A manned flying saucer cabin door control method and system

Abstract

The application provides a manned flying saucer cabin door control method and system, and relates to the technical field of aircraft control. The method comprises the following steps: obtaining acceleration signals of multiple positions of the cabin door through an acceleration sensor array; estimating vibration modal coordinates of the cabin door by decoupling the acceleration signals; generating a control instruction according to the vibration modal coordinates; monitoring the sealing pressure and locking state of the cabin door, and when the monitoring result is normal, outputting the control instruction to control the actuator to exert a control force on the cabin door structure; when the monitoring result is abnormal, adjusting the control instruction and outputting the adjusted control instruction to control the actuator to exert a control force on the cabin door structure, or stopping outputting the control instruction. The method of the application actively avoids damage to core functions such as sealing and locking while suppressing vibration, thereby significantly improving the safety and reliability of the system in harsh environments.

Description

Technical Field

[0001] This invention relates to the field of aircraft control technology, and more specifically, to a method and system for controlling the hatch of a manned flying saucer. Background Technology

[0002] A manned UFO is conducting a flight mission in the low-altitude region, at a relatively low altitude. At this altitude, atmospheric flow is influenced by factors such as ground topography, features, and local heat sources, resulting in nonlinear, rapidly changing turbulence. Turbulence manifests as random fluctuations in airflow velocity and direction, characterized by an energy spectrum that remains distributed across a wide frequency range and exhibits weak spatial correlation. These fluctuating airflows act on the UFO's outer surface, generating a randomly varying pressure distribution, i.e., turbulent aerodynamic forces. The UFO's hatch, as a crucial opening and covering structure on its outer shell, directly bears these turbulent aerodynamic forces on its outer surface. Due to the weak spatial correlation of near-ground turbulence, the aerodynamic forces acting on different locations of the hatch may be asynchronous and possess different frequency characteristics, leading to complex and non-uniform dynamic loads on the hatch.

[0003] A hatch typically consists of an outer skin, an internal reinforcing structure, a frame, seals, a locking mechanism, hinges or rails, and a drive mechanism. The hatch panel itself is made of composite materials or metal, possessing both mass and elasticity. The frame secures the hatch panel to the opening in the fuselage of the flying saucer. The seals ensure the airtightness of the hatch when closed, and their elastic properties also affect the hatch's dynamic response. The locking mechanism provides a mechanical lock, ensuring the hatch closes safely during flight. Hinges or rails connect the hatch to the fuselage, allowing the hatch to open and close. The drive mechanism is responsible for the electric or hydraulic operation of the hatch. These components are assembled together via connectors and connected to the fuselage structure. This combined structure has multiple natural frequencies and vibration modes. When the frequency component of the turbulent aerodynamic forces acting on the hatch is close to the hatch's natural frequency, or when the aerodynamic changes are sufficiently drastic, resonance or forced vibration of the hatch can be excited. The non-uniformity of near-ground turbulence means that this vibration may simultaneously excite multiple vibration modes of the hatch, including bending, torsion, localized panel vibration, and small overall motion relative to the fuselage. The mass distribution, structural stiffness, characteristics of the connectors, and damping level of the hatch all contribute to the possibility that these vibrations can have a large amplitude.

[0004] During prolonged flights in continuous near-ground turbulence, the sustained vibration of the cabin door can lead to a series of problems. For example, high-frequency vibration may increase friction and wear between the seals and the door frame, affecting the long-term reliability of the seal and even potentially reducing airtightness. Vibration may cause changes in the clearance or impact of the locking mechanism, affecting the reliability of the locking and even potentially causing fatigue damage, posing a risk of locking failure. Continuous stress cycles in the cabin door structure will accelerate material fatigue and shorten the service life of cabin components (such as the skin, reinforcing ribs, and connectors). In addition, cabin door vibration generates structural noise that is transmitted into the cabin, affecting the passenger experience. To mitigate these adverse effects, it is necessary to effectively suppress cabin door vibration in near-ground turbulence.

[0005] Active vibration control is a technique that uses real-time sensing of structural vibration and applies reaction forces to counteract it. Acceleration feedback control is a common approach to active vibration suppression. By placing acceleration sensors at critical locations on the structure to measure acceleration signals, the control system calculates control forces based on these signals and drives actuators to apply these forces to reduce vibration. However, in complex structures like manned UFO hatches, facing non-uniform turbulent loads while simultaneously requiring critical functions such as sealing and locking, traditional single-point or simple multi-point vibration control methods are insufficient to effectively handle multimodal coupled vibrations. Furthermore, they fail to adequately consider the potential adverse effects of vibration control on the hatch's critical functions, posing a risk of compromising sealing or locking reliability while suppressing vibration. Therefore, how to accurately sense and effectively suppress multimodal coupled vibrations of manned UFO hatches in near-ground turbulent environments, while simultaneously ensuring the safety of the hatch's sealing and locking functions, has become a pressing technical problem. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for controlling the hatch of a manned flying saucer. By actively controlling and precisely suppressing multiple vibration modes, and by integrating key function monitoring and linking it with the control strategy, the system can suppress vibration while actively avoiding potential damage to core functions such as sealing and locking, thus significantly improving the safety and reliability of the system in harsh environments.

[0007] In a first aspect, the present invention provides a method for controlling the hatch of a manned flying saucer, comprising the following steps:

[0008] After accelerometers are placed at multiple locations on the hatch and arranged into an accelerometer array, acceleration signals at multiple locations on the hatch are obtained through the accelerometer array.

[0009] By decoupling the acceleration signal, the vibration mode coordinates of the hatch are estimated.

[0010] Control commands are generated based on the vibration mode coordinates;

[0011] The system monitors the sealing pressure and locking status of the hatch. When the monitoring results are normal, it outputs control commands to control the actuators to apply control force to the hatch structure. When the monitoring results are abnormal, it adjusts the control commands and outputs the adjusted control commands to control the actuators to apply control force to the hatch structure, or stops outputting control commands.

[0012] The manned UFO hatch control method provided by this invention can accurately capture the multi-point dynamic response of the hatch through distributed sensing in the specific environment where the manned UFO encounters random time-varying and spatially non-uniform turbulent loads during near-ground flight, causing multimodal coupled vibration of the hatch structure. It can also effectively suppress multimodal vibration by actively controlling the hatch and simultaneously monitor the hatch sealing and locking status, and adjust the control strategy when necessary to avoid adverse effects on the key functions of the hatch during the vibration suppression process.

[0013] Secondly, the present invention provides a manned flying saucer cabin door control system, comprising:

[0014] The acquisition module is used to arrange acceleration sensors at multiple locations on the hatch and form an acceleration sensor array, and then obtain acceleration signals at multiple locations on the hatch through the acceleration sensor array.

[0015] The estimation module is used to estimate the vibration mode coordinates of the hatch by decoupling the acceleration signal;

[0016] The generation module is used to generate control commands based on the vibration mode coordinates;

[0017] The control module monitors the sealing pressure and locking status of the hatch. When the monitoring results are normal, it outputs control commands to control the actuators to apply control force to the hatch structure. When the monitoring results are abnormal, it adjusts the control commands and outputs the adjusted control commands to control the actuators to apply control force to the hatch structure, or stops outputting control commands.

[0018] As can be seen from the above, the manned UFO hatch control method provided by this invention, through a strategy of distributed sensing, active control, and linkage with key functional states, effectively suppresses multimodal vibrations of the manned UFO hatch in near-ground turbulent environments. Compared with schemes that do not consider multimodal vibrations or do not link key functional monitoring, this invention can more comprehensively and accurately cope with various vibration forms caused by complex turbulence, significantly reducing the vibration amplitude of the hatch. Simultaneously, by adjusting the control output when abnormal sealing or locking conditions are detected, excessive wear on the seals or adverse impacts on the locking mechanism during vibration suppression are effectively avoided, thereby ensuring the airtightness and locking reliability of the hatch, extending the service life of the hatch components, and improving flight safety and passenger comfort.

[0019] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0020] Figure 1 This is a flowchart of a manned flying saucer cabin door control method provided in an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of a manned flying saucer cabin door control system provided in an embodiment of the present invention.

[0022] Label Explanation:

[0023] 100. Acquisition module; 200. Estimation module; 300. Generation module; 400. Control module. Detailed Implementation

[0024] 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0025] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0026] Reference Appendix Figure 1 This invention provides a method for controlling the hatch of a manned flying saucer, comprising the following steps:

[0027] After accelerometers are placed at multiple locations on the hatch and arranged into an accelerometer array, acceleration signals at multiple locations on the hatch are obtained through the accelerometer array; the locations include the hatch skin, reinforcing ribs and frame;

[0028] By decoupling the acceleration signal, the vibration mode coordinates of the hatch are estimated.

[0029] Control commands are generated based on the vibration mode coordinates;

[0030] The system monitors the sealing pressure and locking status of the hatch. When the monitoring results are normal, it outputs control commands to control the actuators to apply control force to the hatch structure. When the monitoring results are abnormal, it adjusts the control commands and outputs the adjusted control commands to control the actuators to apply control force to the hatch structure, or stops outputting control commands.

[0031] An accelerometer array refers to installing multiple accelerometers in a specific layout at different locations on the hatch structure, forming a sensor network. This can be implemented using piezoelectric accelerometers, microelectromechanical systems (MEMS) accelerometers, or fiber optic accelerometers. For example, sensors can be placed on the hatch skin, reinforcing ribs, and frame. Its main purpose is to acquire dynamic response information of the hatch at multiple points, providing a data foundation for subsequent vibration state analysis. Accelerometer signal decoupling refers to separating the coupled acceleration signals acquired from the accelerometer array using signal processing techniques to extract components representing the individual vibration modes of the hatch. This can be achieved using modal analysis methods, state-space methods, or frequency domain decomposition methods. For example, decoupling can be based on structural dynamics models or data-driven models. Its main purpose is to identify and quantify the contribution of each vibration mode of the hatch at the current moment, decomposing the complex overall vibration into independently analyzable and controllable modal vibrations. Vibration modal coordinates refer to parameters characterizing the vibration state of each vibration mode of the hatch after decoupling. These typically include modal displacement, modal velocity, or modal acceleration. They are primarily used to describe the vibration amplitude or phase of the hatch in a specific mode, providing a basis for generating targeted control commands. Control commands are signals calculated based on the hatch's vibration modal coordinates and used to drive actuators to generate control forces. These commands can be implemented using voltage, current, or digital signals, and primarily instruct the actuators on the magnitude and type of force applied to counteract hatch vibration. Monitoring the hatch's sealing pressure and locking status involves acquiring real-time information on the airtightness (reflected by pressure changes) and mechanical locking status after the hatch is closed using sensors or status detection devices. This can be achieved using pressure sensors, proximity switches, or strain sensors. For example, pressure sensors can be placed near the sealing strip, and status switches can be placed at the latch position. This is mainly to obtain status information on the hatch's critical safety functions, serving as a basis for adjusting vibration control strategies. Adjusting control commands refers to modifying the original control commands when an abnormality is detected in the sealing or locking status of the hatch, thereby changing the control force output of the actuator. This can be achieved by reducing the command amplitude, changing the command frequency, or completely stopping the command output. Its main purpose is to prioritize the protection of the hatch's critical functions and avoid adverse effects caused by control force when the safety status is abnormal.

[0032] The core innovation of this application lies in combining vibration state estimation based on multi-point sensing and modal decoupling with real-time monitoring of the key safety status (sealing and locking) of the hatch, thereby achieving effective suppression of multimodal vibration of the manned flying saucer hatch. At the same time, it can adaptively adjust or stop the control output when the safety status is abnormal, thus achieving the effect of suppressing vibration while ensuring the reliability of the hatch sealing and locking.

[0033] Specifically, the method first acquires acceleration signals from multiple locations on the hatch skin, reinforcing ribs, and frame using an array of accelerometers. These signals contain rich information about the overall and local vibrations of the hatch. Next, these multi-point acceleration signals are decoupled, decomposing the coupled acceleration response into independent responses of each vibration mode, thereby estimating the vibration mode coordinates of the hatch. This allows the system to identify which modes are the dominant vibration components and their amplitudes. Then, based on the estimated vibration mode coordinates, control commands are generated to drive the actuators to apply control forces. These commands are based on an understanding of the hatch's modal vibration state and aim to counteract or reduce these modal vibrations by applying reaction forces. Simultaneously, the system continuously monitors the hatch's sealing pressure and locking status to obtain information on whether critical safety functions are functioning correctly. When monitoring results indicate that the sealing and locking status are normal, the system outputs control commands generated based on the modal information, controlling the actuators to apply control forces to the hatch structure for routine vibration suppression. However, when monitoring results indicate a drop in sealing pressure or an abnormal locking condition, the system adjusts control commands accordingly. This includes reducing or stopping control force output to prevent further interference or damage to the already abnormal sealing or locking structure. The entire process forms a closed-loop control system, which, through the coordinated action of sensing, analysis, control, and safety monitoring, suppresses door vibration and ensures the safety of its critical functions.

[0034] As a preferred embodiment, the solution of this application is implemented as follows: MEMS accelerometers are installed at key locations on the hatch skin, reinforcing ribs, and frame to form an accelerometer array. The acquired acceleration signals are input to an embedded processor. The processor executes a signal processing algorithm, such as a modal decomposition algorithm based on a structural dynamics model, to decouple the acceleration signals and estimate the modal coordinates of the first few main vibration modes of the hatch. Based on these modal coordinates, the processor runs a control algorithm, such as a linear quadratic regulator (LQR) algorithm, to calculate the control force to be applied to the hatch and convert it into control commands to drive piezoelectric actuators or hydraulic actuators. Simultaneously, a pressure sensor is installed near the hatch sealing strip, and a proximity switch is installed at the latch position to monitor the hatch's sealing pressure and locking status in real time. The monitoring signals are also input to the processor. If the detected sealing pressure is below a threshold or the locking switch status is abnormal, the processor will, according to a preset safety strategy, such as multiplying the amplitude of the control command by an adjustment factor less than 1, or directly setting the control command to zero, and then output the adjusted control command to the actuator.

[0035] Through the aforementioned scheme, this application effectively identifies and quantifies the multimodal coupled vibration state of a manned UFO hatch under complex loads by employing multi-point sensing and modal decoupling. This allows for the generation of targeted control commands to suppress hatch vibration. Simultaneously, real-time monitoring of hatch sealing pressure and locking status is introduced, and control output is adjusted or stopped when monitoring results are abnormal. This effectively avoids potential adverse effects of vibration control on critical hatch safety functions, improving the hatch's safety and reliability in near-ground turbulent environments.

[0036] In some embodiments, the step of estimating the vibration mode coordinates of the hatch by decoupling the acceleration signal includes:

[0037] Based on the location distribution of the accelerometers, an acceleration signal matrix is ​​constructed according to the acceleration signals.

[0038] Perform a fast Fourier transform on each acceleration signal in the acceleration signal matrix to obtain the frequency domain acceleration signal matrix;

[0039] A short-time Fourier transform analysis based on a sliding time window is performed on the frequency domain acceleration signal matrix to calculate the power spectral density within each time window, thus obtaining the power spectral density matrix.

[0040] Based on the power spectral density matrix, identify the main frequency components within the current time window;

[0041] The identified main frequency components are matched with a pre-established hatch modal frequency database to determine the main vibration mode of the hatch at the current moment, thus obtaining the main vibration mode information;

[0042] Based on the determined main vibration mode information, the acceleration signal matrix is ​​decoupled to estimate the vibration mode coordinates of the hatch.

[0043] Constructing the acceleration signal matrix involves structuring multi-channel acceleration signals collected from different locations on the hatch, forming a dataset that facilitates unified analysis and processing. Performing a Fast Fourier Transform (FFT) on the acceleration signals converts the time-domain signal into a frequency-domain representation, revealing the signal's frequency composition. Short-Time Fourier Transform (SFT) analysis based on a sliding time window is a time-frequency analysis technique. By sliding a finite-length time window across the signal and performing a Fourier transform within each window, it analyzes how the signal's frequency components change over time, which is particularly important for analyzing non-stationary or transient signals. Calculating the power spectral density quantifies the energy distribution of the signal at different frequencies; the power spectral density matrix contains energy information at different sensor locations, times, and frequencies. Identifying the main frequency components involves extracting frequency points with significant energy from the power spectral density matrix; these frequency points typically correspond to the structure's natural frequencies or forced vibration frequencies. Matching the identified main frequency components with a pre-established hatch modal frequency database correlates the real-time monitored frequency information with the structure's inherent dynamic characteristics, thereby determining which vibration modes are primarily exciting the hatch at the current moment. A pre-established modal frequency database for the hatch can be obtained through finite element analysis or modal experiments, containing frequency information of each natural mode of the hatch. Decoupling the acceleration signal matrix based on the determined main vibration modal information involves using the identified modal information as prior knowledge or guidance to decompose the coupled sensor acceleration signals into individual independent vibration modes, thereby estimating the time-varying amplitude of each mode, i.e., the modal coordinates.

[0044] This application achieves accurate and robust estimation of the hatch's vibration modal coordinates through a multi-stage, multi-domain combined signal processing and modal identification method. First, multi-point acceleration signals are acquired using an accelerometer array, and an acceleration signal matrix is ​​constructed, providing the foundational data for structural dynamics analysis. Subsequently, the overall frequency characteristics of the signals are preliminarily analyzed using Fast Fourier Transform (FFT). Furthermore, short-time Fourier Transform (SFT) based on a sliding time window and power spectral density analysis captures the time-varying frequency changes of the hatch vibration, crucial for identifying time-varying or transiently excited modes caused by turbulence. By identifying the main frequency components in the time-frequency domain, the currently active vibration modes can be located more precisely. Matching these real-time identified frequencies with a pre-established modal frequency database allows for the association of abstract frequency information with specific structural vibration modes, thereby determining the main vibration modes of the current hatch. It is precisely because the current dominant vibration modes can be accurately identified that the subsequent decoupling process based on this modal information can more effectively decompose the coupled sensor signals into individual active modes, thereby improving the accuracy and robustness of modal coordinate estimation under complex loads and noise environments. This strategy, which combines time-domain, frequency-domain, and time-frequency-domain analysis with modal identification, fully utilizes the rich information contained in the acceleration signals, overcomes the limitations of simple decoupling methods in handling complex multimodal coupled vibrations, and provides reliable modal state perception for subsequent precise vibration control.

[0045] Using the above method, this application can effectively extract the multimodal coupled vibration state information of the hatch under near-ground turbulent conditions from complex acceleration signals. This method combines the advantages of time-domain, frequency-domain, and time-frequency-domain analysis, and introduces modal identification and matching steps. This allows for accurate and robust estimation of the main vibration modes of the hatch and their corresponding modal coordinates even under adverse conditions such as non-uniform dynamic loads, noise, and dense modalities. This provides a reliable input for the subsequent generation of precise control commands based on modal coordinates, thereby improving the vibration control effect of the manned UFO hatch under near-ground turbulent conditions and helping to ensure the sealing and locking reliability of the hatch.

[0046] In some embodiments, the step of decoupling the acceleration signal matrix based on the determined primary vibration mode information and estimating the vibration mode coordinates of the hatch includes:

[0047] Subtracting the modal acceleration signal reconstructed based on the determined main vibration mode information from the acceleration signal matrix yields the residual acceleration signal matrix, which is used to characterize the vibration information of the unidentified modes.

[0048] Based on the energy of the residual acceleration signal matrix, the decoupling parameters are adjusted to reduce the impact of mode recognition error on mode decoupling;

[0049] The acceleration signal matrix is ​​weighted and decoupled using the adjusted decoupling parameters to obtain the modal coordinates of each vibration mode. The weights are determined based on the identification confidence of the corresponding mode.

[0050] The residual acceleration signal matrix refers to the signal matrix remaining after removing the contributions of the identified major modes from the original acceleration signal, representing vibration information that was not fully identified or was identified inaccurately. The energy of the residual acceleration signal matrix refers to the sum or average energy of the signals in the residual acceleration signal matrix, and is an indicator of the intensity of unidentified or inaccurately identified vibration information. It can be calculated by taking the mean square value, sum of squares, or integral square of the signals. Decoupling parameters are the set of parameters used to separate the mixed acceleration signal into modal coordinates. These can be, for example, the inverse or pseudo-inverse of the modal matrix, state-space model parameters, etc., and can be implemented using a modal matrix constructed based on structural modal analysis results or parameters obtained through system identification methods. Weighted decoupling refers to assigning different weights to each mode based on the identification confidence level during the decoupling process, thereby adjusting the degree of influence of each mode on the final modal coordinate estimation result. The weights are determined based on the recognition confidence of the corresponding mode. This refers to the weight values ​​used in weighted decoupling, whose magnitudes are positively correlated with the recognition confidence of the corresponding mode. The recognition confidence can be calculated based on various indicators such as the signal-to-noise ratio, modal shape matching degree, and frequency matching degree.

[0051] Based on the aforementioned technical features, the modal decoupling method of this application works as follows: After identifying the main vibration modal information, the signal reconstructed based on these identified modal information is first subtracted from the original acceleration signal matrix, thereby separating the residual acceleration signal matrix. This step explicitly extracts the parts of the original signal that were not fully identified or were inaccurately identified. This residual information reflects the deficiencies in the modal identification process, providing a basis for subsequent evaluation and improvement of the decoupling process. Next, by calculating the energy of the residual acceleration signal matrix, the degree of modal identification error or omission can be quantified. The magnitude of the residual energy directly indicates the intensity of the vibration information that was not fully captured. Then, based on the magnitude of the residual energy, the parameters used for decoupling calculation are dynamically adjusted. This adjustment mechanism allows the decoupling process to adapt to the uncertainties of modal identification. For example, when the residual energy is large, the decoupling parameters can be adjusted to increase robustness to unmodeled dynamics, avoiding large deviations in modal coordinate estimation due to inaccurate identification information. Finally, when decoupling the acceleration signal matrix using the adjusted decoupling parameters, a weighted processing based on the confidence level of each mode identification is introduced. Modes with high confidence levels are assigned higher weights to their corresponding decoupling results, contributing more to the final modal coordinate estimation; modes with low confidence levels are assigned lower weights, suppressing their interference with the estimation results. This entire process forms an adaptive and weighted decoupling mechanism. Based on the initial modal identification and decoupling, by analyzing residuals, adjusting parameters, and introducing confidence level weighting, the accuracy of modal coordinate estimation is significantly improved under conditions of uncertainty in modal identification. This optimization is particularly important in specific scenarios where complex turbulent loads make modal identification difficult, enabling a more accurate perception of the actual vibration state of the hatch and providing a reliable basis for subsequent precise control.

[0052] By adopting the above technical solutions, this application achieves the following technical effects: By separating residual information from the original signal, the uncertainty of modal identification can be quantified. Adaptive adjustment of decoupling parameters based on residual energy enhances the robustness of the decoupling process to unidentified or inaccurately identified modes. Introducing weighting based on identification confidence makes high-confidence modal estimations more reliable, while weakening the influence of low-confidence modes. These measures work together to significantly improve the accuracy and reliability of vibration mode coordinate estimation even when there are errors in modal identification. More accurate modal coordinate estimation provides more precise state information for subsequent vibration control, thereby improving the overall effect of active vibration control and effectively suppressing multimodal coupled vibration of the hatch under complex turbulent loads.

[0053] In some embodiments, the step of weighted decoupling of the acceleration signal matrix using adjusted decoupling parameters to obtain the modal coordinates of each vibration mode includes:

[0054] Obtain the peak power spectral density of each mode;

[0055] Based on the ratio of the peak power spectral density of each mode to the preset noise threshold, the identification confidence of each mode is calculated, and a mode confidence matrix is ​​constructed according to the arrangement of the acceleration signal matrix. The higher the ratio, the higher the confidence.

[0056] Based on the modal confidence matrix, the weighting coefficients of the corresponding modes of each accelerometer are calculated using a normalized exponential function, and a weighted decoupling matrix is ​​constructed to highlight the contribution of high-confidence modes to modal coordinate estimation and suppress the interference of low-confidence modes. The weighting coefficients are proportional to the confidence level.

[0057] Using the adjusted decoupling parameters and weighted decoupling matrix, the acceleration signal matrix is ​​weighted and decoupled to obtain the modal coordinates of each vibration mode. The calculation formula is: Modal coordinates = weighted decoupling matrix * adjusted decoupling parameters * acceleration signal matrix.

[0058] The peak power spectral density (PSD) refers to the maximum energy value at a specific modal frequency in the power spectral density plot of a signal. It can be calculated by performing a Fourier transform on the signal. The preset noise threshold is a pre-defined energy level used to distinguish signal energy from background noise; it can be determined based on sensor noise characteristics or environmental noise levels. Recognition confidence is a quantitative assessment of the reliability of a specific modality's recognition result; it can be calculated using the ratio of the PSD peak to the noise threshold or other statistical methods. The modal confidence matrix is ​​a matrix that arranges the recognition confidence of each modality according to the structure of the acceleration signal matrix; its dimensions are related to the acceleration signal matrix. The normalized exponential function is a mathematical function used to map recognition confidence to weighted coefficients, ensuring these coefficients are normalized. It can be implemented using an exponential form of e divided by the sum. Weighted coefficients are the weight values ​​assigned to different modalities or different sensor signals in decoupling calculations; their magnitude reflects the reliability of the corresponding modality's recognition. A weighted decoupling matrix is ​​a matrix composed of calculated weighting coefficients, used to weight the acceleration signal matrix during decoupling. Weighted decoupling refers to the process of adjusting the input signal or decoupling parameters according to preset weights during modal decoupling calculations.

[0059] This paper addresses the challenge of improving the accuracy of modal coordinate estimation when decoupling an acceleration signal matrix using adjusted decoupling parameters. A weighted decoupling method based on modal recognition confidence is proposed. First, the peak power spectral density (PSD) values ​​for each mode are obtained, providing fundamental data for quantifying the reliability of modal recognition. The PSD peaks reflect the energy intensity of a specific mode in the signal; generally, modes with higher energy are more easily identified. Next, the recognition confidence of each mode is calculated based on the ratio of its PSD peak value to a preset noise threshold, and a modal confidence matrix is ​​constructed. This step quantifies the reliability of modal recognition. By comparing it with the noise threshold, modes with signal energy higher than the noise level can be distinguished. A higher ratio indicates a clearer modal signal, less noise interference, and more reliable recognition results. Constructing the modal confidence matrix maps this reliability information to the structure of the acceleration signal matrix, preparing for subsequent weighted processing. Then, based on the modal confidence matrix, the weighting coefficients for each accelerometer mode are calculated using a normalized exponential function to construct a weighted decoupling matrix. This is a crucial step in achieving weighted decoupling. By using the identification confidence to calculate the weighting coefficients and employing a normalized exponential function, modes with high identification confidence receive larger weights, thus contributing more to the estimation of modal coordinates during decoupling, while modes with low identification confidence receive smaller weights, suppressing their interference. The design of weighting coefficients being proportional to the confidence ensures that more reliable identified modes have higher weights in the decoupling calculation. Constructing the weighted decoupling matrix organizes these weights and applies them to the decoupling process of the entire acceleration signal matrix. Finally, using the adjusted decoupling parameters and the weighted decoupling matrix, the acceleration signal matrix is ​​weighted and decoupled to obtain the modal coordinates of each vibration mode. By applying the previously calculated weighted decoupling matrix to the decoupling calculation, weighted processing based on modal identification confidence is achieved. The calculation formula "modal coordinates = weighted decoupling matrix * adjusted decoupling parameters * acceleration signal matrix" clarifies the specific mathematical implementation of this weighted decoupling. This weighted decoupling method can more effectively utilize the reliability differences of different mode identifications, making the estimation of modes with high identification confidence more accurate, while reducing the negative impact of modes with low identification confidence on the overall estimation, thereby improving the estimation accuracy of the coordinates of each vibration mode. This scheme, combined with the step of adjusting the decoupling parameters based on the energy of the residual acceleration signal matrix, focuses on improving the accuracy of the estimated coordinates of identified modes, while the latter focuses on reducing the impact of unidentified modes on decoupling. The two work synergistically to improve the overall accuracy and robustness of modal coordinate estimation.

[0060] In one specific embodiment, the peak power spectral density (PSD) values ​​corresponding to the frequencies of the identified primary modes can first be extracted from the PSD matrix. For example, if three primary modes are identified, the peak PSD values ​​of these three modes at each sensor location are obtained. Next, a preset noise threshold is set, for example, by determining the noise equivalent PSD level of an acceleration signal based on sensor data or experimental data. Then, the ratio of the peak PSD value of each mode at each sensor location to this noise threshold is calculated; this ratio can serve as a preliminary identification confidence index. These ratios are arranged according to the structure of the acceleration signal matrix (e.g., rows representing sensors, columns representing time or frequency points) to construct a modal confidence matrix. For example, if the acceleration signal matrix is ​​M rows and N columns, the modal confidence matrix can also be M rows and N columns, where each element represents the identification confidence for the corresponding sensor location and the corresponding mode (if multimodal analysis is considered). Subsequently, based on each confidence value in the modal confidence matrix, a normalized exponential function is used to calculate the corresponding weighting coefficient. For example, the function w_ij = exp(k * confidence_ij) / sum(exp(k * confidence_ij)) can be used; where k is an adjustable parameter used to control the steepness of the weight change with confidence, confidence_ij is an element in the modal confidence matrix, and sum is the sum of all relevant weights to achieve normalization. The calculated weighted coefficients are used to construct a weighted decoupling matrix. The structure of this matrix should match the requirements of subsequent decoupling calculations; for example, it could be a diagonal matrix or a more complex structure, depending on the decoupling algorithm. Finally, the decoupling parameter matrix obtained from adjusting the residual acceleration signal matrix energy in the previous steps is multiplied by the constructed weighted decoupling matrix, and then multiplied by the acceleration signal matrix to obtain the modal coordinates of each vibration mode. This calculation process can be performed by a digital signal processor or an embedded system.

[0061] By acquiring the peak power spectral density of each mode and comparing it with a preset noise threshold, the identification reliability of each mode can be quantified. Based on this quantified identification confidence, a normalized exponential function is used to calculate weighting coefficients and construct a weighted decoupling matrix. This allows modes with high identification confidence to receive greater weight in the decoupling calculation, while effectively suppressing the interference of modes with low identification confidence. By using the adjusted decoupling parameters and the constructed weighted decoupling matrix to perform weighted decoupling on the acceleration signal matrix, the modal coordinates of each vibration mode can be estimated more accurately, thereby improving the accuracy and reliability of modal coordinate estimation.

[0062] In some embodiments, the step of generating control commands based on vibration modal coordinates includes:

[0063] Based on the finite element model of the hatch structure, the control force distribution matrix is ​​constructed by determining the transfer function between the actuator position and the vibration of each mode of the hatch. This matrix characterizes the control force influence coefficient of each actuator on each mode.

[0064] Based on the control force allocation matrix and vibration mode coordinates, the required control force for each mode is calculated. During the calculation process, a control force penalty term is added for specific modes that are prone to causing door sealing failure or loosening of the lock, so as to reduce the control force output of the specific modes.

[0065] Based on the required control force for each mode, and combined with the pseudo-inverse matrix of the control force allocation matrix, the control force that each actuator should output is calculated, and the control force is limited to prevent actuator saturation.

[0066] The calculated control force is converted into control commands to drive the actuator.

[0067] The control force allocation matrix is ​​a mathematical matrix characterizing the relationship between the physical forces applied by multiple actuators and the vibration modal responses of the hatch. It can be constructed using analytical methods based on structural dynamics theory or numerical methods based on finite element analysis results. The transfer function is a mathematical model describing the dynamic relationship between the system input (actuator force) and output (modal vibration response). It can be determined using methods such as frequency domain analysis, time domain identification, or modal synthesis. The control force penalty term is an additional term introduced when calculating the control force required for a specific mode, used to reduce the control objective or weight of that mode. It can be implemented using weighting coefficients, penalty factors in the cost function, or objective function corrections. The pseudo-inverse matrix is ​​a generalized inverse matrix of a non-square or singular matrix, used to solve the least-squares solution of a system of linear equations. It can be calculated using methods such as singular value decomposition (SVD), QR decomposition, or iterative algorithms. Limiting processing refers to restricting the calculated control force to a preset maximum and minimum range. It can be implemented using saturation functions, cutoff functions, or dead-zone functions.

[0068] This scheme details how to generate commands to drive actuators to apply control forces based on the estimated door vibration mode coordinates. First, based on a deep understanding of the door structure, a mathematical relationship between the physical force applied by the actuators and the door's vibration mode responses is established through finite element modeling and transfer function analysis, constructing a control force allocation matrix. This matrix clearly characterizes the control force influence coefficient of each actuator on each mode, providing a foundation for subsequently converting the control requirements in the modal space into actuator outputs in the physical space, and is crucial for achieving precise multi-actuator control of multiple modes. Second, based on the currently sensed door vibration state (vibration mode coordinates) and the actuators' influence capabilities on each mode (control force allocation matrix), the theoretically required control force is calculated to effectively suppress the vibration of each mode. Furthermore, during the calculation process, a control force penalty term is added for specific modes that are prone to causing door seal failure or loosening of the lock, thereby reducing the control force output of those specific modes. This feature identifies specific vibration modes that have a potential negative impact on the critical functions of the hatch. By adding a penalty term, the control intensity for these modes is consciously reduced, avoiding unnecessary stress or wear on seals or locking mechanisms due to over-control, thus ensuring the safety of the hatch's critical functions while suppressing vibration. Next, after determining the control force required for each mode, the pseudo-inverse matrix of the control force allocation matrix is ​​used to rationally distribute the control force requirements of the modal space to each actuator. The use of the pseudo-inverse matrix helps handle situations where the number of actuators does not match the number of modes. After calculating the force that the actuator should output, amplitude limiting is an essential step to ensure that the calculated control force is within the safe operating range of the actuator, improving the robustness and reliability of the control system. Finally, the calculated physical control force value is converted into control commands that the actuators can recognize and execute, ensuring that the control system can effectively drive the actuators to apply the required control force to the hatch structure, thereby suppressing hatch vibration. Through the synergistic effect of the above steps, this solution can generate control commands that can effectively suppress hatch vibration and ensure hatch sealing and locking safety under complex loads and actuator constraints, thus solving the technical problem of generating control commands that combine both vibration suppression and hatch safety.

[0069] In a specific embodiment, a precise three-dimensional structural model of the hatch can first be established using commercial finite element analysis software (such as ANSYS or NASTRAN), and modal analysis and frequency response analysis can be performed to obtain the hatch's natural frequencies, mode shapes, and the response of each mode when a unit force is applied at the actuator position. Based on these analysis results, a control force allocation matrix can be constructed, where each column corresponds to a mode, each row corresponds to an actuator, and the matrix elements represent the control influence coefficient of the actuator on that mode. When calculating the control force required for each mode, modern control theory methods such as linear quadratic regulators (LQR) or H∞ control can be used, taking the vibration mode coordinates as state inputs to calculate the optimal modal control force. For specific modes that are pre-determined to easily cause sealing or locking problems (such as certain low-order bending or torsional modes), penalty weights for the control forces of these modes can be added to the cost function of the LQR, or the calculated modal control force can be multiplied by an attenuation factor less than 1. Subsequently, the pseudo-inverse matrix of the control force allocation matrix is ​​calculated using functions provided by numerical computing libraries (such as MATLAB or SciPy). The calculated modal control force vector is then multiplied on the left by this pseudo-inverse matrix to obtain the physical control force vector that each actuator should output. The calculated actuator control force is then saturated and limited to ensure that it does not exceed the actuator's maximum output capability. Finally, the limited control force value is converted into a voltage or current signal via a digital-to-analog converter (DAC) or a specific actuator drive interface, serving as the control command output to drive the actuator.

[0070] Through the above technical solution, this application can generate targeted control commands based on accurate structural models and modal information. In particular, by introducing penalties for specific modes in the control force calculation and limiting the actuator output, this solution can effectively suppress hatch vibration while reducing potential adverse effects on hatch seals and locking mechanisms, thereby improving the safety and reliability of the hatch in complex turbulent environments.

[0071] In some embodiments, when the monitoring results are abnormal, the control commands are adjusted and the adjusted control commands are output to control the actuators to apply control force on the hatch structure, or the control commands are stopped when they are executed.

[0072] Obtain the current actuator's control force output amplitude and frequency information;

[0073] Based on the amplitude and frequency information of the control force output, the control force adjustment factor is calculated. The calculation formula is: adjustment factor = 1 - (amplitude / maximum amplitude) * (frequency / maximum frequency), where the maximum amplitude and maximum frequency are preset actuator safe operation thresholds.

[0074] Based on the control force adjustment factor, the original control command is modified to obtain the adjusted control command. The modification method is: adjusted control command = original control command * adjustment factor;

[0075] Determine whether the amplitude of the adjusted control command is lower than the minimum control command threshold. If it is lower, stop outputting the control command. If it is not lower, send the adjusted control command to the actuator to control the actuator to apply control force on the hatch structure.

[0076] The control force output amplitude refers to the magnitude of the actual control force currently output by the actuator. It can be obtained by measuring and analyzing the actuator's drive signal, or by acquiring force or current signals from internal sensors. The control force output frequency refers to the dynamic rate of change of the actual control force currently output by the actuator. It can be obtained by performing spectral analysis on the actuator's drive or force signals. The maximum amplitude and maximum frequency refer to the upper limits of the actuator's output control force while ensuring the structural and functional safety of the hatch. They can be determined through experimental testing or simulation analysis based on the hatch's structural characteristics, the load-bearing capacity of seals and locking mechanisms, and flight safety requirements. The control force adjustment factor is a proportional coefficient used to correct the original control command amplitude. Its value is typically between 0 and 1, indicating the degree to which the control force needs to be weakened. The minimum control command threshold is a preset lower limit of amplitude below which the control command is considered insufficient to produce effective control or where continued application may pose a risk. It can be determined based on the actuator's minimum effective output capability, the response characteristics of the hatch structure, and safety margins.

[0077] This solution addresses the problem of safely adjusting control commands or halting control when abnormal door sealing pressure or locking status is detected. It provides a specific adaptive adjustment strategy based on the current output state of the actuator. Upon detecting an abnormality, the system first acquires the amplitude and frequency information of the actual control force output by the actuator. Acquiring this information is crucial for understanding the magnitude and dynamic characteristics of the currently applied control force, which is essential for assessing the potential impact of the control force on the already abnormal door state. For example, excessively large control force amplitudes or frequencies similar to the door's structural characteristics may exacerbate seal wear or locking mechanism fatigue. Next, based on the acquired control force output amplitude and frequency information, a control force adjustment factor is calculated. The calculation formula is: Adjustment factor = 1 - (Amplitude / Maximum Amplitude) * (Frequency / Maximum Frequency). Here, the maximum amplitude and maximum frequency are preset actuator safe operating thresholds. This calculation process embodies an adaptive adjustment logic based on the "danger level" of the current control force. The higher the output amplitude or frequency of the actuator, and the closer it is to the preset safety threshold, the smaller the calculated adjustment factor. This indicates a higher potential risk to the abnormal state from the currently applied control force, requiring a greater reduction. Conversely, when the amplitude and frequency are low, the adjustment factor is close to 1, resulting in a smaller reduction. In this way, the system can dynamically determine the degree of control command adjustment based on the actual operating state of the actuator, avoiding blind adjustments. Then, based on the calculated control force adjustment factor, the original control command is corrected to obtain the adjusted control command. The correction method is: adjusted control command = original control command * adjustment factor. Since the adjustment factor is less than or equal to 1, this correction method can directly reduce the amplitude of the original control command proportionally. Based on the adjustment factor calculated in the previous step, high-risk control commands are significantly reduced, while low-risk commands are reduced less, thereby reducing the control force applied to the door, mitigating the stimulation of the abnormal state, helping to prevent further deterioration, and ensuring safe flight requirements. Finally, it is determined whether the amplitude of the adjusted control command is lower than the preset minimum control command threshold. If the force falls below this threshold, it indicates that the corrected control force is very weak, and continuing to apply it may have little effect and still pose a certain risk. In this case, the system chooses to stop outputting control commands; this is a safety strategy under extreme abnormal conditions. If the force does not fall below this threshold, the adjusted control command is sent to the actuator, which applies a weakened but still effective control force to the door structure. This judgment and decision-making process ensures that, in abnormal situations, the system can switch between continuing to apply limited control force to minimize vibration and completely stopping control to maximize safety, depending on the magnitude of the corrected control force. This improves the system's safety and robustness and avoids the vibration runaway problem that might result from simply stopping control.By combining the original control command generated based on modal coordinates with the adjustment factor calculated based on the current state of the actuator, this solution can intelligently adjust or stop the control based on abnormal conditions and potential risks in the actuator output while maintaining a certain vibration suppression capability. This achieves more reliable door control while ensuring the safety of door sealing and locking.

[0078] Through the aforementioned technical means, this application can adaptively adjust control commands or safely stop control based on the current control force output state of the actuator when abnormal door sealing pressure or locking status is detected. This method avoids simplistic and crude command adjustments or stops, reducing the risk of increased door vibration or secondary damage caused by improper control. The system can dynamically weaken the control force according to the potential risk level of the actuator output and safely stop when the control force is too low, thereby improving control safety in abnormal situations, better ensuring the sealing and locking functions of the manned flying saucer door, and meeting the requirements for safe flight.

[0079] Reference Appendix Figure 2 This invention provides a manned flying saucer cabin door control system, comprising:

[0080] The acquisition module 100 is used to arrange acceleration sensors at multiple locations on the hatch and form an acceleration sensor array, and then obtain acceleration signals at multiple locations on the hatch through the acceleration sensor array.

[0081] The estimation module 200 is used to estimate the vibration mode coordinates of the hatch by decoupling the acceleration signal;

[0082] The generation module 300 is used to generate control commands based on the vibration mode coordinates;

[0083] The control module 400 is used to monitor the sealing pressure and locking status of the hatch. When the monitoring results are normal, it controls the actuator to apply control force to the hatch structure by outputting control commands. When the monitoring results are abnormal, it adjusts the control commands and controls the actuator to apply control force to the hatch structure by outputting the adjusted control commands, or stops outputting control commands.

[0084] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0085] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling the hatch of a manned flying saucer, characterized in that, Includes the following steps: After accelerometers are placed at multiple locations on the hatch and arranged into an accelerometer array, acceleration signals at multiple locations on the hatch are obtained through the accelerometer array. By decoupling the acceleration signal, the vibration mode coordinates of the hatch are estimated. The specific steps include: Based on the location distribution of the accelerometers, an acceleration signal matrix is ​​constructed according to the acceleration signals. Perform a fast Fourier transform on each acceleration signal in the acceleration signal matrix to obtain the frequency domain acceleration signal matrix; The frequency domain acceleration signal matrix is ​​analyzed based on a sliding time window, and the power spectral density within each time window is calculated to obtain the power spectral density matrix. Based on the power spectral density matrix, identify the main frequency components within the current time window; The identified main frequency components are matched with a pre-established hatch modal frequency database to determine the main vibration mode of the hatch at the current moment, thus obtaining the main vibration mode information; Based on the determined main vibration mode information, the acceleration signal matrix is ​​decoupled to estimate the vibration mode coordinates of the hatch. The specific steps include: Subtract the modal acceleration signal reconstructed based on the determined main vibration mode information from the acceleration signal matrix to obtain the residual acceleration signal matrix; Adjust the decoupling parameters based on the energy of the residual acceleration signal matrix; The acceleration signal matrix is ​​weighted and decoupled using the adjusted decoupling parameters to obtain the modal coordinates of each vibration mode. The specific steps include: Obtain the peak power spectral density of each mode; Based on the ratio of the peak power spectral density of each mode to the preset noise threshold, the identification confidence of each mode is calculated, and the mode confidence matrix is ​​constructed according to the arrangement of the acceleration signal matrix. Based on the modal confidence matrix, the weighting coefficients of the corresponding modes of each accelerometer are calculated, and a weighted decoupling matrix is ​​constructed. Using the adjusted decoupling parameters and weighted decoupling matrix, the acceleration signal matrix is ​​weighted and decoupled to obtain the modal coordinates of each vibration mode; Control commands are generated based on the vibration mode coordinates; The system monitors the sealing pressure and locking status of the hatch. When the monitoring results are normal, it outputs control commands to control the actuators to apply control force to the hatch structure. When the monitoring results are abnormal, it adjusts the control commands and outputs the adjusted control commands to control the actuators to apply control force to the hatch structure, or stops outputting control commands.

2. The manned flying saucer hatch control method according to claim 1, characterized in that, The placement of the acceleration sensors includes the hatch skin, reinforcing ribs, and frame.

3. The manned flying saucer hatch control method according to claim 1, characterized in that, The steps for generating control commands based on vibration mode coordinates include: By determining the transfer function between the actuator position and the vibration modes of the hatch, a control force distribution matrix is ​​constructed. Calculate the required control force for each mode based on the control force allocation matrix and vibration mode coordinates; Based on the required control force for each mode, and combined with the pseudo-inverse of the control force allocation matrix, calculate the control force that each actuator should output; The calculated control force is converted into control commands to drive the actuator.

4. The manned flying saucer hatch control method according to claim 3, characterized in that, In the process of calculating the required control force for each mode, a control force penalty term is added for specific modes that are prone to causing door sealing failure or loosening of the lock.

5. The manned flying saucer hatch control method according to claim 3, characterized in that, After calculating the control force that each actuator should output, the control force is limited to obtain the final control force.

6. The manned flying saucer hatch control method according to claim 1, characterized in that, When monitoring results are abnormal, the control commands are adjusted and the adjusted control commands are output to control the actuators to apply control force to the hatch structure, or the control commands are stopped when they are executed. Obtain the current actuator's control force output amplitude and frequency information; Calculate the control force adjustment factor based on the control force output amplitude and frequency information; Based on the control force adjustment factor, the original control command is modified to obtain the adjusted control command; Determine whether the amplitude of the adjusted control command is lower than the minimum control command threshold. If it is lower, stop outputting the control command. If it is not lower, send the adjusted control command to the actuator to control the actuator to apply control force on the hatch structure.

7. A manned flying saucer cabin door control system employing the manned flying saucer cabin door control method as described in any one of claims 1-6, characterized in that, include: The acquisition module is used to arrange acceleration sensors at multiple locations on the hatch and form an acceleration sensor array, and then obtain acceleration signals at multiple locations on the hatch through the acceleration sensor array. The estimation module is used to estimate the vibration mode coordinates of the hatch by decoupling the acceleration signal; The generation module is used to generate control commands based on the vibration mode coordinates; The control module monitors the sealing pressure and locking status of the hatch. When the monitoring results are normal, it outputs control commands to control the actuators to apply control force to the hatch structure. When the monitoring results are abnormal, it adjusts the control commands and outputs the adjusted control commands to control the actuators to apply control force to the hatch structure, or stops outputting control commands.

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