A ship power system embedded simulation training method based on an original monitoring system

Abstract

This invention discloses an embedded simulation training method for ship propulsion systems based on existing monitoring systems. This method defines four core steps—mode switching and isolation, command acquisition and uplink, simulation calculation, and parameter downlink and drive—and their synergistic effects to construct a stable and secure training data closed loop. This enables highly realistic and zero-risk embedded simulation training using the existing monitoring system's human-machine interface components, without using real propulsion equipment or interfering with the normal operation of the monitoring system. Furthermore, this invention defines a standardized command uplink and parameter downlink mechanism and integrates dynamic fault injection and intelligent evaluation functions, effectively solving the problems of incomplete training coverage, insufficient realism, and evaluation difficulties caused by reliance on advanced platforms and lack of methodological processes in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of ship simulation training technology, and in particular to an embedded simulation training method for ship power systems based on the original monitoring system. Background Technology

[0002] Embedded simulation training of ship propulsion systems is an important means to improve crew members' operational skills and emergency response capabilities.

[0003] Existing simulation training methods are often tightly coupled with specific hardware systems, lacking a unified, standardized, and platform-independent data interaction and process control mechanism at the methodological level. This results in chaotic and incomplete data and instruction flows during training, failing to form a stable "operation-simulation-feedback" training loop. Furthermore, existing methods often employ simple state settings during fault simulation, failing to organically integrate fault injection into the aforementioned training loop, lacking the realism of dynamic evolution, and also lacking the ability to capture behavior and intelligently evaluate based on full-process data. Therefore, existing methods suffer from insufficient realism, flexibility, and training efficiency. Summary of the Invention

[0004] To address the aforementioned technical issues, this invention proposes an embedded simulation training method for ship power systems based on the original monitoring system. This embedded simulation training method constructs a stable and secure training data closed loop by defining four core steps and their synergistic effects: "mode switching and isolation, command acquisition and uplink, simulation calculation, and parameter downlink and drive." This enables highly realistic and zero-risk embedded simulation training using the human-computer interaction components of the existing monitoring system without using real power equipment or interfering with the normal operation of the monitoring system.

[0005] An embedded simulation training method for ship power systems based on the original monitoring system, the specific training process is as follows: Step 1, Mode Switching and Security Isolation: In response to the mode switching command, the ship's power monitoring system is switched from the actual monitoring mode to the embedded simulation training mode. In the simulation training mode, a dedicated data path is established between the simulation computer and the actual monitoring system, and a security isolation mechanism is established at the same time. Step 2, Command Acquisition and Uplink: Through the command acquisition interface, the operation commands issued by the trainee through the manual operation components of the actual monitoring system are acquired, the operation commands are standardized into control data signals that can be recognized by the simulation computer, and then sent uplink to the simulation computer. Step 3, Simulation Calculation: Using the simulation computer, based on the received control data signals and the current simulation state of the power system, run the simulation model to generate simulation parameters of the power system's operating state; Step 4, parameter downlink and drive: The simulation parameters of the operating status are sent downlink to the actual monitoring system through the signal routing and drive interface. By replacing the signal source or directly updating the data, at least one human-machine interaction component of the actual monitoring system is driven to display the status.

[0006] As a preferred embodiment of the above technical solution, in step one, the security isolation mechanism includes: Physical signal isolation: During training mode, the connection between the real sensors and actuators and the monitoring system is physically disconnected via a hardware switch.

[0007] Mode mutual exclusion logic: The operating mode switching switch is a two-position hardware switch to ensure that the system is in only one mode.

[0008] Data flow control: In training mode, downlink data is only used to drive the display components and does not contain any control signals that drive the actual actuators.

[0009] As a preferred embodiment of the above technical solution, in step two, for analog operation commands, they are converted into digital signals representing the operation quantity through analog-to-digital conversion; for switch operation commands, they are identified as switch status events through status acquisition.

[0010] As a preferred embodiment of the above technical solution, in step two, driving the human-computer interaction component includes: for analog instruments, switching the input signal source to change the real signal from the physical sensor to the simulated signal from the simulation computer; for digital display terminals, directly sending the operating status simulation parameters to them via network communication to update the display content.

[0011] As a preferred embodiment of the above technical solution, fault training can be performed in steps two and three. The specific training steps are as follows: Receive fault injection command; The simulation computer dynamically modifies the parameters, logic, or operating conditions of its internal simulation model according to the fault injection instruction. Calculations are performed based on the modified simulation model to generate simulation parameters for abnormal operating states, thereby simulating equipment failures and chain reactions in the training closed loop.

[0012] As a preferred embodiment of the above technical solution, the training results can be evaluated in step four. The specific evaluation steps are as follows: Record the sequence of operation instructions, the sequence of simulation parameters for running status, and key event points during the training process; Based on preset evaluation rules, the timing accuracy, logical correctness, and fault handling effectiveness of the operation are quantitatively evaluated. Generate an assessment report that includes operational reviews and skills gap analysis.

[0013] The beneficial effects of this invention are as follows: 1. Methodological innovation and universality: A standardized training methodology is creatively defined that does not rely on the ship's integrated platform management system. It is applicable to the power monitoring systems of various types of existing ships and solves the training barrier caused by the "presence or absence" of a platform.

[0014] 2. High realism and zero risk: Through the "virtual-real signal mapping" mechanism, seamless driving of the actual human-machine interaction components is achieved at the method level, ensuring the consistency between the training environment and the real operating environment, while the equipment safety is fundamentally guaranteed through physical isolation.

[0015] 3. Dynamic closed-loop training: Through the orderly coordination of four core steps, a stable training data closed loop is built on the existing monitoring system for the first time, which upgrades the simulation training from static and one-sided operation practice to dynamic, systematic and complete training that closely follows the laws of cognition.

[0016] 4. Intelligent assessment and in-depth analysis: This method naturally captures complete training process data, making data-driven, refined, and intelligent assessment possible. It can effectively pinpoint crew skill deficiencies and improve training quality. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall process and data closed loop of the present invention.

[0018] Figure 2 This is a detailed data processing flowchart for the instruction acquisition and uplink steps of the present invention.

[0019] Figure 3 This is a schematic diagram illustrating the signal replacement principle of the parameter downlink and driving steps of the present invention.

[0020] Figure 4 This is a sequence diagram of closed-loop training and fault injection according to the present invention. Detailed Implementation

[0021] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0022] An embedded simulation training method for ship power systems based on the original monitoring system, the specific training process is as follows: Step 1, Mode Switching and Security Isolation: In response to the mode switching command, the ship's power monitoring system is switched from the actual monitoring mode to the embedded simulation training mode. In the simulation training mode, a dedicated data path is established between the simulation computer and the actual monitoring system, and a security isolation mechanism is established at the same time. Step 2, Command Acquisition and Uplink: Through the command acquisition interface, the operation commands issued by the trainee through the manual operation components of the actual monitoring system are acquired, the operation commands are standardized into control data signals that can be recognized by the simulation computer, and then sent uplink to the simulation computer. Step 3, Simulation Calculation: Using the simulation computer, based on the received control data signals and the current simulation state of the power system, run the simulation model to generate simulation parameters of the power system's operating state; Step 4, parameter downlink and drive: The simulation parameters of the operating status are sent downlink to the actual monitoring system through the signal routing and drive interface. By replacing the signal source or directly updating the data, at least one human-machine interaction component of the actual monitoring system is driven to display the status.

[0023] In this embodiment, in step one, the security isolation mechanism includes: Physical signal isolation: During training mode, the connection between the real sensors and actuators and the monitoring system is physically disconnected via a hardware switch.

[0024] Mode mutual exclusion logic: The operating mode switching switch is a two-position hardware switch to ensure that the system is in only one mode.

[0025] Data flow control: In training mode, downlink data is only used to drive the display components and does not contain any control signals that drive the actual actuators.

[0026] In this embodiment, in step two, for analog operation commands, they are converted into digital signals representing the operation quantity through analog-to-digital conversion; for switch operation commands, they are identified as switch status events through status acquisition.

[0027] In this embodiment, in step two, driving the human-computer interaction component includes: for analog instruments, switching their input signal source to change the real signal from the physical sensor to the simulated signal from the simulation computer; for digital display terminals, directly sending the operating status simulation parameters to them via network communication to update the display content.

[0028] In this embodiment, fault training can be performed in steps two and three. The specific training steps are as follows: Receive fault injection command; The simulation computer dynamically modifies the parameters, logic, or operating conditions of its internal simulation model according to the fault injection instruction. Calculations are performed based on the modified simulation model to generate simulation parameters for abnormal operating states, thereby simulating equipment failures and chain reactions in the training closed loop.

[0029] In this embodiment, the training results can be evaluated in step four. The specific evaluation steps are as follows: Record the sequence of operation instructions, the sequence of simulation parameters for running status, and key event points during the training process; Based on preset evaluation rules, the timing accuracy, logical correctness, and fault handling effectiveness of the operation are quantitatively evaluated. Generate an assessment report that includes operational reviews and skills gap analysis.

[0030] The following provides further supplementary explanations for this embodiment.

[0031] 1. Implementation method based on logical flow Reference Figure 1 This embodiment describes the implementation of the present invention from the perspective of method logic.

[0032] The core of this embedded simulation training method lies in the orderly circulation of control data flow and state data flow between the simulation computer and the actual monitoring system.

[0033] Initialization and Mode Switching: Upon power-up, the system defaults to actual monitoring mode. Upon receiving a mode switching command from an authorized terminal (such as a training control computer), the system performs mode switching and isolation. This process not only changes the software state but, more importantly, triggers a series of hardware interlocking actions, controlling a series of signal switching units to physically establish two independent paths: one is the actual monitoring path from "real sensor → monitoring system," and the other is the simulated training path from "simulation computer → monitoring system." Simultaneously, control commands issued by the monitoring system to the actuators are directed to the simulation computer.

[0034] Training operation and closed-loop formation: Command Stream (Uplink): The trainee's actions in the control room (such as pushing a handle or pressing a button) are captured by the command acquisition interface. The core method of this interface is to identify and standardize the encapsulation of different types of physical signals to form a unified control data packet, which is then sent to the simulation computer through a predetermined protocol.

[0035] State Flow (Downlink): After receiving instructions, the simulation computer calculates the full system simulation parameters for future timeframes. These parameters are then sent down through the signal routing and drive interface. The core method of this interface is "on-demand distribution": for pointer instruments requiring analog drive, standard current signals are generated by calling digital-to-analog converter resources; for digital displays, they are packaged into network data frames and sent directly.

[0036] The updated status information is perceived by the trainees, prompting them to make the next round of decisions and actions. This cycle repeats, forming a cognitive closed loop of "observation-judgment-action-response".

[0037] 2. Implementation methods for command acquisition and uplink Reference Figure 2 This embodiment details the specific implementation of the instruction acquisition and uplink steps.

[0038] For analog command sources (such as host handheld devices), by acquiring their physical position signals, the analog signals enter the analog-to-digital conversion process and are converted into standard digital quantities.

[0039] For digital command sources (such as switches and buttons), their on / off state is identified through the status acquisition stage, and this status signal is identified as a switching event.

[0040] Regardless of whether the source is analog or digital, all data is ultimately standardized through the command acquisition interface, packaged into standard data frames, and transmitted upstream to the simulation computer via a dedicated bus (such as the CAN bus).

[0041] 3. Implementation methods for parameter downlink and driving Reference Figure 3 This embodiment details the specific implementation of the parameter downlink and driving steps.

[0042] In the embedded simulation training mode, the operation mode switching device control parameter input signal switching module switches the input signal source of the pointer-type secondary instrument from the real physical sensor to the simulation signal generated by the simulation computer.

[0043] Specifically, the digital parameters calculated by the simulation computer are converted into a standard analog current signal of 4-20mA by the digital-to-analog converter module. This signal drives the real pointer-type secondary instrument through the activated signal switching module, so that it displays a reading consistent with the simulation state.

[0044] This physical signal level switching ensures both the realism of the display and complete isolation from the real device, guaranteeing absolute safety during the training process.

[0045] 4. Implementation methods for closed-loop and fault training Reference Figure 4This embodiment uses a time-series approach to demonstrate the dynamic process of training loop formation and fault injection.

[0046] In a normal training cycle: the trainee issues an operation command, which is transmitted from the monitoring human-machine interface to the simulation computer; the simulation computer performs model calculations and generates normal state parameters; the parameters are transmitted to the monitoring human-machine interface to update the state display; the trainee observes the display and then performs a new round of operations, forming a closed loop.

[0047] In the fault training loop: the instructor sends a fault injection command to the simulation computer; the simulation computer modifies the internal model parameters or logical relationships; when the trainee issues the operation command again, the simulation model calculates based on the fault state and generates abnormal state parameters; after the abnormal parameters are transmitted, the monitoring system's audible and visual alarm is triggered and the abnormal state is displayed. The trainee must judge and handle the situation as if dealing with a real fault. This process dynamically and organically integrates faults into the training loop.

[0048] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An embedded simulation training method for a ship's power system based on the original monitoring system, characterized in that: The specific training process is as follows: Step 1, Mode Switching and Security Isolation: In response to the mode switching command, the ship's power monitoring system is switched from the actual monitoring mode to the embedded simulation training mode. In the simulation training mode, a dedicated data path is established between the simulation computer and the actual monitoring system, and a security isolation mechanism is established at the same time. Step 2, Command Acquisition and Uplink: Through the command acquisition interface, the operation commands issued by the trainee through the manual operation components of the actual monitoring system are acquired, the operation commands are standardized into control data signals that can be recognized by the simulation computer, and then sent uplink to the simulation computer. Step 3, Simulation Calculation: Using the simulation computer, based on the received control data signals and the current simulation state of the power system, run the simulation model to generate simulation parameters of the power system's operating state; Step 4, parameter downlink and drive: The simulation parameters of the operating status are sent downlink to the actual monitoring system through the signal routing and drive interface. By replacing the signal source or directly updating the data, at least one human-machine interaction component of the actual monitoring system is driven to display the status.

2. The embedded simulation training method for a ship power system based on the original monitoring system according to claim 1, characterized in that: In step one, the security isolation mechanism includes: Physical signal isolation: During training mode, the connection between the real sensors and actuators and the monitoring system is physically disconnected via a hardware switch; Mode mutual exclusion logic: The operating mode switching switch is a two-position hardware switch to ensure that the system is in only one mode; Data flow control: In training mode, downlink data is only used to drive the display components and does not contain any control signals that drive the actual actuators.

3. The embedded simulation training method for a ship power system based on the original monitoring system according to claim 2, characterized in that: In step two, for analog operation commands, they are converted into digital signals representing the operation quantity through analog-to-digital conversion; for switch operation commands, they are identified as switch status events through status acquisition.

4. The embedded simulation training method for a ship power system based on the original monitoring system according to claim 2, characterized in that: In step two, the driving human-machine interaction component includes: for analog instruments, switching the input signal source to change the real signal from the physical sensor to the simulated signal from the simulation computer; for digital display terminals, sending the operating status simulation parameters directly to them via network communication to update the display content.

5. The embedded simulation training method for a ship power system based on the original monitoring system according to claim 1, characterized in that: Fault training can be performed in steps two and three. The specific training steps are as follows: Receive fault injection command; The simulation computer dynamically modifies the parameters, logic, or operating conditions of its internal simulation model according to the fault injection instruction. Calculations are performed based on the modified simulation model to generate simulation parameters for abnormal operating states, thereby simulating equipment failures and chain reactions in the training closed loop.

6. The embedded simulation training method for a ship power system based on the original monitoring system according to claim 1, characterized in that: In step four, the training results can be evaluated. The specific evaluation steps are as follows: Record the sequence of operation instructions, the sequence of simulation parameters for running status, and key event points during the training process; Based on preset evaluation rules, the timing accuracy, logical correctness, and fault handling effectiveness of the operation are quantitatively evaluated. Generate an assessment report that includes operational reviews and skills gap analysis.

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