172results about How to "Strong engineering practicability" patented technology

The invention relates to an underwater acoustic target recognition system and method based on multi-modal depth feature fusion, and belongs to the field of underwater acoustic target recognition. The method comprises the following steps: firstly, performing preprocessing on an obtained underwater acoustic target original audio and associated metadata, and constructing a multi-modal data set; and then the constructed multi-modal sample is input into an identification model, the model extracts deep representation of each modal through a multi-branch feature coding network, depth alignment and complementary aggregation of different modal features are realized by using a cross-modal cross attention mechanism guided by potential query, and a target identification result is output based on a decision network of mixed experts. According to the method, experimental verification is carried out on two disclosed underwater acoustic data sets, the experimental result verifies the effectiveness of the multi-modal deep fusion and hybrid expert adaptive decision strategy adopted by the method, and through mining the complementary advantages of acoustic features and semantic priori, the multi-modal deep fusion and hybrid expert adaptive decision strategy is obtained. And the robustness and generalization ability of the underwater acoustic target recognition system in the strong-noise and multi-working-condition environment are remarkably improved.

The invention discloses a fracturing crack dynamic inversion method fusing optical fiber strain monitoring and crack propagation simulation, and belongs to the technical field of oil and gas field exploitation, and the method comprises the steps: building a state control equation based on a state variable, and predicting the crack width distribution of a next time step according to the built state control equation; calculating a covariance matrix of a next time step prediction error of the state control equation according to the covariance matrix of the system error of the crack propagation model; establishing an observation equation of the distributed optical fiber strain, and calculating the optical fiber strain corresponding to the state variable of the next time step; according to the monitored optical fiber strain data and the optical fiber strain corresponding to the state variable of the next time step, establishing a state updating equation of slit width distribution; and updating the state of the crack unit, and after updating is completed, entering the prediction of the crack width distribution of the next time step again until a set end moment is reached, so that a physical mechanism is fused and strain data is observed.

The invention discloses a radio frequency transceiver gain flatness adaptive calibration circuit and method, and relates to the technical field of radio frequency circuits. According to the invention, the gain flatness self-adaptive calibration circuit is introduced into the radio frequency receiving or transmitting channel, so that after the circuit is manufactured, the gain flatness of the radio frequency channel can be automatically detected and calibrated, and the adverse effects of process deviation, power supply voltage change and temperature fluctuation (PVT) on the gain flatness of the radio frequency receiving or transmitting channel are improved.

The invention relates to a heat supply prediction method and system based on spatial-temporal feature fusion deep learning, and the method comprises the following steps: S1, carrying out the collection and fusion of multi-source heterogeneous data, and constructing an integrated data set; s2, preprocessing the data; s3, constructing a graph structure model of the heat supply system, and constructing a weighted undirected graph; s4, constructing and executing forward calculation of the space-time double-flow deep network; s5, designing a composite loss function including mean square error loss and physical constraint loss, and performing joint optimization training on the space-time double-flow deep network; and S6, performing multi-step heat supply load prediction by using the trained model, outputting a heat supply load curve of each heat exchange station in a specified time period in the future, and integrating a prediction result with a heat supply scheduling system. The method has the advantages that the prediction precision is improved compared with that of a traditional machine learning model by capturing the spatial-temporal characteristics at the same time, and the advantages are more remarkable in extreme weather.

The invention discloses a processor instruction fetching acceleration method and device based on prefetching, and relates to the technical field of computer processors. Pre-decoding the instruction to obtain a first category of the instruction; according to the execution type, classifying part of the instructions of the first category to obtain a second category of the instructions; according to a preset processing method, the instructions of the first category and the instructions of the second category are skipped to update target addresses of the instructions, and the instruction fetching process is achieved. According to the invention, the required instruction can be quickly obtained, and a processing device with high performance, low power consumption, small area and simple structure is realized, so that the processor has good engineering practicability.

The invention relates to the technical field of building structure engineering, in particular to a simplified elastic analysis and design method for an integrated model of a partition wall structure, and provides a simplified elastic analysis and design method based on a physical mechanism and data driving. And instead, a practical design tool which can be directly used for engineering design, is seamlessly connected with the current specification and has definite physical significance is formed based on intelligent calibration of a large-refinement nonlinear analysis result. According to the method, quantitative correlation between elasticity and nonlinear performance is established, theoretical preciseness is guaranteed, and the method has extremely high engineering practicability and serves as preposition and supplement of refined nonlinear analysis to form a complete technical system from rapid scheme design to accurate performance verification.

The invention belongs to the field of ship engineering design, and discloses a ship cabin layout method and system based on three-dimensional knowledge gene layer dynamic fusion. The system comprises a cabin layout reasoning module based on priori knowledge, an intelligent cabin layout optimization algorithm module based on computational knowledge, a human intelligence knowledge cabin layout scheme online design module and a three-dimensional knowledge fusion solving cabin layout design module. Three-dimensional knowledge individuals of the priori knowledge scheme, the algorithm knowledge scheme and the human intelligence knowledge scheme which are obtained respectively are dynamically fused on the evolution algorithm gene level to form an evolution group, and a cabin layout scheme is obtained through operation in a replacement mode, a crossing mode and a mode of combining crossing and a multi-objective function tradeoff method; according to the method, an optimization target and constraint conditions which are difficult to be expressed by mathematical languages in the cabin layout process can be considered in the algorithm solving process, and a more practical ship cabin layout scheme is obtained.

The invention discloses an unbalance compensation method and system for an energy storage converter, and belongs to the field of power electronics and electric energy quality treatment. The system comprises a power instruction analysis module, a current reference generation module, a negative sequence current control loop module, a zero sequence control loop module, a positive sequence control loop module, a pulse width modulation module, a first conversion module and a second conversion module, the current reference generation module is respectively connected with the negative sequence current control loop module and the positive sequence control loop module; the third end and the fourth end of the negative sequence current control loop module are connected with the pulse width modulation module through the second conversion module; the third end and the fourth end of the zero sequence control loop module and the third end and the fourth end of the positive sequence control loop module are connected with the pulse width modulation module through the first conversion module. According to the method, the energy storage and compensation functions of the PCS can be seamlessly integrated under a unified control framework, so that the control system is greatly simplified, and the performance is remarkably improved.

The invention discloses a processor and a method for solving processor data conflict and low-power-consumption execution. When instructions are dispatched, each long instruction is recorded into an OITF table item, and each long instruction is written back, the instruction is removed from the OITF table item; the long instruction which is dispatched but not written back is stored in the table item in the OITF; when each instruction is dispatched, the target information of the instruction is compared with the target information in each table item in the OITF so as to judge whether the instruction has a data conflict with a long instruction which is dispatched and not written back or not, when the data conflict is generated, an assembly line is blocked at a dispatching point, and after the data conflict is relieved, dispatching is continued, and in addition, the data conflict between the instruction and the long instruction is eliminated. And when the dispatched instruction is executed, data operation of different types of instructions is carried out through the shared data operation sub-module. The method can effectively solve the data conflict generated in the operation of the processor, and reduces the power consumption and area of the processor in the execution stage.

The invention discloses a multi-layer semantic perception, distillation and semi-supervised cooperative training target detection method, and the method specifically comprises the following steps: constructing a data set: extracting a first part of images from image data, marking the first part of images to construct a supervised target detection data set, and taking the remaining images as an unmarked image data set, the data volume of the unlabeled image data set is greater than that of the supervised target detection data set; teacher model optimization: performing supervision training on the teacher model on the supervised target detection data set; constructing a teacher model, and executing self-distillation training on the teacher model; pseudo labels are generated for the unlabeled images through a teacher model, and adaptive screening is carried out based on confidence distribution; mapping a pseudo label to a strong enhanced sample through enhanced geometric transformation, carrying out semi-supervised training by using the strong enhanced sample and the pseudo label, and introducing a feature layer distillation constraint at the same time; optimizing a student model; and outputting the target detection model obtained through training.

The invention relates to the technical field of marine environment numerical simulation, in particular to a near-shore typhoon wave refined simulation method based on terrain adaptive grids and parameter dynamic correction, and the method comprises the steps: obtaining basic data and simulation parameters of a target sea area, constructing a computational domain and an initial grid, and constructing a target sea area; the initial grid is an unstructured grid fused with multiple physical constraint factors; performing optimization processing on the initial grid based on a numerical stability criterion to obtain a final calculation grid meeting a calculation convergence requirement; establishing a bidirectional coupling model, and applying the final computational grid to the bidirectional coupling model; carrying out localization iteration calibration on key physical parameters of the bidirectional coupling model to obtain an optimal parameter set; and carrying out typhoon wave process simulation calculation and constructing a typhoon wave feature database by utilizing the final calculation grid and the optimal parameter set, and realizing high-precision simulation and prediction of the typhoon wave process by constructing an adaptive optimization grid, a bidirectional coupling model and a parameter localization calibration mechanism.

This invention relates to the fields of injection molding quality control and artificial intelligence, specifically to a method and system for predicting warpage defects in injection molded products based on a physical information neural network. The method includes: acquiring the basic parameters of the injection molded product and a physical information neural network; collecting measured data and randomly selecting physical sampling points; substituting the measured data and physical sampling points into the network using a double loss function training method; the measured data includes the basic parameters and corresponding measured warpage displacement values; the physical sampling points output corresponding predicted temperature fields, predicted internal stress fields, and predicted warpage displacement fields through an output layer; inputting the basic parameters of the product to be predicted into the trained network, and outputting the warpage defect prediction results. This invention balances data-driven accuracy with the reliability of physical mechanisms, solving the technical problems of pure data-driven models relying on a large number of defect samples and the low efficiency of traditional physical simulation.

This invention belongs to the field of data prediction technology, and provides a method and system for predicting solidification cracks in alloy welding. The method includes: acquiring the thermophysical parameters, scanning speed, and horizontal and vertical distances from the solidification point to the welding point of the alloy to be tested; calculating the theoretical angle between the scanning speed direction and the normal to the fusion line based on the horizontal and vertical distances from the solidification point to the welding point; establishing a continuous growth limiting factor calculation model based on the thermophysical parameters, scanning speed, and theoretical angle, and determining the derivative expression model between the solid-liquid interface temperature and the square root of the solid fraction; establishing a crack sensitivity index calculation model based on the continuous growth limiting factor calculation model and the derivative expression model; converting the crack sensitivity index calculation model into a data curve, and obtaining the welding solidification crack prediction result based on the data change characteristics of the target segment in the data curve. This scheme has a simple calculation process, strong engineering applicability, and improves the accuracy of solidification crack prediction.

The invention discloses a building engineering CAD drawing intelligent identification method and system, a terminal and a medium, and the method comprises the steps: determining a drawing frame identification range, building an original data set, and carrying out the processing based on the original data set, and obtaining a training data set, the training data set comprises a plurality of pictures marked with a drawing frame range and a drawing frame type; training a yolov8 model based on the training data set to obtain a picture frame range and type identification model; reasoning the CAD drawing based on the drawing frame range and type identification model to obtain a drawing frame range and type reasoning result, performing coordinate mapping processing on the drawing frame range and type reasoning result, and recording the result into a drawing identification JSON file. According to the method, the reasonable boundary range and the drawing frame type of the effective design content can be identified from the CAD drawing, so that a subsequent application layer can conveniently develop an automatic drawing frame application algorithm based on the boundary range.

The application provides a deep geothermal resource prediction method based on mechanism-space-distribution fusion, comprising: constructing a multi-dimensional heterogeneous fusion feature system cooperated by a mechanism driven layer, a space perception layer and a data distribution layer, explicitly injecting radioactive heat potential, heat-mass transfer coupling factor, multi-scale space singularity index and unsupervised anomaly score; adopting a recursive feature elimination algorithm to dynamically screen core geochemical fingerprints; fusing gradient boosting tree, random forest and extreme random tree to construct a ternary consensus integrated prediction module, and outputting joint prediction probability through soft voting; based on recall rate anchoring strategy, optimizing asymmetric decision boundary to generate geothermal potential prediction map. The prediction result of the application is highly consistent with the fault structure zone, effectively solves the problems of mechanism loss, high false alarm rate and small sample overfitting, and provides an intelligent technical solution with high precision, low false alarm and interpretability for deep concealed geothermal field exploration.

The application discloses a large-aperture spliced telescope optical system and an imaging method, and belongs to the technical field of optical engineering. The system comprises coaxially arranged first, second and third RC systems, the curvature radii of the primary mirrors of the three sets of systems are different from each other, the curvature radii of the secondary mirrors are different from each other, and the total focal lengths are uniform. External light beams are converged to the same focal point after being reflected once by the three layers of primary mirrors and reflected twice by the corresponding secondary mirrors. According to the application, the aberration of the light beams in different off-axis regions can be independently corrected through the differential curvature multi-group coaxial RC architecture, and the full-field imaging approaches the diffraction limit. The light path parameters of each group are independently adjustable, the control precision of the wavefront consistency is higher, the local light path maintenance and upgrading do not need to replace the whole element, and the engineering use cost is lower. The matching imaging method completes the aberration correction in two stages, the final imaging spot energy is concentrated and free from distortion, and is suitable for astronomical observation, deep space exploration and high-precision imaging of space targets.

The application discloses a distributed interval observer optimization design method for multi-dynamic linear systems, and aims at a multi-dynamic distributed linear system disturbed by a bounded noise. Firstly, a reversible linear transformation is used to decompose an observable virtual subsystem. Then, a distributed interval observer containing output error feedback correction is designed to construct a local state interval estimation. Based on interval operation, an estimation error dynamic and its upper and lower bound explicit expressions are derived to verify the interval effectiveness. Further, Lyapunov stability theory and linear matrix inequality are used to optimize the observer gain and the collaborative coupling gain under Metzler, Hurwitz and numerical reliability constraints. Finally, the observation nodes are updated collaboratively based on the communication topology. The application does not require the system to meet strict assumptions such as cooperativeness, only needs noise upper and lower bound information, can adapt to various dynamic characteristics such as diagonal stability, strong coupling and weak damping oscillation, and has the advantages of high estimation accuracy, good numerical robustness and distributed collaboration support.

The application relates to a device performance test method and device, computer equipment and a storage medium. The method is applied to an upper computer, the upper computer is in communication connection with a benchmark communication device and a to-be-tested communication device respectively, the benchmark communication device and the to-be-tested communication device are in communication connection through at least one line, and the method comprises the following steps: acquiring a test strategy for data receiving performance test of the to-be-tested communication device; controlling the benchmark communication device to send message data to the to-be-tested communication device through at least one target line matched with the test strategy; acquiring message receiving conditions of the to-be-tested communication device for receiving the sent message data through the target lines; and determining whether the data receiving performance of the to-be-tested communication device is normal according to different message receiving conditions. The method can effectively detect the data receiving performance of the device.

The present invention relates to the field of power distribution automation technology, and discloses a characteristic current communication method applicable to the power field, and the steps are as follows: setting characteristic frequency, signal cycle and minimum signal transmission time; setting the single transmission time and total transmission time of characteristic sequence information bits, and designing characteristic sequence C0; the transmitting device transmits characteristic current; the receiving device detects the theoretical transmission signal characteristic frequency and sets the decoding sequence C1; the characteristic frequency of the received signal is detected to obtain Sc1' and Sc2'; Sc1' is judged to obtain C1'; the number of positions Ne where C1' and C1 have different values ​​is calculated; Sc2' is demodulated to obtain the trust degree En of C1'; if Ne≤En, the characteristic current reaches the receiving device; otherwise, it does not reach. The present invention is aimed at the current micro-current communication technology, and through the optimization of the transmission sequence and the improvement of the detection algorithm, the transmission power is reduced to 60% of the original scheme under the premise of not lower than the bit error rate of the current scheme, and the engineering practicability is strong.

This invention relates to the fields of tunnel engineering and 3D geological modeling technology, specifically to an intelligent modeling method and system for 3D geological uncertainty in tunnels based on transition probability geostatistics and sparse boreholes. The method includes: S1, integrating multi-source data to construct a 3D geological conceptual model; S2, statistically characterizing a one-dimensional transition probability matrix, calculating and fitting a spatial continuity and 3D anisotropic variability function model; S3, calculating the prior spatial probabilities and transition adjustment factors for various lithologies, obtaining the posterior lithology distribution of nodes through Bayesian intelligent updating, and initially assigning lithology categories to nodes through random sampling; S4, assigning the most probable lithology category to each grid node, calculating the variance of lithology values ​​across all implementations, and measuring model uncertainty; S5, outputting the optimal 3D uncertainty model for the tunnel; and S6, verification and evaluation. This invention can effectively achieve 3D heterogeneous modeling and explicit quantification of uncertainty under strong geological constraints.

This invention belongs to the interdisciplinary field of artificial intelligence and geological resource assessment, specifically relating to a method and system for predicting the energy storage potential of salt caverns based on multi-source geological information. It aims to address the problems of low prediction accuracy and difficulty in balancing breadth and precision in existing technologies due to single-source data, static models, and lack of adaptive capabilities. The method includes: acquiring multi-source data such as seismic, well logging, core, and geostress data; constructing a geological feature fusion vector containing seven core parameters; establishing a high-dimensional nonlinear mapping model driven by a deep neural network; dynamically adjusting the prediction range based on data coverage density and confidence level; and achieving continuous model iteration through online incremental learning. The system integrates data quality assessment, anomaly handling, and distributed computing modules. By adopting the above technical solutions, this application can achieve a significant improvement in prediction accuracy and adaptive intelligent adjustment of the prediction range.

The invention discloses a sparse sensor optimization layout method for battery thermal safety monitoring. The method comprises the following steps: constructing a full-working-condition temperature field data set through high-fidelity simulation data; defining a multi-task loss function fusing the overall reconstruction error, the hotspot monitoring error and the spatial dispersion; and with minimization of the loss function as a target, an optimal sensor distribution point is automatically searched by adopting an optimization algorithm. According to the method, the problems of sensing blind areas and early warning lag existing in empirical layout are solved, high-precision temperature field reconstruction and early thermal safety early warning can be achieved with the minimum number of sensors, the reliability is high, the cost is low, and the method is suitable for thermal management design of various lithium ion battery systems.

This invention discloses an integrated planning method and system for a multi-jurisdictional unmanned aerial vehicle (UAV) service system. The method constructs an overall planning model with the goal of minimizing total cost, and sequentially establishes a front-end UAV allocation model and a back-end battery swapping station allocation model. With the objectives of minimizing average response time and minimizing the total expected queue length, respectively, the total number of UAVs, charging stations, and backup batteries, as well as the jurisdiction-level configuration scheme, are obtained. This invention achieves integrated collaborative planning of front-end transportation and back-end battery swapping, reducing the total system cost and average response time, balancing the operating load of each jurisdiction, effectively avoiding service interruptions due to a lack of available batteries during peak periods, and significantly improving system reliability and engineering practicality.

This utility model belongs to the field of storage device technology, specifically relating to a device and system for collecting leaked ethylene glycol aqueous solution. It includes a collection tank body, a water inlet, a solenoid valve, a vent, a level gauge, a signal terminal, a drain outlet, a detection port, a controller, and a collection tank base. The water inlet is located on the top left side of the collection tank body via a straight pipe, the signal terminal is installed on the top right side of the collection tank body, and the drain outlet is located at the bottom of the collection tank body via a straight pipe. This utility model, through the coordinated design of the collection tank body, solenoid valve, level gauge, and controller, achieves automatic collection and alarm control of leaked ethylene glycol aqueous solution. When the liquid level reaches the alarm threshold, the controller automatically closes the solenoid valve at the water inlet and sends a signal to prevent the leaked liquid from continuing to spread. Simultaneously, manual collection is achieved through the drain outlet, effectively preventing the slightly toxic ethylene glycol aqueous solution from harming people and the environment, and significantly improving the safety of indoor ski resort air conditioning systems.

This invention discloses a method, apparatus, device, and storage medium for depth extraction of the focus stack weight domain. The method includes: acquiring a multi-focal plane image sequence; calculating focus sharpness pixel-by-pixel and normalizing it along the focal plane to generate an initial weight map; using the original image as a structural reference to perform edge-preserving filtering on the initial weight map to obtain an optimized weight map; constructing a weight-focal plane curve based on the optimized weight map, and sequentially performing three levels of logical judgment: the first level removes textureless regions based on the maximum weight value; the second level removes high-reflectivity false peaks based on waveform flatness; and the third level filters candidate focal plane positions based on peak focus sharpness; and performing sub-pixel fitting on the selected candidate focal plane positions to convert them into physical depth and generate a 3D point cloud. This invention effectively solves problems such as false points on textureless backgrounds, false peaks on highly reflective surfaces, edge breaks in weak textures, and limited depth accuracy through edge-preserving filtering to optimize the weight map, three-level progressive judgment, and sub-pixel fitting.

The invention discloses a packaging heat dissipation structure for a high-power-density device, and relates to the technical field of electronic equipment heat dissipation, the packaging heat dissipation structure comprises a packaging shell connected with the high-power-density device, the packaging shell is provided with a micro-channel for circulation of a cooling working medium, and the micro-channel corresponds to the high-power-density device. After the micro-channel is combined with the packaging structure of the high-power-density device, the interval between the high-power-density device and the micro-channel is reduced, the thermal resistance of the high-power-density device is reduced, the packaging structure does not affect the design of an electronic layer of the high-power-density device, and the practicability is high; the equivalent size of the micro-channel is gradually reduced, the specific surface area of the micro-channel is increased, the pressure drop is reduced, the heat exchange performance is enhanced, the temperature uniformity of the surface of a high-power-density device is further improved, and the situation that the packaging reliability is reduced due to thermal stress generated by a large temperature gradient is avoided. The technical problem that stable operation of a high-power-density device is affected due to the fact that an existing heat dissipation structure has a large temperature gradient is solved.

The application relates to a plane circle center point-based SolidWorks standard part automatic installation method for a parameter-free model, and belongs to the field of computer-aided design and three-dimensional mechanical design automation. The method first selects any part plane and any assembly hole on the part plane through a point selection mode; a sketch is created based on the geometric boundary of the part plane, and the coordinates of the sketch are determined according to the geometric boundary position information of the part plane; all assembly holes with the same hole feature on the part plane are automatically identified according to the extracted selected assembly hole feature, and corresponding sketch coordinates are established; sketch points are established for all sketch coordinates under the part plane; and the sketch-driven part array function is called, after manually assembling a standard part at any sketch point, the standard part assembly is automatically executed at all sketch points. The application can automatically batch install standard parts by using the sketch-driven part array function of an assembly body.

The invention discloses a maneuvering target interception guidance method with arrival angle and field angle constraints. The maneuvering target interception guidance method comprises the following steps: establishing a relative motion equation of an aircraft intercepting a maneuvering target; the relative motion equation is converted into a relative motion model with the distance between the aircraft and the target as an independent variable; setting a change curve of an expected relative front angle, and obtaining a guidance law expression based on a relative motion model; field angle constraint is carried out by limiting the maximum value of the relative front angle curve, the reachable range of the arrival angle is obtained, and under the condition that the arrival angle meets the reachable range, the aircraft adopts the obtained guidance law to carry out flight control. According to the method disclosed by the invention, linear approximate processing does not need to be carried out on the relative motion mathematical model of the aircraft and the target, the precondition hypothesis of a small preposed angle is not needed, and the method has the characteristics of simple design and use method, high applicability and the like.

The invention relates to a tight coupling vision inertial odometer method based on a pulse camera brightness change rate, and belongs to the field of computer vision and robot positioning and navigation. The method comprises the steps of 1) VIO system preparation and data preprocessing, 2) visual feature extraction and pulse observation value calculation, 3) IMU pre-integration, and 4) tight coupling optimization model construction and solution. During operation of the system, for each sliding window, the optimization process of a predicted state vector is completed through the steps 2)-4), carrier motion state estimation at the latest moment in the current sliding window is output, then the sliding window is updated, and the steps 2)-4) are cycled, so that the system continuously outputs high-frequency and high-precision real-time motion state estimation. According to the invention, the microsecond brightness differential signal of the pulse camera is converted into continuous physical supervision on the motion state, and the precision and robustness of the system in challenging scenes such as high speed and dynamic illumination are remarkably improved in a tight coupling mode on the premise of not changing the VIO main body architecture.

The invention discloses a spacecraft analysis redundancy autonomous mining method based on diagnostic capability quantitative characterization, and belongs to the technical field of spacecraft overall. Firstly, a system input and output expression is constructed according to a state equation of a spacecraft control system; then, constructing system input and output expressions of different measurement channel combinations and equivalent expressions of the system input and output expressions; thirdly, giving random characteristics of system equivalent input and output of different measurement channel combinations, and on the basis, giving an analysis redundancy criterion based on a system dynamic model; secondly, a test data matrix is constructed based on spacecraft test data, and an analysis redundancy criterion based on the test data is given; and finally, giving a spacecraft analysis redundancy comprehensive criterion, and realizing spacecraft analysis redundancy autonomous mining. The method can be used for autonomous mining and redundancy analysis of the spacecraft, the autonomous fault diagnosis capability of the spacecraft is improved, and a solution is provided for realizing autonomous fault diagnosis of the spacecraft.