A method and system for constructing a digital human system for ship equipment

Abstract

The invention discloses a method and system for constructing a digital human system for ship equipment, and relates to the technical field of ship equipment. The method comprises: collecting real-time data of a ship power system, a navigation system, a propulsion system, a steering gear system, a power supply system, a life-saving equipment system, a gas detection system, an oil mist concentration detection system, and a temperature monitoring system to obtain equipment-level data; sensing the ship's embodied environment based on screened key equipment indicator data according to a real-time online monitoring system for the marine environment and an intelligent shipping embodied large model to obtain the ship's embodied environment conditions; based on the sensed ship's embodied environment conditions, calling a ship equipment interface to obtain real-time ship navigation reference data; establishing a navigation digital twin model according to the real-time ship navigation reference data; simulating and predicting the behavior of ship equipment using the established navigation digital twin model, and establishing a fault diagnosis system and a health management system.

Description

Technical Field

[0001] The present application relates to the technical field of ship equipment, and in particular to a method and system for constructing a digital human system for ship equipment. Background Art

[0002] Smart ship technology refers to a collection of technologies that can improve the intelligence level of ships in navigation, management, maintenance, cargo transportation and other aspects. As a major shipping country, my country is actively promoting the development of smart ship technology. Due to the complexity of ship equipment, affected by variable loads and high salt fog environment in the ocean, performance degrades quickly and failures occur frequently. Its full life cycle operation and maintenance is the main problem that restricts its performance and affects the navigation mission of ships.

[0003] Therefore, there is an urgent need for a method and system for constructing a digital human system for ship equipment, which can be used for navigation maintenance guidance and fault diagnosis of ship equipment. Summary of the invention

[0004] The embodiments of the present application provide a method and system for constructing a digital human system for ship equipment to solve the above-mentioned technical problems.

[0005] The present application provides a method for constructing a digital human system for ship equipment, including:

[0006] Collect real-time data of ship power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data;

[0007] Using edge computing to process and analyze the collected device-level data and filter key device indicator data;

[0008] According to the real-time online monitoring system of the marine environment and the intelligent shipping embodied large model, the embodied environment of the ship is perceived based on the selected key equipment indicator data to obtain the embodied environment of the ship;

[0009] Based on the perceived embodied environment of the ship, the ship equipment interface is called to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface;

[0010] Establishing a navigation digital twin model based on the real-time ship navigation reference data;

[0011] The established navigation digital twin model is used to simulate and predict the behavior of ship equipment, and a fault diagnosis system and a health management system are established.

[0012] Furthermore, the intelligent shipping embodied large model includes a Kunpeng large model; the real-time online monitoring system for the marine environment and the intelligent shipping embodied large model perceive the ship's embodied environment based on the selected key equipment indicator data to obtain the ship's embodied environment conditions, including:

[0013] The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; wherein the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; the wave dynamic pressure Determined based on the following formula;

[0014] ;

[0015] Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the seawater density; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment;

[0016] The Kunpeng big model is used to perceive the key equipment indicator data and the real-time marine environmental element data to obtain the ship's embodied environment and realize data interaction between the ship's equipment and the ship's embodied environment.

[0017] Further, the real-time ship navigation reference data includes first real-time ship navigation reference data and second real-time ship navigation reference data;

[0018] The route planning interface is used to plan a route for the ship equipment based on the perceived embodied environmental conditions of the ship and the meteorological and hydrological perception data, and obtain the first real-time ship navigation reference data corresponding to the route; wherein the meteorological and hydrological perception data are various observation data related to water cycle and water balance obtained through the ship-borne meteorological and hydrological perception data interface;

[0019] The navigation guidance interface is used to provide navigation guidance for the ship equipment based on the perceived environmental conditions of the ship, the meteorological and hydrological perception data, and the first real-time ship navigation reference data, and obtain the second real-time ship navigation reference data corresponding to the route to achieve autonomous obstacle avoidance and energy optimization of the ship equipment.

[0020] Furthermore, establishing a navigation digital twin model according to the real-time ship navigation reference data includes:

[0021] Establishing a CAD model of the ship equipment based on the first real-time ship navigation reference data and the second real-time ship navigation reference data;

[0022] Converting the model data of the CAD model of the ship equipment to the Unity platform to obtain a Unity-driven virtual device;

[0023] The Unity-driven virtual device including the first real-time ship navigation reference data and the second real-time ship navigation reference data is published as the navigation digital twin model; wherein the navigation digital twin model is used to realize the pairwise data interaction between the perception data of the ship's physical space, the calculation data of the ship's information space and the ship service system data.

[0024] Furthermore, the established navigation digital twin model is used to simulate and predict the behavior of ship equipment, and a fault diagnosis system and a health management system are established, including:

[0025] Normalizing the perception data of the ship's physical space and the calculation data of the ship's information space to obtain an initial time series;

[0026] Given a sliding window length, performing sliding regression on the initial time series to construct a simulated behavior data sample;

[0027] Establishing a simulation data set of the navigation of the ship equipment in the navigation mission execution scenario based on the simulation behavior data sample;

[0028] Generate a Bayesian model according to the simulated data set; update the simulated data set according to the Bayesian model to obtain an updated simulated data set;

[0029] A behavior prediction model is constructed based on a convolutional neural network and a long short-term memory network; wherein the convolutional neural network includes three hidden layers; the input of the behavior prediction model is an updated simulation data set and navigation area chart information, and the output of the behavior prediction model is a predicted probability of the behavior of the ship equipment; the behavior of the ship equipment includes speed, heading and ship attitude;

[0030] Using the updated simulation data set and simulation coefficients to train the behavior prediction model to obtain a trained and optimized behavior prediction model;

[0031] The behavior prediction model completed through training and optimization is used to simulate and predict the behavior of the ship equipment, and the fault diagnosis system and the health management system are established.

[0032] Further, ;

[0033] in, is the simulation coefficient; represents the number of predictions made by the behavior prediction model; is the number of times predicted by the behavior prediction model; p represents the actual output value of the behavior prediction model; represents the estimated value of the behavior prediction model, is the number of nodes in the three hidden layers; is the weight matrix of the long short-term memory network, and the weight matrix is ​​used for linear transformation between different layers.

[0034] Furthermore, the fault diagnosis system is used to identify abnormal behavior of the ship equipment and perform fault prediction; the health management system is used to predict the service life and performance degradation of the ship equipment.

[0035] The present application provides a system for constructing a digital human system for ship equipment, including an equipment-level data acquisition unit, a key equipment indicator data screening unit, a ship embodied environment acquisition unit, a ship equipment interface calling unit, a navigation digital twin model establishment unit, and a behavior simulation prediction unit; wherein,

[0036] The device-level data acquisition unit is used to collect real-time data on the ship's power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain device-level data;

[0037] The key equipment indicator data screening unit is used to process and analyze the collected equipment-level data by using edge computing to screen the key equipment indicator data;

[0038] The ship embodied environment condition acquisition unit is used to sense the ship embodied environment based on the selected key equipment indicator data according to the marine environment real-time online monitoring system and the intelligent shipping embodied large model, and obtain the ship embodied environment condition;

[0039] The ship equipment interface calling unit is used to call the ship equipment interface based on the perceived ship's embodied environment to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface;

[0040] The navigation digital twin model establishing unit is used to establish a navigation digital twin model according to the real-time ship navigation reference data;

[0041] The behavior simulation and prediction unit is used to simulate and predict the behavior of ship equipment using the established navigation digital twin model, and to establish a fault diagnosis system and a health management system.

[0042] Furthermore, the intelligent shipping embodied large model includes a Kunpeng large model; the ship embodied environment condition acquisition unit senses the ship embodied environment based on the screened key equipment indicator data according to the marine environment real-time online monitoring system and the intelligent shipping embodied large model, and obtains the ship embodied environment condition, and is specifically configured as follows:

[0043] The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; wherein the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; the wave dynamic pressure Determined based on the following formula;

[0044] ;

[0045] Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the seawater density; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment;

[0046] The Kunpeng big model is used to perceive the key equipment indicator data and the real-time marine environmental element data to obtain the ship's embodied environment and realize data interaction between the ship's equipment and the ship's embodied environment.

[0047] Furthermore, the fault diagnosis system is used to identify abnormal behavior of the ship equipment and perform fault prediction; the health management system is used to predict the service life and performance degradation of the ship equipment.

[0048] Based on the embodiments provided in this application, real-time data collection is performed on the ship power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data; the collected equipment-level data is processed and analyzed by edge computing to screen key equipment indicator data; according to the real-time online monitoring system of the marine environment and the intelligent shipping embodiment model, the ship embodiment environment is perceived based on the screened key equipment indicator data to obtain the ship embodiment environment; based on the perceived ship embodiment environment, the ship equipment interface is called to obtain real-time ship navigation reference data; wherein, the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface and a navigation guidance interface; a navigation digital twin model is established based on the real-time ship navigation reference data; the established navigation digital twin model is used to simulate and predict the behavior of the ship equipment, and a fault diagnosis system and a health management system are established. Thus, navigation maintenance guidance and fault diagnosis of ship equipment are realized. Specifically, it has the following beneficial effects: real-time data collection of key ship systems can comprehensively monitor the ship's operating status; real-time collection of device-level data can detect potential equipment failures and performance degradations at an early stage; edge computing processing can be used to process data near the data source, reducing the amount of data sent to the central server; edge computing provides fast data processing capabilities, which helps in real-time decision-making and response; sensing the ship's embodied environment can improve the ship's adaptability to changes in the marine environment; real-time reference data can be used to optimize route planning and improve navigation efficiency; by calling the ship's equipment interface, information such as meteorology, hydrology, route planning and navigation guidance can be integrated; improved interaction: standardized interfaces improve data interaction and operational convenience between systems; establishing a digital twin model can simulate the navigation status of a ship in a virtual environment; the fault diagnosis system can identify and locate faults in a timely manner, reducing downtime; the health management system helps monitor equipment health and extend equipment service life; the entire system improves the reliability of ship operation through real-time monitoring and predictive maintenance; and long-term operating costs can be reduced by optimizing maintenance and reducing failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the embodiments of the present invention and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0050] Figure 1 It is a flowchart of an optional method for constructing a digital human system for ship equipment according to an embodiment of the present application;

[0051] Figure 2This is a structural diagram of a construction system of an optional digital human system for ship equipment according to an embodiment of the present application.

[0052] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0054] Alternatively, if Figure 1 As shown, the present application provides a method for constructing a digital human system for ship equipment, comprising:

[0055] S101, collect real-time data of the ship's power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data;

[0056] S102, using edge computing to process and analyze the collected device-level data and filter key device indicator data;

[0057] S103, according to the marine environment online monitoring system and the intelligent shipping embodied large model, the ship's embodied environment is perceived based on the selected key equipment indicator data to obtain the ship's embodied environment status;

[0058] S104, based on the perceived ship's embodied environment, calling the ship equipment interface to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface;

[0059] S105, establishing a navigation digital twin model according to real-time ship navigation reference data;

[0060] S106, using the established navigation digital twin model to simulate and predict the behavior of ship equipment, and establish a fault diagnosis system and health management system.

[0061] Based on the embodiments provided in this application, real-time data collection is performed on the ship power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data; the collected equipment-level data is processed and analyzed by edge computing to screen key equipment indicator data; according to the real-time online monitoring system of the marine environment and the intelligent shipping embodiment model, the ship embodiment environment is perceived based on the screened key equipment indicator data to obtain the ship embodiment environment; based on the perceived ship embodiment environment, the ship equipment interface is called to obtain real-time ship navigation reference data; wherein, the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface and a navigation guidance interface; a navigation digital twin model is established based on the real-time ship navigation reference data; the established navigation digital twin model is used to simulate and predict the behavior of the ship equipment, and a fault diagnosis system and a health management system are established. Thus, navigation maintenance guidance and fault diagnosis of ship equipment are realized. Specifically, it has the following beneficial effects: real-time data collection of key ship systems can comprehensively monitor the ship's operating status; real-time collection of device-level data can detect potential equipment failures and performance degradations at an early stage; edge computing processing can be used to process data near the data source, reducing the amount of data sent to the central server; edge computing provides fast data processing capabilities, which helps in real-time decision-making and response; sensing the ship's embodied environment can improve the ship's adaptability to changes in the marine environment; real-time reference data can be used to optimize route planning and improve navigation efficiency; by calling the ship's equipment interface, information such as meteorology, hydrology, route planning and navigation guidance can be integrated; improved interaction: standardized interfaces improve data interaction and operational convenience between systems; establishing a digital twin model can simulate the navigation status of a ship in a virtual environment; the fault diagnosis system can identify and locate faults in a timely manner, reducing downtime; the health management system helps monitor equipment health and extend equipment service life; the entire system improves the reliability of ship operation through real-time monitoring and predictive maintenance; and long-term operating costs can be reduced by optimizing maintenance and reducing failures.

[0062] Furthermore, the intelligent shipping embodied big model includes the Kunpeng big model; according to the real-time online monitoring system of the marine environment and the intelligent shipping embodied big model, the ship's embodied environment is perceived based on the selected key equipment indicator data to obtain the ship's embodied environment conditions, including:

[0063] The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; wave dynamic pressure Determined based on the following formula;

[0064] ;

[0065] Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the density of seawater; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment;

[0066] The Kunpeng big model is used to perceive key equipment indicator data and real-time marine environmental element data in order to obtain the ship's embodied environment and realize data interaction between ship equipment and the ship's embodied environment.

[0067] Further, the real-time ship navigation reference data includes first real-time ship navigation reference data and second real-time ship navigation reference data;

[0068] The route planning interface is used to plan a route for ship equipment based on the perceived ship's embodied environmental conditions and meteorological and hydrological perception data, and obtain first real-time ship navigation reference data corresponding to the route; wherein the meteorological and hydrological perception data are various observation data related to water cycle and water balance obtained through the ship-borne meteorological and hydrological perception data interface;

[0069] The navigation guidance interface is used to provide navigation guidance for ship equipment based on the perceived ship's embodied environmental conditions, meteorological and hydrological perception data, and the first real-time ship navigation reference data, and obtain the second real-time ship navigation reference data corresponding to the route to achieve autonomous obstacle avoidance and energy optimization of ship equipment.

[0070] Furthermore, a navigation digital twin model is established based on real-time ship navigation reference data, including:

[0071] Establishing a CAD model of the ship equipment based on the first real-time ship navigation reference data and the second real-time ship navigation reference data;

[0072] Convert the model data of the CAD model of the ship equipment to the Unity platform to obtain the Unity-driven virtual device;

[0073] A Unity-driven virtual device including the first real-time ship navigation reference data and the second real-time ship navigation reference data is published as a navigation digital twin model; wherein the navigation digital twin model is used to realize the pairwise data interaction among the perception data of the ship's physical space, the calculation data of the ship's information space, and the ship service system data.

[0074] Furthermore, the established navigation digital twin model is used to simulate and predict the behavior of ship equipment, and a fault diagnosis system and health management system are established, including:

[0075] Normalize the perception data of the ship's physical space and the calculation data of the ship's information space to obtain the initial time series;

[0076] Given a sliding window length, perform sliding regression on the initial time series to construct a simulated behavior data sample;

[0077] Based on the simulated behavior data samples, a simulated data set of ship equipment navigation in the navigation mission execution scenario is established;

[0078] Generate a Bayesian model according to the simulated data set; update the simulated data set according to the Bayesian model to obtain an updated simulated data set;

[0079] A behavior prediction model is constructed based on convolutional neural network and long short-term memory network; the convolutional neural network contains three hidden layers; the input of the behavior prediction model is the updated simulation data set and the navigation area chart information, and the output of the behavior prediction model is the predicted probability of the behavior of the ship equipment; the behavior of the ship equipment includes speed, heading and ship attitude;

[0080] The behavior prediction model is trained using the updated simulation data set and simulation coefficients to obtain a trained and optimized behavior prediction model;

[0081] The behavior prediction model completed through training and optimization is used to simulate and predict the behavior of ship equipment, and a fault diagnosis system and health management system are established.

[0082] Further, ;

[0083] in, is the simulation coefficient; Indicates the number of predictions made by the behavior prediction model; is the number of times predicted by the behavior prediction model; p represents the actual output value of the behavior prediction model; represents the estimated value of the behavior prediction model, is the number of nodes in the three hidden layers; is the weight matrix of the long short-term memory network, which is used for linear transformation between different layers.

[0084] Furthermore, the fault diagnosis system is used to identify abnormal behavior of ship equipment and predict faults; the health management system is used to predict the service life and performance degradation of ship equipment.

[0085] Alternatively, if Figure 2 As shown, the present application provides a system for constructing a digital human system for ship equipment, including an equipment-level data acquisition unit 201, a key equipment indicator data screening unit 202, a ship embodied environment acquisition unit 203, a ship equipment interface calling unit 204, a navigation digital twin model establishment unit 205, and a behavior simulation prediction unit 206; wherein,

[0086] The equipment-level data acquisition unit 201 is used to collect real-time data of the ship's power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data;

[0087] The key equipment indicator data screening unit 202 is used to process and analyze the collected equipment-level data using edge computing to screen the key equipment indicator data;

[0088] The ship embodied environment condition acquisition unit 203 is used to sense the ship embodied environment based on the selected key equipment indicator data according to the marine environment real-time online monitoring system and the intelligent shipping embodied large model, and obtain the ship embodied environment condition;

[0089] The ship equipment interface calling unit 204 is used to call the ship equipment interface based on the perceived ship's embodied environment to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface;

[0090] A navigation digital twin model building unit 205 is used to build a navigation digital twin model according to real-time ship navigation reference data;

[0091] The behavior simulation prediction unit 206 is used to simulate and predict the behavior of ship equipment using the established navigation digital twin model, and to establish a fault diagnosis system and a health management system.

[0092] Furthermore, the intelligent shipping embodied big model includes the Kunpeng big model; the ship embodied environment acquisition unit senses the ship embodied environment based on the real-time online monitoring system of the marine environment and the intelligent shipping embodied big model and the screened key equipment indicator data to obtain the ship embodied environment status, which is specifically configured as follows:

[0093] The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; wave dynamic pressure Determined based on the following formula;

[0094] ;

[0095] Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the density of seawater; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment;

[0096] The Kunpeng big model is used to perceive key equipment indicator data and real-time marine environmental element data in order to obtain the ship's embodied environment and realize data interaction between ship equipment and the ship's embodied environment.

[0097] Furthermore, the fault diagnosis system is used to identify abnormal behavior of ship equipment and predict faults; the health management system is used to predict the service life and performance degradation of ship equipment.

[0098] It should be noted that in the present application, the embodiments implemented on the construction system side of the digital human system for ship equipment can be referenced with the embodiments implemented on the construction method side of the digital human system for ship equipment, and this application will not go into details one by one.

[0099] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for constructing a digital human system for ship equipment, characterized in that: include: Collect real-time data of ship power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain equipment-level data; Using edge computing to process and analyze the collected device-level data and filter key device indicator data; According to the real-time online monitoring system of the marine environment and the intelligent shipping embodied large model, the embodied environment of the ship is perceived based on the selected key equipment indicator data to obtain the embodied environment of the ship; Based on the perceived embodied environment of the ship, the ship equipment interface is called to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface; Establishing a navigation digital twin model based on the real-time ship navigation reference data; The real-time ship navigation reference data includes first real-time ship navigation reference data and second real-time ship navigation reference data; The route planning interface is used to plan a route for the ship equipment based on the perceived embodied environmental conditions of the ship and the meteorological and hydrological perception data, and obtain the first real-time ship navigation reference data corresponding to the route; wherein the meteorological and hydrological perception data are various observation data related to water cycle and water balance obtained through the ship-borne meteorological and hydrological perception data interface; The navigation guidance interface is used to provide navigation guidance for the ship equipment based on the perceived embodied environmental conditions of the ship, the meteorological and hydrological perception data, and the first real-time ship navigation reference data, and obtain the second real-time ship navigation reference data corresponding to the route, so as to achieve autonomous obstacle avoidance and energy optimization of the ship equipment; The establishing of the navigation digital twin model according to the real-time ship navigation reference data comprises: Establishing a CAD model of the ship equipment based on the first real-time ship navigation reference data and the second real-time ship navigation reference data; Converting the model data of the CAD model of the ship equipment to the Unity platform to obtain a Unity-driven virtual device; Publishing the Unity-driven virtual device including the first real-time ship navigation reference data and the second real-time ship navigation reference data as the navigation digital twin model; wherein the navigation digital twin model is used to realize the pairwise data interaction between the perception data of the ship's physical space, the calculation data of the ship's information space, and the ship's service system data; The established navigation digital twin model is used to simulate and predict the behavior of ship equipment, and a fault diagnosis system and health management system are established, including: Normalizing the perception data of the ship's physical space and the calculation data of the ship's information space to obtain an initial time series; Given a sliding window length, performing sliding regression on the initial time series to construct a simulated behavior data sample; Establishing a simulation data set of the navigation of the ship equipment in the navigation mission execution scenario based on the simulation behavior data sample; Generate a Bayesian model according to the simulated data set; update the simulated data set according to the Bayesian model to obtain an updated simulated data set; A behavior prediction model is constructed based on a convolutional neural network and a long short-term memory network; wherein the convolutional neural network includes three hidden layers; the input of the behavior prediction model is an updated simulation data set and navigation area chart information, and the output of the behavior prediction model is a predicted probability of the behavior of the ship equipment; the behavior of the ship equipment includes speed, heading and ship attitude; Using the updated simulation data set and simulation coefficients to train the behavior prediction model to obtain a trained and optimized behavior prediction model; The behavior prediction model completed through training and optimization is used to simulate and predict the behavior of the ship equipment, and the fault diagnosis system and the health management system are established.

2. The method for constructing a digital human system for ship equipment according to claim 1, characterized in that: The intelligent shipping embodied large model includes a Kunpeng large model; the real-time online monitoring system for the marine environment and the intelligent shipping embodied large model perceive the ship's embodied environment based on the selected key equipment indicator data to obtain the ship's embodied environment conditions, including: The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; wherein the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; the wave dynamic pressure Determined based on the following formula; ； Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the seawater density; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment; The Kunpeng big model is used to perceive the key equipment indicator data and the real-time marine environmental element data to obtain the ship's embodied environment and realize data interaction between the ship's equipment and the ship's embodied environment.

3. The method for constructing a digital human system for ship equipment according to claim 1, characterized in that: ； in, is the simulation coefficient; represents the number of predictions made by the behavior prediction model; is the number of times predicted by the behavior prediction model; p represents the actual output value of the behavior prediction model; represents the estimated value of the behavior prediction model, is the number of nodes in the three hidden layers; is the weight matrix of the long short-term memory network, and the weight matrix is ​​used for linear transformation between different layers.

4. The method for constructing a digital human system for ship equipment according to claim 1, characterized in that: The fault diagnosis system is used to identify abnormal behavior of the ship equipment and predict faults; the health management system is used to predict the service life and performance degradation of the ship equipment.

5. A system for constructing a digital human system for ship equipment, the system implementing the method according to claim 1, characterized in that: It includes equipment-level data acquisition unit, key equipment indicator data screening unit, ship embodied environment acquisition unit, ship equipment interface calling unit, navigation digital twin model establishment unit and behavior simulation prediction unit; among them, The device-level data acquisition unit is used to collect real-time data on the ship's power system, navigation system, propulsion system, steering gear system, power supply system, life-saving equipment system, gas detection system, oil mist concentration detection system and temperature monitoring system to obtain device-level data; The key equipment indicator data screening unit is used to process and analyze the collected equipment-level data by using edge computing to screen the key equipment indicator data; The ship embodied environment condition acquisition unit is used to sense the ship embodied environment based on the selected key equipment indicator data according to the marine environment real-time online monitoring system and the intelligent shipping embodied large model, and obtain the ship embodied environment condition; The ship equipment interface calling unit is used to call the ship equipment interface based on the perceived ship's embodied environment to obtain real-time ship navigation reference data; wherein the ship equipment interface includes a ship-borne meteorological and hydrological perception data interface, a route planning interface, and a navigation guidance interface; The navigation digital twin model building unit is used to build a navigation digital twin model according to the real-time ship navigation reference data; The behavior simulation and prediction unit is used to simulate and predict the behavior of ship equipment using the established navigation digital twin model, and to establish a fault diagnosis system and a health management system.

6. The system for constructing a digital human system for ship equipment according to claim 5, characterized in that: The intelligent shipping embodied large model includes a Kunpeng large model; the ship embodied environment acquisition unit senses the ship embodied environment based on the selected key equipment indicator data according to the real-time online marine environment monitoring system and the intelligent shipping embodied large model, and obtains the ship embodied environment, and is specifically configured as follows: The real-time online monitoring system for the marine environment is used to obtain real-time marine environmental element data; wherein the real-time marine environmental element data include: water temperature, conductivity, salinity, dissolved oxygen, pH, turbidity, chlorophyll, nitrate, nitrite, ammonia nitrogen, phosphate, total phosphorus, total nitrogen, seawater flow rate, seawater density, seawater depth, wave amplitude, wave frequency, wave dynamic pressure, temperature, air pressure, relative humidity, rainfall and light; the wave dynamic pressure Determined based on the following formula; ； Wherein, (x, y, z) are the center coordinates of the contact surface between the ship equipment and the seawater; x represents the lateral position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of x is defined as pointing to the starboard side of the ship equipment; y represents the longitudinal position of the center of the contact surface between the ship equipment and the seawater in the horizontal plane, and the positive direction of y is defined as pointing to the stern of the ship equipment; z represents the vertical position of the center of the contact surface between the ship equipment and the seawater, and the positive direction of z is defined as pointing above the sea level, opposite to the direction of gravity; is gravity; is the wave amplitude; is the seawater density; is the wave number; is the seawater depth; is the wave frequency; For time; is the heading angle of the ship equipment; The Kunpeng big model is used to perceive the key equipment indicator data and the real-time marine environmental element data to obtain the ship's embodied environment and realize data interaction between the ship's equipment and the ship's embodied environment.

7. The system for constructing a digital human system for ship equipment according to claim 5, characterized in that: The fault diagnosis system is used to identify abnormal behavior of the ship equipment and predict faults; the health management system is used to predict the service life and performance degradation of the ship equipment.

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