Sensor Layout Method and System for Large-Size Deployable Antennas

Abstract

The present invention provides a sensor layout method and system for large-sized deployable antennas, including the following steps: establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix; establishing a mathematical model for the optimal configuration of sensors as the objective function; initializing the configured sensors, and simultaneously configuring the sensors through population one and population two to generate two initial populations; establishing a fitness function by mapping the objective function in the above step according to the objective function, evaluating the advantages and disadvantages of individuals through the fitness function, and performing selection and optimization using a multi-population genetic algorithm; evaluating the configuration result to determine whether the optimization criterion is satisfied. The present invention can achieve the optimal sensor layout for on-orbit structural state measurement of large-sized deployable antennas, and meet the goal of maximizing the acquisition of structural state information with limited measurement points.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor layout, and in particular, to a sensor layout method and system for a large-sized deployable antenna. Background Art

[0002] Current satellite platforms generally adopt large-scale and large-area deployable antennas to meet the requirements of high-power and high-resolution missions. However, the space microgravity environment makes it difficult for such large antennas on satellites to maintain the configuration on the ground. At the same time, during on-orbit flight, they are extremely vulnerable to external interference, such as excitation by a torque gyro group, large on-board moving parts, etc., which can cause structural deformation and vibration, affecting the imaging quality. Therefore, dynamic monitoring of the large-sized deployable antenna structure during on-orbit operation is very important.

[0003] The layout of sensors has a great impact on the measurement results. If the number of sensors is too small, some information may be lost, resulting in data deviation; if the number of sensors arranged is too large, too much redundant data will be collected, affecting the process of quickly processing important information, and increasing the weight and energy consumption of the spacecraft. Therefore, in order to obtain the on-orbit structural state of the antenna as comprehensively as possible, it is necessary to optimize the configuration of sensors to meet the goal of maximizing the acquisition of structural state information with limited measurement points. Traditional sensor layout methods are often prone to falling into local optimal solutions and it is difficult to obtain the global optimal solution. Therefore, an advanced optimization algorithm needs to be found for sensor layout.

[0004] The patent document with the publication number CN104992002 discloses a strain sensor layout method for an intelligent skin antenna. Its overall idea is: taking the sensor position and the total number as design variables, the linear weighted sum of the displacement estimation error and the total number of sensors as the objective function, giving the upper bound of the total number of sensors, adding 0-1 topological variables to each position variable, using dual variables to represent the sensor position combination, establishing an optimization model, and simultaneously optimizing the sensor position and the total number. However, this patent document mainly uses the particle swarm algorithm for layout optimization and is not applicable to large-area deployable antennas.

[0005] The patent document with the publication number CN107515980A discloses an optimization layout method for sensors, specifically a two-step sequential strain sensor optimization layout method for structural deformation reconstruction, belonging to the technical field of sensor optimization layout. The two-step sequential strain sensor optimization layout method for structural deformation reconstruction includes: (1) performing column-pivoted QR decomposition on the transposed matrix ΨT of the modal strain matrix corresponding to the candidate layout positions extracted from the finite element model to determine m linearly independent initial sensor layout sets, where m is a positive integer; (2) establishing a reconstruction accuracy criterion and an information redundancy criterion, then establishing a sensor layout optimization model, and continuously optimizing and iterating in a step-by-step cumulative manner to determine the final sensor layout. However, in the finite measurement points, this patent document cannot achieve the goal of maximizing the acquisition of structural state information.

[0006] The patent document with the publication number CN104991982A discloses an aircraft aerodynamic elastic inertial sensor layout method. Based on the finite element method for solving the aircraft structural dynamic response, this method corrects the finite element model through a fluid-structure interaction method, conducts fluid-structure interaction analysis for all flight states and disturbance factors; calculates the relatively accurate structural dynamic response, obtains the response of each node in the finite element model; standardizes the data set to generate an elastic wing structural dynamic response data set; and finally uses the clustering method based on distance metric in pattern recognition to cluster the data and optimize to obtain the final sensor positions. However, this patent document is not applicable to large-area deployable antennas.

[0007] The patent document with the publication number CN102096739B discloses an aircraft fuel quantity measurement sensor layout optimization design method. The present invention comprehensively considers the basic principles of aircraft fuel quantity measurement sensor layout optimization design, and in view of the characteristics of complex modern aircraft fuel tank structures, numerous functional components, and high measurement accuracy requirements, proposes a systematic, comprehensive, and highly versatile fuel quantity measurement sensor layout optimization design method. This method first extracts the fuel tank oil fluid model; secondly, divides, discretizes, and generates the feasible installation lines for the sensor feasible layout areas; thirdly, optimizes the sensor layout with the constraints of non-measurable fuel quantity at the bottom and top; and finally, optimizes the sensor layout according to the measurement continuity and attitude error constraints to obtain the final sensor layout optimization result. However, this patent document still has the defect of being easily trapped in local optimal solutions and difficult to obtain global optimal solutions. Summary of the Invention

[0008] Aiming at the defects in the prior art, the purpose of the present invention is to provide a sensor layout method and system for large-size deployable antennas.

[0009] According to a sensor layout method for large-size deployable antennas provided by the present invention, it includes the following steps:

[0010] Modal matrix construction steps: By establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix;

[0011] Objective function establishment steps: Establish a mathematical model for the optimal configuration of sensors as the objective function;

[0012] Sensor configuration steps: Initialize the configuration of sensors, and simultaneously configure sensors through population one and population two to generate two initial populations;

[0013] Selection and optimization steps: Obtain the fitness function according to the objective function mapping in the objective function establishment steps, evaluate the quality of individuals through the fitness function, and perform selection and optimization using a multi-population genetic algorithm;

[0014] Iterative optimization steps: Evaluate the configuration results to determine whether the optimization criteria are met. If they are met, retain the optimal individual. If not, repeat the selection and optimization steps to continue iterative optimization until the optimization criteria are met, stop the iteration, and output the optimal result.

[0015] Preferably, the sensor layout method for large-sized deployable antennas is applicable to the on-orbit working state of satellites.

[0016] Preferably, the selected initial measuring points avoid interference in the antenna deployment and retraction states.

[0017] Preferably, in the modal matrix construction steps, the extracted effective vibration modes should remove the positions on the antenna where sensors cannot be configured.

[0018] Preferably, in the objective function establishment steps, a mathematical model is established according to the model reduction criterion, modal confidence criterion, and condition number of the vibration mode matrix.

[0019] Preferably, in the sensor configuration steps, the positions where sensors are set are the positions of the maximum stress of the structure.

[0020] Preferably, in the sensor configuration steps, the sensors are evenly arranged on the antenna.

[0021] Preferably, in the sensor configuration steps, the configuration of the sensors is determined by population one representing the sensor measuring points and population two representing the directions of the sensor measuring points, and the two co-evolve.

[0022] Preferably, in the sensor configuration steps, for the two initial populations, population one consists of the solutions of the objective function, and population two consists of the constraints representing the measuring point directions.

[0023] The present invention also provides a sensor layout system for large-sized deployable antennas, including the following modules:

[0024] Modal matrix construction module: By establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix;

[0025] Objective function establishment module: Establish a mathematical model for the optimal configuration of sensors as the objective function;

[0026] Sensor configuration module: Initialize the configuration of sensors, and configure sensors simultaneously through population one and population two to generate two initial populations;

[0027] Selection and optimization module: Obtain the fitness function according to the objective function mapping in the objective function establishment step, evaluate the pros and cons of individuals through the fitness function, and perform selection and optimization using a multi-population genetic algorithm;

[0028] Iterative optimization module: Evaluate the configuration results to determine whether the optimization criteria are met. If so, retain the optimal individual. If not, repeat the selection and optimization steps to continue iterative optimization until the optimization criteria are met, stop the iteration, and output the optimal result.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The present invention selects a multi-population genetic algorithm to optimize the sensor layout, and determines the configured sensors simultaneously by population one and population two, which is convenient for obtaining a better solution;

[0031] 2. The multi-population genetic algorithm in the present invention is an adaptive global optimization probabilistic search algorithm, which is not easily trapped in a local optimal solution, can maximize the acquisition of structural state information among limited measurement points, and reduce the weight and power consumption of the spacecraft;

[0032] 3. The present invention adopts an elite retention strategy in the genetic algorithm, that is, the optimal individual of each generation directly enters the next generation population without crossover and mutation. This strategy ensures that the optimal individual of the next generation population will not be worse than the optimal individual of the current generation, avoiding the loss of measurement point information;

[0033] 4. The present invention can ensure real-time and accurate monitoring of the in-orbit mode of a large deployable antenna under the condition of the best number and reasonable position of the sensor layout. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objectives, and advantages of the present invention will become more obvious:

[0035] Figure 1 It is a flowchart of the sensor layout method for a large deployable antenna according to the present invention;

[0036] Figure 2 It is a flowchart of the sensor layout based on a multi-population genetic algorithm according to the present invention. Detailed implementation manners

[0037] The present invention will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0038] Example 1:

[0039] As Figure 1 shown, a sensor layout method for a large-sized deployable antenna provided in this embodiment includes the following steps:

[0040] Modal matrix construction step: By establishing an antenna model, extracting effective vibration modes, constructing a modal matrix, and the extracted effective vibration modes should remove the positions on the antenna where sensors cannot be configured;

[0041] Objective function establishment step: Establish a mathematical model for the optimal configuration of sensors as the objective function, and establish the mathematical model according to the model reduction criterion, modal confidence criterion, and condition number of the vibration mode matrix;

[0042] Sensor configuration step: Initialize the configured sensors, configure the sensors simultaneously through population one and population two to generate two initial populations. The positions where the sensors are set are the positions of the maximum stress of the structure. The sensors are evenly arranged on the antenna. The configuration of the sensors is determined by population one representing the sensor measurement points and population two representing the measurement point directions of the sensors. The two evolve together. The two initial populations, population one is composed of the solutions of the objective function, and population two is composed of the constraints representing the measurement point directions;

[0043] Selection and optimization step: Obtain the fitness function according to the objective function mapping in the objective function establishment step, evaluate the quality of individuals through the fitness function, and perform selection and optimization using a multi-population genetic algorithm;

[0044] Iterative optimization step: Evaluate the configuration result to determine whether it meets the optimization criterion. If it meets, retain the optimal individual. If it does not meet, repeat the selection and optimization steps to continue iterative optimization until the optimization criterion is met, stop the iteration, and output the optimal result.

[0045] The sensor layout method for a large-sized deployable antenna is applicable to the on-orbit working state of a satellite. The selected initial measurement points avoid interference in the antenna deployment and retraction states.

[0046] Example 2:

[0047] A sensor layout system for large-sized deployable antennas provided in this embodiment includes the following modules:

[0048] Modal matrix construction module: By establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix;

[0049] Objective function establishment module: Establish a mathematical model for the optimal configuration of sensors as the objective function;

[0050] Sensor configuration module: Initialize the configuration of sensors, and configure sensors simultaneously through population one and population two to generate two initial populations;

[0051] Selection and optimization module: Obtain the fitness function according to the objective function mapping in the objective function establishment step, evaluate the quality of individuals through the fitness function, and perform selection and optimization using the multi-population genetic algorithm;

[0052] Iterative optimization module: Evaluate the configuration result, determine whether it meets the optimization criterion. If it meets, retain the optimal individual. If it does not meet, repeat the selection and optimization steps to continue iterative optimization until the optimization criterion is met, stop the iteration, and output the optimal result.

[0053] Example 3:

[0054] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0055] A sensor layout method for large-sized deployable antennas provided in this embodiment includes the following steps:

[0056] Step 1: By establishing an antenna model, extracting effective vibration modes, and constructing a modal matrix;

[0057] Step 2: Establish a mathematical model for the optimal configuration of sensors;

[0058] Step 3: Initialize the configuration of sensors, and configure sensors simultaneously through population one and population two to generate two initial populations;

[0059] Step 4: Obtain the fitness function according to the objective function in Step 2, evaluate the quality of individuals through the fitness function, and perform selection and optimization using the multi-population genetic algorithm;

[0060] Step 5: Evaluate the configuration result, determine whether it meets the optimization criterion. If it meets, retain the optimal individual. If it does not meet, repeat Step 4 to continue iterative optimization until the optimization criterion is met, stop the iteration, and output the optimal result.

[0061] The extracted effective vibration modes should remove the positions on the antenna where sensors cannot be configured, such as motors and hinges.

[0062] Initialize the configuration of the sensors. The selected initial measurement points should be easy to measure and accessible, and the positions with the maximum stress of the structure should be selected and evenly arranged on the antenna as much as possible.

[0063] The configuration of the sensor set is determined by population one representing the sensor measurement points and population two representing the directions of the sensor measurement points, and the two co-evolve.

[0064] The method is applicable to the on-orbit working state of the satellite. The selected initial measurement points should also avoid interference in the antenna deployment and retraction states.

[0065] Example 4:

[0066] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0067] A sensor layout method for a large-sized deployable antenna provided by this embodiment. This method establishes a model of the large-sized deployable antenna, determines the modal order, removes the measurement points that are not suitable for arranging sensors, extracts the effective vibration modes, and constructs the modal matrix; and establishes a mathematical model for the optimal configuration of sensors, evaluates the configuration results using the sensor optimization configuration criteria, and selects and iteratively optimizes using a multi-population genetic algorithm according to the evaluation results to obtain the optimal sensor positions and quantities.

[0068] Such as Figure 1 , a sensor layout method for a large-sized deployable antenna, includes the following steps:

[0069] Step 1: Establish an antenna model, extract the effective vibration modes, and construct the modal matrix Φ;

[0070] Step 2: Establish a mathematical model for the optimal configuration of sensors according to optimization criteria such as the model reduction criterion, the modal confidence criterion, and the condition number of the vibration mode matrix;

[0071] Step 3: Initialize the configuration of the sensors, and configure the sensors simultaneously through population one and population two to generate two initial populations, where one population consists of the solutions of the objective function and the other population consists of the constraints representing the directions of the measurement points;

[0072] Step 4: Obtain the fitness function through the mapping of the objective function. The fitness function is used to evaluate the adaptability of each individual, and the maximum fitness means the optimal individual;

[0073] Step 5: Evaluate the configuration results to determine whether they meet the optimization criteria. If not, use a multi-population genetic algorithm for optimization, form two new populations through selection, crossover, and mutation operations, calculate the fitness again until the optimization criteria are met, stop the iteration, and output the optimal result.

[0074] The extracted effective vibration modes should exclude the positions on the large deployable antenna where sensors cannot be configured, such as at the motors and hinges. Initialize the configuration of sensors. The selected initial measurement points should be easy to measure, accessible, and evenly distributed on the large deployable antenna as much as possible. The method is applicable to the on-orbit working state of the satellite. The selected initial measurement points should also ensure non-interference in both the deployed and retracted states of the large deployable antenna.

[0075] Refer to Figure 2 , the multi-population genetic algorithm used for sensor layout includes the following steps:

[0076] Step SS1, encode the parameter set, and jointly configure the sensor layout through population one representing the sensor measurement points and population two representing the sensor measurement directions. A chromosome consists of n bits in total. The number of each bit represents the number of the sensor measurement point arranged on the antenna, and its range is 1 to n (there are m optional sensor measurement points on the antenna). In this way, a chromosome represents a sensor layout scheme, thereby generating the initial population one and population two of sensors;

[0077] Step SS2, map through the objective function f(x) to obtain the fitness function fit(x), calculate the fitness function, and determine whether the initially selected measurement points meet the optimization criteria. If they meet, retain them. If they do not meet, go to step SS3;

[0078] Step SS3, adopt the method of rotating the roulette wheel to select chromosomes according to the fitness ratio;

[0079] Step SS4, judge whether an individual needs to cross according to the crossover probability Pc. If the random number R generated by the individual > Pc, copy the chromosome. If the random number R generated by the individual < Pc, select the parents for uniform multi-point crossover to generate new chromosomes;

[0080] Step SS5, for the chromosomes after replication or crossover, generate a random number S for each bit. If S < Pm (Pm is the mutation rate), mutate the number at this bit to a random number within the optional range of the sensor. After scanning all bits of all chromosomes, the mutation operation is completed;

[0081] Step SS6, calculate the fitness of the new population one and population two again, and repeat step SS2 until the optimal solution is output.

[0082] A sensor layout method for large-sized deployable antennas provided in this embodiment extracts effective vibration modes through the structural layout characteristics of the large-sized deployable antennas of satellites, constructs a modal matrix, and uses a multi-population genetic algorithm to iteratively optimize the number and positions of sensors simultaneously to determine the optimal layout of the measurement points on the antenna structure. It solves the problem of finding the globally optimal measurement points, avoids the loss of measurement point information, and at the same time ensures that the state information of the antenna structure is maximally collected among the limited measurement points and meets the requirements of spacecraft payload lightweighting.

[0083] The present invention can achieve the optimal sensor arrangement for on-orbit structural state measurement of large-sized deployable antennas, meeting the goal of maximizing the collection of structural state information among the limited measurement points.

[0084] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as either software modules for implementing the method or the structures within the hardware component.

[0085] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific implementation manners, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

Claims

1. A sensor layout method for large-sized deployable antennas, characterized in that It includes the following steps: Modal matrix construction step: By establishing an antenna model, extracting the effective vibration modes, and constructing the modal matrix; Objective function establishment step: Establishing a mathematical model for the optimal sensor configuration as the objective function; Sensor configuration step: Initializing the configured sensors, and simultaneously configuring the sensors through population one and population two to generate two initial populations; Selection and optimization step: Obtaining the fitness function according to the objective function mapping in the objective function establishment step, evaluating the quality of individuals through the fitness function, and using the multi-population genetic algorithm for selection and optimization; Iterative optimization step: Evaluating the configuration result to determine whether it meets the optimization criterion. If it meets, retain the optimal individual. If it does not meet, repeat the selection and optimization steps to continue iterative optimization until the optimization criterion is met, stop the iteration, and output the optimal result; The selected initial measurement points avoid interference in the antenna deployment and retraction states; In the modal matrix construction step, the positions on the antenna where sensors cannot be configured should be removed from the extracted effective vibration modes; In the objective function establishment step, a mathematical model is established according to the model reduction criterion, modal confidence criterion, and condition number of the vibration mode matrix; In the sensor configuration step, the positions where the sensors are set are the positions of the maximum stress of the structure; In the sensor configuration step, the configuration of the sensors is determined by population one representing the sensor measurement points and population two representing the directions of the sensor measurement points, and the two evolve together; In the sensor configuration step, for the two initial populations, population one consists of the solutions of the objective function, and population two consists of the constraints representing the measurement point directions; 2. The sensor layout method for large-sized deployable antennas according to claim 1, wherein The sensor layout method for large-sized deployable antennas is applicable to the in-orbit working state of satellites; 3. The sensor layout method for large-sized deployable antennas according to claim 1, wherein In the sensor configuration step, the sensors are evenly arranged on the antenna.

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