Method and system for verifying drag reduction of a racing boat

Abstract

The application provides a racing boat drag reduction verification method and system, the system comprises a power and control module, a measurement module and a drag reduction verification module; the power and control module comprises a propulsion unit, a battery unit and a control unit; the measurement module comprises a thrust measurement unit, an environment monitoring unit and a motion and power parameter measurement unit to collect different test data in the test process; the drag reduction verification module is used for completing the racing boat drag reduction verification based on the test data obtained by the measurement module; the application can significantly improve the repeatability and reliability of the resistance test data, realizes comprehensive quantification of the hull resistance and its influencing factors, and through data correction and uncertainty evaluation, statistical evaluation under 95% confidence level of multiple groups is obtained, so that the result has international comparability and scientific reliability.

Description

Technical Field

[0001] This invention relates to the fields of intelligent motion data processing, motion data measurement, and rowing drag testing, and particularly to a method and system for verifying rowing drag reduction. Background Technology

[0002] In rowing competitions, underwater friction drag accounts for about 50% of the total drag of the rowing boat, and this proportion increases with the increase of speed. Therefore, adopting appropriate drag reduction technologies to reduce friction drag is an inevitable choice to improve speed. Among them, active drag reduction technologies such as ventilation drag reduction and supercavitation drag reduction, as well as passive drag reduction technologies such as superhydrophobic drag reduction, are widely used in the marine field.

[0003] Traditional methods for testing rowing drag, whether model tests in towed pools or actual racecourse tests, have certain limitations. Circulating tank testing, as a mechanistic experiment, can quickly verify the drag-reduction performance of coatings and efficiently select coating formulations with high drag-reduction potential. However, its drawback is that this laboratory-scale testing differs significantly from the actual sailing conditions of a racing boat. Towed pool testing, on the other hand, is a real-scale test with good controllability and repeatability. It allows for the measurement of hull drag under standardized conditions, and the test data is relatively stable and reliable. However, its disadvantages include high testing costs, long testing cycles, limited tow speeds, difficulty in covering the actual speed range of high-level athletes, and differences between the testing environment and real water. Athlete-based boat testing most closely resembles real-world usage scenarios, reflecting actual drag changes during paddling and the coating's performance in natural water. It is a crucial step in evaluating the final application effect. However, its disadvantages include an unstable testing environment, significant influence from wind, waves, temperature, and other factors, increased human error, limited repeatability and accuracy, and difficulty in detailed mechanistic analysis.

[0004] To take into account the advantages of the above three traditional testing methods, namely high efficiency, high repeatability, and close resemblance to actual boat motion, a drag reduction testing scheme for rowing propellers is proposed to provide platform support for systematic comparative testing. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this application provides Specifically, the present invention provides the following technical solutions: On one hand, the present invention provides a method for verifying drag reduction in racing boats, the method comprising: S1. Set up the exercise test plan and test groups, and obtain test data; S2. Preprocess the experimental data to obtain preprocessed data; S3. Calculate key parameters based on the preprocessed data; S4. Correct the key parameters to obtain corrected data; the data correction includes speed correction and drag data correction; the drag data correction includes viscous drag coefficient correction, wave-making drag coefficient correction, air drag correction and water temperature correction. S5. Perform statistical analysis based on the corrected data and calculate the uncertainty to obtain the final drag reduction verification results.

[0006] Preferably, the test data includes: timestamp, thrust, speed, rotational speed of both thrusters, air temperature, water temperature, wind speed, wind direction, and atmospheric pressure.

[0007] Preferably, the key parameters include total drag, drag coefficient, viscous drag coefficient, wave-making drag coefficient, speed, Reynolds number, Froude number, etc.

[0008] Preferably, in step S2, the preprocessing of the experimental data includes: First, the raw parameter data collected based on the timestamp is aligned; Secondly, the aligned data undergoes integrity, rationality, and consistency checks. Subsequently, the data that meets the verification requirements is subjected to noise reduction processing to obtain the noise-reduced data; Finally, the steady-state data segments of the denoised data are filtered out, and the data corresponding to the filtered steady-state data segments are used to obtain reliable preprocessed data.

[0009] Preferably, the steady-state data segment selection method is as follows: first, a sliding window operation (with a window length of, for example, set to N) is performed on the denoised data, and the standard deviation of the speed within the window is calculated. Rate of change of heading and longitudinal acceleration fluctuation ,in, The heading angle is represented by t, and time is represented by t. Secondly, , and Each window is compared with a preset steady-state threshold, and only the data in the window that meets all the steady-state threshold requirements can be marked as a steady-state segment. The steady-state thresholds include the speed standard deviation threshold, the heading rate of change threshold, and the longitudinal acceleration fluctuation threshold.

[0010] Preferably, in S3, the key parameters include average speed, average total resistance, water characteristic parameters, wetted surface area, characteristic length, total drag coefficient, Reynolds number, and Froude number; The average speed is the average velocity of the hull relative to the water during the steady-state data segment; the average total resistance is the average total thrust generated by the propulsion system during the steady-state data segment; the water characteristic parameters include water density and kinematic viscosity coefficient; the characteristic length is the design waterline length.

[0011] Preferably, in step S4, the speed correction method is as follows: When the actual average speed of the word experiment target speed If there is a deviation, the measured total resistance will be... Total drag corrected to target speed The revised calculation method is as follows: .

[0012] Preferably, in step S4, the correction method for viscous drag and wave-making drag is as follows: Calculate the form factor 1+k, and correct the viscous drag coefficient and wave-making drag coefficient based on the form factor. The correction method for the viscous drag coefficient is as follows: ,in, Indicates the viscous drag coefficient. Represents the coefficient of frictional resistance of a flat plate; the coefficient of wave resistance. The correction method is as follows: ,in, Indicates the total drag coefficient; The form factor is calculated as follows: First, calculate the residual drag coefficient. ,in The total drag coefficient is... Let be the coefficient of frictional resistance of the flat plate; then, the ratio will be... As the vertical axis, the ratio that is sensitive to the low-speed region will be used. Plot a scatter plot with n as the horizontal axis, where n represents The power of n, where n is a positive integer greater than 1. The Froude number is represented; furthermore, in the low-speed range, a linear fit is performed on the scatter plot and extrapolated to the zero point on the horizontal axis to obtain the vertical intercept. The shape factor can be obtained as: .

[0013] Preferably, in S4, air resistance The correction method is as follows:

[0014] in, Indicates air density, Indicates the relative wind speed of the ship; This represents the orthographic projection area of ​​the portion of the ship's hull above the waterline. This represents the air drag coefficient.

[0015] Preferably, in step S4, the water temperature correction method is to correct the total resistance coefficient by adjusting the water temperature. : First, the total drag coefficient and Reynolds coefficient are calculated using the water density and kinematic viscosity corresponding to the actual water temperature. When it is necessary to unify data from different water temperatures to a reference water temperature, the frictional drag coefficient is reduced accordingly. The method to correct it:

[0016] Then, using The corrected resistance value is obtained by combining the water density at the reference water temperature.

[0017] Preferably, in step S5, the uncertainty assessment method is as follows: Calculate random uncertainty and systematic uncertainty; Determine the propagation of uncertainty and calculate the expanded uncertainty of the total drag coefficient; The random uncertainty is estimated by the sample standard deviation of the results of repeated trials, that is, the standard uncertainty of the average of the results of multiple repeated trials is: Where Q is the number of repetitions and s represents the sample standard deviation. Indicates the standard uncertainty of repeatability; The calculation methods for system uncertainty include: First, establishing the total drag coefficient. Data conversion equation: ,in, The total drag is represented by S, the wetted surface area is represented by V, and the average speed is represented by V. The density of water is expressed; then, the sensitivity coefficient is calculated. : That is, the total drag coefficient For each input quantity The partial derivatives; The expanded uncertainty of the total drag coefficient is calculated as follows: First, calculate the combined standard uncertainty of the total drag coefficient. : ,in, Indicates the factor affecting the total drag. All input quantities; then calculate the expanded uncertainty. : , where K is the inclusion factor.

[0018] Preferably, in step S5, the statistical analysis is performed as follows: after multiple effective repeated experiments, the average total resistance and the average total resistance coefficient are calculated; and the difference in the average total resistance coefficient between different experimental groups is determined to be statistically significant through independent samples t-test and nonparametric equivalence method.

[0019] Preferably, S5 further includes: After all tests are completed, the average total drag coefficient is calculated. Average total resistance Standard deviation of drag coefficient and expanded uncertainty ; Plot the average total drag coefficient of different test groups The drag reduction verification results are obtained by varying the average speed, Froude number, or Reynolds number.

[0020] Secondly, the present invention also provides a drag reduction verification system for racing boats, which includes: a power and control module, a measurement module and a drag reduction verification module; The power and control module includes a propulsion unit, a battery unit, and a control unit. The propulsion unit has two parallel thrusters to provide power to the boat under test. The control unit is connected to the propulsion unit and controls the thrusters through closed-loop PID control and achieves heading and attitude control through thrust differential control. The battery unit supplies power to the propulsion unit and the control unit. The measurement module includes a thrust measurement unit, an environmental monitoring unit, and a motion and dynamic parameter measurement unit to collect different test data during the test process; The drag reduction verification module is used to process and calculate the test data based on the test data obtained by the measurement module, and to perform drag reduction verification of the racing boat as described above.

[0021] Thirdly, the present invention also provides an apparatus comprising at least a memory and a processor, wherein the processor, based on the collected racing boat test data, calls computer instructions stored in the memory to execute the racing boat drag reduction verification method as described above.

[0022] Compared with existing technologies, this solution has at least the following beneficial effects: This invention overcomes the problems of excessive human factors and poor repeatability in traditional manual rowing tests, as well as boundary and scale effects in towed pool tests, by introducing a controllable propulsion system and closed-loop speed control strategy under real water conditions. This allows the racing boat to maintain a stable, uniform, straight-line state during testing, significantly improving the repeatability and reliability of drag test data. The pump-jet propulsion structure and the symmetrically arranged propeller arms effectively reduce wake disturbances and local flow field distortion, ensuring the test environment is closer to natural navigation conditions. Simultaneously, the system integrates multiple parameter sensors for thrust, speed, attitude, water temperature, and wind speed, supporting high-precision synchronous data acquisition and real-time control feedback, achieving comprehensive quantification of hull drag and its influencing factors. By introducing an uncertainty assessment model, this invention can provide a statistical evaluation of the drag coefficient at a 95% confidence level, making the results internationally comparable and scientifically reliable. Furthermore, the system structure is lightweight and modular, facilitating disassembly and rapid adaptation to different boat types, improving testing efficiency and reducing testing costs, thus possessing high engineering application value. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of the drag reduction verification method for racing boats according to an embodiment of the present invention; Figure 2 This is a structural block diagram of the drag reduction verification system for racing boats according to an embodiment of the present invention; Figure 3 This is a structural diagram of the propeller frame portion according to an embodiment of the present invention; Figure 4 This is a physical example of the oar frame and racing boat assembly according to an embodiment of the present invention. Detailed Implementation

[0025] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] Those skilled in the art should understand that the following specific embodiments or implementation methods are a series of optimized configurations listed to further explain the specific content of the invention. These configuration methods can be combined or used in conjunction with each other, unless the invention explicitly states that some or a specific embodiment or implementation method cannot be associated with or used in conjunction with other embodiments or implementation methods. Furthermore, the following specific embodiments or implementation methods are merely optimized configurations and are not intended to limit the scope of protection of the invention.

[0027] This proposal aims to accurately test and verify the drag performance of racing boats under four categories of conditions: testing the drag-reducing coating effect, testing the effect of new boat types, testing the synergistic effect of coating and boat type applications, and testing and evaluating uncertainties. Specifically, testing the drag-reducing coating effect aims to accurately measure the change in the total drag system (CT) of a traditional racing boat before and after applying the coating, covering multiple typical racing speed conditions and providing absolute changes and relative percentages. Testing the new boat type effect aims to analyze the difference in total drag between the new boat type without coating and the traditional boat type at the same speed conditions, and to show trend changes, absolute and relative values. Testing the synergistic effect of coating and boat type applications aims to examine the total drag performance under the combination of a new boat type and a new coating, including identifying whether a synergistic drag-reducing effect exists and proposing optimization suggestions. The main objective of testing and evaluating uncertainties is to construct a systematic uncertainty model for all total drag system data and provide evaluation results at, for example, a 95% confidence level, to meet ITTC international standards.

[0028] In this embodiment, simultaneously combined Figure 1 and Figure 2 As shown in this embodiment, the solution can be implemented by setting up a system to verify and test the drag reduction of the racing boat. The basic setup of this system includes the following components: a power and control module and a measurement module. In addition, the system also includes a drag reduction verification module for performing data calculation and comparison. Of course, the system can also be considered to include the racing boat or hull to be measured.

[0029] I. Power and Control Module Furthermore, the power and control module includes a propulsion unit, a battery unit, and a control unit, as well as a safety protection unit, which mainly includes a BMS device, fuses, and waterproof connectors. In this embodiment, the propulsion unit has two parallel thrusters, preferably direct-drive motors with a zero-leakage sealing structure. The thrusters are connected to the control unit via a CAN bus, and the thruster drivers can be built-in, powered by, for example, DC 24V. In this embodiment, the thruster motors use an axial direct-drive method and lightweight materials to reduce overall weight and improve safety and reliability.

[0030] Combination Figure 3 As shown, the propulsion unit has a symmetrical structure with consistent thrust on both sides. It includes a propeller frame and two thrusters, which are axially parallel on both sides of the propeller frame and propel in the same direction. The propeller frame adopts a height-adjustable structure, preferably a foldable and detachable design. The propeller frame mainly includes a lower fixed plate, an upper bracket, and a height-adjusting bracket. The lower fixed plate is used to fix the propeller frame to the upper part of the racing boat, such as the position where the athlete sits. The upper bracket is connected to the lower fixed plate through a thrust sensor. There are two height-adjusting brackets, left and right, which are connected to the upper bracket through an adjustable structure. The lower ends of the left and right height-adjusting brackets are connected to the two thrusters respectively. In this embodiment, the thrust sensor is a six-component sensor. When connected, its upper part is connected to the midpoint of the upper bracket, and its lower part is connected to the lower fixed plate connected to the hull. The thrust sensor is connected by a connecting flange, which allows for convenient disassembly and replacement, and can be adapted to different hulls. The propulsion unit is fixed at the rear of the middle of the hull. In actual measurements, the upper boundaries of the two propellers on both sides of the propulsion unit are located about 150 mm underwater to minimize the impact of the propeller flow on the hull.

[0031] The thruster design must consider the requirements of lightweight construction and low flow field disturbance. In this embodiment, the thruster shell is made of aluminum alloy, the propeller is made of stainless steel, and the thruster adopts a pump-jet propulsion method. The propeller frame is also preferably made of lightweight and high-strength materials and has undergone hydrodynamic optimization design.

[0032] The battery unit employs a main battery and an auxiliary battery power supply. The main battery can be set to DC 48V to power the thruster motor, providing power; the auxiliary power supply can be set to DC 24V to power the driver and other equipment. In another embodiment, the driver and other equipment can also be powered by the main battery. In this case, a DC-DC converter can be added to convert the voltage to the rated voltage of the driver and other equipment. The BMS device is mainly used for overcharge, over-discharge, short circuit, and cell balancing control and protection. Fuses are mainly used for centralized protection, and waterproof connectors are mainly used for waterproof protection of the equipment, with a waterproof rating of IP68.

[0033] Within the control unit, the control strategy primarily includes overall control and heading and attitude control. Overall control employs a closed-loop PID controller, using the speed provided by a laser velocimeter or GPS module as feedback. The PID controller precisely maintains the target speed by adjusting the total thrust (or speed / power) of both propellers. Heading and attitude control utilizes the thrust differential between the two propellers to achieve heading control. The boat's attitude (pitch and roll) mainly relies on the hull's inherent stability. If the attitude deviation exceeds a threshold due to propeller imbalance or external disturbances, the system can correct it by fine-tuning the differential thrust or marking the test data as invalid.

[0034] In this embodiment, the control unit design balances real-time responsiveness and system safety. Specifically, the overall control employs a proportional-integral-derivative (PID) control algorithm. The algorithm includes: real-time acquisition of speed signals from a laser velocimeter or GPS module, comparison with a preset target speed, and calculation of the speed deviation; the controller outputs instantaneous corrections based on the proportional element, corrects long-term deviations using the integral element, and suppresses dynamic overshoot using the derivative element, thereby achieving closed-loop regulation of the thrust of both thrusters. The PID parameters (Kp, Ki, Kd) are automatically tuned through step response experiments during the water commissioning phase to ensure the system reaches steady state within 5 seconds with an overshoot of less than 5%.

[0035] In terms of attitude and heading control, the system uses an inertial measurement unit (IMU) to collect pitch, roll, and yaw angle data in real time and compares them with set attitude thresholds. When an attitude deviation exceeding ±2° or a roll rate exceeding 0.5° / s is detected, the control unit automatically calculates the thrust difference correction ΔT, and then... The control method fine-tunes the speed difference between the left and right thrusters to achieve active attitude correction, where θ represents the current attitude deviation angle and t represents time. If the attitude deviation fails to recover to the threshold range within 5 consecutive seconds, the system determines that the test data is invalid and automatically records it as an abnormal flight.

[0036] Furthermore, the control unit adopts an anti-interference CAN bus communication structure, supports bus redundancy design and signal verification mechanism, ensuring the reliability of command data transmission. The control logic completes the sampling-judgment-command output closed loop within 0.01 seconds, with a total control delay of less than 10 ms. The system has real-time monitoring and alarm functions for temperature, current, and communication status. When overcurrent, stall, or overtemperature occurs, it automatically enters a reduced-power operation mode and triggers a safety shutdown procedure.

[0037] Furthermore, redundant channels can be configured in the control unit to enable functions such as emergency shutdown via wireless telemetry. Additionally, the control unit can be equipped with necessary alarms and handling measures for overcurrent, stall, or over-temperature. In this embodiment, the CAN bus control response time is less than 10ms, and the overload protection function ensures continuous operation for more than 8 hours.

[0038] Furthermore, before system testing, the power and control modules are debugged and calibrated. The calibration process can be divided into three stages: bench testing (verifying electrical and communication links and calibrating basic thruster functions); thrust testing (static thrust detection of a single thruster); and waterborne calibration, including speed calibration (establishing thrust-speed curves using GPS or laser velocimetry) and PID tuning (fine-tuning the PID controller parameters, including proportional gain Kp, integral gain Ki, and derivative gain Kd). During fine-tuning, a step response test is first conducted in still water. By acquiring real-time speed change curves, the system overshoot, steady-state error, and rise time are calculated. Subsequently, the Ziegler-Nichols tuning method or an adaptive tuning algorithm based on least squares is used to iteratively adjust these three parameters. Ultimately, the system response is adjusted to a target tolerance range where the steady-state error is less than ±2%, the overshoot is less than 5%, and the rise time does not exceed 3 seconds, thus ensuring the stability and speed of the control system at different speeds. Simultaneously, endurance verification is conducted, which involves testing or measuring the battery's continuous capability at set or measured flight speeds. In addition, safety-triggered tests are also included, such as redundancy tests for emergency shutdown and communication interruption.

[0039] II. Measurement Module The measurement module mainly includes a thrust measurement unit, an environmental monitoring unit, and a motion and dynamic parameter measurement unit. In this embodiment, when conducting drag testing on the racing boat, it is preferable to record the following data parameters during the test: timestamp, thrust, speed, dual-propeller speed, air temperature, water temperature, wind speed, wind direction, and atmospheric pressure.

[0040] 1. Thrust Measurement Unit In this system, the thrust measurement unit is mainly implemented by a thrust sensor. A six-dimensional thrust sensor (i.e., a six-component sensor) is preferred. During installation, ensure that the sensor's measurement axis coincides with the thrust line of action to avoid errors introduced by additional bending moment or eccentricity. Before starting the system measurement, perform a full-chain in-situ calibration of the sensor and its connected signal conditioner. For direct thrust measurement, a high-precision six-dimensional thrust sensor is installed at the connection between the propeller arm and the hull, such as... Figure 3 As shown.

[0041] When the racing boat is in self-propelled mode, the thrust sensor is used to directly determine the total thrust required by the propulsion module to maintain a stable speed, because in stable uniform linear motion, the total thrust equals the total drag. The thrust sensor can directly measure the force generated by the propulsion system; in this embodiment, the sensor range is 200N. In this embodiment, a high-precision bidirectional force sensor is preferably used to accurately measure the resultant force generated by the propulsion unit.

[0042] In actual testing, after setting up the basic thrust measurement unit on the tested racing boat, the boat's appearance was as follows: Figure 4 As shown.

[0043] 2. Environmental monitoring unit The environmental monitoring unit is mainly used to acquire parameters such as temperature, humidity, wind speed, wind direction, atmospheric pressure, water temperature, water level, and flow velocity at the test site. These parameters are used to correct the wind resistance model and to determine the degree of environmental interference and the impact of external hydrological disturbances on the test results.

[0044] 3. Motion and dynamic parameter measurement unit It is mainly used to measure various parameter data during the experiment.

[0045] 1) Speed ​​measurement Various types of speed measurement sensors can be used. In this embodiment, a non-contact laser Doppler velocimeter is used to measure the speed of the racing boat relative to the water. In addition, auxiliary / redundant sensors and a GNSS receiver supporting real-time dynamic differential technology are also provided to measure the speed of the racing boat relative to the ground. The sensors are calibrated before the actual measurement experiment.

[0046] 2) Acceleration, attitude, and heading measurements In this embodiment, a high-performance inertial measurement unit (IMU) is used to measure acceleration and attitude, integrating attitude and navigation reference functions. The IMU sensor synchronously outputs three-axis acceleration. During installation, the IMU sensor is rigidly mounted near the center of gravity of the racing boat, and its coordinate system is precisely aligned with the boat's coordinate system.

[0047] III. Drag Reduction Verification Process Combination Figure 1 As shown, the test process for rowing drag is as follows: 1. Set up a motion test plan and define test groups to obtain data for different test groups during different test processes (target test speed). Test groups can be set as follows: Table 1 Experimental Groups

[0048] In the tests, target speeds were set at 2.0 m / s, 3.0 m / s, 4.0 m / s, 5.0 m / s, and 6.0 m / s. During the tests, each test group and speed combination required at least five valid and independent repeatable tests. To ensure the independence and repeatability of each test, sufficient interval time or different flight paths should be ensured between each two tests to reduce wake interference. Repeated tests were conducted according to the requirements of ITTC Procedure 7.5-02-02-02 for uncertainty analysis.

[0049] The standard procedure for a single test includes: setting the starting point of the acceleration zone, controlling acceleration with a PID speed controller to reach a steady-state speed and attitude, continuously recording the parameters collected by each sensor, maintaining a stable measurement period for a certain duration, smoothly decelerating and exiting the measurement zone, and then stopping recording. After a certain interval, the next test is conducted.

[0050] 2. Data preprocessing and validity testing First, the acquired raw parameter data undergoes basic checks for completeness, rationality, and consistency after multi-source data alignment based on timestamps. Second, a low-pass filter with an optimized cutoff frequency is used to denoise the sensor signals, achieving a balance between noise suppression and signal feature preservation. Finally, a steady-state identification algorithm based on quantization criteria is employed. By setting stability thresholds for key motion parameters such as speed, heading, and acceleration, and combining this with a sliding window statistical method, the automatic identification of steady-state data segments is achieved. Specifically, the system first performs a sliding window operation of length N on the raw time-series data, calculating the standard deviation of speed within the window. Rate of change of heading and longitudinal acceleration fluctuation ,in, Let t represent the heading angle and t represent time. Then, the above statistics are compared with preset steady-state thresholds for window-by-window evaluation. Only windows that simultaneously meet all steady-state criteria are marked as steady-state segments, thus achieving automatic and objective screening of steady-state data segments in each experimental voyage, providing a reliable data foundation for subsequent analysis.

[0051] 3. Calculation of key parameters After data preprocessing, key parameters are calculated. In this embodiment, the key parameters and their calculation methods specifically include the following: (1) Average speed (V / (m / s)) The average velocity relative to water (STW) within the steady-state data segment is calculated using the following formula. If only the velocity relative to ground (SOG) is available, and the water flow is negligible or the water flow velocity has been measured, then the SOG is corrected to the velocity relative to water.

[0052]

[0053] In the formula: N is the total number of sampling points in the steady-state range. It is the sum of all water velocity samples within this segment.

[0054] (2) Average total resistance ( / (ox)) The calculation of average total drag is equivalent to calculating the average total thrust produced by the propulsion system during the steady-state range, which is the total drag at that speed. In total resistance In the calculation: If the direct towing method is used, the total resistance is determined by the average reading of the thrust sensor in the steady-state range, i.e. This is the average value directly measured by the sensor. For self-propelled testing, the average speed or power within the steady-state range is converted to average thrust using the thruster calibration curve (thrust vs. speed / power relationship), or the average value of the thrust sensor measurements is directly used as the average. The calculation formula is as follows: .

[0055] (3) Water body characteristic parameters Calculate the water density by referring to the standard water physical property table or using formulas (such as those recommended by ITTC) based on the average water temperature (°C) recorded during the steady-state period. (kg / m³) and kinematic viscosity coefficient H (m² / s).

[0056] (4) Wet surface area (S / (m²)) 2 and characteristic length (L / (m)) The wetted surface area S is usually taken as the waterline corresponding to the total displacement; the characteristic length L is usually taken as the design waterline length. These two parameters must be precisely determined for each ship type (traditional and new). S is usually calculated based on the hull CAD model under static buoyancy, corresponding to the total displacement (hull + equipment + load) up to the actual test. L is usually taken as the design waterline length (LWL).

[0057] Due to the influence of wave formation and sailing attitude, the dynamic wetted surface area should be accurately determined. It is rather complex; in this embodiment, the nominal wetted surface area at rest is used.

[0058] (5) Calculation of dimensionless coefficients The specific calculation methods for the total drag coefficient, Reynolds number, and Froude number (refer to ITTC standards) are as follows: Total drag coefficient:

[0059] Reynolds number:

[0060] Froude number:

[0061] In the formula, It is the total resistance; S is the fluid density; S is the wetted surface area; L is the ship's length. It refers to velocity (especially velocity measured in real time); H is the kinematic viscosity coefficient; It is gravitational acceleration.

[0062] 4. Data Correction After calculating the key parameters, the data needs further correction. The specific correction method is as follows: (1) Speed ​​correction If the measured average speed of a single test target speed There is a slight deviation, and the measured resistance needs to be adjusted. Drag correction to target speed To ensure the comparability of data from different voyages under the same benchmark, this embodiment assumes that viscous drag dominates the speed range of the racing boat, and its total drag... With speed Since it is directly proportional, the specific calculation formula for the speed correction in this embodiment is as follows: .

[0063] (2) Resistance data correction is achieved through shape factor and friction / residual resistance classification. The correction of resistance data mainly includes the correction of viscous drag coefficient and wave-making drag coefficient. In this embodiment, a shape factor (1+k) is introduced to amplify and correct the frictional drag coefficient of the flat plate. The correction method for the viscous drag coefficient is as follows: ,in, This represents the corrected viscous drag coefficient, which includes flat plate friction and additional drag from the hull shape. The coefficient of friction of a flat plate is used to characterize the basic frictional resistance under the same Reynolds number conditions; wave-making drag coefficient. for: ,in, This represents the measured total drag coefficient. This step is equivalent to removing the corrected viscous component from the total drag to obtain the wave-making drag component purely caused by wave generation, volume changes, and free surface disturbance. Furthermore, to improve comparability between different test conditions, the scheme also includes supplementary corrections for other influencing factors, including: air resistance correction, water temperature and viscosity correction, and residual minor drag correction.

[0064] The shape factor (1+k) can be achieved by utilizing the low-speed region (typically the Froude number). <0.20 The resistance test data (0.25) was fitted to separate viscous resistance from residual resistance. The method used in this embodiment is as follows: First, the residual resistance coefficient is calculated: ,in The total drag coefficient is... This represents the coefficient of friction resistance of the flat plate. Subsequently, the ratio... As the vertical axis, the ratio (or more sensitive to low-speed range) A scatter plot is drawn with the x-axis as the horizontal axis. In the low-speed range, the relationship between the two is approximately linear. The y-intercept can be obtained by linearly fitting the data and extrapolating it to the zero point of the horizontal axis. By definition, shape factors satisfy the following relationship: Furthermore, at the low-speed limit, the remaining drag approaches zero, that is: Therefore, the intercept is the shape factor k, and the shape factor is calculated as follows: The acquisition of low-speed test data must meet the requirements for calculable parameters. Requirements include model drag, wetted surface area, mass, fluid properties, and speed, to ensure the stability of the extrapolation results. 。 This solution first calculates the residual drag ratio. Then, extrapolate to find the form factor 1+k, which is different from the traditional method of directly extrapolating the total drag ratio (C). T / C F The physical logic of finding (1+k) is clearer, and by extrapolating the residual resistance with a smaller value, the interference of friction resistance calculation error can be reduced, thereby improving the accuracy and stability of shape factor extrapolation.

[0065] This requires an additional series of low-speed tests. The data collected during these low-speed tests must be sufficient to calculate the aforementioned parameters. .

[0066] The classification of resistance components helps in understanding the coating (the main influence). and some of the impacts on k) and ship type (mainly affecting k and Each has its own drag reduction mechanism.

[0067] (3) Air drag correction During testing, when wind conditions are unfavorable and inconsistent, or when the aerodynamic characteristics of the above-water portions of different ship types vary significantly, air resistance must be considered. Therefore, air resistance corrections are necessary for the data. When air resistance needs to be considered, air resistance... The correction method is as follows:

[0068] In the formula, Indicates air density, This indicates relative wind speed, which is the speed of the ship relative to the air. This represents the orthographic projection area of ​​the portion of a ship or ship model above the waterline. This represents the air drag coefficient.

[0069] (4) Friction resistance correction through water temperature correction Changes in water temperature affect frictional resistance and thus total resistance by altering the water's density and viscosity. When making corrections, the physical properties (water density) corresponding to the actual water temperature are first used. ρ Calculate the total drag coefficient using the kinematic viscosity coefficient H. and Reynolds coefficient If it is necessary to standardize data across different water temperatures, then the data should be recalculated to a reference water temperature. This recalculation is based on the frictional resistance coefficient. This can be achieved through adjustments:

[0070] Then, using The corrected total resistance value can be calculated by comparing the water density at the reference water temperature with the water density at the reference temperature.

[0071] 5. Data statistics and uncertainty assessment (1) Statistical analysis: For each test condition (ship type, speed), the average total resistance was calculated based on the results of 5 valid repeated tests. and average total drag coefficient The corresponding standard deviation was obtained. The data obtained from 5 repeated trials are expressed as mean ± standard deviation (M ± SD), and the measurement dispersion is described in conjunction with the uncertainty.

[0072] Mean analysis: This embodiment uses a two-independent-samples t-test and employs an equivalent nonparametric method when variances are unequal. The t-test statistic is calculated by pooling the standard deviations and compared with the significance level. α The significance level in this embodiment is compared with the critical value at 0.05. α (Using a critical value of 0.05). When p When the value is ≤0.05, the two groups of resistance performance are considered to be statistically significant. This statistical test can be used to: 1) verify the real impact of different designs on resistance performance; 2) quantitatively evaluate the effectiveness of the optimization scheme; 3) avoid misjudging random fluctuations as effective improvements, thereby providing a reliable statistical basis for ship type optimization.

[0073] (2) Uncertainty analysis Identify the basic sources of error: Type A uncertainty (random uncertainty): originating from repeated measurements. The numerical dispersion over time, small fluctuations in speed, etc. The standard uncertainty is estimated by the sample standard deviation of repeated test results; the standard uncertainty of the average of multiple repeated test results is... Where Q is the number of repetitions and s represents the sample standard deviation. This indicates the standard uncertainty of repeatability.

[0074] Type B uncertainty (systematic uncertainty): originating from the calibration uncertainty of force sensors, velocity sensors, temperature sensors, IMUs, etc.; captain and wet area Measurement uncertainty; caused by water temperature measurement uncertainty ρ and ν The uncertainty is determined by the model itself; if blockage or aerodynamic corrections are applied, the uncertainty is adjusted accordingly. These are typically estimated based on calibration certificates, equipment specifications, or references. The instrument's resolution is also a source of Type B uncertainty.

[0075] Establish Data conversion equation: .

[0076] Calculate the sensitivity coefficient : For each input quantity ( The partial derivatives of (etc.), i.e. , wait.

[0077] Uncertainty propagation: Combined standard uncertainty It is obtained by propagating and synthesizing the standard uncertainties of each input quantity through sensitivity coefficients. For uncorrelated input quantities, , Indicates the factor affecting the total drag. All input quantities. The Type A and Type B uncertainties are propagated separately and then combined, or the standard uncertainties of each component (regardless of Type A or Type B) are directly combined in this way.

[0078] The expanded uncertainty is calculated as follows: Typically, the inclusion factor is taken. This corresponds to a confidence level of approximately 95%.

[0079] Based on the above uncertainty calculations, this embodiment presents the various influencing factors and their propagation by compiling an uncertainty budget table, as shown in Table 2.

[0080] Table 2 Uncertainty Budget Representation Example

[0081] 6. Results Presentation After all tests are completed, the average total drag coefficient under all operating conditions is summarized in tabular form. Average total resistance Standard deviation of drag coefficient and expanded uncertainty .

[0082] Next, we will draw a chart: Average Total Resistance Coefficient With speed (or The results of the four experimental groups were plotted on the same graph, and error bars were used to represent the changes. (95% confidence interval). The graph can be plotted using existing techniques.

[0083] Graphs of surface roughness and contact angle data: Plotting can be done using libraries such as Python's Matplotlib and Seaborn to support the plotting of confidence intervals.

[0084] Determining the shape factor is invaluable for a deeper understanding of hydrodynamic characteristics. However, whether to include this analysis during actual test set verification depends on the balance between the desired depth of analysis and practical operation, and can be determined by the actual testing needs. In this embodiment, the shape factor is used based on the need for more precise testing. Uncertainty analysis is not an isolated final step; its consideration should be integrated throughout the entire experimental design. The estimated main sources of uncertainty can be used to guide decisions on sensor selection, calibration accuracy requirements, or the number of repeated trials. Presenting the results with clear confidence intervals (error bars) directly meets the user's requirements for "confidence level."

[0085] The above is a preferred embodiment of this solution, which introduces different key step settings and the main process and method of drag reduction verification.

[0086] In another embodiment, the solution of the present invention can also be implemented through a racing boat drag reduction verification system, which includes a power and control module, a measurement module and a drag reduction verification module, to form a system capable of testing and verifying drag reduction for racing boats under different conditions. The power and control module includes a propulsion unit, a battery unit, and a control unit. The propulsion unit has two parallel thrusters to provide power to the boat under test. The control unit is connected to the propulsion unit and controls the thrusters through closed-loop PID control and achieves heading and attitude control through thrust differential control. The battery unit supplies power to the propulsion unit and the control unit. The measurement module includes a thrust measurement unit, an environmental monitoring unit, and a motion and dynamic parameter measurement unit to collect different test data during the test process; The drag reduction verification module is used to process and calculate the test data based on the test data obtained by the measurement module, and to perform drag reduction verification of the racing boat as described above.

[0087] In yet another embodiment, the present invention can also be implemented by means of a device, which includes one or more processors and a memory, wherein the processor can call computer instructions in the memory to execute the methods described in the above embodiments.

[0088] A processor may be a central processing unit (CPU) or other form of processing unit with data processing and / or information execution capabilities, and may control other components in an electronic device to perform desired functions.

[0089] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory.

[0090] In one example, the device may also include input and output devices, which are interconnected via a bus system and / or other forms of connection mechanisms.

[0091] The logic and / or steps represented in the flowchart or otherwise described herein may be specifically implemented in any readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0092] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for verifying drag reduction in racing boats, characterized in that, The method includes: S1. Set up the exercise test plan and test groups, and obtain test data; S2. Preprocess the experimental data to obtain preprocessed data; S3. Calculate key parameters based on the preprocessed data; S4. Correct the key parameters to obtain corrected data; the data correction includes speed correction and drag data correction; the drag data correction includes viscous drag coefficient correction, wave-making drag coefficient correction, air drag correction and water temperature correction. S5. Perform statistical analysis based on the corrected data and calculate the uncertainty to obtain the final drag reduction verification results.

2. The method according to claim 1, characterized in that, In step S2, the preprocessing of the experimental data includes: First, the raw parameter data collected based on the timestamp is aligned; Secondly, the aligned data undergoes integrity, rationality, and consistency checks. Subsequently, the data that meets the verification requirements is subjected to noise reduction processing to obtain the noise-reduced data; Finally, the steady-state data segments of the denoised data are filtered out, and the data corresponding to the filtered steady-state data segments are used to obtain reliable preprocessed data.

3. The method according to claim 2, characterized in that, The method for filtering the steady-state data segment is as follows: First, a sliding window operation is performed on the denoised data, and the standard deviation of the speed within the window is calculated. Rate of change of heading and longitudinal acceleration fluctuation ,in, Indicates the heading angle; Secondly, , and Each window is compared with a preset steady-state threshold, and only the data in the window that meets all the steady-state threshold requirements can be marked as a steady-state segment. The steady-state thresholds include the speed standard deviation threshold, the heading rate of change threshold, and the longitudinal acceleration fluctuation threshold.

4. The method according to claim 1, characterized in that, In S3, the key parameters include average speed, average total resistance, water body characteristic parameters, wetted surface area, characteristic length, total drag coefficient, Reynolds number, and Froude number. The average speed is the average velocity of the hull relative to the water during the steady-state data segment; the average total resistance is the average total thrust generated by the propulsion system during the steady-state data segment; the water characteristic parameters include water density and kinematic viscosity coefficient; the characteristic length is the design waterline length.

5. The method according to claim 1, characterized in that, In S4, the speed correction method is as follows: When the actual average speed of the word experiment target speed If there is a deviation, the measured total resistance will be... Total drag corrected to target speed The revised calculation method is as follows: 。 6. The method according to claim 1, characterized in that, In S4, the correction methods for viscous drag and wave-making drag are as follows: Calculate the form factor 1+k, and correct the viscous drag coefficient and wave-making drag coefficient based on the form factor. The correction method for the viscous drag coefficient is as follows: ,in, Indicates the viscous drag coefficient. This represents the coefficient of frictional resistance of a flat plate and the coefficient of wave-making resistance. The correction method is as follows: ,in, Indicates the total drag coefficient; The form factor is calculated as follows: First, calculate the residual drag coefficient. ,in The total drag coefficient is... Let be the coefficient of frictional resistance of the flat plate; then, the ratio will be... As the vertical axis, the ratio that is sensitive to the low-speed region will be used. Plot a scatter plot with n as the horizontal axis, where n represents The power of n, where n is a positive integer greater than 1. The Froude number is represented; furthermore, in the low-speed range, a linear fit is performed on the scatter plot and extrapolated to the zero point on the horizontal axis to obtain the vertical intercept. The shape factor can be obtained as: .

7. The method according to claim 1, characterized in that, In S4, air resistance The correction method is as follows: in, Indicates air density, Indicates the relative wind speed of the ship; This represents the orthographic projection area of ​​the portion of the ship's hull above the waterline. This represents the air drag coefficient.

8. The method according to claim 1, characterized in that, In step S4, the water temperature correction method is to correct the total resistance coefficient by adjusting the water temperature. : First, the total drag coefficient and Reynolds coefficient are calculated using the water density and kinematic viscosity corresponding to the actual water temperature. When it is necessary to unify data from different water temperatures to a reference water temperature, the frictional drag coefficient is reduced accordingly. The method to correct it: Then, using The corrected resistance value is obtained by combining the water density at the reference water temperature.

9. The method according to claim 1, characterized in that, In S5, the uncertainty assessment method is as follows: Calculate random uncertainty and systematic uncertainty; Determine the propagation of uncertainty and calculate the expanded uncertainty of the total drag coefficient; The random uncertainty is estimated by the sample standard deviation of the results of repeated trials, that is, the standard uncertainty of the average of the results of multiple repeated trials is: Where Q is the number of repetitions and s represents the sample standard deviation. Indicates the standard uncertainty of repeatability; The calculation methods for system uncertainty include: First, establishing the total drag coefficient. Data conversion equation: ,in, The total drag is represented by S, the wetted surface area is represented by V, and the average speed is represented by V. The density of water is expressed; then, the sensitivity coefficient is calculated. : That is, the total drag coefficient For each input quantity The partial derivatives; The expanded uncertainty of the total drag coefficient is calculated as follows: First, the combined standard uncertainty of the total drag coefficient is calculated. : ,in, Indicates the factor affecting the total drag. All input quantities; then calculate the expanded uncertainty. : , where K is the inclusion factor.

10. A drag reduction verification system for racing boats, characterized in that, The system includes: a power and control module, a measurement module, and a drag reduction verification module; The power and control module includes a propulsion unit, a battery unit, and a control unit. The propulsion unit has two parallel thrusters to provide power to the boat under test. The control unit is connected to the propulsion unit and controls the thrusters through closed-loop PID control and achieves heading and attitude control through thrust differential control. The battery unit supplies power to the propulsion unit and the control unit. The measurement module includes a thrust measurement unit, an environmental monitoring unit, and a motion and dynamic parameter measurement unit to collect different test data during the test process; The drag reduction verification module is used to process and calculate the test data based on the test data obtained by the measurement module, using the method described in any one of claims 1-9, in order to perform drag reduction verification for the racing boat.

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