Ship propulsion shafting digital twinning method

Abstract

The invention belongs to the technical field of ship power device design methods, and particularly relates to a ship propulsion shafting digital twinning method. The method comprises the following steps: establishing a geometric model of the propulsion shafting; constructing a shafting 1D prediction model; carrying out shafting dynamics analysis; constructing a digital twinborn body of the propulsion shaft system; establishing a relation between the digital twinborn body and the entity; iterating the digital twin 1D prediction model; according to the method, the visual three-dimensional geometric model is built based on the 1D prediction model, the overall digital twinning level of the ship propulsion shafting is improved, the visibility of the propulsion shafting is enhanced, and the life analysis, fault early warning and performance calculation capabilities of digital twinning of the propulsion shafting are improved; based on comparison between real-time data updating of a data acquisition system and historical operation data, a scheme is provided for updating iteration of a ship propulsion shafting 1D prediction model.

Description

Technical Field

[0001] The present application belongs to the technical field of ship power plant design methods, and in particular, relates to a digital twin method for ship propulsion shaft systems. Background Art

[0002] The propulsion shaft system, also known as the transmission shaft system, includes the transmission shaft, connection device, support device, sealing device, etc. It is an important part of the ship's power plant. With the continuous improvement of the ship design concept, the structure of the propulsion shaft system has become more complex, the application requirements are higher, and the operation status of the shaft system has a greater impact on the reliability and maneuverability of the power plant. In order to ensure that the propulsion shaft system reduces the possibility of shaft system operation failure during design and application, the shaft system is analyzed for life, fault warning and performance calculation, and the method of using digital twins to perform real-time analysis and prediction of its operation status has become mature. Usually, different disciplines such as dynamics, thermodynamics, material mechanics, fluid mechanics, elastic mechanics, and vibration mechanics are integrated to construct a one-dimensional mathematical model. In the traditional digital twin method, more attention is usually paid to the establishment of the mathematical model of the corresponding entity, or the establishment and verification of various types of models, and not much attention is paid to the visualization of the mathematical model. The overall digital twin method of the propulsion shaft system only performs digital twins on each part of the propulsion shaft system separately, and lacks visualization process on the mobile device side. Therefore, the monitoring and prediction of the operation status of the propulsion shaft system lacks comprehensiveness, comprehensiveness, and visibility. Summary of the invention

[0003] The purpose of this application is to propose a mobile-based digital twin method for the propulsion shaft system, in order to address the problem that the overall digital twin of the propulsion shaft system lacks comprehensiveness, integration and visibility, while taking into account the overall operating conditions, so as to improve the reliability and visibility of the digital twin model.

[0004] To achieve the above objectives, this application adopts the following technical solutions.

[0005] A propulsion shaft system digital twin method of the present invention comprises the following steps:

[0006] Step 1: Establish the geometric model of the propulsion shaft system

[0007] Specifically, it means to establish a virtual geometric model based on the physical propulsion shaft system object, in which the motor is used as the input end of the propulsion shaft system to provide propulsion power. The required data mainly include input power, speed, frequency, torque, external dimensions, etc.; the data required for the propulsion shaft system mainly include the overall layout of the shaft system, the inner and outer diameters of each shaft segment, the material properties of each component of the shaft system, the model and position of each bearing, the model and size of each connecting part, etc.; the data required for the load end mainly include external dimensions, mass, output power, torque, etc.

[0008] Step 2: Build a 1D prediction model for the shaft system

[0009] Specifically, based on the propulsion shaft system geometric model established in step 1, a propulsion shaft system 1D prediction model is established. The calculation model includes:

[0010] Torque power calculation model: N = K*D 5 *ρ*n 2

[0011] P=N*n / 9550

[0012] Where N is the shaft output torque, K is the propeller torque coefficient, D is the propeller diameter, ρ is the water density, n is the shaft speed, and P is the shaft output power;

[0013] Step 3: Shafting Dynamics Analysis

[0014] Specifically, based on the propulsion shaft system geometric model established in step 1, the finite element method is used to establish a vibration and alignment calculation model based on the rotor dynamics of the propeller shaft system, including:

[0015] Total weight of shaft system:

[0016] Where G is the total weight of the shaft system, ρ i is the mass density of each shaft segment, D i is the outer diameter of each shaft segment, d i is the inner diameter of each shaft segment, l i is the length of each axis, G e is the total mass of other equipment in the propulsion shaft system, i is the number of shaft sections, and I is the total number of shaft sections;

[0017] Vibration calculation model of rotor dynamics equation:

[0018] Where, [M] is the propulsion shaft system mass matrix, [C] is the propulsion shaft system damping matrix, [K] is the propulsion shaft system stiffness matrix, x is the propulsion shaft system displacement, F is the propulsion shaft system force, and t refers to the propulsion shaft system operation time;

[0019] Finite element method is used to establish the calibration calculation model:

[0020] [K]a 2n×1 =P 2n×1

[0021] In the formula, a 2n×1 is the node displacement vector, P 2n×1 is the system load vector;

[0022] Step 4: Build a digital twin of the propulsion shaft system

[0023] Specifically, according to the geometric model in step one, based on the requirements of visualization, interactivity and feedback, the digital twin model of the propulsion shaft system is imported into the selected 3D modeling development engine; according to the calculation and analysis models in steps two and three, a suitable programming language is selected as the scripting language to write the relevant processing logic;

[0024] Step 5: Build the connection between digital twins and entities

[0025] Based on the digital twin in step 4, establish an information interaction and real-time update system between the virtual and physical propulsion shaft system.

[0026] Specifically, it means selecting the information data that needs to be collected, including: real-time shaft system speed, shaft system output torque, shaft system output power, shaft system vibration frequency, shaft system vibration amplitude, shaft system rotation time, bending stress of each shaft section of the shaft system, and reaction force of each support bearing of the shaft system.

[0027] Import the collected information data into the human-computer interaction software, and link it with the parameters in the digital twin of the propulsion shaft system in the mobile terminal. Use the programming language to mobilize the corresponding calculation software to solve the calculation and analysis models in steps two and three.

[0028] Step 6: Digital Twin 1D Prediction Model Iteration

[0029] Specifically, according to the solution results in step 5, the rule model is constructed, including:

[0030] Create boundary conditions:

[0031] a. The shaft speed is less than the critical speed, that is, n <n cr ;

[0032] b. The bending stress σ at each shaft end of the shaft system is not greater than the maximum allowable stress [σ], that is, σ<[σ];

[0033] c. The difference in reaction force between the front and rear bearings of the large gear does not exceed 20% of the total weight of the span shaft section and the large gear, that is, ΔN<0.2G C ;

[0034] Based on the experimental data after connecting to the entity, when the experimental error is greater than 2.5%, data calibration is performed, the entity data is re-measured and fed back to the digital twin, the static characteristic index of the sensor instrument is determined, the system error value is eliminated, and the similarity between the digital twin and the entity is improved;

[0035] The aforementioned propulsion shaft system digital twin method is further refined, including: using a suitable 3D engine, in the form of animation and free perspective rotation, to achieve all-round observation and visualization of the propulsion shaft system digital twin model, displaying the corresponding calculation and analysis results at the corresponding position, and processing the results. The processing methods include: storage, export, drawing, simulation calculation, etc.

[0036] Its beneficial effects are:

[0037] 1) Based on 3D modeling software and 1D prediction model, the calculation results are displayed in a visual form, which enhances the efficiency of human-computer data interaction, makes the expression of calculation results more in line with the understanding of the human brain, simplifies complex data, and makes important data intuitive and easy to understand;

[0038] 2) The construction of digital twins based on entities can realize simulation experiments with smaller errors, reduce design problems, improve design efficiency, and realize the propulsion shaft system digital twin to perform life analysis, fault warning and performance calculation on the entity.

[0039] 3) Based on the accumulation of real data, the digital twin model can be updated and iterated, the errors caused by the data acquisition system can be eliminated, the accuracy of the digital twin can be improved, and the fault prediction capability of the digital twin of the propulsion shaft system can be enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 To promote the implementation flow chart of the shaft system digital twin method;

[0041] Figure 2 Build the client software framework for digital twins. DETAILED DESCRIPTION

[0042] The present application is described in detail below in conjunction with specific embodiments.

[0043] This application is a propulsion shaft system digital twin method, which is mainly used in the technical design and design application stage of ship shaft systems. In order to improve the level of propulsion shaft system digital twins, enhance the visibility of propulsion shaft systems, improve the design and application level of propulsion shaft systems, and improve the life analysis, fault warning, and performance calculation capabilities of propulsion shaft system digital twins, in the propulsion shaft system digital twin design method, based on the 1D prediction model, a visual three-dimensional geometric model is built, and certain technical means are used to connect it with the entity, and the state parameters are updated in real time to realize the overall design application of the propulsion shaft system digital twin.

[0044] The basic principle of the digital twin method of ship propulsion shaft system in this application is as follows Figure 1 As shown, the basic steps include the following:

[0045] Step 1: Establish a geometric model of the propulsion shaft system. Specifically, a virtual geometric model is established based on the physical propulsion shaft system object. The motor is used as the input end of the propulsion shaft system to provide propulsion power. The required data mainly include input power, speed, frequency, torque, and external dimensions. The data required for the propulsion shaft system mainly include the overall layout of the shaft system, the inner and outer diameters of each shaft segment, the material properties of each component of the shaft system, the model and position of each bearing, the model and size of each connection part, etc. The data required for the load end mainly include external dimensions, mass, output power, torque, etc.

[0046] Step 2: Construct a 1D prediction model for the shaft system. Specifically, based on the geometric model of the propulsion shaft system established in step 1, a 1D prediction model for the propulsion shaft system is established. The calculation model includes:

[0047] Torque power calculation model: N = K*D 5 *ρ*n 2 and P = N*n / 9550;

[0048] Where N is the shaft output torque, K is the propeller torque coefficient, D is the propeller diameter, ρ is the water density, n is the shaft speed, and P is the shaft output power;

[0049] Step 3: Shaft system dynamics analysis. Specifically, based on the propulsion shaft system geometry model established in step 1, the finite element method is used to establish a vibration and alignment calculation model based on the rotor dynamics of the propeller shaft system, including: Total weight of the shaft system:

[0050] Where G is the total weight of the shaft system, ρ i is the mass density of each shaft segment, D i is the outer diameter of each shaft segment, d i is the inner diameter of each shaft segment, l i is the length of each axis, G e is the total mass of other equipment in the propulsion shaft system, i is the shaft segment number, and I is the total number of shaft segments;

[0051] Vibration calculation model of rotor dynamics equation:

[0052] Where, [M] is the propulsion shaft system mass matrix, [C] is the propulsion shaft system damping matrix, [K] is the propulsion shaft system stiffness matrix, x is the propulsion shaft system displacement, F is the propulsion shaft system force, and t refers to the propulsion shaft system operation time;

[0053] Using the finite element method, the calibration calculation model is established: [K]a 2n×1 =P 2n×1 ;

[0054] In the formula, a 2n×1 is the node displacement vector, P 2n×1is the system load vector;

[0055] Step 4: Build a digital twin of the propulsion shaft system.

[0056] Specifically, according to the geometric model in step one, based on the requirements of visualization, interactivity and feedback, the digital twin model of the propulsion shaft system is imported into the selected 3D modeling development engine; according to the calculation and analysis models in steps two and three, a suitable programming language is selected as the scripting language to write the relevant processing logic;

[0057] Step 5: Build the connection between the digital twin and the entity.

[0058] Based on the digital twin in step 4, establish an information interaction and real-time update system between the virtual body and the physical body of the propulsion shaft system. Specifically, select the information data that needs to be collected, including:

[0059] a. Real-time shaft speed;

[0060] b. Shaft output torque;

[0061] c. Shaft output power;

[0062] d. Shaft vibration frequency;

[0063] e. Shaft system vibration amplitude;

[0064] f. Axis rotation time;

[0065] g. Bending stress of each shaft section of the shaft system;

[0066] h. The reaction force of each supporting bearing of the shaft system;

[0067] Import the collected information data into the human-computer interaction software, and link it with the parameters in the digital twin of the propulsion shaft system in the mobile terminal. Use the programming language to mobilize the corresponding calculation software to solve the calculation and analysis models in steps two and three.

[0068] Step 6: Iteration of digital twin 1D prediction model.

[0069] Specifically, based on the solution results in step 5, the rule model is constructed, including: establishing boundary conditions:

[0070] a. The shaft speed is less than the critical speed, that is, n <n cr ;

[0071] b. The bending stress σ at each shaft end of the shaft system is not greater than the maximum allowable stress [σ], that is, σ<[σ];

[0072] c. The difference in reaction force between the front and rear bearings of the large gear does not exceed 20% of the total weight of the span shaft section and the large gear, that is, ΔN<0.2G C ;

[0073] Based on the experimental data after connecting to the entity, when the experimental error is greater than 2.5%, data calibration is performed, the entity data is re-measured and fed back to the digital twin, the static characteristic index of the sensor instrument is determined, the system error value is eliminated, and the similarity between the digital twin and the entity is improved;

[0074] By using a suitable 3D engine, the digital twin model of the propulsion shaft system can be observed and visualized in all directions through animation and free-viewing angle rotation, and the corresponding calculation and analysis results can be displayed at the corresponding position, and the results can be processed. The processing methods include: storage, export, drawing, simulation calculation, etc.

[0075] The following is an example of a propulsion shaft system to illustrate the research method of the present invention and verify the feasibility of the propulsion shaft system digital twin method. The example takes a propulsion shaft system test bench as the research object, and the shaft system includes two intermediate shafts, a stern shaft, a thrust bearing, two intermediate bearings, two stern bearings, a load hydraulic cylinder, a large mass disc, several flanges and couplings.

[0076] First, the geometric model of the propulsion shaft system is established according to the design assembly drawing of the propulsion shaft system. In order to improve the accuracy of the calculation and the visibility of the digital twin, the propulsion shaft system rig is modeled as a whole, including the flanges and couplings on the rig. Based on the geometric model of the propulsion shaft system, it is meshed.

[0077] Select appropriate software as the digital twin development engine, import the geometric model of the propulsion shaft system into the software, and select an appropriate programming language as the scripting language to write the processing logic related to the statics and dynamics analysis of the propulsion shaft system. The development of digital twin software uses the pop-up management module as the core to implement the respective logic, and the data that needs to be transmitted between components is interacted through the public data module. The corresponding data obtained by the data acquisition system is imported into the public data module and assigned to the relevant units for real-time data interaction and update.

[0078] Analyze the static and dynamic calculation results, with the goal of calculating the output torque and power and the actual output torque and power with an error of less than 2.5%, perform data calibration and add boundary conditions:

[0079]

[0080] Where n0 is the actual speed of the propulsion shaft system, Δn is the difference between the speed of the digital twin and the actual speed, N0 is the actual output torque of the propulsion shaft system, ΔN is the difference between the output torque of the digital twin and the actual torque, and σ is the bending stress at each shaft end.

[0081] Table 1 Comparison between actual torque power and predicted torque power

[0082] Serial number Actual speed (r / min) Actual power (kW) Predicted power (kW) error 1 100 0.23 0.24 4.3％ 2 200 1.99 1.93 3.0％ 3 500 30.6 30.1 1.6％ 4 1000 244.5 240.83 1.5％

[0083] Combined with Table 1, this method is used to generate digital twins of propulsion shaft systems. The error between the digital twins and the propulsion shaft system entities is small, and the static and dynamic analysis data are valid. In general, when the shaft system speed, torque, and bending stress are within the specified range and the data acquisition system is normal, the digital twins obtained by this method have good accuracy and high visualization, achieving the expected goal. The final digital twin client software architecture is as follows: Figure 2 shown.

[0084] Due to the limitation of computer hardware conditions, the digital twin method used in this embodiment has limited calculation accuracy of digital twin dynamics, and only the effectiveness of the method proposed in this invention is verified. Facing different objects, digital twin personnel can calibrate the target data according to the actual situation, and then update and iterate the calculation model to obtain more accurate propulsion shaft system dynamics analysis results.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application, rather than to limit the scope of protection of the present application. Although the present application has been described in detail with reference to the preferred embodiments, ordinary technicians in this field should understand that the technical solution of the present application can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present application.

Claims

1. A propulsion shaft system digital twin method, characterized in that: The steps include: Step 1: Establish a propulsion shaft system geometric model, specifically, establish a virtual geometric model based on the physical propulsion shaft system object, collect shaft system object data, and use the motor as the input end of the propulsion shaft system to provide propulsion power; Step 2: constructing a 1D prediction model of the shaft system; specifically, establishing a 1D prediction model of the propulsion shaft system based on the geometric model of the propulsion shaft system established in step 1; Step 3: shaft system dynamics analysis: specifically, based on the propulsion shaft system geometric model established in step 1, using the finite element method, a vibration and alignment calculation model based on the rotor dynamics of the propeller shaft system is established; Step 4: Build a digital twin of the propulsion shaft system. Specifically, based on the geometric model in step 1, and based on the requirements of visualization, interactivity, and feedback, the digital twin model of the propulsion shaft system is imported into the selected 3D modeling development engine. According to the calculation and analysis model in steps 2 and 3, select a suitable programming language as the scripting language to write the relevant processing logic; Step 5: Establish the connection between the digital twin and the entity; Based on the digital twin in step 4, establish the information interaction and real-time update system between the virtual body and the entity of the propulsion shaft system; Specifically, it means selecting the information data to be collected, importing the collected information data into the human-computer interaction software, and linking it with the parameters in the digital twin of the propulsion shaft system in the mobile terminal, and mobilizing the corresponding calculation software through the programming language to solve the calculation and analysis models in steps two and three; Step 6: Iteration of the digital twin 1D prediction model; specifically, building a rule model based on the solution results in step 5, including: Establish boundary conditions, and based on the experimental data after connecting to the entity, perform data calibration when the experimental error is greater than 2.5%, re-measure the entity data and feed it back to the digital twin, determine the static characteristic indicators of the sensor instrument, eliminate the system error value, and improve the similarity between the digital twin and the entity.

2. The propulsion shafting digital twin method according to claim 1, characterized in that: The shaft system object data includes: motor input power, speed, frequency, torque, and overall dimensions; overall layout of the propulsion shaft system, inner and outer diameters of each shaft segment, material properties of each shaft system component, model and position of each bearing, model and size of each connecting part; overall dimensions, mass, output power, and torque of the load end part.

3. The propulsion shafting digital twin method according to claim 1, characterized in that: The calculation model in step 2 includes: Torque power calculation model: N = K*D 5 *ρ*n 2 and P = N*n / 9550; Where N is the shaft output torque, K is the propeller torque coefficient, D is the propeller diameter, ρ is the water density, n is the shaft speed, and P is the shaft output power.

4. The propulsion shafting digital twin method according to claim 1, characterized in that: The vibration and alignment calculation model based on the rotor dynamics of the propeller shaft system in step 3 specifically includes: Total weight of shaft system: Where G is the total weight of the shaft system, ρ i is the mass density of each shaft segment, D i is the outer diameter of each shaft segment, d i is the inner diameter of each shaft segment, l i is the length of each axis, G e is the total mass of other equipment in the propulsion shaft system, i is the number of shaft sections, and I is the total number of shaft sections; Vibration calculation model of rotor dynamics equation: Where, [M] is the propulsion shaft system mass matrix, [C] is the propulsion shaft system damping matrix, [K] is the propulsion shaft system stiffness matrix, x is the propulsion shaft system displacement, F is the propulsion shaft system force, and t refers to the propulsion shaft system operation time; Using the finite element method, the calibration calculation model is established: [K]a 2n×1 =P 2n×1 ; In the formula, a 2n×1 is the node displacement vector, P 2n×1 is the system load vector.

5. The propulsion shafting digital twin method according to claim 1, characterized in that: The boundary conditions in step 6 specifically refer to: a. The shaft speed is less than the critical speed, that is, n <n cr ; b. The bending stress at each shaft end of the shaft system is not greater than the maximum allowable stress, that is, σ<[σ]; c. The difference in reaction force between the front and rear bearings of the large gear does not exceed 20% of the total weight of the span shaft section and the large gear, that is, ΔN<0.2G C .

6. The propulsion shafting digital twin method according to claim 1, characterized in that: The information data that needs to be collected in step five include: real-time shaft rotation speed, shaft output torque, shaft output power, shaft vibration frequency, shaft vibration amplitude, shaft rotation time, bending stress of each shaft section of the shaft, and reaction force of each support bearing of the shaft.

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