102 results about "Space exploration" patented technology

The invention discloses a star soil water-ice in-situ quantitative analysis system and method, and belongs to the technical field of planetary science and space exploration, the star soil water-ice in-situ quantitative analysis system comprises a detection platform, and a star soil collection unit and a star soil water vapor heating extraction unit are arranged outside a cabin of the detection platform; a first detection unit, a second detection unit, a control unit and a gas distribution unit are arranged in a cabin of the detection platform; the gas distribution unit is used for distributing the water vapor extracted by the star soil water vapor heating and extracting unit to the first detection unit and the second detection unit for analyzing the content and isotope composition of the water vapor of the star soil; the first detection unit and the second detection unit adopt different detection analysis technologies; and the control unit is used for controlling the detection analysis process of the analysis system. According to the system, an in-situ sampling analysis mode of'quantitative sampling of water-containing star soil, low-loss sample transfer, efficient heating extraction and high-precision instrument analysis' is adopted, so that accurate quantitative analysis of star soil water ice is realized.

The invention discloses an unmanned aerial vehicle mobile crowd sensing data acquisition trajectory optimization method based on communication enhancement deep reinforcement learning, and the method comprises the steps: constructing a mobile device and an unmanned aerial vehicle mobile model under a mobile crowd sensing scene for an application scene of mobile crowd sensing data collection; and a data transmission channel model and an unmanned aerial vehicle data acquisition model. In order to realize balance between the information age of data and the energy consumption of the unmanned aerial vehicle, the invention provides a communication enhanced trajectory optimization CETO algorithm, specifically, the trajectory of the unmanned aerial vehicle is optimized through balanced exploration and utilization of a network part of deep reinforcement learning in a continuous action space, and the energy consumption of the unmanned aerial vehicle is optimized through a communication mechanism. And each unmanned aerial vehicle can adaptively optimize the local state of the unmanned aerial vehicle by using the sharing state of the neighbor of the unmanned aerial vehicle. Experiments show that the CETO algorithm provided by the invention shows remarkable superiority and feasibility in the aspects of unmanned aerial vehicle trajectory design and data acquisition task completion.

The invention relates to the technical field of space exploration and lunar soil experiments, in particular to a melting centrifugal type mineral particle morphology remodeling device and a lunar soil glass ball preparation method. The device comprises a mineral protolith high-temperature melting system, a mineral melting slurry conveying system, a centrifugal mineral particle size control system and a mineral particle cooling and morphology remodeling system. The preparation method of the lunar soil glass ball comprises the following steps: adding basalt mineral powder and mineral melting additive powder into a melting centrifugal mineral particle morphology remodeling device to obtain simulated lunar soil glass balls with different particle sizes, and performing morphology transformation on the simulated lunar soil glass balls with different particle sizes by using an ion beam gun. And the lunar soil glass ball state of the impact melting history is reduced. According to the method, high-precision engineering mass production of components, morphology and mechanical properties of the lunar soil glass balls is realized through a fusion centrifugal forming and ion beam surface control composite process, and the problem of soil mechanical behavior deviation caused by morphology distortion of existing simulated lunar soil is solved.

The present disclosure is directed polymer-free, non-composite densified carbon nanotube (DCN) structures from thin carbon nanotube (CNT) films and methods of making the same. CNT thin films can be cut, folded, stacked and pre-arranged in the form of cylinders, discs, domes, frames, gaskets, jars, rings, sacks, seals and sheets on a smooth reaction vessel surface and subsequently densified with the use of chlorosulfonic acid (HClSO3) at elevated temperatures. The disclosed DCN structures can be used as EMI shielding, lightweight structural and functional components in extreme conditions commonly encountered in space exploration, polar expeditions and military operations, and also as hydrophilic filtration media that resist surface fouling and provide high flux.

The invention discloses a satellite orbit control method based on a continuous time near-end strategy optimization reinforcement learning algorithm, and the method comprises the following steps: 1, determining an action, namely acceleration, taken by a satellite, and the execution time of the action based on the continuous time near-end strategy optimization reinforcement learning algorithm; and step 2, realizing satellite orbit control based on the action taken by the satellite and the execution time obtained in the step 1. The advanced near-end strategy optimization reinforcement learning algorithm (PPO) and the continuous time control framework are combined, a high-precision, stable and energy-efficiency-optimized satellite orbit control solution is provided, remarkable technical advancement and wide application prospects are achieved, and powerful technical support is provided for future space exploration and satellite operation.

The invention provides an unmanned aerial vehicle autonomous exploration method based on boundary detection and probability sampling fusion, and the method comprises the steps: firstly generating a high-quality viewpoint through a probability sampling model, and providing precise data support for path planning in an exploration stage; secondly, efficient collaboration of global planning and local planning is achieved by means of a layered planning architecture and a topological path search technology; and finally, through a re-planning mechanism, the robustness and task continuity of the unmanned aerial vehicle in the exploration process in a complex unknown environment are ensured. Aiming at the technical defects that the existing autonomous exploration method is easy to fall into local optimum, low in calculation efficiency, insufficient in track smoothness and the like, the invention provides a solution suitable for an unknown environment, and a space exploration task can be efficiently and quickly completed.

The invention provides an SMT solver rewriting system defect detection method based on rewriting space exploration, and aims to solve the problems that in the prior art, an SMT solver rewriting system is insufficient in verification, test input is difficult to trigger a rewriting rule, errors are difficult to verify and the like. The method comprises the following steps: 1) collecting and automatically verifying rewriting rules in an SMT solver, and constructing a high-quality rule base; 2) performing structure transformation on the existing test formula by adopting mimicry variation to enable the existing test formula to be matched with a rewriting rule mode, thereby activating more rewriting opportunities; 3) constructing an equivalence graph based on a generative equivalence saturation technology, and systematically generating semantic equivalence but structural diversity formula variants; and 4) inputting the original formula and the variant formula into an SMT solver, comparing the solving result with the performance behavior, and detecting potential defects. The invention also provides corresponding system implementation, and supports an automatic test process, rule management, formula generation and defect recording.

The invention relates to the technical field of spacecrafts, in particular to a spacecraft defense material and a preparation method thereof, and designs a structure capable of effectively absorbing and dispersing impact energy on microscopic and macroscopic scales by utilizing computer simulation and an advanced material modeling technology. A base material with high strength, high toughness, light weight and corrosion resistance is selected, nanofibers, nanoparticles or nanosheet layers are embedded into the base material by utilizing a nanotechnology so as to enhance the mechanical property and the impact resistance of the base material, and the shape, the structure and the performance of the material are accurately controlled by adopting an advanced manufacturing technology. The prepared materials are stacked, bonded or mechanically connected together to form a final defense structure, and the structure is strictly tested. By combining a nanotechnology, composite material engineering and an additive manufacturing defense material, the deep requirement of a space exploration task is met, and the safety of astronauts and the smooth completion of the task are ensured.

The application discloses a small animal independent ventilation non-magnetic cage feeding system for indoor air intake and exhaust in a sub-magnetic space, which comprises the following parts: an external magnetic field shielding room, a small animal feeding non-magnetic cage, a non-magnetic cage placing rack, a ventilation unit and an air purification unit and the like; the external magnetic field shielding room mainly shields the external geomagnetic field and provides a required sub-magnetic environment for small animal cultivation; the non-magnetic cage placing rack is mainly used for placing the small animal feeding non-magnetic cage and is equipped with independent ventilation pipelines required for small animal feeding and is also made of non-magnetic materials; the non-magnetic feeding system for small animal cultivation in the sub-magnetic space disclosed in the application is mainly used for in-depth research on the influence mechanism of the sub-magnetic field environment on living beings, so as to further improve the survival rate and life quality of astronauts in future space exploration and interstellar travel.

An electronic watch can be configured to have a function for space exploration and / or terrestrial planet surface exploration. The watch can include a time display device and a processor subsystem. The processor subsystem can be configured to maintain a coordinated planet time of a terrestrial planet, obtain longitude data representing a longitude of interest on the terrestrial planet, the longitude of interest being different from the prime meridian of the planet, determine a local true solar time, LTST, at the longitude of interest as a function of the coordinated planet time, and control the time display device of the electronic watch to display the LTST using a time equation that takes into account an orbital eccentricity and an axial tilt of the terrestrial planet.

The application discloses a robot unknown environment autonomous exploration navigation method based on CTSAC, which combines the powerful sequence perception ability of the Transformer with the Soft Actor-Critic deep reinforcement learning framework, and introduces a periodic review mechanism, course learning, laser radar partition optimization processing and refined reward setting. The state of the robot is represented by the laser radar data and the gyroscope data after laser radar partition optimization processing. Meanwhile, the state information is used to obtain the corresponding reward value after refined reward setting, and the corresponding experience sequence is stored in the experience pool. The data sampled from the experience pool is used to train the neural network. The application is suitable for robots to perceive the surrounding environment through sensors, plan paths to reach the specified target point or establish an environment map in an unknown environment, and is used for complex tasks such as space exploration, search and rescue and reconnaissance.

The invention discloses a mineral combination analysis method based on Monte Carlo, and relates to the field of mineral analysis, and the method comprises the following steps: multi-source data fusion and preprocessing; constructing a physical model and generating an initial solution; performing multi-scale feature fusion extraction; monte Carlo random sampling and solution space exploration are carried out; performing physical-data dual-drive evaluation and screening; carrying out iterative updating and model optimization; and carrying out convergence judgment and result output. Through multi-source data fusion, a physical-data dual-drive model and a Monte Carlo method, and in combination with multi-scale feature fusion and iterative optimization, the problem of multiplicity of solutions of mineral combination recognition is effectively solved. According to the method, geophysics, geochemistry, remote sensing, drilling core and mineral spectrum data can be integrated, the model is updated through iteration, the most possible mineral combination is gradually converged, uncertainty evaluation is provided, and therefore the accuracy and reliability of mineral recognition are improved.

This invention discloses a lithology identification method based on hybrid mode decomposition and fuzzy entropy-PSO optimization of drilling signals, belonging to the field of integrated deep earth space exploration and drilling geophysical exploration technology. The method first acquires real-time seismic monitoring signals during drilling; then, it uses an empirical and variational hybrid mode decomposition (EVMD) method to decompose the original signal, removing strong noise disturbances; finally, it employs a particle swarm optimization (PSO) algorithm combined with adaptive optimization using fuzzy entropy as the objective function to obtain the optimal parameter combination [K, α] of EVMD, and decomposes it to obtain the optimal modal data and construct a multi-dimensional feature vector, completing the real-time identification and judgment of strata lithology and rock mass structural characteristics. This invention effectively solves the technical problems of traditional methods, such as difficulty in separating strong noise, fixed parameters that cannot be adaptively adapted, mode aliasing, and poor real-time performance. It achieves extremely high lithology identification accuracy and is suitable for deep earth space development, deep resource exploration, and intelligent construction of underground engineering projects.

The application belongs to the technical field of space exploration imaging, and provides an imaging instrument view direction calibration method, comprising the following steps: obtaining a calibration image and identifying a target star point to find a predicted view line pointing center; obtaining a calibration view line pointing center of the imaging instrument in the calibration image and calculating a center pointing error; calculating lens parameters and star point fitting errors of the imaging instrument; generating an azimuth angle grid and an elevation angle grid of the lens view line pointing, and calculating a center pointing error and a star point fitting error of each grid point formed by the azimuth angle grid and the elevation angle grid to form a dispersion matrix and a fitting error matrix respectively; calculating a normalized goodness matrix and determining a lens optimized pointing. The method can realize accurate calibration of the imaging instrument lens pointing and lens parameters without knowing the lens view line center pointing, does not need to consider the lens field of view size, corrects the error caused by the imaging instrument pointing deviation, and improves the measurement accuracy.

1. Name of the design product: non-pneumatic tire. 2. Use of the design product: The product is a non-pneumatic tire which does not need to be inflated during use, and is used for small unmanned exploration vehicles for space exploration, etc. 3. Design points of the design product: in shape. 4. Picture or photograph best indicating the design points: perspective view. 5. The tread pattern of the product is evenly distributed over the entire circumference, and the rear view, top view, bottom view are omitted; the left view is symmetrical with the right view, and the left view is omitted.

This invention discloses a large-model-guided risk scheduling method and system for multi-energy microgrids. First, a physical model of the multi-energy microgrid is constructed and reconstructed as a Markov decision process considering conditional value of risk (CVaR). Second, a dual-timescale deep reinforcement learning architecture integrating large language model inference is built, designing an inner-loop real-time control loop and an outer-loop LLM inference loop. Third, an inference-driven action space exploration mechanism is established, using LLM to achieve directional bias injection and adaptive variance modulation, explicitly guiding the exploration direction and intensity of reinforcement learning. Finally, the CVaR index is integrated into risk-aware exploration and control, iteratively optimizing and outputting the optimal unit output and reserve capacity scheduling scheme. This invention significantly improves the convergence efficiency and sample utilization of reinforcement learning, ensures the economy of the scheduling strategy and its robustness in extreme scenarios, balances the operating cost and risk control of multi-energy microgrids, and possesses strong engineering practicality.

An electronic watch may be provided having functionality for space exploration and / or surface exploration on a terrestrial planet. The watch may comprise a time displaying means and a processor subsystem. The processor subsystem may be configured to maintain a coordinated planetary time of a terrestrial planet, obtain longitudinal data representing a longitude of interest on the terrestrial planet which is different from the planet's prime meridian, determine a local true solar time, LTST, at the longitude of interest as a function of the coordinated planetary time and using an equation of time which accounts for orbital eccentricity and rotational axis tilt of the terrestrial planet, and to control the time displaying means of the electronic watch to display the LTST.

1. Name of the product in this design: Robot (Wide-area closed-chain five-link double-wheel leg). 2. Purpose of this design: As a space exploration device, it is used for the transportation and delivery of materials on the planetary surface, as well as for cleaning solar panels and equipment maintenance. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention discloses a flare prediction method based on multiple deep learning algorithms, and the method comprises the steps: carrying out the data cleaning, processing missing values and abnormal values, dividing a data set, and enhancing the numerical stability of a model through Min-Max normalization. In view of numerous magnetic field features, XGBoost is adopted for feature selection. In order to solve the problem of class imbalance in a data set, minority class samples are generated through SMOTE, majority class samples are reduced through undersampling, and therefore the proportion of positive and negative samples is balanced. And then, respectively inputting the data into 1DCNN, TCN and LSTM models, and fusing prediction results of the three models by using a weighted average method to obtain a final prediction result. According to the method, multiple deep learning technologies are utilized to express sequence data features, more accurate prediction of the solar flare is realized through comprehensive processing, the solar flare prediction efficiency and accuracy are improved, and an important guarantee is provided for space exploration and activities.

The invention belongs to the field of remote sensing satellite system engineering, and relates to a ground large closed-loop test system and method for a space exploration load working mode. A new space exploration load on-orbit working mode is designed according to the characteristics of an observation target, and the interior of the load is designed into a local sky area mode and a window tracking mode; the whole satellite load observation mode is designed into a natural rendezvous monitoring mode, a fixed-point staring monitoring mode, a scanning imaging mode and a target tracking mode; and aiming at a detection load mode, a dynamic star simulator is adopted to simulate an imaging sky area, and a simulated motion fragment target is added into the dynamic star simulator, so that simulation of a real imaging scene is realized. Meanwhile, in order to ensure that the load can successfully match and verify the local star catalogue and the sky area, a normal window tracking mode is switched to, so that the pointing direction corresponding to the sky area simulated by the dynamic star simulator is consistent with the pointing direction of the control broadcast, the on-orbit real working condition and time sequence can be accurately simulated, and the sufficiency of the ground test is improved.

The invention discloses a material iteration exploration method and system based on theories and experiments, and relates to the technical field of experimental scheme generation. According to the material iteration exploration method based on the theory and the experiment, modeling prediction based on initial parameters and optimization instructions is constructed, experimental parameters are screened and recommended in combination with experimental feasibility constraints, resources are scheduled to execute the experiment, data are collected, and data are aligned and analyzed to generate an optimization strategy to feed back and update a complete closed loop of a model. The method breaks the separation barrier of theory and experiment, achieves dynamic cooperation of the theory and experiment, can reduce blind experiments through accurate model prediction and parameter recommendation, improves the pertinence and success rate of the experiment, can continuously improve the prediction precision by means of reverse optimization of experimental data on the model, and finally efficiently compresses the material scientific space exploration period. And the resource loss and the cost investment in the research and development process are obviously reduced.

The application relates to a high-precision micro-nano temperature sensor for near-space detection and belongs to the technical field of temperature measurement. The application adopts a micro-bridge type structure, uses a platinum (Pt) resistance as a temperature measurement sensitive element, and is coated with a radiation-proof plating film on the outer surface of the sensor, and specifically comprises a sensing component, a first electrode, a second electrode, a power supply and a wire; the sensing component comprises a base, an insulating layer, a thermistor and a radiation-proof silver film; the base plays a bearing and external mounting role, the thermistor is attached to the insulating layer which is attached to the base, the thermistor is a platinum film, temperature measurement is realized, the radiation-proof aluminum film is plated on the outer layer, external interference is shielded, and the aluminum film is connected with the wire and the electrode as an electrode. The application has the characteristics of small volume, good resistance linearity, small heat capacity and strong radiation-proof capability, can achieve high measurement precision and very small response time, and solves the problems of temperature precision and response time of near-space detection.

The invention discloses a micro-grid scheduling optimization method and system based on a multi-objective parrot-shaped Arctic pole optimization algorithm, and the method comprises the steps: building a multi-objective optimization scheduling model of a micro-grid, and the multi-objective optimization scheduling model at least comprises an operation maintenance cost objective function and an environment protection cost objective function; a multi-strategy fused multi-target parrot-shaped north pole optimization algorithm is adopted to solve the multi-target optimization scheduling model, and a Pareto optimal solution set is obtained; and determining an optimal output strategy of each distributed power generation unit in the microgrid according to the Pareto optimal solution set. The space exploration capability of the algorithm in the early stage and the optimization precision of the algorithm in the later stage are ensured, and the optimization effect of micro-grid dispatching is improved.

A compact vibratory burrowing probe, particularly beneficial in low gravity space exploration environments, uses lateral or stirring-like vibrations to fluidize a surrounding regolith, thereby decreasing the penetration resistance, and compensating for the light overhead weight to improve the burrowing action of the probe into the surface of the terrain of explored moons, planets, or asteroids. Included is a novel vibratory mechanism capable of imparting the novel lateral or stirring vibration, as well as a more conventionally oriented longitudinal vibration.

To provide a silicone material and a method for producing the same, the material being capable of withstanding temperatures well below -100°C and having a tensile yield strength greater than 3 MPa and an elongation at break exceeding 300%, which are required in many space applications such as space exploration missions.SOLUTION: The invention relates to poly(dimethyl-co-diethyl)siloxane of formula (IIIa), poly(methylhydro-co-diethyl)siloxane, a composition for producing silicone rubber comprising the polymers, a silicone rubber obtainable by curing the composition, and use of the silicone rubber in the aerospace industry.SELECTED DRAWING: None

The invention provides a solar system planet orbit parameter inversion method and system, and belongs to the technical field of astronomical data processing and celestial body orbit calculation, and the method comprises the steps: obtaining the Chebyshev polynomial order and coefficient of a planet; carrying out time normalization processing on a planet position observation moment, and carrying out planet position accurate calculation by adopting Chebyshev polynomial interpolation; estimating the number of initial Kepler orbits; establishing a mathematical model between the planetary position and the Kepler orbital element, constructing an objective function, and performing Jacobian matrix calculation and orbital element solution iterative optimization processing; and performing quadratic polynomial fitting on the multiple groups of Kepler orbit elements to generate Kepler orbit elements in a quadratic polynomial coefficient form. The method is used for meeting the requirement for low calculation amount of medium-precision solar system planetary orbit parameters and planetary positions in the fields of astronomical research, astronomical observation, spaceflight orbit design, space exploration task planning and the like.

The invention discloses a path planning method, device and equipment for underground unknown environment space detection, a medium and a product, and relates to the field of robot autonomous navigation and path planning, the method comprises the following steps: constructing and discretizing a robot dynamic model, and obtaining environment point cloud data and a robot state in real time; on the basis of the environment point cloud data, online fine adjustment is conducted on a unified element learning symbol distance function model obtained through pre-training, the current robot state serves as a starting point, the discrete dynamics model and the current unified element learning symbol distance function model are combined, and an optimal control sequence is solved in a rolling mode through a model prediction control method; and executing the control instruction and updating the state, and circularly executing until the task is completed. According to the method, rapid adaptation and geometric modeling of a new environment are realized by utilizing a meta-learning framework, online optimization is carried out in combination with predictive control, the perception and planning capability of a robot to an unknown irregular underground space is improved, and the adaptability, safety and task completion efficiency of path planning are enhanced.

The application discloses a micro-grid scheduling optimization method and system based on a multi-target arctic sea parrot optimization algorithm, and the method comprises the following steps: establishing a multi-target optimization scheduling model of a micro-grid, wherein at least an operation and maintenance cost target function and an environmental protection cost target function are included in the multi-target optimization scheduling model; solving the multi-target optimization scheduling model by using a multi-strategy fusion multi-target arctic sea parrot optimization algorithm to obtain a Pareto optimal solution set; and determining an optimal output strategy of each distributed power generation unit in the micro-grid according to the Pareto optimal solution set. The algorithm has space exploration ability in the early stage and optimization precision in the later stage, and the optimization effect of micro-grid scheduling is improved.

A method for making a superconducting, electrically conductive solder column that is mechanically compliant and capable of operating at low cryogenic temperatures for quantum computing and AI computing in datacenters and at elevated temperatures for applications found in extraterrestrial space exploration. The solder column can have an indium alloy core and a surface covered by a braided structure comprising a plurality of small diameter niobium wires coated with a thin layer of indium-alloy. The niobium braided structure can limit deformation of the indium alloy core when the solder column structure is subjected to elevated temperatures exceeding a liquidus temperature of the indium alloy core during the coating process and during post-manufacturing operations. The braided niobium wires can limit the deformation of the indium alloy core when the column structure falls below the ductile to brittle transition temperature during exposure to low cryogenic temperatures.

The application belongs to the field of ground mobile robots, and particularly relates to a polygon rolling robot based on composite cam regulation and control, which comprises a planar six-bar mechanism (A), a center driving assembly (B), a first moving guide rod group (C1), a second moving guide rod group (C2), a first cam connecting rod assembly (D1), a second cam connecting rod assembly (D2) and a center cam (E). The polygon rolling robot based on composite cam regulation and control has high structural symmetry, can rely on single-degree-of-freedom driving to realize rolling on unstructured terrain, and adopts the center cam on both sides of the robot to adjust the structural trajectory for realizing high-speed rolling of the robot. The stable and fast moving performance makes the robot applicable to fields such as environmental survey and space exploration, and has a broad prospect.