Component hot plugging and component automatic identification are implemented based on the panel / component driver library, logic diagram programming is implemented based on the module program library, and sound and picture data identification is implemented based on the sound and picture recognition model. The functional layer includes training project creation and editing, rule creation and editing, system scenario creation and editing, device model creation and editing and project management and analysis. The application layer includes multi-scenario human error prevention training, rapid construction of training scenarios, training simulation scenario perception, training data statistical analysis and training process management.

[0009] The third aspect of the present application provides a method for building an anti-human error training device, and the method for building an anti-human error training system includes: according to the requirements of the training project, sorting out the training scenarios and training function requirements, and decomposing them into operation requirements and feedback form requirements; selecting multiple training components in the anti-human error training device according to the operation requirements and feedback form requirements, and completing the construction of the training panel in combination with the panel and multiple training components; completing the logic construction on the control platform according to the operation requirements and feedback form requirements, that is, editing the training projects and rules; after the editing is completed, anti-human error training can be carried out, and based on the preset projects and rule programs, the training panel displays the response results generated by the operation during the training process.

[0010] The fourth aspect of the present application provides a method for preventing human errors, which is implemented by a user operating on a control platform of a training device for preventing human errors, the control platform of the training device for preventing human errors being connected to the training device for preventing human errors of the embodiment of the present application, and used to implement the functions of the software architecture of the training device for preventing human errors. The control platform of the training device for preventing human errors is provided with a project rule editing interface, a scenario creation interface, and a training management and analysis interface.

[0011] The operating method of the control platform for anti-human error training includes: receiving a scene creation operation of a user on a scene creation interface; creating a training scene according to the scene creation operation of the user on the scene creation interface; connecting multiple training components corresponding to the training scene in an anti-human error training device according to the training scene; receiving a logic diagram programming operation of a user on a project rule editing interface for the training scene; creating training projects and rules based on the logic diagram programming operation of the user on the project rule editing interface for the training scene; receiving a training management and analysis operation of a user on a training management and analysis interface; conducting training on the training project according to the training management and analysis operation of the user on the training management and analysis interface, and adopting corresponding data analysis methods to conduct data analysis work.

[0012] In a specific implementation of the present application, the project rule editing interface includes an editing menu, a training project management interface, a project editing interface and a rule editing interface.

[0013] Receive the user's logical diagram programming operations for training scenarios on the project rule editing interface, including: receiving the user's new project, deletion project and naming instructions on the training project management interface; receiving the definition nodes and judgment conditions set by the user on the editing menu; receiving the user's call instructions for rules in the rule library on the training project management interface and the rule editing instructions on the rule editing interface.

[0014] Training projects and rules are created based on the user's logical diagram programming operations for training scenarios on the project rule editing interface, including: creating training projects according to the user's new project, deletion project and naming instructions on the training project management interface; defining the initialization node, success node or failure node of the training project in the project editing interface according to the definition node set by the user on the editing menu; calling the rules of the rule library in the training project management interface and adding them to the project editing interface according to the user's calling instructions on the training project management interface; creating rules by combining the rules in the rule library and the user's rule editing instructions on the rule editing interface; setting the training project process in the project editing interface according to the judgment conditions set by the user in the editing menu, or setting the conditional branches of input and output judgment in the rule editing interface.

[0015] In a specific implementation of the present application, the project rule editing interface also includes a list of connected devices.

[0016] Connect multiple training components corresponding to the training scenarios in the anti-human error training device according to the training scenarios, including: automatically identifying and classifying the connected training components on the connection device list interface according to the training scenarios; connecting or changing the virtual components according to the user's virtual component addition and editing operations on the connection device list interface.

[0017] In a specific implementation of the present application, the scene creation interface includes a scene library interface, a device model editing interface and a system scenario editing interface.

[0018] Receiving the scene creation operation of the user on the scene creation interface, the method for preventing human error training also includes: receiving the scene definition operation of the user on the editing menu; calling up the scene library interface, the device model editing interface and the system scenario editing interface according to the scene definition operation of the user on the editing menu. The scene library interface has two submenus: the device model library and the system scenario library.

[0019] Receiving the scene creation operation of the user on the scene creation interface, including: receiving the calling operation of the user on the scene library interface; receiving the editing operation of the user on the device model editing interface; receiving the editing operation of the user on the system scenario editing interface.

[0020] According to the scene creation operation performed by the user on the scene creation interface, a training scene is created, including: according to the calling operation performed by the user on the scene library interface, the scene model is called from the device model library and the system scene library in the scene library interface, and the connected training component or the created virtual component is associated with the scene model; according to the editing operation performed by the user on the device model editing interface, the reference of the training component in the scene model is edited; according to the editing operation performed by the user on the system scene editing interface, the position of the training component in the system process is edited.

[0021] In a specific implementation of the present application, the training management and analysis interface includes a training project management interface, a training management and analysis menu, a training analysis function, and a project management interface. The training management and analysis menu includes training start, training pause, training stop, training data, and training analysis.

[0022] The fifth aspect of the present application provides a computer device, the computer device comprising a processor and a memory. The processor is used to execute a human error prevention training method of the fourth aspect of the present application. The memory is used to store executable instructions of the processor.

[0023] The beneficial effect of the technical solution of the present application is that: an expandable panel equipped with a computing unit is used to connect various training components, and a universal interface supporting hot plugging is used to realize the physical connection and data transmission between panels and panels, and between panels and components, so that a training panel that can be freely combined is formed based on the expandable panel equipped with a computing unit and multiple training components, so that the anti-human error training equipment has the ability to simulate different functional panels and collect information and interact in real time. The embodiment of the present application uses a modular design method to complete the design of the panel and the panel / component interface, and uses the "panel + component" design scheme and hot plug technology to realize the rapid construction of nuclear power plant training equipment. The anti-human error training equipment has extremely high scalability, can cover most of the nuclear power plant anti-human error training scenarios (such as operation, electrical, thermal hydraulics, etc.), and meet most of the requirements of nuclear power plant anti-human error training. The embodiment of the present application realizes the rapid equipment construction that meets the functional requirements of various anti-human error skill training in different nuclear power work scenarios. Compared with previous equipment and systems, the modular design makes the present application have the advantages of low cost, high efficiency and high scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The figure is a schematic diagram of the structure of a human error prevention training device provided by an embodiment of the present application during application.

[0025] Figure 2 Shown is a structural schematic diagram of a training panel in a human error prevention training device provided in an embodiment of the present application.

[0026] Figure 3 Shown is a schematic diagram of a software architecture of a human error prevention training device provided in an embodiment of the present application.

[0027] Figure 4 The figure is a simplified flowchart of a method for building a human error prevention training device provided in one embodiment of the present application.

[0028] Figure 5 The figure is a schematic diagram comparing the process of a method for building a training device for preventing human errors provided by an embodiment of the present application and a traditional building method.

[0029] Figure 6 Shown is a schematic diagram of a project rule editing interface on a control platform of an anti-human error training device provided by an embodiment of the present application.

[0030] Figure 7 Shown Figure 6 Schematic diagram of the changing status of the project rule editing interface shown.

[0031] Figure 8 Shown is a schematic diagram of a scene creation interface on a control platform of an anti-human error training device provided in one embodiment of the present application.

[0032] Fig. 9 Shown is a schematic diagram of a training management and analysis interface on a control platform of an anti-human error training device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] At least one embodiment of the present application provides a training device for preventing human errors, referring to Figure 1 and Figure 2 The anti-human error training device includes a plurality of training panels, each of which includes a panel 1 and a plurality of training components (i.e. Figure 1 Small and medium squares). Multiple training components are integrated with a digital display screen for code or name display. The panel 1 is equipped with a computing unit 5. The panel 1 has multiple input and output ports that support hot plugging. The multiple input and output ports are used for connection between different training panels, between the panel and the training components, between the panel and the computer console 6, and between the panel and the output device 8. The panel and the computer console 6 are connected through a data bus 7 connected to the input and output ports. The computer console 6 is used to issue instructions and input training programs to the anti-human error training device through the input and output ports, and collect training process information for analysis and interactive operation processing. The output device 8 is used to output simulation scenario information.

[0035] For example, the output device may be a display device. The input and output ports may be a universal interface supporting hot plugging. The input and output ports are used for connecting panels to each other, connecting panels to the computer console 6, and connecting panels to output devices. Panel 1 is an expandable panel. The training process information includes training data. The processing of the interactive operation includes the computer console determining whether the current training process is successful / failed and whether the training process continues by analyzing the input signal of the training panel. The simulation scenario information output by the output device 8 may be in the form of VR, etc.

[0036] The computer console 6 can also be used to control the start, pause, and end of training, create and edit training tasks, and edit simulation scenarios.

[0037] The number of panels 1 can be determined according to actual needs, and the present application embodiment does not specifically limit this. For example, in some embodiments, refer to Figure 1 The plurality of panels 1 include a first panel 1A, a second panel 1B, a third panel 1C, a fourth panel 1D, a fifth panel 1E and a sixth panel 1F.

[0038] According to the technical solution provided in the embodiment of the present application, an expandable panel equipped with a computing unit is used to connect various training components, and a universal interface supporting hot plugging is used to realize the physical connection and data transmission between panels and panels, and between panels and components, so that a training panel that can be freely combined is formed based on the expandable panel equipped with a computing unit and multiple training components, so that the anti-human error training equipment has the ability to simulate different functional panels and collect information and interact in real time. The embodiment of the present application uses a modular design method to complete the design of the panel and the panel / component interface, and uses the "panel + component" design scheme and hot plug technology to realize the rapid construction of nuclear power plant training equipment. The anti-human error training equipment has extremely high scalability, can cover most of the nuclear power plant anti-human error training scenarios (such as operation, electrical, thermal hydraulics, etc.), and meet most of the requirements of nuclear power plant anti-human error training. The embodiment of the present application realizes the rapid equipment construction that meets the functional requirements of various anti-human error skill training in different nuclear power work scenarios. Compared with previous equipment and systems, the modular design makes the present application have the advantages of low cost, high efficiency and high scalability.

[0039] In at least one embodiment of the present application, reference Figure 2 , multiple training components are divided into three types, including display component 2, acquisition component 3 and operation component 4. Display component 2 is used to simulate the actual display. Acquisition component 3 is used to collect user's action and sound information. Operation component 4 is used to simulate the actual operation mode. In this way, all training components are designed by simulating the actual display equipment and operation equipment in the nuclear power plant. There is no need to restore the actual equipment according to different scenarios and content requirements of human error prevention training, and no secondary development is required.

[0040] It should be noted that the number of display components 2, acquisition components 3 and operation components 4 that can be set on each panel 1 can be one or more, and can be set according to actual needs. Figure 2 , a panel 1 may be provided with 3 display components, 2 acquisition components, and 5 operation components.

[0041] In at least one embodiment of the present application, the display components mainly include various instruments and digital display screens. The operation components mainly include buttons, knobs, keyboards and mice. The acquisition components mainly include video and audio acquisition devices.

[0042] At least one embodiment of the present application further provides a software architecture of a human error prevention training device, and the software architecture of the human error prevention training device is applicable to the human error prevention training device of the embodiment of the present application. Figure 3 The software architecture of the anti-human error training device includes a basic layer, a service layer, a functional layer and an application layer. The basic layer includes but is not limited to a system scenario library, a device model library, a virtual component library, a panel / component driver library, a module program library and a sound and picture recognition model library. The service layer includes but is not limited to system scenario call definition, device model call definition, component hot plugging, component automatic identification, logic diagram programming and sound and picture data identification. Component hot plugging and component automatic identification are implemented based on the panel / component driver library, logic diagram programming is implemented based on the module program library, and sound and picture data recognition is implemented based on the sound and picture recognition model. The functional layer includes but is not limited to training project creation and editing, rule creation and editing, system scenario creation and editing, device model creation and editing and project management and analysis. The application layer includes but is not limited to multi-scenario anti-human error training, rapid construction of training scenarios, perception of training simulation scenarios, statistical analysis of training data and training process management.

[0043] It should be noted that on the basis of the functional layer, multi-scenario anti-human error training, rapid construction of training scenarios, perception of training simulation scenarios, statistical analysis of training data and training process management are realized in the application layer.

[0044] According to the technical solution provided in the embodiment of the present application, service layer functions such as component hot swapping and automatic identification, logic diagram programming, and audio and video data recognition are implemented based on the basic layers such as the module library, panel / component driver library, and audio and video recognition model, thereby realizing the collaborative and rapid construction of training equipment software / hardware. Develop a logic diagram programming environment based on the module library, use the module library to implement simple logic diagram programming to edit training projects and rules, and combine the construction of training equipment to realize various required training functions. Based on the system scenario library and the equipment model library, realize the simple combination of system scenarios and equipment models with the training process, and use virtual components to replace the functions of missing physical simulation operation components.

[0045] The embodiment of the present application applies a modular concept and proposes a "panel + component" equipment construction method based on hot-swap technology and a simulation feedback construction method based on logic diagram programming, thereby realizing the rapid construction of anti-human error training equipment that meets various training function requirements in different scenarios.

[0046] In the software architecture for the human error prevention training device provided in at least one embodiment of the present application, the system scenario library includes a nuclear power plant system flow chart. The equipment model library includes an equipment model diagram. In this way, a scenario-based training form is realized by using the system scenario library including the nuclear power plant system flow chart and the equipment model library including the equipment model diagram in combination with an external display component.

[0047] The embodiment of the present application is applied to the human error prevention training of nuclear power plant personnel. It adopts modular human error prevention training equipment and logic diagram programming method, realizes the rapid construction of equipment required to meet different scenarios and different human error prevention training contents, and can realize automated and situational training forms. During the construction process, the human error prevention training equipment adopts the "building blocks" construction method, and the software completes the project editing through the graphical programming method of logic diagrams. There is no need to restore the actual equipment according to different human error prevention training scenarios and content requirements, and no secondary development is required.

[0048] At least one embodiment of the present application also provides a method for building a training device to prevent human errors. Figure 4 ,The method of building the anti-human error training system includes the following steps.

[0049] S1: According to the training project requirements, sort out the training scenarios and training function requirements, and break them down into operation requirements and feedback form requirements.

[0050] S2: Select multiple training components in the human error prevention training equipment according to the operation requirements and feedback form requirements, and complete the construction of the training panel by combining the panel and multiple training components.

[0051] S3: Complete the logic construction on the control platform according to the operation requirements and feedback form requirements, that is, the editing of training items and rules.

[0052] S4: After editing is completed, training on preventing human errors can be carried out. Based on the preset projects and rule procedures, the training panel will display the response results generated by the operation during the training process.

[0053] According to the technical solution provided in the embodiment of the present application, a "panel + component" anti-human error training device is provided by applying a modular concept. At the same time, a rapid construction method for the anti-human error training device is formed by combining hot-swap technology and graphical programming technology, thereby realizing modular and code-free rapid construction of the anti-human error training device.

[0054] At least one embodiment of the present application also provides a method for training against human errors. The method for training against human errors is implemented by the user operating on the control platform of the training device against human errors. The control platform of the training device against human errors is connected to the training device against human errors of the embodiment of the present application and is used to implement the functions of the software architecture of the training device against human errors. The control platform of the training device against human errors is provided with a project rule editing interface, a scenario creation interface and a training management and analysis interface. The method for operating the control platform of the training against human errors includes the following steps.

[0055] S10: receiving a scene creation operation from a user on a scene creation interface.

[0056] S20: Creating a training scenario according to the scenario creation operation performed by the user on the scenario creation interface.

[0057] S30: Connecting a plurality of training components corresponding to the training scenario in the human error prevention training device according to the training scenario.

[0058] S40: receiving a logic diagram programming operation of the user for a training scenario on a project rule editing interface.

[0059] S50: Creating training projects and rules based on the user's logic diagram programming operation for the training scenario on the project rule editing interface.

[0060] S60: receiving a training management analysis operation of the user on the training management analysis interface.

[0061] It should be noted that the training management analysis interface is called out according to the user's operation through training management.

[0062] S70: Perform training for the training project according to the training management and analysis operation performed by the user on the training management and analysis interface, and use corresponding data analysis methods to perform data analysis.

[0063] According to the technical solution provided in the embodiment of the present application, through the above S10 and S20, the creation and editing of scenes are realized. Through the above S40 and S50, the creation and editing of training projects and rules based on the control platform are realized, and the editing and automatic management of project programs are realized. Through the above S60 and S70, training based on the control platform is realized. For different training functions, traditional training equipment needs to be redesigned and manufactured (refer to Figure 5 ), and the embodiment of the present application only requires the application of existing hardware modules and control platform editing to realize new training functions.

[0064] In at least one embodiment of the present application, reference Figure 6 and Figure 7The project rule editing interface includes an editing menu 9, a training project management interface 10, a project editing interface 12 and a rule editing interface 13. S40-1 to S40-3 are a specific implementation of the above S40. S50-1 to S50-4 are a specific implementation of the above S50.

[0065] S40 - 1 : receiving the user's instructions for creating, deleting and naming a project on the training project management interface 10 .

[0066] Specifically, the user clicks Create, Delete Project in the training project management interface 10 to create a training project and name it. On the training management interface 10, the user can complete operations such as creating a project and calling and creating rules in the rule library.

[0067] S40 - 2 : Receive the definition node and judgment condition set by the user on the editing menu 9 .

[0068] For example, the edit menu 9 may include defining nodes, defining scenes, defining outputs, defining modules and determining conditions.

[0069] S40 - 3 : receiving a calling instruction from the user on the training project management interface 10 and a rule editing instruction on the rule editing interface 13 .

[0070] For example, the user may input rule description information in the text input box of the rule editing interface 13, and the processor generates a rule editing instruction according to the rule description information.

[0071] It should be noted that the rules can be edited by entering the rule editing interface 13, in which the text content of the training rules can be input, and the logic diagram programming can also be completed to realize the editing of the training rules.

[0072] S50 - 1 : Creating a training project according to the user's instructions of creating, deleting and naming a project on the training project management interface 10 .

[0073] S50 - 2 : defining the initialization node I, the success node S or the failure node F of the training project in the project editing interface 12 according to the definition node set by the user in the editing menu 9 .

[0074] Specifically, the user can use the definition node in the editing menu 9 to define the initialization node I, the success node S or the failure node F of the training rule in the rule editing interface 13.

[0075] The user can also use the definition module in the editing menu 9 to obtain changes from the operating device and call the collection device to collect actions or sounds in the rule editing interface 13.

[0076] S50 - 3 : according to the calling instruction of the user on the training project management interface 10 , the rules of the rule base in the training project management interface 10 are called and added to the project editing interface 12 .

[0077] S50 - 4 : Create rules by combining the rules in the rule library and the rule editing instructions of the user on the rule editing interface 13 .

[0078] S50 - 5 : Setting the training project flow in the project editing interface 12 according to the judgment condition set by the user in the editing menu 9 , or setting the conditional branch of input and output judgment in the rule editing interface 13 .

[0079] For example, the user can use the judgment condition in the editing menu 9 to determine whether the training rule 1 is successful in the project editing interface 12, so as to decide whether to enter the training of the training rule 2. For another example, the judgment condition and branch for any input and output can be set in the rule editing interface 13, such as the judgment condition can be to determine whether the display values ​​A and B of the display component are within the range.

[0080] In at least one embodiment of the present application, reference Figure 6 and Figure 7 The project rule editing interface also includes a connection device list 11. S30-1 and S30-2 are a specific implementation of the above S30.

[0081] S30 - 1 : Automatically identify and classify connected training components in the connected device list interface 11 according to the training scenario.

[0082] Specifically, the display component and the operation component in the connection device list 11 are called, and the input and output information of the training device are defined using the define input (such as function, value or text) and define output (such as function, value or text) in the edit menu 9.

[0083] S30 - 2 : connecting or changing a virtual component according to the user's virtual component adding and editing operation on the connection device list interface 11 .

[0084] In this way, the user can complete the naming of training components and the addition and editing of virtual components on the connection device list 11 interface.

[0085] In at least one embodiment of the present application, reference Figure 8 The scene creation interface includes a scene library interface 14, a device model editing interface 15 and a system scenario editing interface 16. Before the above S10, S01 and S02 are also included. S10-1 to S10-3 are a specific implementation of the above S10. S20-1 to S20-3 are a specific implementation of the above S20.

[0086] S01: receiving the user's operation of defining a scene on the editing menu 9.

[0087] S02: According to the user's operation of defining a scene on the editing menu 9, the scene library interface 14, the device model editing interface 15 and the system scenario editing interface 16 are called out. The scene library interface 14 has two submenus: the device model library and the system scenario library.

[0088] For example, the device model and the system flow chart can be called to open the device model editing interface 15 and the system scenario editing interface 16, and the device and system elements corresponding to the connected devices can be defined in the two interfaces.

[0089] S10 - 1 : receiving a calling operation of the user on the scene library interface 14 .

[0090] S10 - 2 : receiving the user's editing operation on the device model editing interface 15 .

[0091] S10 - 3 : receiving the user's editing operation on the system scenario editing interface 16 .

[0092] S20 - 1 : According to the calling operation of the user on the scenario library interface 14 , the scenario model is called from the device model library and the system scenario library in the scenario library interface 14 , and the connected training component or the created virtual component is associated with the scenario model.

[0093] For example, scenario models include control room console, control room display, system flow chart, etc. The equipment model library includes but is not limited to control room console and control room display. The system scenario library includes but is not limited to system flow chart and system modeling diagram.

[0094] S20 - 2 : According to the user's editing operation on the device model editing interface 15 , edit the reference of the training component in the scenario model.

[0095] S20 - 3 : According to the user's editing operation on the system scenario editing interface 16 , edit the position of the training component in the system process.

[0096] In at least one embodiment of the present application, reference Fig. 9 The training management and analysis interface includes a training project management interface 10, a training management and analysis menu 17, a training analysis function 18 and a project management interface 19. The training management and analysis menu 17 includes training start, training pause, training stop, training data and training analysis.

[0097] The training management and analysis interface is used to call different data analysis methods to perform data analysis. Thus, in the training management and analysis menu 17, functions such as training start, pause, stop, and the management and analysis functions of training data can be realized.

[0098] It should be noted that, in the training project management interface 10, the user can view the progress of the training in real time and implement management. The training analysis function 18 can be statistically analyzed by project, by rule, by equipment and by scenario.

[0099] It should be recognized that the human error prevention training equipment, software architecture and method disclosed in the embodiments of the present application are suitable for human error prevention training for nuclear power plant operators and on-site workers. In addition, they can be applied to human error prevention training in other industries through simple modification.

[0100] At least one embodiment of the present application further provides a computer device, which includes a processor and a memory. The processor is used to execute a human error prevention training method provided by any of the above embodiments of the present application. The memory is used to store executable instructions of the processor, such as application programs. The number of processors can be one or more. The application program stored in the memory can include one or more modules, each corresponding to a set of instructions. In addition, the processor is configured to execute instructions to execute the above human error prevention training method.

[0101] The computer device may also include a power supply component configured to manage power of the computer device, a wired or wireless network interface configured to connect the computer device to a network, and an input / output (I / O) interface. The computer device may operate based on an operating system stored in the memory, such as Windows Server 2003. TM , Mac OSX TM , Unix TM , Linux TM , FreeBSD TM or similar.

[0102] At least one embodiment of the present application further provides a computer-readable storage medium on which computer executable instructions are stored. When the executable instructions are executed by a processor, a human error prevention training method provided in any of the above embodiments of the present application is implemented.

[0103] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the computer device, enables the computer device to execute the human error prevention training method. The human error prevention training method is executed by an agent program.

[0104] Those of ordinary skill in the art will appreciate that the algorithmic steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] At least one embodiment of the present application further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a human error prevention training method provided in any of the above embodiments of the present application.

[0106] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a computer program product that contributes to the prior art, and the computer program product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the anti-human error training method of each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program check codes.

[0107] It should be noted that the combination of the various technical features in the embodiments of the present application is not limited to the combination described in the embodiments of the present application or the combination described in the specific embodiments, and all technical features described in the present application can be freely combined or combined in any way unless there is a contradiction between them.

[0108] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0109] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A training device for preventing human errors, characterized in that: Includes multiple training panels, Each training panel includes a panel and a plurality of training components connected to the panel via a universal interface supporting hot plugging, the plurality of training components are integrated with a digital display screen for code or name display, and the panel is equipped with a computing unit; The panel has multiple input and output ports supporting hot plugging, and the multiple input and output ports are respectively used for connection between different training panels, between the panel and the training components, between the panel and the computer console, and between the panel and the output device; the panel and the computer console are connected through a data bus connected to the input and output ports; The computer console is used to issue instructions and input training programs to the human error prevention training equipment through the input and output ports, and collect training process information for analysis and interactive operation processing; the output device is used to output simulation scenario information.

2. The anti-human error training device according to claim 1, characterized in that: The multiple training components are divided into three types, including display components, acquisition components and operation components. The display components are used to simulate actual displays; the acquisition components are used to collect user motion and sound information; and the operation components are used to simulate actual operation modes.

3. A software architecture for a human error prevention training device, characterized in that: The anti-human error training device according to claim 1 or 2, wherein the software architecture of the anti-human error training device includes a basic layer, a service layer, a functional layer and an application layer. The basic layer includes system scenario library, device model library, virtual component library, panel / component driver library, module program library and audio and video recognition model library; The service layer includes system scenario call definition, device model call definition, component hot swap, component automatic identification, logic diagram programming and audio and video data identification. Component hot swap and component automatic identification are implemented based on the panel / component driver library, logic diagram programming is implemented based on the module program library, and audio and video data identification is implemented based on the audio and video recognition model. The functional layer includes training project creation and editing, rule creation and editing, system scenario creation and editing, equipment model creation and editing, and project management and analysis; The application layer includes multi-scenario anti-human error training, rapid construction of training scenarios, perception of training simulation scenarios, statistical analysis of training data, and training process management.

4. A method for constructing a training device to prevent human errors, characterized in that: include: According to the training project requirements, sort out the training scenarios and training function requirements, and break them down into operation requirements and feedback form requirements; Select multiple training components in the anti-human error training device according to the operation requirements and feedback form requirements, and complete the construction of a training panel in the anti-human error training device as claimed in claim 1 or 2 by combining the panel and the multiple training components; Complete the logic construction on the control platform according to the operation requirements and feedback form requirements, that is, the editing of training items and rules; After editing is completed, training on preventing human errors can be carried out. Based on preset projects and rule procedures, the training panel will display the response results generated by the operations during the training process.

5. A training method for preventing human errors, characterized in that: The anti-human error training method is implemented by the user's operation on the control platform of the anti-human error training device. The control platform of the anti-human error training device is connected to the anti-human error training device according to claim 1 or 2, and is used to implement the function of the software architecture of the anti-human error training device according to claim 3. The control platform of the anti-human error training device is provided with a project rule editing interface, a scenario creation interface and a training management analysis interface, wherein the anti-human error training method includes: Receive the scene creation operation of the user on the scene creation interface; Create a training scenario based on the scenario creation operation of the user on the scenario creation interface; Connect multiple training components corresponding to the training scenarios in the human error prevention training device according to the training scenarios; Receive the user's logic diagram programming operation for the training scenario on the project rule editing interface; Create training projects and rules based on the user's logic diagram programming operations for training scenarios on the project rule editing interface; Receive training management and analysis operations from users on the training management and analysis interface; Conduct training on training projects based on the user's training management and analysis operations on the training management and analysis interface, and use corresponding data analysis methods to perform data analysis work.

6. The method for preventing human error training according to claim 5, characterized in that: The project rule editing interface includes the editing menu, training project management interface, project editing interface and rule editing interface. Among them, receiving the user's logic diagram programming operation for the training scenario on the project rule editing interface includes: receiving the user's new project, deletion project and naming instructions on the training project management interface; receiving the definition node and judgment condition set by the user on the editing menu; receiving the user's call instruction of the rule in the rule library on the training project management interface and the rule editing instruction on the rule editing interface; The training projects and rules are created based on the user's logical diagram programming operations for training scenarios on the project rule editing interface, including: creating training projects according to the user's new project, deletion project and naming instructions on the training project management interface; defining the initialization node, success node or failure node of the training project in the project editing interface according to the definition node set by the user on the editing menu; calling the rules of the rule library in the training project management interface and adding them to the project editing interface according to the user's calling instructions on the training project management interface; creating rules by combining the rules in the rule library and the user's rule editing instructions on the rule editing interface; setting the training project process in the project editing interface according to the judgment conditions set by the user in the editing menu, or setting conditional branches for input and output judgments in the rule editing interface.

7. The method for preventing human error training according to claim 6, characterized in that: The project rule editing interface also includes a list of connected devices. Among them, multiple training components corresponding to the training scenarios in the anti-human error training equipment are connected according to the training scenarios, including: automatically identifying and classifying the connected training components in the connection device list interface according to the training scenarios; connecting or changing virtual components according to the user's virtual component addition and editing operations on the connection device list interface.

8. The method for preventing human error training according to claim 5, characterized in that: The scene creation interface includes the scene library interface, the device model editing interface and the system scenario editing interface. Wherein, receiving the scene creation operation of the user on the scene creation interface, previously, the method for preventing human error training also includes: receiving the operation of defining the scene on the editing menu by the user; calling out the scene library interface, the device model editing interface and the system scene editing interface according to the operation of defining the scene on the editing menu by the user, the scene library interface having two submenus, the device model library and the system scene library; Receiving a scene creation operation from a user on a scene creation interface, including: receiving a call operation from a user on a scene library interface; receiving an edit operation from a user on a device model edit interface; receiving an edit operation from a user on a system scenario edit interface; According to the scene creation operation performed by the user on the scene creation interface, a training scene is created, including: according to the calling operation performed by the user on the scene library interface, the scene model is called from the device model library and the system scene library in the scene library interface, and the connected training component or the created virtual component is associated with the scene model; according to the editing operation performed by the user on the device model editing interface, the reference of the training component in the scene model is edited; according to the editing operation performed by the user on the system scene editing interface, the position of the training component in the system process is edited.

9. The method for preventing human error training according to claim 5, characterized in that: include: The training management and analysis interface includes the training project management interface, training management and analysis menu, training analysis functions and project management interface; The training management and analysis menu includes training start, training pause, training stop, training data and training analysis.

10. A computer device, characterized in that: include: A processor, configured to execute a human error prevention training method according to any one of claims 5 to 9; as well as A memory is used to store executable instructions of the processor.

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