Ship rapidity analysis and prediction method and system

Abstract

The invention discloses a ship rapidity analysis and forecast method and system, and the method comprises the steps: collecting ship model test data and corresponding ship geometric data, storing the data in a database, and displaying the data in a webpage form; primarily screening out matched ships according to the combination of input target ship geometric parameters; performing secondary screening according to the input design operation parameters and / or additional design characteristic parameters of the target ship; displaying the resistance performance and the propulsion performance of different ships in a graph form for all the ships obtained through secondary screening, and determining a mother type ship according to a comparison result; obtaining the residual resistance coefficient of the target ship by using a map interpolation method; calculating the total resistance and the effective power of the target ship according to the operation parameters, the geometric parameters and the residual resistance coefficient of the target ship; designing by applying the MAU propeller series atlas to obtain a mapping relation between the expected navigational speed of the target ship and the performance of the target ship; and after the target ship completes the model test, test data are stored in the database.

Description

Technical Field

[0001] This application relates to the field of ship performance, and particularly to a ship speed analysis and prediction method and system. Background Art

[0002] The quality of a ship's speed performance directly affects its market competitiveness. An excellent ship form can not only win orders for design and construction units, but also help shipowners achieve the goals of fuel saving, emission reduction, cost reduction and efficiency improvement. Therefore, mastering the characteristics of ship speed and evaluating the competitiveness of ship forms to provide reference for ship form optimization design is an issue that needs to be solved. At the initial stage of ship form design, usually only general information such as the main dimensions of the ship is known. At this time, how to quickly evaluate the speed performance at this scale to decide whether to continue with the design is an urgent challenge. In addition, clarifying the speed performance index data of the same type of ships can provide important support for the design of new ships.

[0003] Currently, the mainstream solutions for ship speed prediction mostly rely on computational fluid dynamics (CFD) analysis. Although CFD can simulate the hydrodynamic performance of ships through software, its calculation cycle is long, making it difficult to quickly respond to market demands, and there are certain accuracy issues, especially the influence of propeller design is not fully considered. In the model test during the mid-stage of ship form design, the selection of the spare propeller is the basis for subsequent design. Through the analysis methods of parent ships and propeller diagrams, key parameters such as the diameter and pitch ratio of the propeller can be obtained, providing a basis for the selection of the spare propeller, thus ensuring the smooth progress of the model test. However, a large number of parent ships are required, and the whole process involves complex calculations and cumbersome diagram queries, with high requirements for users. Moreover, the traditional parent ship method mainly focuses on the resistance performance of ships. Common methods such as the naval coefficient method have limited accuracy and reliability, and lack the evaluation of propulsion performance, providing limited information for designers. In addition, some existing parent ship method systems display single information, lack data visualization functions, are difficult to compare the performance of different parent ships, and cannot visually display the geometric characteristics of parent ships, which is not conducive to quickly locating ship forms with excellent performance and similar characteristics. Therefore, developing a convenient and reliable ship speed prediction and performance analysis system to provide reference for preliminary design and basis for model tests has become an important current demand. Summary of the Invention

[0004] To solve the problems in the prior art that the rapidity analysis and prediction of ships require a large number of parent ships for support, the calculation and operation are complex and cumbersome, the prediction efficiency of ship speed performance is low, and the accuracy is poor, the present invention provides a method for analyzing and predicting the rapidity of ships. This method screens step by step based on a large amount of historical ship model test data to find matching ships, and then determines the parent ship after comparing the resistance performance and propulsion performance of different ships. The combination of the resistance estimation method of the parent ship method and the propeller design method based on diagrams can quickly find the parent ship closest to the target ship, and efficiently and accurately calculate, analyze and predict the various performances of the target ship. The present invention also relates to a system for analyzing and predicting the rapidity of ships.

[0005] The present invention is realized through the following technical solutions:

[0006] A method for analyzing and predicting the rapidity of ships, comprising the following steps:

[0007] Data collection and storage step: Collect a number of ship model test data including resistance performance data and propulsion performance data, as well as corresponding ship geometric data, and store them in the database of the server for users to call the data in the form of a web page;

[0008] Data two-level screening step: According to several combinations of the overall length of the ship, the length between perpendiculars, the molded breadth, the draft of the ship, the block coefficient, and the number of propellers in the target ship geometric parameters input by the user at the client, the processor in the server initially screens out the matching ships in the database according to the preset first screening condition combination; then, according to the designed operating parameters and / or additional design feature parameters of the target ship input by the user at the client, the processor in the server performs a secondary screening within the data corresponding to the ships initially screened out according to the preset second screening condition combination, and screens out the matching ships;

[0009] Performance comparison step: The processor in the server compares and analyzes the resistance performance data and propulsion performance data of all the ships obtained by the secondary screening, displays the resistance performance and propulsion performance of different ships in the form of a graph at the client, and determines the parent ship according to the performance comparison result;

[0010] Correction step for the residual resistance coefficient of the parent ship: The processor interpolates in the TOD60 series of diagrams according to several geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolates in the TOD60 series of diagrams according to the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship. Calculate the ratio of the theoretical residual resistance coefficients between the target ship and the parent ship to obtain a correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship, thereby obtaining the corrected residual resistance coefficient of the target ship;

[0011] Calculation steps for the total resistance and effective power of the target ship: Based on the expected speed in the designed operating parameters of the target ship input by the client, and the overall length of the ship, length between perpendiculars, molded breadth, draft, and block coefficient in the geometric parameters of the target ship, as well as the corrected residuary resistance coefficient of the target ship obtained, the processor calculates the total resistance and effective power of the target ship.

[0012] Steps for predicting the performance of the target ship: The processor combines the main engine parameters of the target ship input by the user at the client, the calculated effective power of the target ship, and the propulsion performance data in the ship model test data of the parent ship, and applies the MAU propeller series diagrams to design the propeller of the diagram, obtaining the mapping relationship between the expected speed of the target ship and the performance of the target ship, and further realizing the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed, and received power of the propeller related to the performance of the target ship.

[0013] Steps for updating test data: After predicting the performance of the target ship, a model test is completed, and the data obtained from the model test is stored as updated test data in the database of the server.

[0014] Preferably, in the data collection and storage step, the resistance performance data includes the residuary resistance coefficient and roughness allowance; the propulsion performance data includes thrust deduction, wake fraction, open water efficiency, relative rotative efficiency, hull efficiency, and propulsion efficiency; the ship geometric data includes block coefficient, length-to-breadth ratio, breadth-to-draft ratio, wetted surface area, waterline length, and bilge keel area.

[0015] Preferably, in the two-stage data screening step, according to several combinations of the sea margin coefficient, shafting efficiency, limiting diameter, propeller axis height above the baseline, and expected speed in the designed operating parameters of the target ship input by the user at the client, and / or according to several combinations of the draft condition, energy-saving device, and fin in the additional design feature parameters of the target ship input by the user at the client, the processor in the server performs secondary screening within the corresponding designed operating parameters and / or additional design feature parameter data of the ship that matches in the primary screening according to the preset second screening condition combination.

[0016] Preferably, in the step of correcting the residuary resistance coefficient of the parent ship, after initially correcting the residuary resistance coefficient in the resistance performance data of the ship model test data of the parent ship by the correction coefficient, and further according to the residuary resistance correction coefficient input by the user at the client, the processor in the server performs secondary correction on the initially corrected residuary resistance coefficient.

[0017] Preferably, in the step of correcting the residual resistance coefficient of the parent ship type, the processor interpolates in the TOD60 series of charts to obtain the theoretical residual resistance coefficient of the target ship based on the block coefficient, length-to-beam ratio, and beam draft ratio in the geometric parameters of the target ship, and then interpolates in the TOD60 series of charts to obtain the theoretical residual resistance coefficient of the parent ship type based on the block coefficient, length-to-beam ratio, and beam draft ratio in the ship's geometric data of the parent ship type.

[0018] Preferably, in the step of calculating the total resistance and effective power of the target ship, the steps of calculating the total resistance and effective power of the target ship include:

[0019] Determine the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship according to the wetted surface area, waterline length, bilge keel area in the ship's geometric data of the parent ship type and the roughness allowance in the resistance performance data.

[0020] Calculate the frictional resistance coefficient of the target ship based on the expected speed and kinematic viscosity coefficient in the design operation parameters of the target ship input by the client in combination with the waterline length of the target ship.

[0021] Calculate the total resistance coefficient of the target ship based on the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship and the corrected residual resistance coefficient of the target ship.

[0022] Calculate the total resistance of the target ship based on the total resistance coefficient, expected speed, and wetted surface area of the target ship.

[0023] Calculate the effective power of the target ship based on the total resistance and expected speed of the target ship.

[0024] Preferably, in the step of predicting the performance of the target ship, the steps of predicting the mapping relationship between the expected speed of the target ship and the performance of the target ship include:

[0025] Perform propeller design on the basis of the maximum continuous power, the speed corresponding to the maximum continuous power, power reserve, speed reserve in the main engine parameters of the target ship and the thrust deduction, wake fraction, relative rotative efficiency in the propulsion performance data of the ship model test data of the parent ship type to obtain the propeller diameter and open water characteristic curve of the target ship, and the open water characteristic curve is a curve of thrust coefficient, torque coefficient, and open water efficiency with respect to the advance coefficient.

[0026] Interpolate the advance coefficient on the open water characteristic curve to obtain the open water efficiency of the target ship.

[0027] Calculate the hull efficiency of the target ship according to the thrust deduction and wake fraction of the parent ship type.

[0028] Calculate the propulsion efficiency of the target ship based on the open water efficiency, hull efficiency of the target ship, and the relative rotative efficiency of the parent ship.

[0029] Calculate the power received by the propeller of the target ship based on the effective power and propulsion efficiency of the target ship.

[0030] Calculate the propeller revolution speed of the target ship based on the wake fraction of the parent ship, the expected speed in the design operation parameters of the target ship input by the client, the advance coefficient of the target ship, and the propeller diameter.

[0031] A ship rapidity analysis and prediction system, including a data collection and storage module, a data two-stage screening module, a performance comparison module, a parent ship residual resistance coefficient correction module, a target ship total resistance and effective power calculation module, a target ship performance prediction module, and a test data update module that are connected in sequence; among them,

[0032] The data collection and storage module is used to collect a number of ship model test data including resistance performance data and propulsion performance data and the corresponding ship geometric data, store them in the database of the server, and provide the data for users to call in the form of a web page;

[0033] The data two-stage screening module is used to, according to several combinations of the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers in the target ship geometric parameters input by the user on the client side, the processor in the server initially screens out matching ships in the database according to the preset first screening condition combination; then, according to the design operation parameters and / or additional design feature parameters of the target ship input by the user on the client side, the processor in the server performs a secondary screening within the data corresponding to the ships that match the initial screening according to the preset second screening condition combination, and secondarily screens out matching ships;

[0034] The performance comparison module is used to, by the processor in the server, compare and analyze the resistance performance data and propulsion performance data of all the ships obtained through the secondary screening, display the resistance performance and propulsion performance of different ships in the form of a graph on the client side, and determine the parent ship according to the performance comparison result;

[0035] The parent ship residual resistance coefficient correction module is used to, by the processor, interpolate in the TOD60 series atlas according to several geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolate in the TOD60 series atlas according to the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship, calculate the ratio of the theoretical residual resistance coefficients between the target ship and the parent ship to obtain a correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship, so as to obtain the corrected residual resistance coefficient of the target ship;

[0036] The total resistance and effective power calculation module of the target ship is used to calculate the total resistance and effective power of the target ship by the processor based on the expected speed in the designed operating parameters of the target ship input by the client, the overall length of the ship, the length between perpendiculars, the molded breadth, the draft and the block coefficient in the geometric parameters of the target ship, and the corrected residual resistance coefficient of the target ship obtained;

[0037] The target ship performance prediction module is used to design the diagram propeller by the processor in combination with the main engine parameters of the target ship input by the user at the client, the calculated effective power of the target ship, and the propulsion performance data in the ship model test data of the parent ship, and apply the MAU propeller series diagram to obtain the mapping relationship between the expected speed of the target ship and the performance of the target ship, so as to realize the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed and propeller received power related to the target ship performance;

[0038] The test data update module is used to complete the model test after the target ship performance prediction, and store the data obtained from the model test as updated test data in the database of the server.

[0039] Preferably, in the parent ship residual resistance coefficient correction module, the processor interpolates in the TOD60 series diagram according to the block coefficient, length-width ratio, breadth-draft ratio in the geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolates in the TOD60 series diagram according to the block coefficient, length-width ratio, breadth-draft ratio in the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship; and, after correcting the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship by the correction coefficient, the initial correction is completed, and the processor in the server also performs a secondary correction on the residual resistance coefficient after the initial correction according to the residual resistance correction coefficient input by the user at the client.

[0040] Preferably, the work of the total resistance and effective power calculation module of the target ship includes:

[0041] Determine the wetted surface area, waterline length, bilge keel area and roughness allowance of the target ship according to the wetted surface area, waterline length, bilge keel area in the ship geometric data of the parent ship and the roughness allowance in the resistance performance data;

[0042] Calculate the frictional resistance coefficient of the target ship according to the expected speed in the designed operating parameters of the target ship input by the client, the kinematic viscosity coefficient and the waterline length of the target ship;

[0043] Calculate the total resistance coefficient of the target ship according to the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship and the corrected residual resistance coefficient of the target ship;

[0044] Based on the total resistance coefficient, expected speed and wetted surface area of the target ship, the total resistance of the target ship is calculated.

[0045] Based on the total resistance and expected speed of the target ship, the effective power of the target ship is calculated.

[0046] The beneficial effects of the present invention are as follows:

[0047] The present invention provides a method for analyzing and predicting the seakeeping performance of a ship. This method collects a number of ship model test data including resistance performance data and propulsion performance data, as well as corresponding ship geometric data, and stores them in the database of the server. The data is provided for users to call in the form of a web page. Storing a large amount of ship model test data in the database can show a rich data form when selecting a parent ship, accurately select the parent ship closest to the target ship. The three-dimensional graphics in the ship geometric data can provide a visual comparison method in the process of selecting the parent ship, compare the geometric characteristics of different ships, and facilitate finding ship types with similar characteristics and excellent performance; according to a number of combinations of geometric parameters of the target ship input by the user at the client, including the overall length of the ship, the length between perpendiculars, the beam, the draft of the ship, the block coefficient, and the number of propellers, the processor in the server initially filters out the matching ships in the database according to the preset first screening condition combination. In this way, according to the basic parameters of the ship, in the process of selecting the parent ship, ships with large differences from the target ship can be quickly and efficiently filtered out; then, according to a number of design operation parameters and / or additional design feature parameters of the target ship input by the user at the client, the processor in the server performs a secondary screening within the design operation parameter data corresponding to the ships initially filtered out according to the preset second screening condition combination. The ships that match the secondary screening are selected. In this way, according to the operation parameters and / or additional design feature parameters of the target ship, ships with parameters similar to the target ship can be quickly further screened out, narrowing the range of selecting the parent ship; the processor in the server compares and analyzes the resistance performance data and propulsion performance data of all the ships obtained from the secondary screening, and displays the resistance performance and propulsion performance of different ships in the form of a graph at the client, and determines the parent ship according to the performance comparison result. In this way, among the ships after the secondary screening, multi-angle visual comparison can be carried out on the data such as the resistance performance data and propulsion performance of each ship, and a ship type with similar characteristics and excellent performance can be efficiently and accurately found as the parent ship; the processor interpolates in the TOD60 series of charts according to a number of geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolates in the TOD60 series of charts according to the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship. Calculate the ratio of the theoretical residual resistance coefficients between the target ship and the parent ship to obtain a correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship. Using the chart interpolation method, the residual resistance coefficient of the target ship can be accurately and efficiently obtained without conducting a model test on the target ship, avoiding processes such as model processing and testing, and saving a lot of time; based on the expected speed in the design operation parameters of the target ship input by the client, the overall length of the ship, the length between perpendiculars, the beam, the draft, and the block coefficient in the geometric parameters of the target ship, and the corrected residual resistance coefficient of the target ship obtained, the processor can accurately and efficiently calculate the total resistance and effective power of the target ship through a standard formula;Combined with the main engine parameters of the target ship input by the user at the client, the effective power of the target ship calculated by the processor, and the propulsion performance data in the ship model test data of the parent ship, the MAU propeller series atlas is applied to design the atlas propeller, and the mapping relationship between the expected speed of the target ship and the performance of the target ship is obtained. Furthermore, the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed, and received power of the propeller related to the performance of the target ship can be predicted. In this way, by using the atlas propeller method for design, the geometric characteristics and performance data of the standard atlas propeller can be utilized, and there is no need to design from scratch. Compared with traditional model tests and CFD simulations, it reduces costs and saves a large amount of time, and the results are reasonable and credible. After the performance prediction of the target ship, the model test is completed, and the data obtained from the model test is stored as updated test data in the database of the server. In this way, the amount of ship data in the database can be increased, and thus the accuracy of selecting the parent ship can be improved. Through operations such as data collection and storage, two - pole screening of ships, performance comparison of ships, correction of the residual resistance coefficient of the parent ship, calculation of the total resistance and effective power of the target ship, performance prediction of the target ship, and update of test data, it is possible to gradually screen through a large amount of historical ship model test data to find a matching ship, and then determine the parent ship after comparing the resistance performance and propulsion performance of different ships. The combination of the resistance estimation method of the parent ship method and the atlas propeller design method can quickly find the parent ship closest to the target ship and efficiently and accurately calculate, analyze, and predict the performance of the target ship.;

[0048] The historical ship model data stored in the database of the present invention includes rich ship model data such as resistance performance data and propulsion performance data, which can provide multi - angle data support for the selection of the parent ship.

[0049] The present invention uses the TOD60 series atlas interpolation method to obtain the theoretical residual resistance coefficients of the target ship and the parent ship, and then obtains the correction coefficient according to the ratio of the two theoretical residual resistance coefficients, and uses it to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship. In this way, by using the atlas interpolation method, the residual resistance coefficient of the target ship can be accurately and efficiently obtained without conducting a model test on the target ship, avoiding processes such as model processing and testing, and saving a large amount of time. Then, the user can input an additional correction coefficient at the client according to experience to perform a secondary adjustment on the initially corrected residual resistance coefficient. In this way, under certain special demand scenarios or according to experience, the adjustment of the residual resistance coefficient can be flexibly completed without terminating the target ship performance prediction process and readjusting parameters, thus saving time.

[0050] The present invention can first calculate key data such as the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship based on the geometric parameters of the target ship input by the client in combination with the parent ship, and then calculate the frictional resistance coefficient of the target ship according to parameters such as the expected speed, waterline length, and kinematic viscosity coefficient of the target ship. Then, in combination with the corrected residual resistance coefficient of the target ship, the total resistance coefficient of the target ship is calculated. Then, based on the total resistance coefficient, expected speed, and wetted surface area of the target ship, the total resistance of the target ship is calculated. Finally, based on the total resistance and expected speed of the target ship, the effective power of the target ship is calculated. In all calculation processes, standardized formulas are used for calculation based on valid ship data, and the calculated results are accurate and reliable. At the same time, since the calculation process is automatically completed in the processor, the calculation process is efficient. This series of calculation and processing logics is of great significance in the field of ship design and performance analysis, and can provide strong support for ship performance evaluation, design optimization, navigation planning, etc., ensuring that the ship achieves efficient, economical, and safe operation goals in actual applications.

[0051] The present invention can perform propeller design based on the total resistance coefficient, wetted surface area of the target ship, and thrust deduction, wake fraction, and relative rotative efficiency in the propulsion performance data of the ship model test data of the parent ship to obtain the propeller diameter and open water characteristic curve of the target ship, and then use the interpolation method to obtain the open water efficiency of the target ship. The hull efficiency of the target ship is calculated based on the thrust deduction and wake fraction. Then, based on the open water efficiency, hull efficiency of the target ship, and relative rotative efficiency of the parent ship, the propulsion efficiency of the target ship is calculated. Based on the effective power and propulsion efficiency of the target ship, the power received by the propeller of the target ship is calculated. Finally, based on the wake fraction of the parent ship, the expected speed, advance coefficient, and propeller diameter of the target ship, the propeller speed of the target ship is calculated. Among them, the thrust deduction, wake fraction, and relative rotative efficiency are related to the parent ship. Since the target ship is similar to the parent ship, the thrust deduction, wake fraction, and relative rotative efficiency of the parent ship can be directly used as the parameters of the target ship itself, skipping the complex parameter acquisition process and saving the time for obtaining the three parameters. In all calculation processes, standardized formulas are used for calculation based on valid ship data, and the calculated results are accurate and reliable, providing strong support for the accurate evaluation of ship performance. At the same time, since the calculation process is automatically completed in the processor, avoiding the tediousness of manual calculation, the calculation process is efficient. Saving parameter acquisition time and the automatic calculation method reduces the cost of ship design and performance analysis. This calculation and processing logic provides an efficient and accurate design and analysis method for the ship industry, promoting the progress of ship technology. The accurate calculation results contribute to the optimization of ship design, improve the performance and quality of ships, and promote the ship industry to move towards a higher level.

[0052] The present invention also relates to a ship speed analysis and prediction system, which corresponds to the above-mentioned ship speed analysis and prediction method and can be understood as a system that implements the above-mentioned ship speed analysis and prediction method. It includes a data collection and storage module, a two-stage data screening module, a performance comparison module, a residual resistance coefficient correction module for the parent ship, a total resistance and effective power calculation module for the target ship, a performance prediction module for the target ship, and a test data update module. Each module works in cooperation with each other, and it is a system for ship speed prediction and performance analysis that is convenient to use and highly reliable, providing a reference for the preliminary design of ships and a basis for model tests. The present invention can be understood as predicting the ship speed by the parent ship method, which has the characteristics of accuracy and reliability. By using the parent ship method combined with series charts, the reliability is further improved. It can realize the functions of data search, comparison, calculation, and comprehensive output through the system platform, and display various rich data forms; the performance comparison module can have data charts and test photos of the ships after two-stage screening on the client side, and can also be displayed in three-dimensional geometry to show the resistance performance and propulsion performance of different ships, compare the characteristics of the parent ships from multiple angles, help analyze the ship performance and screen suitable parent ship data, and can very conveniently select multiple ships for performance comparison analysis and use them as parent ships to predict the ship speed. The whole process is simple and efficient. The parent ship method and the propeller design process based on charts are implemented in the server-client B / S network architecture to achieve rapid prediction and evaluation of the resistance and propulsion performance of ships, providing a reliable reference basis for the pre-design evaluation of ships. The designed two-stage data screening module adds a secondary screening process during the ship type screening process, making it more flexible for users to select the parent ship, avoiding the system giving inappropriate parent ships and affecting the final prediction result, improving the comparison efficiency of the parent ship and the prediction accuracy. The residual resistance coefficient correction module for the parent ship corrects the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship through a specifically calculated correction coefficient, and then obtains the corrected residual resistance coefficient of the target ship. Then, the corrected residual resistance coefficient of the target ship is used to calculate the total resistance and effective power of the target ship to improve the accuracy of the resistance and ship speed prediction of the target ship. The series of logical calculations of the total resistance and effective power calculation module for the target ship and the performance prediction module for the target ship are automatically completed in the processor, and some data of the parent ship are used for calculation and processing, saving the time for parameter acquisition and the automatic calculation method, reducing the cost of ship design and performance analysis, as well as the labor cost, improving the design efficiency, shortening the design cycle, and reducing the resource consumption in the design process, making ship design and performance analysis more economical and efficient. Brief Description of the Drawings

[0053] Figure 1 It is a flowchart of the ship speed analysis and prediction method of the present invention.

[0054] Figure 2Example diagram of input parameters for the target ship of the present invention.

[0055] Figure 3 Example diagram of data obtained after the first screening of the present invention.

[0056] Figure 4 Example diagram of data obtained after the second screening of the present invention.

[0057] Figure 5 Example diagram of performance comparison of ships selected through two - stage screening of the present invention.

[0058] Figure 6 Example diagram of ship model pictures of ships selected through two - stage screening of the present invention.

[0059] Figure 7 Example diagram of three - dimensional geometric figures of ship models of ships selected through two - stage screening of the present invention.

[0060] Figure 8 Schematic diagram of the calculation principle combining with TOD60 series diagrams of the present invention.

[0061] Figure 9 Example diagram of secondary correction of the residual resistance coefficient of the present invention.

[0062] Figure 10 Example diagram of self - propulsion result parameters input for the target ship of the present invention.

[0063] Figure 11 Structure diagram of the ship speed performance analysis and prediction system of the present invention. Detailed implementation manners

[0064] The present invention will be described below with reference to the accompanying drawings.

[0065] Ship speed performance analysis and prediction is an important part of ship performance evaluation, mainly studying the resistance, propulsion efficiency, required power, etc. of ships at different speeds. The present invention discloses a ship speed performance analysis and prediction method. This method conducts step - by - step screening based on a large amount of historical ship model test data to find matching ships, and then determines the parent ship after comparing the resistance performance and propulsion performance of different ships. The combination of the resistance estimation method of the parent ship and the diagram - type propeller design method can quickly find the parent ship closest to the target ship, and efficiently and accurately predict the performance of the target ship. This method can be executed by a processor or an electronic device with processing capabilities, such as Figure 1As shown, collect the test data set of the ship model and the ship's geometric data, then conduct a primary screening based on the input target ship geometric parameters of several combinations, conduct a secondary screening based on the input target ship design operating parameters and / or additional design feature parameters of several combinations, then determine the parent ship of the target ship according to the performance comparison results of the selected matching ships in the form of a graph, then use the chart interpolation method to correct the residual resistance coefficient of the parent ship to obtain the corrected residual resistance coefficient of the target ship, and calculate the total resistance and effective power of the target ship based on the operating parameters, geometric parameters and corrected residual resistance coefficient of the target ship, etc. Finally, apply the MAU propeller series chart to design the chart propeller, obtain the mapping relationship between the expected speed of the target ship and the performance of the target ship, and after the target ship completes the model test, store the data obtained from the model test as updated test data in the database. The present invention conducts a step-by-step screening based on a large amount of historical ship model test data to find a matching ship, and visually compares data such as resistance performance and propulsion performance of different ships in the form of a graph, and determines the parent ship after comparing from different dimensions, so as to improve the reliability of the parent ship and increase the accuracy of the final prediction result. The combination of the resistance estimation method of the parent ship method and the chart propeller design method. The parent ship method can quickly find the parent ship closest to the target ship by using detailed parameters including more abundant residual resistance coefficient, self-propulsion factor, etc., and efficiently and accurately calculate, analyze and predict the performance of the target ship. Specifically, the method includes the following steps:

[0066] 1. Data collection and storage step: Collect a number of ship model test data including resistance performance data and propulsion performance data and the corresponding ship geometric data, and store them in the database of the server for users to call the data in the form of a web page.

[0067] In the embodiment of the present application, a large number of ship model test data and the corresponding ship geometric data are stored in the database and provided for users to call the data in the form of a web page. When selecting the parent ship, it can display a rich data form and accurately select the parent ship closest to the target ship. The three-dimensional graph in the ship geometric data can provide a visual comparison method in the selection process of the parent ship, compare the geometric characteristics of different ships, and facilitate finding a ship type with similar characteristics and excellent performance.

[0068] Preferably, the resistance performance data includes residual resistance coefficient, roughness allowance, etc., and the propulsion performance data includes thrust deduction, wake fraction, open water efficiency, relative rotative efficiency, hull efficiency, propulsion efficiency, etc.

[0069] II. Two-level data screening steps: Based on several combinations of the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers in the target ship's geometric parameters input by the user on the client side, the processor in the server performs a primary screening in the database to select matching ships according to the preset first screening condition combination; then, based on the designed operating parameters and / or additional design feature parameters of the target ship input by the user on the client side, the processor in the server performs a secondary screening within the data corresponding to the ships selected in the primary screening according to the preset second screening condition combination, and selects the matching ships.

[0070] In the embodiment of the present application, similarity screening processing of ships can be performed based on information such as the main dimensions of the target ship determined in the initial stage of ship design, including the geometric parameters of the target ship such as the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers, the designed operating parameters of the target ship such as the service margin coefficient, shafting efficiency, limiting diameter, propeller axis height above the baseline, and expected speed, the main engine parameters of the target ship such as the maximum continuous power, the rotational speed corresponding to the maximum continuous power, power reserve, and rotational speed reserve, and the additional design feature parameters such as the draft condition, energy-saving device, and fin. As Figure 2 shown, the user can input several combinations of the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers in the geometric parameters of the target ship on the client side. The processor in the server performs a primary screening in the database according to the input parameter combination to select matching ships, so that a large number of dissimilar ships can be quickly filtered out under the geometric parameters of the target ship. Figure 3 shows the matching ships selected under a certain screening condition. As Figure 3 shown, it includes data such as the test number, model number, length between perpendiculars (LPP), molded breadth (B), forward draft (Tf), aft draft (Ta), block coefficient (Cb), length-to-breadth ratio (L / B), and breadth-to-draft ratio (B / T) of the ship. The user can input several combinations of the designed operating parameters and / or additional design feature parameters of the target ship on the client side. The processor in the server performs a secondary screening within the data corresponding to the ships selected in the primary screening according to the input screening condition combination to select the matching ships. Figure 4 shows the ships selected after the secondary screening under a certain screening condition. As Figure 4 shown, 3 ships are selected, including data such as the test number, model number, and ship name.

[0071] III. Performance comparison steps: The processor in the server compares and analyzes the resistance performance data and propulsion performance data of all the ships obtained from the secondary screening, displays the resistance performance and propulsion performance of different ships in the form of a graph on the client side, and determines the parent ship according to the performance comparison result.

[0072] Based on the matching ships selected after secondary screening, the embodiments of the present application can perform comparative analysis of the performance data of each matching ship in the form of a graph on the client side. For example, Figure 5 As shown, the three curves are respectively the performance data curves of three ships. Among them, the X-axis is the Froude number (Fn), and the Y-axis is the performance data of the ship. The performance data includes the residual resistance coefficient, thrust deduction, wake fraction, open water efficiency, relative rotative efficiency, hull efficiency, propulsion efficiency, etc. By selecting the variable Y, different performance data of the ships can be compared. At the same time, through the ship model photos of the ships (such as Figure 6 shown) and three-dimensional geometric models (such as Figure 7 shown), etc., it can be judged whether its characteristics are similar to those of the target ship. Finally, through multi-dimensional comparative analysis of graphs and tables, several ships are selected as the parent ships of the target ship.

[0073] IV. Steps for correcting the residual resistance coefficient of the parent ship: The processor interpolates in the TOD60 series of charts according to several geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolates in the TOD60 series of charts according to the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship. Calculate the ratio of the theoretical residual resistance coefficient between the target ship and the parent ship to obtain the correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship, so as to obtain the corrected residual resistance coefficient of the target ship.

[0074] As Figure 8 shown, the embodiments of the present application can interpolate in the TOD60 series of chart data according to data such as the block coefficient, length-width ratio, and width-draft ratio of the target ship to obtain the theoretical residual resistance coefficient of the target ship on the chart; it can interpolate in the TOD60 series of chart data according to data such as the block coefficient, length-width ratio, and width-draft ratio of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship on the chart; then, according to the ratio of the theoretical residual resistance coefficient of the target ship on the chart to the theoretical residual resistance coefficient of the parent ship on the chart (i.e., the correction coefficient), correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship, so as to obtain the corrected residual resistance coefficient (Cr) of the target ship. As Figure 9 shown, on the basis of the initial correction, the user can manually set the residual resistance correction coefficient according to experience in combination with the scale differences (including block coefficient, length-width ratio, width-draft ratio, etc.) between the target ship and the parent ship or the numerical calculation results, that is, multiply the coefficient manually input (default is 1) on the residual resistance coefficient after automatic correction (initial correction) for secondary correction. In this way, under certain experience or special requirement scenarios, the adjustment of the residual resistance coefficient can be flexibly completed without terminating the performance prediction process of the target ship and readjusting the parameters, thus saving time.

[0075] V. Calculation steps for the total resistance and effective power of the target ship: The processor calculates the total resistance and effective power of the target ship based on the expected speed in the designed operating parameters of the target ship input by the client, the overall length of the ship, the length between perpendiculars, the molded breadth, the draft, and the block coefficient in the geometric parameters of the target ship, as well as the corrected residuary resistance coefficient of the target ship obtained.

[0076] Furthermore, the calculation steps for the total resistance and effective power of the target ship may also include the following steps:

[0077] Determine the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship based on the wetted surface area, waterline length, bilge keel area in the ship's geometric data of the parent ship and the roughness allowance in the resistance performance data;

[0078] Calculate the frictional resistance coefficient of the target ship based on the expected speed of the target ship input by the client, the kinematic viscosity coefficient, and the waterline length of the target ship;

[0079] Calculate the total resistance coefficient of the target ship based on the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship, and the corrected residuary resistance coefficient of the target ship;

[0080] Calculate the total resistance of the target ship based on the total resistance coefficient, expected speed, and wetted surface area of the target ship;

[0081] Calculate the effective power of the target ship based on the total resistance and expected speed of the target ship.

[0082] In the embodiment of the present application, the frictional resistance coefficient of the target ship is calculated by the following formula:

[0083] C fs = 0.075 / (lgR n - 2) 2

[0084] R n = VL WL / ν

[0085] where C fs is the frictional resistance coefficient of the target ship, V is the expected speed of the target ship, L WL is the waterline length of the target ship, and ν is the kinematic viscosity coefficient;

[0086] The total resistance coefficient of the target ship is calculated by the following formula:

[0087]

[0088] where C ts is the total resistance coefficient of the target ship, S sis the wetted surface area of the target ship, S bk is the bilge keel area of the target ship, C fs is the frictional resistance coefficient of the target ship, ΔC f is the roughness allowance of the target ship, C r is the residuary resistance coefficient of the target ship, C AA is the air resistance coefficient;

[0089] The total resistance of the target ship is calculated by the following formula:

[0090]

[0091] where, R ts is the total resistance of the target ship, C ts is the total resistance coefficient of the target ship, ρ is the water density, V is the expected speed of the target ship, S s is the wetted surface area of the target ship;

[0092] The effective power of the target ship is calculated by the following formula:

[0093] Ehp = R ts × V / 1000

[0094] where, Ehp is the effective power of the target ship, R ts is the total resistance of the target ship, V is the expected speed of the target ship.

[0095] The corresponding relationships between multiple expected speeds and effective powers, etc. of the target ship are calculated by the above method, as shown in Table 1, including the expected speed of the target ship, correction coefficient, residuary resistance coefficient of the parent ship, residuary resistance coefficient of the target ship, frictional resistance coefficient, total resistance, effective power, etc. It can be seen from this that different residuary resistance coefficients of the parent ship correspond to different expected speeds of the target ship.

[0096] Table 1 Corresponding relationships between multiple expected speeds and effective powers, etc. of the target ship

[0097]

[0098] Preferably, in view of the similar hull forms of the target ship and the parent ship in the embodiments of the present application, the wetted surface area, waterline length, bilge keel area and roughness allowance of the target ship can be considered to be the same as those of the parent ship.

[0099] VI. Steps for predicting the performance of the target ship: The processor combines the main engine parameters of the target ship input by the user at the client, the effective power of the target ship calculated, and the propulsion performance data in the ship model test data of the parent ship, and applies the MAU propeller series atlas to design the atlas propeller, obtaining the mapping relationship between the expected speed of the target ship and the performance of the target ship, thereby realizing the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed, and received power of the propeller related to the performance of the target ship.

[0100] Further, the prediction steps of the mapping relationship between the expected speed of the target ship and the performance of the target ship may also include the following steps:

[0101] According to the maximum continuous power, the speed corresponding to the maximum continuous power, power reserve, speed reserve in the main engine parameters of the target ship, and the thrust deduction, wake fraction, relative rotative efficiency, shafting efficiency, etc. in the propulsion performance data of the ship model test data of the parent ship (as Figure 10 shown, the thrust deduction, wake fraction, relative rotative efficiency, etc. of the parent ship can be filled in by the client), as Figure 8 shown, perform atlas propeller design to obtain the propeller diameter and open water characteristic curve of the target ship. The open water characteristic curve is a curve of thrust coefficient, torque coefficient, and open water efficiency with respect to the advance coefficient; where the advance coefficient J s can be calculated by the following formula:

[0102]

[0103] where K ts is the thrust coefficient, C ts is the total resistance coefficient of the target ship, S s is the wetted surface area of the target ship, D is the propeller diameter, t is the thrust deduction of the parent ship, and w s is the wake fraction of the parent ship;

[0104] Perform interpolation of the advance coefficient on the open water characteristic curve to obtain the open water efficiency of the target ship;

[0105] According to the thrust deduction and wake fraction of the parent ship, calculate the hull efficiency of the target ship. The calculation formula for the hull efficiency (Etah) is as follows:

[0106]

[0107] where t is the thrust deduction of the parent ship, and w s is the wake fraction of the parent ship;

[0108] According to the open water efficiency, hull efficiency of the target ship, and the relative rotative efficiency of the parent ship, calculate the propulsion efficiency of the target ship;

[0109] According to the effective power and propulsion efficiency of the target ship, the received power of the propeller of the target ship is calculated. The calculation formula of the received power of the propeller (Dhp) is as follows:

[0110] Dhp = Ehp / Etad

[0111] where Ehp is the effective power of the target ship, and Etad is the propulsion efficiency of the target ship;

[0112] According to the wake fraction of the parent ship, the expected speed in the design operation parameters of the target ship input by the client, the advance coefficient of the target ship, and the propeller diameter, the rotational speed of the propeller of the target ship is calculated. The calculation formula of the rotational speed of the propeller of the target ship (Nt) is as follows:

[0113] Nt = (1 - w s ) × V s / (J s ) × D

[0114] where w s is the wake fraction of the parent ship, V s is the expected speed of the target ship, J s is the advance coefficient of the target ship, and D is the propeller diameter of the target ship.

[0115] Preferably, in the embodiments of the present application, in view of the similar hull forms of the target ship and the parent ship, the thrust deduction, wake fraction, relative rotative efficiency, and shafting efficiency of the target ship can be considered to be the same as those of the parent ship.

[0116] The mapping relationship between the expected speed of the target ship predicted by the above method and the performance of the target ship is shown in Table 2, including the expected speed of the target ship, residual resistance coefficient, effective power, advance coefficient, open water efficiency, propulsion efficiency, rotational speed of the propeller, received power of the propeller, etc.

[0117] Table 2 Mapping relationship between the expected speed of the target ship and the performance of the target ship

[0118]

[0119] VII. Test data update step: After predicting the performance of the target ship, a model test is completed, and the data obtained from the model test is stored as updated test data in the database of the server.

[0120] In the embodiments of the present application, after predicting the expected speed and performance data of the target ship, a model test is carried out on the target ship, and the data obtained from the test is stored as updated test data in the database of the server, so as to increase the amount of ship data in the database, thereby improving the accuracy of selecting the parent ship.

[0121] The present invention can collect and store data, screen ships at both ends, compare ship performance, correct the residual resistance coefficient of the mother ship, calculate the total resistance and effective power of the target ship, predict the performance of the target ship, and update test data. It can find matching ships based on a large amount of historical ship model test data through step-by-step screening, and then determine the mother ship after comparing the resistance performance and propulsion performance of different ships. The mother ship method resistance estimation and the atlas propeller design method are combined to quickly find the mother ship closest to the target ship, and efficiently and accurately calculate, analyze and predict various performances of the target ship.

[0122] Based on the same inventive concept, one or more embodiments of the present specification also provide a ship rapidity analysis and forecasting system. Since the principle of the problem solved by the ship rapidity analysis and forecasting system is similar to that of the aforementioned ship rapidity analysis and forecasting method, the implementation of the ship rapidity analysis and forecasting system can refer to the aforementioned implementation of the ship rapidity analysis and forecasting method, and the repeated parts will not be repeated.

[0123] Figure 11 This is a structural diagram of a ship rapidity analysis and prediction system provided in one or more embodiments of this specification. Figure 11 As shown, the ship rapidity analysis and prediction system includes a data collection and storage module 101, a two-level data screening module 102, a performance comparison module 103, a parent ship residual resistance coefficient correction module 104, a target ship total resistance and effective power calculation module 105, a target ship performance prediction module 106 and a test data update module 107.

[0124] The data collection and storage module 101 is used to collect a number of ship model test data including resistance performance data and propulsion performance data and corresponding ship geometry data, store them in the database of the server, and provide the data for users to call in the form of web pages.

[0125] The two-level data screening module 102 is used to perform a primary screening of matching ships in the database by the processor in the server according to a preset first screening condition combination based on several combinations of the total length of the ship, the length between perpendiculars, the width, the ship draft, the square coefficient, and the number of propellers among the geometric parameters of the target ship input by the user on the client; and then perform a secondary screening by the processor in the server according to a preset second screening condition combination in the data corresponding to the matching ships screened out in the primary screening according to the design operation parameters and / or additional design feature parameters of the target ship input by the user on the client, so as to screen out matching ships at the secondary level.

[0126] The performance comparison module 103 is used for the processor in the server to compare and analyze the resistance performance data and propulsion performance data of all ships obtained by the secondary screening, display the resistance performance and propulsion performance of different ships on the client in the form of a graph, and determine the parent ship according to the performance comparison results.

[0127] The mother ship residual resistance coefficient correction module 104 is used to interpolate the theoretical residual resistance coefficient of the target ship from the TOD60 series atlas by the processor according to several geometric parameters of the target ship, and then interpolate the theoretical residual resistance coefficient of the mother ship from the TOD60 series atlas according to the ship geometric data of the mother ship. Calculate the ratio of the theoretical residual resistance coefficients between the target ship and the mother ship to obtain a correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the mother ship, so as to obtain the corrected residual resistance coefficient of the target ship.

[0128] The target ship total resistance and effective power calculation module 105 is used to calculate the total resistance and effective power of the target ship by the processor based on the expected speed in the design operation parameters of the target ship input by the client, the ship length between perpendiculars, molded breadth, draft and block coefficient in the geometric parameters of the target ship, and the corrected residual resistance coefficient of the target ship obtained.

[0129] The target ship performance prediction module 106 is used to design the propeller of the atlas by the processor in combination with the main engine parameters of the target ship input by the user at the client, the calculated effective power of the target ship, and the propulsion performance data in the ship model test data of the mother ship, apply the MAU propeller series atlas, obtain the mapping relationship between the expected speed of the target ship and the performance of the target ship, and then realize the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed and propeller received power related to the target ship performance.

[0130] The test data update module 107 is used to complete the model test after the target ship performance prediction, and store the data obtained from the model test as updated test data in the database of the server.

[0131] Furthermore, in the mother ship residual resistance coefficient correction module 104, the processor interpolates the theoretical residual resistance coefficient of the target ship from the TOD60 series atlas according to the block coefficient, length-width ratio, and breadth-draft ratio in the geometric parameters of the target ship, and then interpolates the theoretical residual resistance coefficient of the mother ship from the TOD60 series atlas according to the block coefficient, length-width ratio, and breadth-draft ratio in the ship geometric data of the mother ship; and after correcting the residual resistance coefficient in the resistance performance data of the ship model test data of the mother ship by the correction coefficient, the primary correction is completed. Also, according to the residual resistance correction coefficient input by the user at the client, the processor in the server performs a secondary correction on the residual resistance coefficient after the primary correction.

[0132] Furthermore, the work of the target ship total resistance and effective power calculation module 105 includes:

[0133] Determine the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship based on the wetted surface area, waterline length, bilge keel area in the ship geometric data of the parent ship and the roughness allowance in the resistance performance data;

[0134] Calculate the frictional resistance coefficient of the target ship based on the expected speed and kinematic viscosity coefficient in the design operation parameters of the target ship input by the client in combination with the waterline length of the target ship;

[0135] Calculate the total resistance coefficient of the target ship based on the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship, and the corrected residual resistance coefficient of the target ship;

[0136] Calculate the total resistance of the target ship based on the total resistance coefficient, expected speed, and wetted surface area of the target ship;

[0137] Calculate the effective power of the target ship based on the total resistance and expected speed of the target ship.

[0138] The ship speed prediction method and system proposed by the present invention uses the parent ship method to predict data such as ship speed. Compared with traditional methods, it has the characteristics of accuracy and reliability. By using the parent ship method combined with series spectra, the reliability is further improved. The present invention selects a matching ship by gradually screening based on a large amount of historical ship model test data. The primary and secondary screening can use multi-dimensional and different combinations of data, which is flexible and efficient, improves the comparison efficiency of the parent ship, selects the parent ship closest to the target ship, and improves the prediction accuracy. After screening, the present invention provides charts of data, test photos of the ships after two-stage screening, and can also be displayed in three-dimensional geometry to display the resistance performance and propulsion performance of different ships, compare the characteristics of the parent ship from multiple angles, help analyze the ship performance and screen suitable parent ship data, and can very conveniently select multiple ships for performance comparison analysis and use them as the parent ship to predict the ship speed. The whole process is simple and efficient. Data such as the total resistance, effective power, and expected speed of the target ship are automatically calculated according to professional formulas, and some data of the parent ship are used for calculation and processing, saving the time for parameter acquisition, simplifying the calculation method, reducing the cost of ship design and performance analysis, reducing the labor cost, improving the design efficiency, shortening the design cycle, and reducing the resource consumption in the design process, making ship design and performance analysis more economical and efficient.

[0139] It should be noted that the above-described specific embodiments can enable those skilled in the art to understand the present invention more comprehensively, but do not limit the present invention in any way. Therefore, although this specification has described the present invention in detail with reference to the accompanying drawings and embodiments, those skilled in the art should understand that the present invention can still be modified or equivalently replaced. In short, all technical solutions and their improvements that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the patent of the present invention.

Claims

1. A method for analyzing and predicting the speed performance of a ship, characterized in that, Including the following steps: Data collection and storage step: Collect a number of ship model test data including resistance performance data and propulsion performance data, as well as corresponding ship geometric data, and store them in the database of the server for users to call the data in the form of a web page; Two-level data screening step: According to several combinations of the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers in the target ship geometric parameters input by the user at the client, the processor in the server initially screens out matching ships in the database according to the preset first screening condition combination; Then, according to the design operation parameters and / or additional design feature parameters of the target ship input by the user at the client, the processor in the server performs a secondary screening within the data corresponding to the ships initially screened out according to the preset second screening condition combination, and screens out matching ships in the secondary screening; Performance comparison step: The processor in the server compares and analyzes the resistance performance data and propulsion performance data of all ships obtained from the secondary screening, displays the resistance performance and propulsion performance of different ships in the form of a graph at the client, and determines the parent ship type according to the performance comparison result; Correction step for the residual resistance coefficient of the parent ship type: The processor interpolates in the TOD60 series of charts according to several geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolates in the TOD60 series of charts according to the ship geometric data of the parent ship type to obtain the theoretical residual resistance coefficient of the parent ship type, calculates the ratio of the theoretical residual resistance coefficients between the target ship and the parent ship type to obtain the correction coefficient, and then uses the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship type, thereby obtaining the corrected residual resistance coefficient of the target ship; Calculation step for the total resistance and effective power of the target ship: The processor calculates the total resistance and effective power of the target ship based on the expected speed in the design operation parameters of the target ship input by the client, the overall length of the ship, length between perpendiculars, molded breadth, draft, and block coefficient in the geometric parameters of the target ship, and the corrected residual resistance coefficient of the target ship obtained; Performance prediction step for the target ship: The processor combines the main engine parameters of the target ship input by the user at the client, the calculated effective power of the target ship, and the propulsion performance data in the ship model test data of the parent ship type, applies the MAU propeller series of charts, designs the propeller of the chart, obtains the mapping relationship between the expected speed of the target ship and the performance of the target ship, and further realizes the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed, and received power of the propeller related to the performance of the target ship; Test data update step: After the performance prediction of the target ship, complete the model test, and store the data obtained from the model test as updated test data in the database of the server.

2. The ship speed performance analysis and prediction method according to claim 1, wherein In the data collection and storage step, the resistance performance data includes the residual resistance coefficient and roughness allowance; the propulsion performance data includes thrust deduction, wake fraction, open water efficiency, relative rotative efficiency, hull efficiency, and propulsion efficiency; the ship geometric data includes block coefficient, length-width ratio, beam-draft ratio, wetted surface area, waterline length, and bilge keel area.

3. The ship speed performance analysis and prediction method according to claim 1, characterized in that In the two-stage data screening step, according to several combinations of the sea margin coefficient, shafting efficiency, limiting diameter, propeller axis height above baseline, and expected speed in the design operation parameters of the target ship input by the user at the client, and / or according to several combinations of the draft condition, energy-saving device, and fin in the additional design feature parameters of the target ship input by the user at the client, the processor in the server performs secondary screening within the design operation parameters and / or additional design feature parameter data of the ships that match the preset second screening condition combinations in the primary screening.

4. The ship speed performance analysis and prediction method according to claim 1, characterized in that In the step of correcting the residual resistance coefficient of the parent ship, after correcting the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship with the correction coefficient, the initial correction is completed. Also, according to the residual resistance correction coefficient input by the user at the client, the processor in the server performs secondary correction on the residual resistance coefficient after the initial correction.

5. The ship speed performance analysis and prediction method according to any one of claims 1 to 4, characterized in that In the step of correcting the residual resistance coefficient of the parent ship, the processor interpolates in the TOD60 series of diagrams to obtain the theoretical residual resistance coefficient of the target ship based on the block coefficient, length-width ratio, and beam-draft ratio in the geometric parameters of the target ship, and then interpolates in the TOD60 series of diagrams to obtain the theoretical residual resistance coefficient of the parent ship based on the block coefficient, length-width ratio, and beam-draft ratio in the ship geometric data of the parent ship.

6. The ship speed performance analysis and prediction method according to claim 2, wherein In the step of calculating the total resistance and effective power of the target ship, the calculation steps for the total resistance and effective power of the target ship include: Determine the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship based on the wetted surface area, waterline length, bilge keel area in the ship geometric data of the parent ship and the roughness allowance in the resistance performance data. Calculate the frictional resistance coefficient of the target ship based on the expected speed and kinematic viscosity coefficient in the design operation parameters of the target ship input at the client in combination with the waterline length of the target ship. Calculate the total resistance coefficient of the target ship based on the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship, and the corrected residual resistance coefficient of the target ship. Calculate the total resistance of the target ship based on the total resistance coefficient, expected speed, and wetted surface area of the target ship. Calculate the effective power of the target ship based on the total resistance and expected speed of the target ship.

7. The ship speed performance analysis and prediction method according to claim 6, characterized in that In the step of predicting the performance of the target ship, the prediction steps for the mapping relationship between the expected speed of the target ship and the performance of the target ship include: Based on the maximum continuous power, the rotational speed corresponding to the maximum continuous power, the power reserve, the rotational speed reserve in the target ship's main engine parameters, and the thrust deduction, wake fraction, and relative rotative efficiency in the propulsion performance data of the ship model test data of the parent ship, a propeller design is carried out using the propeller diagram to obtain the propeller diameter and the open water characteristic curve of the target ship. The open water characteristic curve is a curve of the thrust coefficient, torque coefficient, and open water efficiency with respect to the advance coefficient; Interpolation of the advance coefficient is performed on the open water characteristic curve to obtain the open water efficiency of the target ship; Based on the thrust deduction and wake fraction of the parent ship, the hull efficiency of the target ship is calculated; Based on the open water efficiency, hull efficiency of the target ship, and the relative rotative efficiency of the parent ship, the propulsion efficiency of the target ship is calculated; Based on the effective power and propulsion efficiency of the target ship, the power received by the propeller of the target ship is calculated; Based on the wake fraction of the parent ship, the expected speed in the design operation parameters of the target ship input by the client, the advance coefficient of the target ship, and the propeller diameter, the propeller rotational speed of the target ship is calculated; 8. A ship rapidity analysis and prediction system, characterized in that, It includes a data collection and storage module, a data two-stage screening module, a performance comparison module, a parent ship residual resistance coefficient correction module, a target ship total resistance and effective power calculation module, a target ship performance prediction module, and a test data update module that are connected in sequence. Among them, The data collection and storage module is used to collect a number of ship model test data including resistance performance data and propulsion performance data and the corresponding ship geometric data, store them in the database of the server, and provide the data for users to call in the form of a web page; The data two-stage screening module is used to, according to several combinations of the overall length of the ship, length between perpendiculars, molded breadth, draft of the ship, block coefficient, and number of propellers in the target ship geometric parameters input by the user on the client, perform a primary screening in the database by the processor in the server according to the preset first screening condition combination to select matching ships; then, according to the design operation parameters and / or additional design feature parameters of the target ship input by the user on the client, perform a secondary screening in the data corresponding to the ships selected in the primary screening by the processor in the server according to the preset second screening condition combination to select matching ships; The performance comparison module is used to, by the processor in the server, compare and analyze the resistance performance data and propulsion performance data of all the ships obtained from the secondary screening, display the resistance performance and propulsion performance of different ships in the form of a graph on the client, and determine the parent ship according to the performance comparison result; The parent ship residual resistance coefficient correction module is used to, by the processor, interpolate in the TOD60 series of diagrams according to several geometric parameters of the target ship to obtain the theoretical residual resistance coefficient of the target ship, and then interpolate in the TOD60 series of diagrams according to the ship geometric data of the parent ship to obtain the theoretical residual resistance coefficient of the parent ship, calculate the ratio of the theoretical residual resistance coefficient between the target ship and the parent ship to obtain the correction coefficient, and then use the correction coefficient to correct the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship, so as to obtain the corrected residual resistance coefficient of the target ship; The total resistance and effective power calculation module of the target ship is used to calculate the total resistance and effective power of the target ship by the processor based on the expected speed in the designed operating parameters of the target ship input by the client, the overall length, length between perpendiculars, molded breadth, draft and block coefficient in the geometric parameters of the target ship, and the corrected residual resistance coefficient of the target ship obtained; The target ship performance prediction module is used to design the diagram propeller by the processor in combination with the main engine parameters of the target ship input by the user at the client, the calculated effective power of the target ship, and the propulsion performance data in the ship model test data of the parent ship, and apply the MAU propeller series diagram to obtain the mapping relationship between the expected speed of the target ship and the performance of the target ship, so as to realize the prediction of the effective power, advance coefficient, open water efficiency, propulsion efficiency, propeller speed and propeller received power related to the target ship performance; The test data update module is used to complete the model test after the target ship performance prediction, and store the data obtained from the model test as updated test data in the database of the server.

9. The ship speed performance analysis and prediction system according to claim 8, characterized in that, In the parent ship residual resistance coefficient correction module, the processor interpolates in the TOD60 series diagram to obtain the theoretical residual resistance coefficient of the target ship according to the block coefficient, length-width ratio, breadth-draft ratio in the geometric parameters of the target ship, and interpolates in the TOD60 series diagram to obtain the theoretical residual resistance coefficient of the parent ship according to the block coefficient, length-width ratio, breadth-draft ratio in the ship geometric data of the parent ship; and, after correcting the residual resistance coefficient in the resistance performance data of the ship model test data of the parent ship by the correction coefficient, the initial correction is completed, and the processor in the server also performs a secondary correction on the residual resistance coefficient after the initial correction according to the residual resistance correction coefficient input by the user at the client.

10. The ship speed performance analysis and prediction system according to claim 8 or 9, characterized in that, The work of the total resistance and effective power calculation module of the target ship includes: Determine the wetted surface area, waterline length, bilge keel area, and roughness allowance of the target ship according to the wetted surface area, waterline length, bilge keel area in the ship geometric data of the parent ship and the roughness allowance in the resistance performance data; Calculate the frictional resistance coefficient of the target ship according to the expected speed in the designed operating parameters of the target ship input by the client, the kinematic viscosity coefficient, and the waterline length of the target ship; Calculate the total resistance coefficient of the target ship according to the wetted surface area, bilge keel area, frictional resistance coefficient, roughness allowance of the target ship and the corrected residual resistance coefficient of the target ship; Calculate the total resistance of the target ship according to the total resistance coefficient, expected speed and wetted surface area of the target ship; Calculate the effective power of the target ship according to the total resistance and expected speed of the target ship.

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