Self-circulation jet flow stability expansion control system for water-jet propeller

Abstract

The invention relates to the technical field of ship propulsion control, in particular to a self-circulation jet flow stability expansion control system for a water-jet propeller, which comprises a self-circulation jet flow regulation and control unit, a flow state monitoring module, a vector jet flow generation module, an intelligent control module and a self-sustaining energy module, the flow state monitoring module obtains pressure distribution data of the back slope surface of the elbow-shaped water inlet flow channel through a pressure sensor, the intelligent control module extracts flow separation dominant frequency characteristics and dynamically generates jet pulse frequency, momentum coefficient and vector angle compensation amount, and the vector jet generation module executes instructions through an independent adjusting mechanism. The self-sustaining energy module uses pipeline differential pressure to generate electricity and supply power. The system solves the problems of turbulence and energy waste of a traditional fixed parameter control flow field, accurately inhibits vortexes, improves the stability of the flow field and the energy utilization rate, and guarantees the propulsive efficiency and the service life of equipment.

Description

Technical Field

[0001] This invention relates to the field of ship propulsion control technology, and more specifically, to a self-circulating jet stabilization control system for waterjet propulsion systems. Background Technology

[0002] Ship propulsion control is an important technology. During ship navigation, waterjet propulsion generates thrust through high-speed jets, and its operational stability directly affects the ship's speed, maneuverability, and energy consumption.

[0003] This technology suppresses flow separation and vortexes by regulating the water flow state, which is of great significance for improving propulsion efficiency, reducing operating noise, and ensuring navigation safety. Traditional jet control methods that rely on fixed parameters are no longer able to cope with dynamic flow field changes under complex working conditions.

[0004] However, traditional waterjet propulsion jet control technology suffers from core problems of insufficient flow field stability and poor control adaptability. Existing solutions use jet parameters with fixed frequency and momentum, failing to consider the dynamic flow characteristics of the separation zone on the back slope of the curved inlet channel. When the water flow forms a separation vortex on the back slope, the fixed-parameter jet cannot accurately suppress vortex development, leading to increased flow field turbulence. At the same time, the jet angle and pulse pattern are not dynamically adjusted according to the dominant frequency characteristics and geometric shape of the flow separation, resulting in wasted jet energy or control failure. This leads to decreased propulsion efficiency, increased pipeline vibration, and long-term operation can also exacerbate equipment wear and increase maintenance costs, making it difficult to meet the stability requirements of the propulsion system when ships navigate in complex waters. To solve this technical problem, we provide a self-circulating jet stabilization control system for waterjet propulsion. Summary of the Invention

[0005] The purpose of this invention is to provide a self-circulating jet stabilization control system for waterjet propulsion systems to solve the problems mentioned in the background art.

[0006] 1. Since traditional systems use fixed jet parameters, they cannot cope with the turbulent flow field caused by dynamic flow characteristics. Therefore, this case uses a flow monitoring module to obtain pressure data and an intelligent control module to extract the main frequency characteristics and generate dynamic jet commands, which can accurately suppress vortices and improve flow field stability.

[0007] 2. Because traditional systems do not adjust the jet angle and pulse pattern according to the flow characteristics, energy is wasted or control fails. Therefore, this case uses a vector jet generation module to adjust the angle and a parameter matching module to optimize the pulse frequency and momentum coefficient, which can improve energy utilization and enhance control adaptability.

[0008] To achieve the above objectives, a self-circulating jet stabilization control system for a waterjet propulsion system is provided, comprising a self-circulating jet control unit, characterized in that it includes: The flow monitoring module consists of pressure sensors arranged upstream of the separation zone on the back slope of the curved water inlet channel, used to acquire pressure distribution data on the back slope in real time. The vector jet generating module includes multiple rows of jet holes spaced apart along the axis of the bend, and each jet hole is independently configured with a pitch angle adjustment mechanism and a yaw angle adjustment mechanism. The intelligent control module, which communicates with the flow monitoring module, is built-in. The spectrum analysis module is used to extract the dominant frequency characteristics of flow separation in the pressure distribution data of the back slope surface. The parameter matching module dynamically generates jet control commands based on the main frequency characteristics, including the jet pulse frequency range, jet momentum coefficient, and jet vector angle compensation amount. The execution drive module outputs jet control commands to the pitch angle adjustment mechanism and yaw angle adjustment mechanism of the vector jet generating module, and performs regulation while monitoring the pipeline pressure difference during the regulation process; The self-sustaining energy module uses pipeline pressure difference to drive a micro turbine to generate electricity, which then powers the intelligent control module.

[0009] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The flow monitoring module and the intelligent control module work together. The flow monitoring module captures pressure distribution data in real time through the pressure sensor on the back slope of the curved inlet channel. The spectrum analysis module of the intelligent control module extracts the main frequency characteristics of flow separation. Based on this, the parameter matching module dynamically generates the jet pulse frequency, momentum coefficient and vector angle compensation. The execution drive module controls the angle adjustment mechanism of the vector jet generation module to accurately suppress vortex development for different flow separation patterns. This solves the problem of turbulence caused by the inability of traditional fixed parameters to adapt to dynamic flow fields and significantly improves the uniformity of the flow field.

[0010] 2. The self-sustaining energy module uses pipeline pressure difference to drive a micro turbine to generate electricity, powering the system and achieving energy self-circulation, reducing additional energy consumption. The parameter matching module has a built-in historical database and self-learning mechanism. It calls the benchmark parameters for similar operating conditions, and optimizes the parameters and updates the database for new operating conditions with the goal of improving the flow field. It can also switch to a backup strategy when the sensor signal is abnormal, ensuring continuous and effective control under complex operating conditions, avoiding energy waste or control failure, and reducing equipment wear and maintenance costs.

[0011] 3. The independent pitch and yaw angle adjustment mechanism of the multi-row jet orifice group, combined with the angle compensation amount generated by the parameter matching module, can specifically counteract the vortex effect in different rotation directions. The signal reliability verification unit filters effective data through weighted decision-making. The standardized debugging interface constructs the flow channel geometric correlation function during the initialization stage, further improving the accuracy of control commands and the reliability of system operation, ensuring stable propulsion efficiency, reducing pipeline vibration, and extending equipment service life. Attached Figure Description

[0012] Figure 1 This is an overall block diagram of the present invention; Figure 2 This is a flowchart of the module assembly of the present invention.

[0013] The meanings of the labels in the diagram are as follows: 1. Self-circulating jet control unit; 11. Flow monitoring module; 12. Vector jet generation module; 13. Intelligent control module; 131. Spectrum analysis module; 132. Parameter matching module; 133. Execution drive module; 14. Self-sustaining energy module. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] This invention provides a self-circulating jet stabilization control system for waterjet propulsion systems. Please refer to [link to relevant documentation]. Figures 1-2 As shown, it includes a self-circulating jet control unit 1, characterized in that it includes: The flow monitoring module 11 consists of pressure sensors arranged upstream of the separation zone on the back slope of the curved water inlet channel, which are used to acquire pressure distribution data on the back slope in real time. The vector jet generating module 12 includes multiple rows of jet holes spaced apart along the axis of the bend, and each jet hole is independently configured with a pitch angle adjustment mechanism and a yaw angle adjustment mechanism. The intelligent control module 13, which is communicatively connected to the flow monitoring module 11, has the following built-in features: Spectrum analysis module 131 is used to extract the flow separation dominant frequency characteristics from the back slope pressure distribution data; To accurately capture the flow separation characteristics of the back slope of the curved inlet channel, the spectrum analysis module 131 processes the pressure pulsation signal through multiple steps to extract the dominant frequency characteristics of the flow separation. The specific process is as follows: After the pressure sensors in the flow monitoring module 11 synchronously collect the pressure pulsation signal on the back slope, a dynamic time window is used to extract pressure fluctuation periodic samples. Multiple pressure sensors deployed upstream of the back slope separation zone synchronously collect pressure pulsation signals, recording the pressure changes as the water flows across the back slope. The time window length is automatically adjusted according to the water flow velocity; when the ship is traveling at high speed, the time window is set to 0.5 seconds, and when traveling at low speed, it is set to 2 seconds. Through this time window, pressure fluctuation periodic samples are extracted from the continuous signal. Each sample contains one or more complete pressure fluctuation processes. The extracted pressure fluctuation periodic samples are bandpass filtered to eliminate high-frequency noise. Based on the working characteristics of the water jet propulsion system, the frequency range of the bandpass filter is set. This range covers the frequencies that may be generated by flow separation. Signals higher than 10 Hz are mostly high-frequency noise such as sensor vibration and water flow turbulence. The pressure fluctuation samples are input into the bandpass filter to filter out signals with frequencies exceeding the set range, retaining the mid-to-low frequency fluctuations related to flow separation. The pressure amplitude change rate is identified by scanning. A threshold is set for the characteristic frequency bands. The dominant frequency with the largest duration within the characteristic frequency band is identified as the main frequency feature of flow separation. A threshold is set for the rate of change of pressure amplitude. When the rate of change of pressure amplitude exceeds this threshold, it indicates that there may be significant flow separation. The filtered sample is frequency-scanned, and all frequency bands that meet the rate of change of amplitude threshold are recorded. These frequency bands are the characteristic frequency bands. The duration of each characteristic frequency band in the sample is counted. For example, if the 1-3 Hz frequency band lasts for 0.8 seconds, the 3-5 Hz frequency band lasts for 0.2 seconds, and the total sample time is 1 second, then the 1-3 Hz frequency band with the largest duration is identified as the main characteristic frequency band. The center frequency within this frequency band is the main frequency feature of flow separation. The result is transmitted to the parameter matching module 132. The extracted main frequency feature of flow separation is packaged into a signal and transmitted to the parameter matching module 132 in real time. This signal serves as the core basis for generating jet control commands and provides reliable basic data for the subsequent dynamic adjustment of jet parameters by the parameter matching module 132, ensuring that the jet control can specifically suppress vortex development.

[0016] The parameter matching module 132 dynamically generates jet control commands based on the main frequency characteristics, including the jet pulse frequency range, jet momentum coefficient, and jet vector angle compensation amount. To ensure that the jet pulse frequency accurately matches the dynamic characteristics of flow separation, the parameter matching module 132 dynamically adjusts the multiple relationship between the jet pulse frequency and the main frequency based on the ratio of the flow separation main frequency to the channel characteristic frequency, generating the jet pulse frequency range as follows: First, the inherent characteristic frequency of the flow channel is determined. Based on the received flow separation main frequency characteristics, the ratio of the received flow separation main frequency to the flow channel characteristic frequency is calculated. The flow channel characteristic frequency is the inherent frequency determined by the geometric structure of the curved inlet flow channel. It is measured experimentally during system initialization and stored in the database of parameter matching module 132. The flow separation main frequency characteristics transmitted by spectrum analysis module 131 are received, and the ratio of this main frequency to the flow channel characteristic frequency is calculated. This ratio reflects the relative relationship between the flow separation frequency and the inherent frequency of the flow channel and is the core basis for subsequent frequency adjustment. The multiple relationship between the jet pulse frequency and the main frequency is dynamically adjusted according to the different interval ranges of this ratio. Three intervals are preset. The first interval is the normal range for the flow channel characteristic frequency and the flow separation main frequency to adapt. The second interval is less than 0.4, and the third interval is greater than 0.8. When the ratio is within the first interval, the first preset multiple relationship is adopted. By using jet pulses synchronized with the main frequency, the development of vortices is smoothly suppressed. When the ratio is less than the lower limit of the first interval, the second preset multiple relationship is adopted. By using a higher frequency jet, the stable structure of the low-frequency vortex is broken. When the ratio is greater than the upper limit of the first interval, the anti-saturation control mode is activated and the third preset multiple relationship is adopted. By using a low-frequency strong pulse, the high-frequency vortex is gradually weakened. At the same time, a feedback correction coefficient for the pressure fluctuation intensity is introduced to dynamically adjust the pulse frequency in real time. The pressure fluctuation data of the current back slope is obtained through the flow monitoring module 11, and the fluctuation amplitude is calculated as the basis for correction. When the pressure fluctuation intensity is high, a positive correction coefficient is introduced to enhance the suppression of vortices by the jet. When the fluctuation intensity is low, a negative correction coefficient is introduced to avoid wasting jet energy. The jet pulse frequency generated by the parameter matching module 132 can determine the basic adjustment strategy based on the inherent frequency relationship between flow separation and the flow channel, and can also be corrected in real time through pressure fluctuation feedback. This ensures that the jet frequency can accurately suppress vortices under different working conditions, while avoiding system overload or energy waste, and improving the adaptability and efficiency of flow field control.

[0017] To ensure that the jet momentum coefficient accurately matches the energy intensity of the current flow separation, the parameter matching module 132 dynamically adjusts the momentum coefficient based on the energy spectral density corresponding to the dominant flow separation frequency, combined with pipeline pressure difference feedback. The rule for determining the jet momentum coefficient is as follows: Based on the energy spectral density value corresponding to the flow separation dominant frequency characteristic, a mapping relationship between it and the jet momentum coefficient is established. When the energy spectral density is in different characteristic intervals, a corresponding momentum coefficient adjustment mechanism is adopted. First, the energy spectral density is calculated based on the flow separation dominant frequency characteristic, and the corresponding characteristic interval is divided. The flow separation dominant frequency characteristic output by the spectrum analysis module 131 is received, and the energy spectral density value corresponding to the dominant frequency is calculated through energy spectral analysis. This value reflects the energy intensity of the vortex. The energy spectral density is divided into three characteristic intervals, corresponding to weak, medium, and strong levels of flow separation, respectively. Energy, for example, corresponds to weak vortex energy in the low energy spectral density range and strong vortex energy in the high energy spectral density range. Different momentum coefficient adjustment strategies are adopted for different energy spectral density ranges. When the energy spectral density is in the low energy spectral density range, a "basic momentum + fine-tuning" mode is used, with a preset minimum momentum coefficient as the benchmark, and fine-tuned by ±5% based on subtle changes in pressure fluctuations to avoid excessive jet momentum interfering with the normal flow field. When in the middle range, a "step-by-step increasing" mode is activated, with the initial momentum coefficient set to 0.4. If the vortex energy is not continuously detected to be weakening, it is increased by 0.1 every 5 seconds (maximum). (Not exceeding 0.6), by gradually increasing momentum to suppress vortex development, when in the high range, a "strong momentum intervention" mode is triggered, directly adopting a higher initial momentum coefficient and maintaining this intensity until the energy spectral density drops to the middle range, rapidly weakening the dominant role of strong vortices in the ANEA flow field. A jet momentum coefficient matching the current flow state is dynamically generated through a built-in fuzzy decision algorithm, and the momentum coefficient is adaptively compensated and adjusted based on real-time monitoring of pipeline pressure difference data. The momentum coefficient is optimized through a fuzzy decision algorithm and compensated in real-time based on pipeline pressure difference. The algorithm takes into account parameters such as the current energy spectral density range, pressure fluctuation trend, and vortex duration, and dynamically generates an appropriate momentum coefficient based on a preset rule base. For example, when the energy spectral density is in the middle range but the pressure fluctuation is on the rise, the momentum coefficient output by the algorithm is 0.1 higher than the step adjustment value. The execution drive module 133 monitors the pressure difference in the jet pipeline in real time and reverses the deviation between the actual output intensity of the jet and the preset value. If the pressure difference is lower than expected, the momentum coefficient is positively compensated; if the pressure difference is higher than expected, negative compensation is performed to ensure that the actual jet momentum is consistent with the target value.

[0018] To accurately suppress vortices rotating in different directions, the parameter matching module 132 determines the vortex rotation direction by analyzing the main frequency phase difference of the pressure sensor, and generates a jet vector angle compensation value accordingly. The method for generating the jet vector angle compensation value is as follows: By analyzing the dominant frequency phase difference of pressure sensors at different axial positions, the rotation direction of the separation vortex is calculated. Pressure sensors arranged along the axis of the bend are used to acquire the dominant frequency phase information at each position. Each pressure sensor synchronously records the pressure pulsation phase corresponding to the dominant frequency of the flow separation. The phase difference reflects the rotational characteristics of the vortex during axial propagation. The dominant frequency phase difference between adjacent sensors is calculated. If the phase of the later sensor leads that of the earlier sensor along the water flow direction, it indicates that the vortex exhibits a clockwise rotational trend during axial propagation; if the phase lags, it exhibits a counterclockwise rotational trend. Based on the rotation direction of the separation vortex, the yaw angle or pitch angle of the jet is adjusted accordingly. The system generates targeted compensation values. When clockwise rotation is detected, the jet yaw angle is controlled to increase the dynamic compensation value to suppress vortex development. When clockwise rotation of the separated vortex is detected, the yaw angle of the vector jet generation module 12 is controlled to increase the dynamic compensation value. For example, if the initial yaw angle is 0 degrees, it is increased by 5 degrees according to the compensation rule, causing the jet to shift to the left. The jet impact force can directly hinder the clockwise rotation trend of the vortex and suppress vortex expansion. When counterclockwise rotation is detected, the jet pitch angle is controlled to decrease the compensation value. When counterclockwise rotation of the separated vortex is detected, the jet pitch angle is controlled to decrease the compensation value. For example, if the initial pitch angle is 3 degrees... The angle is reduced by 2 to 1 degree, causing the jet to be slightly adjusted downwards. By changing the jet impact direction, the counterclockwise rotational energy of the vortex is counteracted. The compensation amount is positively correlated with the dominant frequency amplitude; the larger the dominant frequency amplitude, the stronger the vortex energy, and the greater the compensation amount. For example, the compensation amount is 3 degrees when the dominant frequency amplitude is 200 Pa, and increases to 6 degrees when the amplitude rises to 400 Pa, ensuring that the compensation intensity matches the vortex energy. After generating the angle compensation amount, the adjustment effect is verified through a three-dimensional flow field reconstruction model to ensure accurate and effective compensation. The compensation effect is verified through a three-dimensional flow field reconstruction model based on real-time pressure distribution data from various pressure sensors. By combining the changes in pipeline pressure difference after jet angle adjustment, a three-dimensional flow field model is reconstructed to intuitively display the changes in vortex morphology. If the model shows that the vortex rotation speed decreases and the range shrinks, it indicates that the compensation amount is appropriate. If the vortex morphology does not improve significantly or even worsens, it indicates that the compensation amount is insufficient or the direction is deviated, and the compensation amount needs to be recalculated. When the three-dimensional flow field model shows that the vortex is effectively suppressed, the current jet vector angle compensation amount is locked until the flow separation state changes again. This achieves targeted control of vortices with different rotation characteristics, effectively avoids the drawback of fixed-angle jets being unable to adapt to the dynamic changes of vortices, and significantly improves the stability of the flow field.

[0019] To achieve precise control of flow separation with different geometries, the parameter matching module 132 integrates a multi-parameter coupled control mechanism, matches differentiated jet patterns, and dynamically corrects the angle compensation. When generating jet control commands, it identifies the geometric features of flow separation by using the back slope pressure distribution characteristics obtained by the flow monitoring module 11. For planar flow separation regions, a high-frequency, low-momentum jet control mode is used, while for three-dimensional vortex structure separation regions, a low-frequency, high-momentum jet control mode is used. The angle compensation of the vector jet generation module 12 is dynamically adjusted in real time based on the geometric morphological parameters of the separation zone's spatial scale and the flow channel's characteristic scale. Based on the backslope pressure distribution data acquired by the flow monitoring module 11, the geometric morphology of the flow separation is analyzed. Pressure values ​​at different locations are collected using a pressure sensor array deployed on the backslope, generating a pressure distribution heatmap. The pressure distribution in the planar flow separation region appears as continuous stripes, while the pressure distribution in the three-dimensional vortex structure region appears as discrete vortices. Comparing the pressure distribution characteristics with a preset morphological template, if the pressure change in the heatmap mainly extends along the axial direction of the backslope, it is determined to be planar flow separation; if the pressure change is radial... The axial direction exhibits periodic fluctuations, indicating a three-dimensional vortex structure separation. For separation regions with different geometric shapes, corresponding jet frequency and momentum combinations are adopted. The jet pulse frequency is set to the high-frequency band, forming a continuous "air curtain" effect through dense jet pulses to block the expansion of the planar separation layer. The jet momentum coefficient is set to a low value to avoid strong jet impact causing new flow field disturbances. Only slight disturbances are needed to disrupt the stability of the separation layer. For example, if a planar separation layer extending along the axial direction of the bend is detected, a high-frequency (5 Hz) low-momentum (0.2) jet is activated to suppress the thickening of the separation layer through continuous pulses. The jet pulse frequency is set to the low-frequency band to concentrate the jet energy within the rotation period of the vortex, enhancing the impact effect on the vortex core. The jet momentum coefficient is set to a high value to directly break the vortex structure using the impact force of the strong jet, weakening its rotational energy. For example, when multiple spiral vortices are identified, a low-frequency (2 Hz) high-momentum (0.7) jet is used, spraying once every half vortex cycle to precisely impact the vortex core and disintegrate the vortex. The angle compensation of the vector jet is adjusted in real time based on the ratio of the spatial scale of the separation zone to the characteristic scale of the flow channel. The spatial scale of the separation zone refers to the maximum radial width of the separation area or the diameter of the vortex, and the characteristic scale of the flow channel refers to the inner diameter or radius of curvature of the bend. The ratio of the two is calculated. When the ratio is <0.3, the separation area is small, and the angle compensation is set at 80% of the base value to avoid the jet range from exceeding the separation area. When the ratio is >0.6, the separation area is close to the flow channel scale, and the angle compensation is set at 120% of the base value to expand the jet coverage area to fully suppress separation. The three-dimensional vortex structure also needs to add an additional 5-10 degrees of angle compensation based on the tilt angle of the vortex (calculated through the pressure phase difference) to ensure that the jet direction is perpendicular to the vortex rotation plane, effectively improving the vortex suppression effect under different complex flow fields and ensuring the stability of the water flow in the flow channel.

[0020] To enable the jet control parameters to quickly adapt to different ship operating conditions, the parameter matching module 132 achieves efficient calling and dynamic optimization of control parameters through the collaboration of historical database and autonomous learning mechanism. The specific implementation method is as follows: The historical database pre-stores the ship's baseline control parameters under various typical operating conditions, providing direct reference for similar scenarios. The parameter matching module 132 has a built-in historical database storing the set of baseline control parameters for different operating conditions. When the similarity between the current flow separation dominant frequency characteristics and historical records reaches a preset matching level, the associated historical baseline parameters are preferentially called. Typical operating conditions are divided according to ship speed (e.g., low speed, medium speed, high speed), load (e.g., empty, half-load, full load), and water environment. Under each operating condition, the flow separation dominant frequency characteristics and the corresponding optimal jet control parameters are experimentally recorded, including pulse frequency range, momentum coefficient, and angle compensation. For example, when the ship is at high speed and empty in calm water, the baseline parameters corresponding to a dominant frequency of 3 Hz are a pulse frequency of 6 Hz, a momentum coefficient of 0.3, and a yaw angle compensation of 2 degrees. The flow separation dominant frequency characteristics and the corresponding optimal jet control parameters under each operating condition are recorded. The flow separation frequency characteristics are bound and stored with the reference parameters to form a "frequency-parameter" mapping table. At the same time, the flow field improvement effect corresponding to the parameter is recorded as the basis for subsequent similarity matching. When the system is running, it determines whether to call the reference parameters by comparing the current and historical flow separation characteristics. The current flow separation frequency characteristics are extracted and compared with the frequency characteristics of each entry in the historical database to calculate the similarity. A preset similarity threshold is set. When the similarity between the current frequency and the historical record reaches the threshold, the associated reference parameters are directly called. For example, if the current operating condition frequency is 4.2 Hz and the similarity with the historical 4 Hz operating condition meets the standard, the corresponding pulse frequency of 8 Hz and momentum coefficient of 0.35 are called. After calling the reference parameters, the parameters are fine-tuned by ±10% based on the current pressure fluctuation intensity to ensure that the parameters are more consistent with the real-time flow field state. When the similarity is lower than the preset matching level, the autonomous learning mechanism is activated. With the improvement rate of flow field uniformity as the optimization target, the initial control parameter combination is generated based on the closest parameters in the historical database. This includes the initial values ​​of pulse frequency, momentum coefficient, and angle compensation. The parameter combination is adjusted within the preset disturbance range. After each adjustment, the flow field uniformity improvement rate is detected by the flow monitoring module 11. With the maximum improvement rate as the target, the parameter combination with significant control effectiveness is selected and used as the new parameter to adapt to the current operating condition. The new parameter is bound to the current flow separation main frequency characteristics and stored in the historical database to form a new "main frequency-parameter" mapping relationship for subsequent similar operating conditions, thereby improving the system's adaptability and control accuracy.

[0021] To ensure stable generation of jet control commands even when pressure sensor signals are abnormal, the parameter matching module 132 is configured with a signal reliability verification unit to filter effective data through weighted decision-making and activate a backup strategy when signals are missing. When the main frequency identification results of multiple pressure sensors deviate, the weighted decision-making mechanism is activated to filter effective data. A preset main frequency difference threshold is used. When the threshold is exceeded, it is judged as "significant deviation". Weights are assigned according to the installation position and historical performance of the sensors. The weight of sensors close to the core of the separation zone is set to a high value (0.8), and the weight of sensors at the edge is set to a low value (0.5). The weight of sensors with low error rates in historical data is increased by an additional 0.1-0.2 to ensure that the signals of the core area and high reliability sensors have a greater influence. The main frequency identification results of each sensor are multiplied by the corresponding weight and then summed to obtain the weighted average main frequency and sensor B. The weighted main frequency is (3×0.8+5×0.5)÷(0.8+0.5)≈3.8 Hz. This is used as the effective main frequency feature to generate jet control commands. If the main frequency signal remains missing, the system switches to a backup control strategy based on ship motion parameters. A jet control command is generated through a dynamic speed mapping mechanism, and the power enhancement mode of the self-sustaining energy module 14 is activated to compensate for control deviations. The system monitors the signal transmission status of each sensor in real time. If signal interruption, data corruption, or a main frequency identification result consistently exceeds a reasonable range for a duration exceeding a preset threshold, it is determined that the main frequency signal is missing. Real-time data from the ship's navigation system is then retrieved to obtain motion parameters such as speed, heading angle, and draft. A speed of 15 knots, a heading angle of 30 degrees, and a full-load draft of 5 meters are parameters that are related to the flow state of the water in the channel. A mapping relationship between speed and jet control parameters is established: for low-speed navigation (<5 knots), the corresponding parameters are low pulse frequency (2 Hz) and low momentum coefficient (0.2); for medium-speed navigation (5-15 knots), the corresponding parameters are medium pulse frequency (4-6 Hz) and medium momentum coefficient (0.3-0.5); and for high-speed navigation (>15 knots), the corresponding parameters are high pulse frequency (8 Hz) and high momentum coefficient (0.6-0.7). Simultaneously, the jet angle is corrected according to the heading angle, activating the power enhancement mode of the self-sustaining energy module 14. By increasing the power generation of the micro-turbine, stronger energy support is provided to the jet actuator, compensating for potential control deviations due to the backup strategy, ensuring stable operation of the system even under abnormal sensor conditions, and avoiding flow field runaway due to signal problems.

[0022] The parameter matching module 132 is equipped with a standardized debugging interface. During the system initialization phase, artificially simulated characteristic separation flow field data is injected to record the optimal jet parameters corresponding to the predetermined flow field control indicators. The debugging interface supports manual input of flow channel geometry parameters, including bend diameter, radius of curvature, wall roughness, and simulated flow separation characteristics, including the range of the planar separation zone and the rotation frequency of the three-dimensional vortex. Simultaneously, flow field control indicators can be preset. Technicians can inject multiple sets of artificially simulated characteristic separation flow field data into the system through the interface. For example, simulating scenarios such as "planar separation of a 1-meter diameter bend with a radius of curvature of 2 meters" and "three-dimensional vortex separation of a 0.8-meter diameter bend with a radius of curvature of 1.5 meters," covering flow channel geometry and separation morphology. Based on the typical combination of these parameters, a flow channel geometric feature correlation function is constructed. For the injected simulated data, the optimal jet parameters are determined through debugging experiments, and then the flow channel geometric feature correlation function is constructed. For each set of injected simulated flow field data, the jet control parameters, including pulse frequency, momentum coefficient, and angle compensation, are gradually adjusted until the flow field control indicators meet the standards. The parameter values ​​at this point are recorded as the optimal jet parameters for that geometric scenario. For example, for "three-dimensional vortex separation of a bend with a diameter of 1 meter and a curvature radius of 2 meters," the optimal parameters obtained through debugging are a pulse frequency of 5 Hz, a momentum coefficient of 0.6, and an angle compensation of 4 degrees. Based on multiple sets of "flow channel geometric parameters - optimal jet parameters" data, a correlation function is constructed. The function uses the bend diameter, curvature radius, wall geometry, and other parameters as inputs. The system takes certain features as input and outputs corresponding jet parameter correction rules, clarifying the influence of different geometric features on the parameters. When the diameter increases, the pulse frequency needs to be increased accordingly; when the radius of curvature decreases, the momentum coefficient needs to be enhanced. A diameter-related correction factor is added to the pulse frequency reference value, a radius of curvature-related correction factor is added to the momentum coefficient, and a wall geometric feature compensation factor is added to the angle compensation amount. For the pulse frequency reference value, the correction factor is set according to the correlation between the bend diameter and the optimal pulse frequency. For example, when the diameter is 1 meter, the correction factor is 1.0 (reference value); when the diameter increases to 1.2 meters, the correction factor is adjusted to 1.1 (pulse frequency increased by 10% based on the reference value), ensuring that the pulse frequency matches the flow channel capacity. The larger the diameter, the higher the jet frequency is required. To cover a wider flow field region, a correction factor is set for the momentum coefficient based on the correlation between the radius of curvature and vortex intensity. For example, the correction factor is 1.0 when the radius of curvature is 2 meters, and 1.2 when it decreases to 1.5 meters. This is because the smaller the curvature, the more severe the flow channel bending and the stronger the vortex energy, requiring higher momentum jet suppression. For the angle compensation, a compensation factor is set based on geometric features such as wall roughness and protruding structures. For example, the compensation factor is 1.0 when the wall is smooth, and 1.3 when there are obvious protrusions. The angle compensation is increased by 30% from the reference value. This ensures that the jet direction can cover the local separation area caused by wall irregularities, ensuring that the jet control is accurate from the start-up stage and avoiding flow field control failure due to geometric differences.

[0023] The parameter matching module 132 evaluates the control performance by executing the pipeline differential pressure change characteristics of the drive module 133. When the differential pressure improvement rate is lower than the preset performance threshold, a step-by-step parameter optimization program is initiated. The pulse frequency is first adjusted to shift towards higher frequencies, then the momentum coefficient is increased, and finally, the vector angle is fine-tuned until the pressure difference fluctuation is restored to the predetermined stable range and the optimized parameter set is locked.

[0024] To ensure the jet control effectively suppresses flow separation, the parameter matching module 132 assesses control performance by monitoring changes in pipeline pressure differential. When the improvement rate is insufficient, it initiates step-by-step parameter optimization. The specific implementation method is as follows: The execution drive module 133 collects real-time pressure difference data of the jet pipeline, i.e., the pressure difference between the jet outlet and the main flow channel. The parameter matching module 132 evaluates the control effect by analyzing the pressure difference changes, continuously recording the real-time value of the pipeline pressure difference to form a pressure difference change curve. When the jet effectively suppresses vortices, the water flow in the channel is more uniform, and the pressure difference fluctuation amplitude will gradually decrease. If the control is ineffective, the pressure difference fluctuation will remain high or intensify. The percentage decrease in the pressure difference fluctuation amplitude per unit time is calculated. This rate reflects the suppression efficiency of the jet control on flow separation. A preset efficiency threshold is set. If the actual improvement rate is lower than this threshold, it indicates that the current jet parameters are insufficient to suppress flow separation. This triggers a step-by-step parameter optimization program, adjusting parameters progressively according to the priority order of "pulse frequency → momentum coefficient → vector angle" until the pressure difference fluctuation stabilizes. Using the current pulse frequency as a baseline, adjustments are then made progressively towards higher frequencies while simultaneously monitoring pressure difference changes. High-frequency jets can break the stable structure of vortices through denser pulses, accelerating flow field homogenization. If the pressure difference improvement rate rises to 18% when adjusted to 8 Hz, frequency adjustment is paused, and the frequency is maintained for continued observation. If it rises to... If the improvement rate still doesn't meet the target after 10 Hz, proceed to the next optimization step. Based on the current momentum coefficient, gradually increase the intensity to enhance the jet's impact force and dismantle the stubborn vortex. For example, if the improvement rate after frequency optimization is still 12%, increase the momentum coefficient from 0.4 to 0.5. At this point, the pressure difference improvement rate rises to 16% (meeting the target), and the momentum coefficient is locked. If increasing it to 0.6 still doesn't meet the target, proceed to the next step. Make small adjustments (±1 degree each time) to the yaw or pitch angle of the current jet to optimize the jet's impact direction, making it act more precisely on the vortex. In the core region, for example, the momentum coefficient improvement rate is 14% after optimization. Adjusting the yaw angle from 3 degrees to 4 degrees makes the jet direction more closely match the vortex rotation tangent, and the pressure difference improvement rate rises to 17% (meeting the target). When the pressure difference fluctuation amplitude drops to the predetermined stable range (within ±200 Pa) and remains there for more than 3 seconds, the parameter matching module 132 locks the current pulse frequency, momentum coefficient, and angle compensation, forming and storing an optimized parameter set. For example, ultimately locking an 8 Hz pulse frequency, a 0.5 momentum coefficient, and a 4-degree yaw angle as the optimal control parameters for this flow state. If similar flow separation characteristics occur subsequently, this parameter set can be directly called, shortening the control response time and ultimately achieving flow field stability. This avoids energy waste or control failure caused by blind parameter adjustments, ensuring the operating efficiency of the waterjet propulsion system.

[0025] The drive module 133 executes and outputs jet control commands to the pitch angle adjustment mechanism and yaw angle adjustment mechanism of the vector jet generation module 12, and performs regulation while monitoring the pipeline pressure difference during the regulation process. The self-sustaining energy module 14 uses pipeline pressure difference to drive a micro turbine to generate electricity, which powers the intelligent control module 13.

[0026] This invention includes a self-circulating jet control unit 1, comprising a flow monitoring module 11, a vector jet generation module 12, an intelligent control module 13, and a self-sustaining energy module 14. The flow monitoring module 11 acquires pressure distribution data on the back slope of the curved inlet channel through a pressure sensor. The intelligent control module 13 extracts the flow separation main frequency characteristics and dynamically generates the jet pulse frequency, momentum coefficient, and vector angle compensation. The vector jet generation module 12 executes commands through an independent adjustment mechanism. The self-sustaining energy module 14 generates electricity using pipeline pressure difference. This system solves the problems of flow field turbulence and energy waste caused by traditional fixed parameter control, accurately suppresses vortices, improves flow field stability and energy utilization, and ensures propulsion efficiency and equipment lifespan.

[0027] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A self-circulating jet stabilization control system for a waterjet propulsion system, comprising a self-circulating jet control unit (1), characterized in that, include: The flow monitoring module (11) consists of pressure sensors arranged upstream of the separation zone on the back slope of the curved water inlet channel, which are used to acquire pressure distribution data on the back slope in real time. The vector jet generating module (12) includes multiple rows of jet holes spaced apart along the axis of the bend, and each jet hole is independently configured with a pitch angle adjustment mechanism and a yaw angle adjustment mechanism. The intelligent control module (13), which is communicatively connected to the flow monitoring module (11), has the following built-in features: The spectrum analysis module (131) is used to extract the flow separation main frequency characteristics in the back slope pressure distribution data; The parameter matching module (132) dynamically generates jet control commands based on the main frequency characteristics, including the jet pulse frequency range, jet momentum coefficient, and jet vector angle compensation amount. The drive module (133) is executed to output jet control commands to the pitch angle adjustment mechanism and yaw angle adjustment mechanism of the vector jet generation module (12) and to perform regulation, while monitoring the pipeline pressure difference during the regulation process; The self-sustaining energy module (14) uses pipeline pressure difference to drive a micro turbine to generate electricity, which powers the intelligent control module (13).

2. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The specific process by which the spectrum analysis module (131) extracts the flow separation main frequency characteristics is as follows: After the pressure sensor in the flow monitoring module (11) synchronously collects the pressure pulsation signal on the back slope, the pressure fluctuation period sample is extracted by using a dynamic time window. The pressure fluctuation period sample is bandpass filtered to eliminate high-frequency noise. The characteristic frequency band with pressure amplitude change rate exceeding the set threshold is identified by scanning. The dominant frequency with the largest duration in the characteristic frequency band is identified as the flow separation main frequency feature, and the result is transmitted to the parameter matching module (132).

3. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The method for the parameter matching module (132) to generate the jet pulse frequency range is as follows: Based on the received flow separation main frequency characteristics, the ratio of its frequency to the flow channel characteristic frequency is calculated, and the multiple relationship between the jet pulse frequency and the main frequency is dynamically adjusted according to the different ranges of this ratio. When the ratio is in the first interval, the first preset multiple relationship is adopted. When the ratio is less than the lower limit of the first interval, the second preset multiple relationship is adopted. When the ratio is greater than the upper limit of the first interval, the anti-saturation control mode is activated and the third preset multiple relationship is adopted. At the same time, the feedback correction coefficient of pressure fluctuation intensity is introduced to dynamically adjust the pulse frequency in real time.

4. The self-circulating jet stabilization control system for a waterjet propulsion system according to claim 1, characterized in that: The parameter matching module (132) determines the jet momentum coefficient according to the following rules: Based on the energy spectral density value corresponding to the flow separation main frequency characteristics, a mapping relationship between it and the jet momentum coefficient is established. When the energy spectral density is in different characteristic ranges, a corresponding momentum coefficient adjustment mechanism is adopted. The built-in fuzzy decision algorithm dynamically generates a jet momentum coefficient that matches the current flow state, and the momentum coefficient is adaptively compensated and adjusted in combination with the real-time monitored pipeline pressure difference data.

5. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The method by which the parameter matching module (132) generates the jet vector angle compensation is as follows: The phase difference of the main frequency of pressure sensors at different axial positions was analyzed to deduce the rotation direction of the separated vortex. When clockwise rotation was detected, the jet yaw angle was controlled to increase the dynamic compensation amount to suppress the development of the vortex system. When counterclockwise rotation was detected, the jet pitch angle was controlled to reduce the compensation amount. The magnitude of the compensation amount was positively correlated with the amplitude of the main frequency. The compensation effect was verified by a three-dimensional flow field reconstruction model.

6. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The parameter matching module (132) integrates a multi-parameter coupled control mechanism. When generating jet control commands, it identifies the geometric features of flow separation by using the back slope pressure distribution characteristics obtained by the flow monitoring module (11). For the planar flow separation region, a high-frequency low-momentum jet control mode is adopted, and for the three-dimensional vortex structure separation region, a low-frequency high-momentum jet control mode is adopted. The angle compensation of the vector jet generation module (12) is dynamically corrected in real time based on the geometric morphological characteristic parameters of the separation region spatial scale and the flow channel characteristic scale.

7. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The parameter matching module (132) has a built-in historical database that stores a set of benchmark control parameters for different operating conditions of the ship. When the similarity between the current flow separation main frequency characteristics and the historical records reaches a preset matching level, the associated historical benchmark parameters are called first. When the similarity is lower than the preset matching level, the autonomous learning mechanism is activated. With the improvement rate of flow field uniformity as the optimization goal, the combination of jet control parameters is adjusted within the preset disturbance range, and the set of parameters that significantly improve control efficiency is updated to the database.

8. The self-circulating jet stabilization control system for a waterjet propulsion system according to claim 1, characterized in that: The parameter matching module (132) is configured with a signal reliability verification unit. When the main frequency identification results output by multiple pressure sensors deviate, a weighted decision-making mechanism is activated to filter valid data. If the main frequency signal is continuously missing, the system switches to the backup control strategy based on the ship's motion parameters, generates jet control commands through the speed dynamic mapping mechanism, and activates the power enhancement mode of the self-sustaining energy module (14) to compensate for the control deviation.

9. The self-circulating jet stabilization control system for a waterjet propulsion device according to claim 1, characterized in that: The parameter matching module (132) is equipped with a standardized debugging interface. During the system initialization phase, artificially simulated feature separation flow field data is injected, and the optimal jet parameters corresponding to the predetermined flow field control index are recorded. Based on this, a flow channel geometric feature correlation function is constructed, and a diameter correlation correction factor is added to the pulse frequency reference value, a curvature radius correlation correction factor is added to the momentum coefficient, and a wall geometric feature compensation factor is added to the angle compensation amount.

10. The self-circulating jet stabilization control system for a waterjet propulsion system according to claim 1, characterized in that: The parameter matching module (132) evaluates the control performance by executing the pipeline differential pressure change characteristics of the drive module (134). When the differential pressure improvement rate is lower than the preset performance threshold, a step-by-step parameter optimization program is initiated. The pulse frequency is first adjusted to shift towards higher frequencies, then the momentum coefficient is increased, and finally, the vector angle is fine-tuned until the pressure difference fluctuation is restored to the predetermined stable range and the optimized parameter set is locked.

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