A method for obtaining a target digital twin, an electronic device and a storage medium

Abstract

The present invention provides a method for obtaining a target digital twin, an electronic device and a storage medium, and relates to the field of digital twin technology. The target digital twin is a digital twin of a cutter suction dredger. The method can obtain a target operation process model and comprehensive forecast information, integrate initial data corresponding to the cutter suction dredger, all preset models in a preset model library, initial system data corresponding to a target dredging ship control system, a target operation process model and comprehensive forecast information to obtain the target digital twin, update the initial data based on intermediate system data corresponding to the target dredging ship control system generated by the target digital twin, and further update the target digital twin. It can be seen that the present invention can apply digital twin technology to a cutter suction dredger to obtain a target digital twin, can significantly improve the operating efficiency and safety of the dredger, and is conducive to promoting the intelligent process of water conservancy projects and port construction.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a method for obtaining a target digital twin, an electronic device and a storage medium. Background Art

[0002] Cutter suction dredger is a kind of ship widely used in dredging operations, mainly used to remove sediments in waterways, ports and lakes. Digital twin technology is a technology that combines physical systems with virtual models. It realizes accurate simulation and optimization of physical systems through real-time data acquisition, model simulation and optimization algorithms. In recent years, digital twin technology has begun to be applied to the fields of shipbuilding and marine engineering. In the operation process of traditional cutter suction dredgers, due to the lack of real-time and high-precision model support, it is often difficult to achieve accurate control and optimization of the operation process. Therefore, digital twin technology can be introduced to construct the digital twin of the cutter suction dredger, that is, the target digital twin, to achieve accurate control and optimization of the operation process, thereby improving the operation efficiency and safety of the cutter suction dredger, which is conducive to promoting the intelligent process of water conservancy projects and port construction. However, in the existing technology, due to the significant professional characteristics of the dredging industry, the professional application requirements of digital twin technology are high. Therefore, digital twin technology has not yet been maturely applied in cutter suction dredgers. Summary of the invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is:

[0004] According to a first aspect of the present invention, a method for obtaining a target digital twin is provided, wherein the target digital twin is a digital twin of a cutter suction dredger, and the method comprises the following steps:

[0005] Based on the initial data corresponding to the cutter suction dredger and the preset model library, the target operation process model corresponding to the cutter suction dredger is obtained, wherein the initial data corresponding to the cutter suction dredger is the data obtained after standardization of the data collected by the cutter suction dredger during the current operation process, and the target operation process model corresponding to the cutter suction dredger is a virtual model that can simulate and optimize the current operation process of the cutter suction dredger.

[0006] Based on the initial data corresponding to the cutter suction dredger and the preset model library, comprehensive forecast information is obtained. The comprehensive forecast information includes: real-time cross-section diagram of soil layers and hydrological perception compensation results.

[0007] The initial data corresponding to the cutter suction dredger, all preset models in the preset model library, the initial system data corresponding to the target dredging ship control system, the target operation process model and the comprehensive forecast information are integrated to obtain the target digital twin. The initial system data corresponding to the target dredging ship control system include working parameters, control parameters and management data. The working parameters include mud flow rate and mud density. The control parameters include motor speed, diesel engine speed and winch speed. The management data includes maximum excavation output, maximum transportation output and maximum shore discharge output.

[0008] The intermediate system data corresponding to the target dredging vessel control system is input into the target dredging vessel control system so that the initial data corresponding to the cutter suction dredger is updated. The intermediate system data corresponding to the target dredging vessel control system is generated by the target digital twin, including working parameters, control parameters and management data.

[0009] The updated initial data corresponding to the cutter suction dredger is synchronized to the target digital twin in real time, and the step of obtaining the target operation process model corresponding to the cutter suction dredger based on the initial data corresponding to the cutter suction dredger and the preset model library is entered to update the target digital twin.

[0010] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, in which a computer program is stored. The computer program is loaded and executed by a processor to implement the aforementioned method.

[0011] According to a third aspect of the present invention, there is provided an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method when executing the computer program.

[0012] The present invention has at least the following beneficial effects:

[0013] The present invention provides a method for obtaining a target digital twin, an electronic device and a storage medium, wherein the target digital twin is a digital twin of a cutter suction dredger. The method can obtain a target operation process model and comprehensive forecast information, integrate initial data corresponding to the cutter suction dredger, all preset models in a preset model library, initial system data corresponding to a target dredging ship control system, a target operation process model and comprehensive forecast information to obtain the target digital twin, update the initial data based on intermediate system data corresponding to the target dredging ship control system generated by the target digital twin, and further update the target digital twin according to the updated initial data. It can be seen that the present invention can apply digital twin technology to a cutter suction dredger to obtain a target digital twin, can significantly improve the operating efficiency and safety of the dredger, and is conducive to promoting the intelligent process of water conservancy projects and port construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 A flowchart of a method for obtaining a target digital twin provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0017] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar tasks, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0018] An embodiment of the present invention provides a method for obtaining a target digital twin, wherein the target digital twin is a digital twin of a cutter suction dredger, and the method comprises the following steps: Figure 1 As shown:

[0019] S1. Based on the initial data corresponding to the cutter suction dredger and the preset model library, a target operation process model corresponding to the cutter suction dredger is obtained, wherein the initial data corresponding to the cutter suction dredger is the data obtained after standardization of the data collected by the cutter suction dredger during the current operation process, and the target operation process model corresponding to the cutter suction dredger is a virtual model that can simulate and optimize the current operation process of the cutter suction dredger.

[0020] Specifically, the data collected by the cutter suction dredger during operation include working condition data, ship data, and process data. The working condition data include soil drilling data and real-time water depth data, the ship data include ship draft, ship engine power and energy consumption, and the process data include auger speed, mud flow rate, mud density, mud pump vacuum and traverse speed.

[0021] Furthermore, the soil drilling data includes: geological data, soil physical property data and mechanical property data; the geological data includes soil layer number, soil layer depth range and soil layer type; the physical property data includes particle size, density, porosity and plasticity index; the mechanical property data includes compressive strength, shear strength and unconfined compressive strength.

[0022] Furthermore, the water depth data includes the geographical location of the measurement point and the recorded water depth value.

[0023] Specifically, the preset model library includes several preset models, which are three-dimensional models related to the cutter suction dredger, including: a hull simulation model, a dredging equipment model, a power model, a soil model, a reamer breaking model and a pipeline transportation model.

[0024] Specifically, the model depth level of each preset model is a preset depth level. The preset depth level is the depth level determined by technical personnel in this field according to actual needs. The depth level is used to standardize the establishment and application of water transport engineering information models to ensure the accuracy and detail of the models in different stages and application scenarios. It will not be repeated here.

[0025] Specifically, the hull simulation model includes several moving structures and each moving structure is associated with the hull simulation model, so that the hull simulation model can be deformed with the movement of the moving structure. Among them, those skilled in the art know that the rotation axis, maximum rotation angle and minimum rotation angle of the moving structure are set by those skilled in the art according to actual needs and will not be repeated here.

[0026] Furthermore, the driving parameters corresponding to the motion structure are associated with the control parameters of the target dredging ship control system through linear mapping and PID control algorithm so that the hull simulation model and the target dredging ship control system can synchronize the motion control of the cutter suction dredger in real time. The target dredging ship control system is the dredging ship control system corresponding to the cutter suction dredger, wherein the PID control algorithm is adopted to adjust the control gain so that the target dredging ship control system outputs the position of the motion structure, and at the same time, the sensor is used to monitor the position and motion state of the motion structure in real time, and the position and motion state of the motion structure monitored in real time are fed back to the target dredging ship control system. The target dredging ship control system can adjust the control parameters in real time according to the received position and motion state of the motion structure, which can ensure the stability of the control parameters and can also ensure that the motion structure can move accurately.

[0027] Specifically, the hull posture of the hull simulation model and the water depth data are associated through the nonlinear mapping method of the neural network and the PID control algorithm so that the hull posture of the hull simulation model can be adjusted as the water depth changes.

[0028] Specifically, based on the reamer breaking soil model and the soil model, the reamer posture is associated with the current soil layer soil drilling data parameters so that the reamer posture can be adjusted as the soil layer changes. The reamer posture is adjusted by mapping the relative relationship between the water depth position given by the reamer depth sensor and the working soil layer elevation position, so that the reamer is always tangent to the working soil layer and the intersection angle with the horizon is maintained at 60°.

[0029] Specifically, the pipeline transportation model and the power model are associated with the process data so that the values ​​of the pipeline transportation model and the power model are synchronized with the process data in real time.

[0030] S2. Based on the initial data corresponding to the cutter suction dredger and the preset model library, comprehensive forecast information is obtained. The comprehensive forecast information includes: real-time cross-section diagram of soil layers and hydrological perception compensation results.

[0031] S3. Integrate the initial data corresponding to the cutter suction dredger, all preset models in the preset model library, the initial system data corresponding to the target dredging ship control system, the target operation process model and the comprehensive forecast information to obtain the target digital twin. The initial system data corresponding to the target dredging ship control system includes working parameters, control parameters and management data. The working parameters include mud flow rate and mud density. The control parameters include motor speed, diesel engine speed and winch speed. The management data is the dredging output that characterizes the work efficiency, including the maximum excavation output, the maximum transportation output and the maximum shore discharge output.

[0032] Specifically, the target digital twin can be understood as a virtual model of the cutter suction dredger and the target dredging vessel control system.

[0033] Specifically, the target dredging vessel control system includes a reamer control system, a bridge control system, a transverse anchor truck control system, and a mud pump control system.

[0034] S4. Input the intermediate system data corresponding to the target dredging ship control system into the target dredging ship control system so as to update the initial data corresponding to the cutter suction dredger. The intermediate system data corresponding to the target dredging ship control system is generated by the target digital twin, including working parameters, control parameters and management data.

[0035] S5. Synchronize the updated initial data corresponding to the cutter suction dredger to the target digital twin in real time, and proceed to step S1 to update the target digital twin.

[0036] Specifically, when the cutter suction dredger is operating, the target digital twin is used for real-time monitoring to provide timely feedback on the working status of the cutter suction dredger.

[0037] Furthermore, the sensor data such as flow meters, concentration meters, pressure gauges, encoders, etc. deployed on the cutter suction dredger are communicated and connected with the visualization dashboard, and the real-time data presented by the visualization dashboard is analyzed to identify anomalies and trends to achieve real-time monitoring of the target digital twin.

[0038] Specifically, twin information can be extracted based on the indicators of the target digital twin to support decision making.

[0039] Specifically, after each anchor pile replacement cycle of the cutter suction dredger is completed, step S4 and step S5 are executed. The anchor pile replacement cycle is the time required for the entire process from one anchor pile fixing to the next anchor pile fixing of the cutter suction dredger.

[0040] Through the above steps, the target operation process model and comprehensive forecast information are obtained, the initial data corresponding to the cutter suction dredger, all preset models in the preset model library, the initial system data corresponding to the target dredging ship control system, the target operation process model and the comprehensive forecast information are integrated to obtain the target digital twin, the initial data is updated based on the intermediate system data corresponding to the target dredging ship control system generated by the target digital twin, and the target digital twin is further updated according to the updated initial data. The digital twin technology can be applied to the cutter suction dredger to obtain the target digital twin, and the data association between the cutter suction dredger and the target data twin can be ensured, which can significantly improve the operating efficiency and safety of the dredger, and is conducive to promoting the intelligent process of water conservancy projects and port construction.

[0041] Specifically, the step of standardizing the data collected by the cutter suction dredger during the current operation to obtain initial data includes the following steps:

[0042] Data cleaning is performed on data collected by the cutter suction dredger during the current operation process to obtain first intermediate data, wherein the data cleaning includes removing duplicate data, processing missing values, and identifying and correcting errors in the data.

[0043] The first intermediate data is transformed to obtain second intermediate data, wherein the data transformation includes converting all data into a unified format, using a unified coding system for categorical variables, and standardizing numerical data.

[0044] The second intermediate data is integrated to obtain initial data, wherein the data integration includes merging data from different sources and defining a unified data structure and relationship for storage.

[0045] Specifically, step S1 also includes the following steps:

[0046] An initial operation process model library is obtained based on a plurality of preset operation conditions, wherein the initial operation process model library includes a plurality of initial operation process models.

[0047] Specifically, the initial operation process model corresponds one-to-one to the preset operation conditions.

[0048] Furthermore, the initial operation process model is a virtual model that can simulate and optimize the operation process of the cutter suction dredger under its corresponding preset operating conditions. Those skilled in the art know that the preset operating conditions are operating conditions pre-set by those skilled in the art according to actual needs and will not be elaborated here.

[0049] Build a rapid modeling system based on the preset model library and initial operation process module library.

[0050] Input the initial data into the rapid modeling system to obtain the target operation process model.

[0051] Specifically, the process of generating the target operation process model by the rapid modeling system also includes the following steps:

[0052] An intermediate workflow model is determined from all initial workflow models based on the initial data.

[0053] Several intermediate models are determined from a preset database based on the initial data.

[0054] Several intermediate models are called at the same time to be combined to obtain several intermediate model groups.

[0055] An intermediate model group corresponding to the current operating conditions is selected from a number of intermediate model groups and used as the key model group.

[0056] All models in the key model group are fused with the intermediate job process model to obtain the target job process model.

[0057] Through the above steps, the preset model library includes several preset models, and the functions, attributes and relationships between the preset models are relatively clear. A rapid modeling system is built according to the preset model library and the initial operation process module library, and the initial data is input into the rapid modeling system to obtain the target operation process model. The target operation process model can be obtained quickly and digital-analog linkage can be realized.

[0058] Specifically, step S2 includes the following steps:

[0059] The initial data is processed to obtain soil layer information corresponding to each soil layer, and the soil layer information includes: soil layer thickness, soil type, soil physical property data and soil mechanical property data.

[0060] Specifically, the soil layer thickness is determined based on the effective soil breaking thickness of the cutter suction dredger.

[0061] The soil layer information and real-time hydrological data corresponding to all soil layers are fused to obtain a comprehensive dataset.

[0062] Build predictive models based on preset models and comprehensive datasets in the preset model library.

[0063] The forecast information generated by the prediction model is used as comprehensive forecast information.

[0064] Specifically, the process of generating forecast information by the prediction model also includes the following steps:

[0065] The soil model is constructed based on the soil layer information corresponding to each soil layer.

[0066] The soil model is sectioned in real time based on the real-time sectioning rules to obtain the real-time sectioning diagram of the soil layer.

[0067] Based on the hydrological perception compensation rule, the hydrological information corresponding to the current operating area of ​​the cutter suction dredger is processed to obtain the hydrological perception compensation result.

[0068] Through the above steps, a comprehensive data set is obtained based on soil layer information and hydrological data, and comprehensive forecast information is obtained based on the comprehensive data set and the preset model component prediction model. The comprehensive forecast information includes: real-time cross-section diagram of the soil layer, hydrological perception compensation results, and can be obtained during the operation of the cutter suction dredger to avoid the impact caused by the complex marine environment and the difficulty of real-time data collection, thereby reducing the difficulty and processing volume of real-time data collection while improving the quality and accuracy of the data.

[0069] Specifically, when the current operation of the cutter suction dredger is completed and the next operation is about to be carried out, the latest soil layer information and water depth data obtained from the current operation are mapped to the soil model to update the soil model, and then based on the geological exploration data and water depth data of the next operation area, the state parameters of the soil model, such as soil type, density, and water content, are adjusted to update the soil model again.

[0070] In a specific embodiment, after step S3 and before step S4, the following steps are further included to update the target digital twin:

[0071] Compare the output of the target digital twin with the actual operation results to obtain verification results, which are used to verify the accuracy and reliability of the target digital twin;

[0072] The parameters of the target digital twin are adjusted according to the verification results so as to update the target digital twin.

[0073] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, which can be set in an electronic device to store a computer program related to a method in a method embodiment, and the computer program is loaded and executed by the processor to implement the method provided in the above embodiment.

[0074] An embodiment of the present invention further provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the above embodiment when executing the computer program.

[0075] An embodiment of the present invention further provides a computer program product, which includes program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present invention described above in this specification.

[0076] The present invention provides a method for obtaining a target digital twin, an electronic device and a storage medium, wherein the target digital twin is a digital twin of a cutter suction dredger. The method can obtain a target operation process model and comprehensive forecast information, integrate initial data corresponding to the cutter suction dredger, all preset models in a preset model library, initial system data corresponding to a target dredging ship control system, a target operation process model and comprehensive forecast information to obtain the target digital twin, update the initial data based on intermediate system data corresponding to the target dredging ship control system generated by the target digital twin, and further update the target digital twin according to the updated initial data. It can be seen that the present invention can apply digital twin technology to a cutter suction dredger to obtain a target digital twin, can significantly improve the operating efficiency and safety of the dredger, and is conducive to promoting the intelligent process of water conservancy projects and port construction.

[0077] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are only for illustration, not for limiting the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention.

Claims

1. A method for obtaining a target digital twin, characterized in that: The target digital twin is a digital twin of a cutter suction dredger, and the method comprises the following steps: Based on the initial data corresponding to the cutter suction dredger and the preset model library, a target operation process model corresponding to the cutter suction dredger is obtained, wherein the initial data corresponding to the cutter suction dredger is data obtained after standardization of data collected during the current operation of the cutter suction dredger, and the target operation process model corresponding to the cutter suction dredger is a virtual model capable of simulating and optimizing the current operation process of the cutter suction dredger. The data collected during the operation of the cutter suction dredger include working condition data, ship data, and process data, wherein the working condition data include soil drilling data and real-time water depth data; Based on the initial data and preset model library corresponding to the cutter suction dredger, comprehensive forecast information is obtained, and the comprehensive forecast information includes: real-time cross-section diagram of soil layer and hydrological perception compensation result; in the step of obtaining comprehensive forecast information based on the initial data and preset model library corresponding to the cutter suction dredger, the following steps are included: Process the initial data to obtain soil layer information corresponding to each soil layer, including soil layer thickness, soil type, and soil physical property data; Fusion of soil layer information and real-time hydrological data corresponding to all soil layers to obtain a comprehensive data set; Build prediction models based on preset models and comprehensive data sets in the preset model library; The forecast information generated by the forecast model is used as comprehensive forecast information; The initial data corresponding to the cutter suction dredger, all preset models in the preset model library, the initial system data corresponding to the target dredging ship control system, the target operation process model and the comprehensive forecast information are integrated to obtain the target digital twin. The target dredging ship control system is the dredging ship control system corresponding to the cutter suction dredger. The initial system data corresponding to the target dredging ship control system includes working parameters, control parameters and management data. The working parameters include mud flow rate and mud density. The control parameters include motor speed, diesel engine speed and winch speed. The management data includes maximum excavation output, maximum transportation output and maximum shore discharge output. Inputting the intermediate system data corresponding to the target dredging vessel control system into the target dredging vessel control system so as to update the initial data corresponding to the cutter suction dredger, the intermediate system data corresponding to the target dredging vessel control system being generated by the target digital twin, including working parameters, control parameters and management data; The updated initial data corresponding to the cutter suction dredger is synchronized to the target digital twin in real time, and the step of obtaining the target operation process model corresponding to the cutter suction dredger based on the initial data corresponding to the cutter suction dredger and the preset model library is entered to update the target digital twin.

2. The method for obtaining a target digital twin according to claim 1, characterized in that: The ship data include ship draft, engine power and energy consumption, and the process data include auger speed, mud flow rate, mud density, mud pump vacuum and traverse speed.

3. The method for obtaining a target digital twin according to claim 1, characterized in that: The soil drilling data includes: geological data, soil physical property data and mechanical property data; the geological data includes soil layer number, soil layer depth range and soil layer type; the physical property data includes particle size, density, porosity and plasticity index; the mechanical property data includes compressive strength, shear strength and unconfined compressive strength.

4. The method for obtaining a target digital twin according to claim 1, characterized in that: The water depth data includes the geographical location of the measurement point and the recorded water depth value.

5. The method for obtaining a target digital twin according to claim 1, characterized in that: The preset model library includes several preset models, which are three-dimensional models related to the cutter suction dredger, including: hull simulation model, dredging equipment model, power model, soil model, reamer breaking model and pipeline transportation model.

6. The method for obtaining a target digital twin according to claim 1, characterized in that: In the step of obtaining a target operation process model corresponding to the cutter suction dredger based on the initial data corresponding to the cutter suction dredger and the preset model library, the following steps are also included: Based on a number of preset operating conditions, an initial operating process model library is obtained, wherein the initial operating process model library includes a number of initial operating process models, and the initial operating process models correspond to the preset operating conditions one by one. The initial operating process model is a virtual model capable of simulating and optimizing the operating process of the cutter suction dredger under its corresponding preset operating conditions; Build a rapid modeling system based on the preset model library and initial operation process module library; Input the initial data into the rapid modeling system to obtain the target operation process model.

7. The method for obtaining a target digital twin according to claim 1, characterized in that: The process of generating forecast information from the prediction model also includes the following steps: Construct a soil model based on the soil layer information corresponding to each soil layer; Based on the real-time sectioning rules, the soil model is sectioned in real time to obtain the real-time sectioning diagram of the soil layer; Based on the hydrological perception compensation rule, the hydrological information corresponding to the current operating area of ​​the cutter suction dredger is processed to obtain the hydrological perception compensation result.

8. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores a computer program, which is loaded and executed by a processor to implement the method for obtaining a target digital twin as described in any one of claims 1 to 7.

9. An electronic device, comprising: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for obtaining a target digital twin as described in any one of claims 1 to 7 when executing the computer program.

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