Optimization Design Method and Device of Infrared Lamp Array for Spacecraft Thermal Test

Abstract

The present invention provides an optimized design method, system, device and computer-readable medium for an infrared lamp array used in spacecraft thermal tests. The method includes: constructing an initial infrared lamp array, the initial infrared lamp array including m rows and n columns, with a row spacing between adjacent infrared lamps in each row and a column spacing between adjacent infrared lamps in each column, and each infrared lamp having a height from the irradiated surface, where m and n are positive integers greater than or equal to 1; and performing optimized iterative calculations on the row spacing, the column spacing and the height by using a first optimization algorithm, the objective function of the first optimization algorithm including the non-uniformity of the heat flux distribution of the infrared lamp array, and the condition for stopping the iteration including that the non-uniformity of the heat flux distribution is less than a first target value. This method has a fast calculation speed and improves the efficiency of the optimized design.

Description

Technical Field

[0001] The present invention mainly relates to the field of spacecrafts, and particularly to an optimized design method, system, device and computer-readable medium for an infrared lamp array used in spacecraft thermal tests. Background Art

[0002] An infrared lamp array is a commonly used external heat flux simulation device. Because of its flexible use, less occlusion of the spacecraft surface, and the ability to be reused, it is widely used in spacecraft vacuum thermal tests. The heat flux uniformity of the infrared lamp array is an important index for evaluating its design quality. Poor heat flux uniformity will affect the results of the vacuum thermal test, reduce the accuracy of the thermal test, and even affect the thermal design of the spacecraft, causing economic losses.

[0003] When conducting spacecraft thermal tests, the traditional lamp array design is to design the position and height of the lamp array according to experience, and appropriately adjust the layout of the lamp array according to the measured heat flux uniformity. This is not only time-consuming and laborious, but also difficult to meet the standard of heat flux non-uniformity. In some cases, in order to improve the heat flux uniformity, heating sheets are used to simulate the external heat flux. Although the requirement of heat flux uniformity can be met, it will damage the physical properties of the spacecraft surface and is not suitable for the thermal test of the flight model. Moreover, the cost of the heating sheets is high and they can only be used once, which greatly increases the thermal test cost and the time cost of thermal modification.

[0004] Currently, the research on the uniformity of infrared lamp arrays generally uses genetic algorithms to optimize the existing infrared lamp arrays, which requires an initial array design as the basis. And these studies only consider the basic rectangular heat dissipation surface (the irradiated surface), and do not study other shaped heat dissipation surfaces. In addition, although genetic algorithms are good at finding the global optimal solution, they have a slow convergence speed and a long running time, and do not have advantages in practical engineering applications. The design method that completely relies on mathematical calculations also ignores the guiding role of engineering experience in lamp array design. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an optimized design method, device and computer-readable medium for an infrared lamp array used in spacecraft thermal tests that can quickly obtain optimized results.

[0006] To solve the above technical problems, the present invention provides an optimization design method for an infrared lamp array used in spacecraft thermal tests, including: constructing an initial infrared lamp array, where the initial infrared lamp array includes m rows and n columns, there is a row spacing between adjacent infrared lamps in each row, there is a column spacing between adjacent infrared lamps in each column, and each infrared lamp has a height from the irradiated surface, and both m and n are positive integers greater than or equal to 1; and using a first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height, where the objective function of the first optimization algorithm includes the non-uniformity of the heat flux distribution of the infrared lamp array, and the condition for stopping the iteration includes that the non-uniformity of the heat flux distribution is less than a first target value.

[0007] In an embodiment of the present application, the constraint conditions of the first optimization algorithm include that the row spacing and the column spacing gradually decrease from the center of the infrared lamp array to the periphery, and the height gradually decreases from the center of the infrared lamp array to the periphery.

[0008] In an embodiment of the present application, in the step of constructing the initial infrared lamp array, it further includes: setting an initial row spacing of the row spacing and an initial column spacing of the column spacing based on engineering experience.

[0009] In an embodiment of the present application, the first optimization algorithm includes a particle swarm optimization algorithm.

[0010] In an embodiment of the present application, in the step of using the first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height, it further includes: setting a row spacing limit, a column spacing limit, and / or a height limit; determining whether the row spacing exceeds the row spacing limit, determining whether the column spacing exceeds the column spacing limit, and / or determining whether the height exceeds the height limit; when it exceeds, making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit.

[0011] In an embodiment of the present application, the step of making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit includes:

[0012] When x > x max then make x = 2 * x max - x;

[0013] When x < x min then make x = 2 * x min - x;

[0014] where x represents the row spacing, the column spacing, or the height, x min , x maxrespectively represent the maximum and minimum values among the row spacing limit, the column spacing limit, or the height limit.

[0015] In an embodiment of the present application, in the step of performing optimization iteration calculations on the row spacing, the column spacing, and the height by using the first optimization algorithm, it further includes: when the number of iterations is greater than a preset threshold and the non-uniformity of the heat flux distribution is not less than the first target value, reconstructing the initial infrared lamp array into a second infrared lamp array, the area of the second infrared lamp array being equal to that of the initial infrared lamp array, the second infrared lamp array including m + 1 rows and n columns, or the second infrared lamp array including m rows and n + 1 columns.

[0016] In an embodiment of the present application, it further includes: dividing the irradiated surface in the spacecraft thermal test into a plurality of rectangular basic irradiated surfaces, and constructing the initial infrared lamp array for the rectangular basic irradiated surfaces.

[0017] In an embodiment of the present application, it further includes: dividing the initial infrared lamp array into four quadrants, and the step of performing optimization iteration calculations on the row spacing, the column spacing, and the height by using the first optimization algorithm includes: selecting one of the four quadrants as the target quadrant, and performing optimization iteration calculations on the row spacing, the column spacing, and the height of the infrared lamps in the target quadrant.

[0018] In an embodiment of the present application, the shape of the irradiated surface includes any one or a combination of more than one of rectangle, L shape, concave shape, and convex shape.

[0019] In an embodiment of the present application, it further includes: sequentially constructing the initial infrared lamp array for each of the rectangular basic irradiated surfaces, and performing optimization iteration calculations on the row spacing, the column spacing, and the height by using the first optimization algorithm; obtaining the total heat flux distribution non-uniformity according to the heat flux distribution non-uniformity of each rectangular basic irradiated surface; performing optimization iteration calculations on the current parameters of each rectangular basic irradiated surface by using the second optimization algorithm, and the condition for stopping the iteration includes that the total heat flux distribution non-uniformity is less than the second target value.

[0020] The present application also provides an optimized design system for an infrared lamp array used in spacecraft thermal tests to solve the above technical problems. The system includes: a lamp array construction module for constructing an initial infrared lamp array, where the initial infrared lamp array includes m rows and n columns. There is a row spacing between adjacent infrared lamps in each row, a column spacing between adjacent infrared lamps in each column, and each infrared lamp has a height from the irradiated surface. Both m and n are positive integers greater than or equal to 1; a lamp array uniformity optimization module for performing optimized iterative calculations on the row spacing, the column spacing, and the height using a first optimization algorithm. The objective function of the first optimization algorithm includes the non-uniformity of the heat flux distribution of the infrared lamp array, and the condition for stopping iteration includes that the non-uniformity of the heat flux distribution is less than a first target value.

[0021] In an embodiment of the present application, it further includes a visualization module for displaying the heat flux distribution of the initial infrared lamp array.

[0022] The present application also provides an optimized design device for an infrared lamp array used in spacecraft thermal tests to solve the above technical problems. The device includes: a memory for storing instructions executable by a processor; a processor for executing the instructions to implement the method as described above.

[0023] The present application also provides a computer-readable medium storing computer program code, and the computer program code implements the method as described above when executed by a processor.

[0024] The optimized design method, system, and device for the infrared lamp array used in spacecraft thermal tests of the present application take the row spacing, column spacing, and height of the infrared lamp array as optimization parameters, and use an optimization algorithm to optimize these optimization parameters, so as to quickly obtain an optimization result; by setting constraint conditions to constrain the row spacing, column spacing, and height, the convergence speed of the optimization algorithm is further accelerated; and when constructing the initial infrared lamp array, the initial row spacing and initial column spacing are set based on engineering experience, giving play to the guiding role of engineering experience, further accelerating the convergence speed of the optimization algorithm, and improving the calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings are provided to provide a further understanding of the present application, and they are incorporated into and constitute a part of this application. The drawings illustrate embodiments of the present application and, together with this specification, serve to explain the principles of the present invention. In the drawings:

[0026] Figure 1 is an exemplary flowchart of the optimized design method for an infrared lamp array used in spacecraft thermal tests according to an embodiment of the present application;

[0027] Figure 2 is a schematic structural diagram of the initial infrared lamp array in the optimized design method for an infrared lamp array used in spacecraft thermal tests according to an embodiment of the present application;

[0028] Figure 3 and Figure 4 is a schematic diagram showing the division of an initial infrared lamp array into four quadrants according to an optimization design method of an embodiment of the present application;

[0029] Figure 5 is a schematic diagram showing the setting of constraint conditions according to an optimization design method of an embodiment of the present application;

[0030] Figures 6A - 6F is a schematic diagram showing different shapes of the illuminated surface and its segmentation methods in an optimization design method of an embodiment of the present application;

[0031] Figure 7 is an exemplary flowchart of an optimization design method for an infrared lamp array for spacecraft thermal tests according to another embodiment of the present application;

[0032] Figure 8 is a block diagram of an optimization design system for an infrared lamp array for spacecraft thermal tests according to an embodiment of the present application;

[0033] Figure 9A is a schematic diagram of the optimized position of the infrared lamp array obtained according to an optimization design method of an embodiment of the present application;

[0034] Figure 9B is a heat flux distribution diagram of the optimized infrared lamp array obtained according to an optimization design method of an embodiment of the present application;

[0035] Figure 9C is a schematic diagram comparing the optimization results of an optimization design method of an embodiment of the present application and other methods;

[0036] Figure 10 is a system block diagram of an optimization design device for an infrared lamp array for spacecraft thermal tests according to an embodiment of the present invention. Detailed implementation manners

[0037] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some examples or embodiments of the present application. For those of ordinary skill in the art, without creative efforts, the present application can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structures or operations.

[0038] As shown in this application and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0039] Unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps described in these embodiments do not limit the scope of this application. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn according to the actual proportional relationship. Technologies, methods, and devices known to those of ordinary skill in the relevant field may not be discussed in detail, but in appropriate cases, the said technologies, methods, and devices should be regarded as part of the authorization specification. In all the examples shown and discussed here, any specific value should be interpreted as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that: similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0040] In the description of this application, it should be understood that the orientation or positional relationships indicated by orientation words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal", and "top, bottom" are usually based on the orientation or positional relationships shown in the drawings. It is only for the convenience of describing this application and simplifying the description. Without contrary instructions, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the protection scope of this application; the orientation words "inside, outside" refer to the inside and outside relative to the contour of each component itself.

[0041] For ease of description, spatial relative terms, such as "above", "over", "on the upper surface", "upper", etc., may be used herein to describe the spatial positional relationship of one device or feature to other devices or features as shown in the figures. It should be understood that the spatial relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, a device described as "above" or "over" other devices or structures will then be positioned "below" or "under" the other devices or structures. Thus, the exemplary term "above" can include both orientations of "above" and "below". The device may also be positioned in other different ways (rotated 90 degrees or at other orientations), and the corresponding explanations for the spatial relative descriptions used herein will be made accordingly.

[0042] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of differentiating the corresponding components. Without further statement, the above terms have no special meaning and thus should not be construed as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some of the terms mentioned in the specification of this application may be selected by the applicant according to his or her judgment, and their detailed meanings are described in the relevant parts of this description. In addition, it is required to understand this application not only through the actual terms used, but also through the meaning implied by each term.

[0043] Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the operations before or below do not necessarily need to be executed precisely in sequence. On the contrary, they can be executed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or one or several operations may be removed from these processes.

[0044] Figure 1 is an exemplary flowchart of an optimization design method for an infrared lamp array for spacecraft thermal tests according to an embodiment of this application. Refer to Figure 1 As shown, the optimization design method of this embodiment includes the following steps:

[0045] Step S110: Construct an initial infrared lamp array. The initial infrared lamp array includes m rows and n columns. There is a row spacing between adjacent infrared lamps in each row, and a column spacing between adjacent infrared lamps in each column. Each infrared lamp has a height from the irradiated surface. Both m and n are positive integers greater than or equal to 1; and

[0046] Step S120: Use the first optimization algorithm to perform iterative calculations on the row spacing, column spacing, and height. The objective function of the first optimization algorithm includes the non-uniformity of the heat flux distribution of the infrared lamp array, and the condition for stopping the iteration includes that the non-uniformity of the heat flux distribution is less than the first target value.

[0047] The above steps S110 - S120 will be described below with reference to the accompanying drawings.

[0048] In step S110, in order to obtain an optimized infrared lamp array, an initial infrared lamp array is first constructed. In the spacecraft thermal test, the non-uniformity of the heat flux distribution is used to evaluate the design quality of the infrared lamp array. For example, when the non-uniformity of the heat flux distribution of the infrared lamp array is less than a certain first target value, it means that the infrared lamp array is suitable for the spacecraft thermal test. It can be understood that the initial infrared lamp array has not been optimized, and its non-uniformity of the heat flux distribution can be greater than the first target value. Therefore, it is expected to adjust the initial infrared lamp array through optimization so that its non-uniformity of the heat flux distribution reaches the first target value.

[0049] In some embodiments, the first target value is 10%.

[0050] In step S110, the initial infrared lamp array includes m rows and n columns. The specific values of m and n are not limited in this application.

[0051] Figure 2 is a schematic structural diagram of the initial infrared lamp array in an optimization design method of an infrared lamp array for spacecraft thermal tests according to an embodiment of the present application. Refer to Figure 2 shown. Each infrared lamp 210 is represented by a circle. An infrared lamp array composed of 7 rows and 6 columns of infrared lamps is formed as shown in Figure 2 shown. As shown in Figure 2 shown, this infrared lamp array is located in the XY coordinate system, the rows are parallel to the X-axis, the columns are parallel to the Y-axis, the contour of the infrared lamp array is rectangular, and there is a row spacing △x between adjacent infrared lamps in each row, and a column spacing △y between adjacent infrared lamps in each column. Figure 2 The spacing is marked with a straight line with a double-headed arrow in Figure 2 and is not used to limit the actual spacing measurement method. In some embodiments, the spacing is calculated according to the position coordinates of each infrared lamp, such as

[0052] Figure 2 shown, the position coordinates of the center of the circle 210.

[0053] Although only one row spacing △x and one column spacing △y are marked in Figure 2 , when constructing the initial infrared lamp array in step S110, the row spacings in each row can be different, and the column spacings in each column can be different.

[0054] In some embodiments, the line spacing in each row is equal.

[0055] In some embodiments, the column spacing in each column is equal.

[0056] In some embodiments, in step S110, the initial line spacing of the line spacing and the initial column spacing of the column spacing are set based on engineering experience. In some embodiments, the range of the initial line spacing and the initial column spacing is 0.3 - 0.6 meters.

[0057] In some embodiments, the initial line spacing is equal to the initial column spacing. In some embodiments, both the initial line spacing and the initial column spacing are equal to 0.38 meters.

[0058] The height of the infrared lamp from the illuminated surface refers to the distance between the infrared lamp and the illuminated surface. The lower the height, the closer the infrared lamp is to the illuminated surface, and the higher the average heat flux of the illuminated surface; the higher the height, the farther the infrared lamp is from the illuminated surface, and the lower the average heat flux of the illuminated surface.

[0059] In step S120 of the present application, an optimization algorithm is used to optimize the height, line spacing, column spacing, etc. of each infrared lamp in the infrared lamp array to obtain a uniform heat flux distribution.

[0060] According to the traditional calculation method, only the position parameters of the infrared lamps are used as optimization parameters, rather than the spacing between the infrared lamps. However, what actually affects the non-uniformity of the heat flux distribution of the infrared lamp array is the spacing between the infrared lamps. Once the positions of the lamps are changed during each update iteration of the algorithm, the spacing parameters will also change accordingly, resulting in a lot of computational redundancy. The present application uses the line spacing and column spacing as optimization parameters, which can reduce this computational redundancy.

[0061] The first optimization algorithm in step S120 can be any optimization algorithm.

[0062] In some embodiments, the first optimization algorithm includes a particle swarm optimization algorithm. The particle swarm algorithm is a very simple optimization algorithm. The number of parameters to be adjusted in a single calculation is small, and each particle "learns by itself" and "learns from each other" at the same time, and the calculation speed is very fast.

[0063] In step S120, the optimization parameters of the first optimization algorithm include the line spacing, column spacing, and height of the initial infrared lamp array.

[0064] In step S120, the non-uniformity of the heat flux distribution can be calculated or estimated based on the line spacing, column spacing, and height.

[0065] In some embodiments, the non-uniformity of the heat flux distribution can be obtained based on the existing heat flux distribution database.

[0066] In some embodiments, before step S110 of the present application, the Monte Carlo method is used to calculate the radiant heat flux distribution of a single infrared lamp at different heights, so as to obtain a database of the radiant heat flux distribution of a single infrared lamp. In some embodiments, the range of these different heights is 0.3 - 0.6 meters, and the calculation step size is 0.01 meters. According to these embodiments, in step S120, the non-uniformity of the heat flux distribution corresponding thereto can be obtained or estimated from the database according to the row spacing, column spacing, and height of the infrared lamp. For example, according to the current row spacing, column spacing, and height of the infrared lamp, the radiant heat flux distribution of each single lamp can be obtained, so as to calculate the non-uniformity of the heat flux distribution of the infrared lamp array. If there is no corresponding row spacing, column spacing, and height in the database, the radiant heat flux distribution of each single lamp in the infrared lamp array can be estimated by methods such as linear interpolation, so as to obtain the non-uniformity of the heat flux distribution.

[0067] In some embodiments, in the step of performing optimization iteration calculation on the row spacing, column spacing, and height by using the first optimization algorithm in step S120, it further includes: setting a row spacing limit, a column spacing limit, and / or a height limit; determining whether the row spacing exceeds the row spacing limit, determining whether the column spacing exceeds the column spacing limit, and / or determining whether the height exceeds the height limit; when it exceeds, making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit.

[0068] It can be understood that in the optimization iteration algorithm, in one iteration, the row spacing, column spacing, and height are optimized and calculated to obtain the optimized row spacing, column spacing, and height. In order to accelerate the convergence speed of the optimization algorithm, corresponding limits are set for the row spacing, column spacing, and / or height in these embodiments, which helps to quickly complete the optimization algorithm.

[0069] In some embodiments, a row spacing limit is set, and it is determined whether the row spacing exceeds the row spacing limit. When it exceeds, the row spacing is made within the row spacing limit.

[0070] In some embodiments, a column spacing limit is set, and it is determined whether the column spacing exceeds the column spacing limit. When it exceeds, the column spacing is made within the column spacing limit.

[0071] In some embodiments, a height limit is set, and it is determined whether the height exceeds the height limit. When it exceeds, the height is made within the height limit.

[0072] In some embodiments, a row spacing limit and a column spacing limit are set, and at the same time, it is determined whether the row spacing and the column spacing exceed their limits. When any one of them exceeds, it is made to return to the corresponding limit.

[0073] In some embodiments, a row spacing limit, a column spacing limit, and a height limit are set, and at the same time, it is determined whether the row spacing, the column spacing, and the height exceed their limits. When any one of them exceeds, it is made to return within the corresponding limit.

[0074] In some embodiments, the steps of making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit include:

[0075] When x > x max , make x = 2 * x max - x;

[0076] When x < x min , make x = 2 * x min - x;

[0077] Wherein, x represents the row spacing, the column spacing, or the height, and x min , x max respectively represent the maximum value and the minimum value among the row spacing limit, the column spacing limit, or the height limit.

[0078] In some embodiments, the optimization design method of the present application further includes: dividing the initial infrared lamp array into four quadrants, and the steps of performing optimization iterative calculation on the row spacing, the column spacing, and the height by using the first optimization algorithm include: selecting one of the four quadrants as the target quadrant, and performing optimization iterative calculation on the row spacing, the column spacing, and the height of the infrared lamps in the target quadrant.

[0079] Figure 3 And Figure 4 are schematic diagrams of dividing the initial infrared lamp array into four quadrants according to the optimization design method of an embodiment of the present application. Figure 3 For representing the initial infrared lamp array with the number of rows m and the number of columns n being even, Figure 4 For representing the initial infrared lamp array with the number of rows m or the number of columns n being odd.

[0080] Refer to Figure 3 shown, which includes 4 * 4 = 16 infrared lamps. When both m and n are even, this infrared lamp array has an axisymmetric structure, including symmetry about the X-axis and symmetry about the Y-axis. The number of infrared lamps in each quadrant is equal, as Figure 3 shown, which is 4. Figure 3 The target quadrant 310 selected is circled by the dashed square frame in

[0081] Refer to Figure 4 shown, which includes 3 * 3 = 9 infrared lamps. When at least one of m or n is odd, the number of infrared lamps included in the four quadrants into which this infrared lamp array is divided is not completely equal. AsFigure 4 As shown, the selected target quadrant 410 is circled by a dashed box, which is the upper right quadrant among the four quadrants of this infrared lamp array, and includes 4 infrared lamps.

[0082] According to these embodiments, the target quadrant can be used to represent this infrared lamp array. Only the row pitch, column pitch, and height of the infrared lamps in the target quadrant are used for optimization calculation, and based on the symmetry of the lamp array, the obtained optimization results are applied to the other four quadrants, further reducing the time of the optimization design method and improving the optimization speed.

[0083] In some embodiments, the constraint conditions of the first optimization algorithm in step S120 include that the row pitch and column pitch gradually decrease from the center of the infrared lamp array to the periphery, and the height gradually decreases from the center of the infrared lamp array to the periphery. For a uniformly distributed infrared lamp array, there will be a phenomenon that the central heat flux is high and the peripheral heat flux is low. In order to make the heat flux distribution more uniform, the distribution of the infrared lamp array located in the center can be made relatively sparse, that is, having a larger pitch, and the distribution of the infrared lamp array located in the periphery can be made relatively dense, that is, having a smaller pitch. The present application adds the above constraint conditions to the first optimization algorithm, making the rules more reasonable, which can accelerate the convergence speed of the algorithm and the calculation is not easily trapped in a local optimum.

[0084] Figure 5 It is a schematic diagram of setting constraint conditions according to the optimization design method of an embodiment of the present application. Figure 5 Taking a 6*6 infrared lamp array as an example and combining the previous example, this infrared lamp array is divided into four quadrants, and 3*3 infrared lamps in the upper right quadrant 510 are taken as the initial infrared lamp array. Since the quadrant 510 is located in the upper right corner of this infrared lamp array, its left and lower sides are close to the center of the infrared lamp array, and its upper right side is close to the periphery of the infrared lamp array. Therefore, the column pitches along the X-axis are Δx1, Δx2, Δx3 from the center to the periphery respectively, and the row pitches along the Y-axis are Δy1, Δy2, Δy3 from the center to the periphery respectively, where the magnitudes of the row pitch and column pitch satisfy the relationship defined by the following formula (1):

[0085]

[0086] Each infrared lamp in the quadrant 510 has a height h ij , i = 1 - 3, j = 1 - 3, and is represented by the following matrix (2):

[0087]

[0088] Combined with Figure 5 , h 11 corresponds to Figure 5 the infrared lamp 521 in 33Corresponding to the infrared lamp 522, and so on. According to the above constraints, the height h ij satisfies the relationship defined by the following formula (3):

[0089]

[0090] In some embodiments, the optimization design method of the present application further includes: dividing the irradiated surface in the spacecraft thermal test into a plurality of rectangular basic irradiated surfaces, and constructing an initial infrared lamp array for the rectangular basic irradiated surfaces. The present application does not limit the size and shape of the irradiated surface. In some cases, if the irradiated surface itself is rectangular, the initial infrared lamp can be directly constructed according to the irradiated surface, or a larger rectangular irradiated surface can be divided into a plurality of smaller rectangular basic irradiated surfaces, and the plurality of smaller rectangular basic irradiated surfaces can be equal or unequal. When the areas of the plurality of smaller rectangular basic irradiated surfaces are equal, an initial infrared lamp array is constructed for one of them, and the optimization parameters can be quickly obtained according to the optimization design method of the present application.

[0091] In some embodiments, the shape of the irradiated surface includes any one or a combination of more than one of rectangle, L-shape, concave shape, and convex shape.

[0092] Figures 6A - 6F are schematic diagrams of different shapes of the irradiated surface and its division methods in the optimization design method of an embodiment of the present application. Figures 6A - 6F The viewing angles of are all front views of the satellite surface. Among them, Figure 6A and 6B represent the L-shaped irradiated surface, Figure 6A is before division, Figure 6B is after division, where the division line is indicated by a dashed line. After division, the L-shaped irradiated surface 610 is divided into two parts 611 and 612. Figure 6C and 6D represent the concave-shaped irradiated surface, Figure 6C is before division, Figure 6D is after division, where the division line is indicated by a dashed line. After division, the concave-shaped irradiated surface 620 is divided into three parts 621, 622, and 623. Figure 6E and 6F represent the convex-shaped irradiated surface, Figure 6E is before division, Figure 6F is after division, where the division line is indicated by a dashed line. After division, the convex-shaped irradiated surface 630 is divided into two parts 631 and 632.

[0093] Figures 6A - 6F is only an example and is not used to limit the specific shape of the irradiated surface, the specific division method, and the number of parts into which it is divided. In some embodiments, for example, Figure 6FEach part 631, 632 in it can also be divided into multiple small rectangles, and each small rectangle is used as a basic rectangle being illuminated.

[0094] In some embodiments, step S110 further includes: determining the number of rows and columns according to the area of the basic rectangle being illuminated. For example, assuming the length of the basic rectangle being illuminated is L and the width is W, and the initial row spacing and initial column spacing determined in combination with engineering experience, the number of rows m and columns n of the initial infrared lamp array can be calculated.

[0095] In some embodiments, in the step of performing optimization iteration calculations on the row spacing, column spacing, and height using the first optimization algorithm, it further includes: when the number of iterations is greater than a preset threshold and the non-uniformity of the heat flux distribution is not less than a first target value, reconstructing the initial infrared lamp array into a second infrared lamp array, the area of the second infrared lamp array being equal to that of the initial infrared lamp array, the second infrared lamp array including m + 1 rows and n columns, or the second infrared lamp array including m rows and n + 1 columns. In these embodiments, a preset threshold is usually set as the maximum value of the number of iterations. For example, the preset threshold is 100. When the number of iterations reaches 100 times, according to the first optimization algorithm in step S120, the non-uniformity of the heat flux distribution is still greater than the first target value, that is, the first optimization algorithm does not meet the condition for stopping iteration. At this time, reconstruct an initial infrared lamp array, increasing the number of rows or columns by 1 on the basis of the original initial infrared lamp array. And on this basis, make all the infrared lamps in the second infrared lamp array evenly distributed, that is, the initial row spacing and initial column spacing in the second infrared lamp array both become smaller.

[0096] In some embodiments, the optimization design method of the present application further includes:

[0097] Step S130: Sequentially construct an initial infrared lamp array for each basic rectangle being illuminated, and perform optimization iteration calculations on the row spacing, column spacing, and height using the first optimization algorithm;

[0098] Step S132: Obtain the total non-uniformity of the heat flux distribution according to the non-uniformity of the heat flux distribution of each basic rectangle being illuminated;

[0099] Step S134: Perform optimization iteration calculations on the current parameters of each basic rectangle being illuminated using the second optimization algorithm, and the conditions for stopping iteration include that the total non-uniformity of the heat flux distribution is less than a second target value.

[0100] In the above step S130, when the areas of each basic rectangle being illuminated are equal, there is no need to repeatedly construct the initial infrared lamp array, but use the optimization result of one of the basic rectangles being illuminated as the result of other basic rectangles being illuminated to achieve result reuse.

[0101] The optimal parameters such as the row spacing, column spacing, and height of all the infrared lamps in the irradiated surface have been obtained through step S130. However, for the segmented irradiated surface, after combining the segmented parts, the overall total heat flux distribution non-uniformity may not be optimal. Therefore, steps S132 - S134 are adopted to optimize the overall total heat flux distribution non-uniformity.

[0102] In step S132, the non-uniformity of the heat flux distribution of each rectangular basic irradiated surface can be superimposed to obtain the total heat flux distribution non-uniformity.

[0103] Steps S110 - S120 can be implemented when the current parameters provided to each infrared lamp are the same. Different current parameters may affect the heat flux distribution.

[0104] In some cases, the current parameters of the infrared lamps located at different positions in the infrared lamp array can be controlled separately. For example, as Figure 5 shown, the first current parameter can be provided to the 3 * 3 infrared lamps in quadrant 510, and other current parameters can be provided to the infrared lamps in other quadrants. For example, as Figures 6A - 6F shown, different current parameters can be provided to the infrared lamps in different rectangular basic irradiated surfaces that are segmented out.

[0105] In step S134, the second optimization algorithm can be the same as or different from the first optimization algorithm. In the second optimization algorithm, the current parameters are used as the optimization parameters. After multiple iterations, the optimal current parameters are obtained. The optimal current parameters can be a matrix of current parameters for different infrared lamps, which includes multiple current parameters. When the optimal current parameters are applied to each infrared lamp, the total heat flux distribution non-uniformity is made less than the second target value.

[0106] In step S134, the second target value can be the same as or different from the first target value. In some embodiments, the second target value is 10%.

[0107] Figure 7 is an exemplary flowchart of an optimization design method for an infrared lamp array used in a spacecraft thermal test in another embodiment of the present application. Among them, multiple steps are related to steps S110 - S120 of the Figure 1 shown embodiment. Reference can be made to the foregoing drawings and description content, and the same content will not be elaborated again.

[0108] Refer to Figure 7 shown. The optimization design method of this embodiment includes the following steps:

[0109] Step S710: Divide the irradiated surface into q rectangular basic irradiated surfaces.

[0110] Step S712: Initialize the number of rows and columns of the lamp array, initialize the lamp array position parameters, and calculate the initial non-uniformity of the heat flux distribution. In this step, the lamp array can be the initial infrared lamp array in Step S110, with the initialized number of rows being m and the number of columns being n. The initialization of the lamp array position parameters can be the initial row spacing and initial column spacing set based on engineering experience, as well as the height of each infrared lamp. And calculate the initial non-uniformity of the heat flux distribution based on these initial parameters.

[0111] Step S714: Use the Particle Swarm Optimization (PSO) algorithm to optimize the row spacing, column spacing, and height, and calculate the non-uniformity of the heat flux distribution δ.

[0112] Step S716: Judge whether δ < the first target value? If yes, execute Step S722; if not, execute Step S718.

[0113] Step S718: Judge whether the number of iterations < the preset threshold? If yes, execute Step S714; if not, return to Step S720.

[0114] Step S720: Increment the number of rows or columns of the lamp array by 1, and then continue to execute Step S714.

[0115] In some embodiments, Steps S710 - S720 are a complete process. When the judgment result of Step S716 is yes, instead of executing Step S722, the row spacing, column spacing, and height calculated in the current iteration are output as the optimization result, and the entire process ends.

[0116] Step S722: Calculate the total non-uniformity of the heat flux distribution Σδ of q rectangular basic illuminated surfaces.

[0117] Step S724: Use PSO to optimize the current parameters of the lamp arrays for each rectangular basic illuminated surface, and calculate the total non-uniformity of the heat flux distribution Σδ.

[0118] The lamp array for the rectangular basic illuminated surface here refers to the infrared lamp array corresponding to each rectangular basic illuminated surface. For different rectangular basic illuminated surfaces, the current parameters of their infrared lamp arrays can be the same or different.

[0119] Step S726: Judge whether Σδ < the second target value? If yes, execute Step S728; if not, execute Step S724.

[0120] Step S728: Output the optimization parameters. The optimization parameters here include the optimal row spacing, column spacing, and height obtained after Step S716, as well as the optimal current parameters of the lamp arrays for each rectangular basic illuminated surface obtained after Step S726.

[0121] Figure 8It is a block diagram of an optimization design system for an infrared lamp array used in spacecraft thermal tests according to an embodiment of the present application. The optimization design method described above can be specifically implemented by using this optimization design system 800. The figures and descriptions above can all be used to illustrate the optimization design system 800 of this embodiment, and repeated content will not be elaborated. Refer to Figure 8 As shown, this optimization design system 800 includes: a lamp array construction module 810 and a lamp array uniformity optimization module 820. The lamp array construction module 810 is used to construct an initial infrared lamp array. The initial infrared lamp array includes m rows and n columns. There is a row spacing between adjacent infrared lamps in each row, and a column spacing between adjacent infrared lamps in each column. Each infrared lamp has a height from the irradiated surface. Both m and n are positive integers greater than or equal to 1; the lamp array uniformity optimization module 820 is used to perform optimization iterative calculations on the row spacing, column spacing, and height by using a first optimization algorithm. The objective function of the first optimization algorithm includes the non-uniformity of the heat flux distribution of the infrared lamp array. The condition for stopping the iteration includes that the non-uniformity of the heat flux distribution is less than a first target value. According to this embodiment, the steps S110 and related steps shown in Figure 1 can be implemented by using the lamp array construction module 810, and the steps S120 and related steps shown in Figure 1 can be implemented by using the lamp array uniformity optimization module 820.

[0122] In some embodiments, the present application writes an automated design platform for controlling module calculations according to the MFC framework, and realizes functions such as data storage, module communication, and result display in the platform.

[0123] In some embodiments, this optimization design system 800 further includes a single lamp heat flux calculation module (not shown in the figure), which is used to calculate the single lamp radiation heat flux distribution of infrared lamps at different currents and different heights by using the Monte Carlo method, so as to obtain a single lamp heat flux distribution database of infrared lamps. In order to improve the calculation efficiency of the Monte Carlo method, each module program in software development is developed by using FORTRAN90, and then converted into a dynamic link library file (Dynamic Link Library, DLL) through compilation and linking. By using the DLL, the program is modularized. In order to process user input and output information, the software calculation interface is developed based on the multi-document framework of the MFC (Microsoft Foundation Classes) application. Through the main interface, users can implement functions such as inputting calculation parameters, selecting the shape of the heat dissipation surface, and starting calculations.

[0124] In some embodiments, this optimization design system 800 further includes a visualization module 830, which is used to display the heat flux distribution of the initial infrared lamp array. In these embodiments, the visualization module 830 can perform visualization processing on the calculation results through an auxiliary interface or post-processing software, such as previewing the lamp array design and heat flux distribution, etc.

[0125] Figure 9A It is a schematic diagram of the optimized position of the infrared lamp array obtained by the optimization design method according to an embodiment of the present application. Figure 9B It is a heat flux distribution diagram of the optimized infrared lamp array obtained by the optimization design method according to an embodiment of the present application. Figure 9C It is a schematic diagram comparing the optimization results of the optimization design method and other methods according to an embodiment of the present application.

[0126] In Figures 9A - 9B In the shown embodiment, the automatic optimization design of the infrared lamp array is carried out on a 2.1m×2.0m rectangular heat dissipation surface by using the optimization design method described above in the present application. The initial lamp array automatically calculated by the program during optimization is 6×6, the first target value is set to 10%, and the preset threshold of the number of iterations is 150 times. The optimal heat flux non-uniformity at the 150th step of calculation is 12.05%, which is greater than the first target value. Therefore, the initial infrared lamp array is reconstructed into a second infrared lamp array of 7×6. After 16 calculations, a heat flux non-uniformity of 9.25% is obtained, and after 110 calculations, a heat flux non-uniformity of 7.52% is obtained. The total optimization time is 120 min.

[0127] Figure 9A Shown in is the optimized 7×6 infrared lamp array, in which the row spacing 910, column spacing 920, and the height 930 of the 3*4 lamp array in the upper right quadrant are marked, all of which are the results of optimization. It can be seen from this that the optimized row spacing and column spacing gradually decrease from the center to the periphery, and the height of the infrared lamp gradually decreases from the center to the periphery.

[0128] Figure 9B It is shown in a visual way Figure 9A the heat flux distribution of the infrared lamp array shown in, where the X-axis and Y-axis are coordinate axes, and FLUX is the heat flux density. The heat flux non-uniformity is 7.52%, meeting the requirement of δ<10%.

[0129] To compare the influence of the improvement strategy of the present application on the optimization speed of the infrared lamp array, taking a 2.1m×2.0m heat dissipation surface as an example, with the specified lamp array being 7 rows and 6 columns, the optimization design of the lamp array is carried out using the genetic algorithm, particle swarm algorithm, and the optimization design method of the present application respectively. Figure 9C For comparison of calculation results.

[0130] Refer to Figure 9C shown in, where the horizontal axis is time, with the unit of minute (min), and the vertical axis is the heat flux distribution non-uniformity δ, with the unit of %. In Figure 9C are respectively shown the result curve of the genetic algorithm, the particle swarm algorithm curve, and the curve of the optimization design method of the present application. From Figure 9CIt can be seen that when using the genetic algorithm to optimize the lamp array, it took 75.8 minutes for the non-uniformity of the heat flux distribution to drop below 10%, and the final non-uniformity of the heat flux distribution after 305.4 minutes of calculation was 6.75%; when using the particle swarm algorithm for optimization, it took 56 minutes for the non-uniformity of the heat flux distribution to drop below 10%, and the time used was reduced by 26.1%. However, the final non-uniformity stabilized at 9.88% after 100 minutes of calculation and could not continue to decrease; while using the optimization design method of the present application for optimization, the non-uniformity of the heat flux dropped to 9.25% after only 8 minutes. Compared with using the genetic algorithm, the time used was reduced by 89.4%. The final non-uniformity of the heat flux after 55 minutes of calculation was 7.52%. The overall time used was reduced by 82%. Although the final optimization result was relatively worse by 0.77%, the acceleration effect was significant and could meet the requirements of practical engineering applications.

[0131] The present application further includes an optimization design device for an infrared lamp array used in a spacecraft thermal test, including a memory and a processor. Among them, the memory is used to store instructions executable by the processor; the processor is used to execute the instructions to implement the optimization design method for the infrared lamp array used in the spacecraft thermal test described above.

[0132] Figure 10 It is a system block diagram of the optimization design device for the infrared lamp array used in a spacecraft thermal test according to an embodiment of the present invention. Refer to Figure 10 As shown, the optimization design device 1000 may include an internal communication bus 1001, a processor 1002, a read-only memory (ROM) 1003, a random access memory (RAM) 1004, and a communication port 1005. When applied to a personal computer, the optimization design device 1000 may further include a hard disk 1006. The internal communication bus 1001 can realize data communication between components of the optimization design device 1000. The processor 1002 can make judgments and issue prompts. In some embodiments, the processor 1002 may be composed of one or more processors. The communication port 1005 can realize data communication between the optimization design device 1000 and the outside. In some embodiments, the optimization design device 1000 can send and receive information and data from the network through the communication port 1005. The optimization design device 1000 may further include different forms of program storage units and data storage units, such as a hard disk 1006, a read-only memory (ROM) 1003, and a random access memory (RAM) 1004, which can store various data files used for computer processing and / or communication, as well as possible program instructions executed by the processor 1002. The processor executes these instructions to implement the main part of the method. The results processed by the processor are transmitted to the user device through the communication port and displayed on the user interface.

[0133] The above-mentioned optimization design method can be implemented as a computer program, stored in the hard disk 1006, and loaded into the processor 1002 for execution to implement the optimization design method of the present application.

[0134] The present invention further includes a computer-readable medium storing computer program code, which implements the optimization design method described above when executed by a processor.

[0135] When the optimization design method is implemented as a computer program, it can also be stored in a computer-readable storage medium as an article of manufacture. For example, the computer-readable storage medium may include, but is not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read-only memories (EPROMs), cards, sticks, key drives). In addition, the various storage media described herein can represent one or more devices and / or other machine-readable media for storing information. The term "machine-readable medium" may include, but is not limited to, wireless channels and various other media (and / or storage media) that can store, contain, and / or carry code and / or instructions and / or data.

[0136] It should be understood that the embodiments described above are merely illustrative. The embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For hardware implementation, the processor can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, and / or other electronic units designed to perform the functions described herein, or a combination thereof.

[0137] Some aspects of the present application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above-mentioned hardware or software can all be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor can be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, aspects of the present application may be embodied as a computer product located on one or more computer-readable media, which includes computer-readable program code. For example, the computer-readable media may include, but is not limited to, magnetic storage devices (such as hard disks, floppy disks, magnetic tapes...), optical disks (such as compact disks CD, digital versatile disks DVD...), smart cards, and flash memory devices (such as cards, sticks, key drives...).

[0138] The computer-readable media may contain a propagated data signal having computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take various forms, including electromagnetic forms, optical forms, etc., or suitable combinations thereof. The computer-readable media can be any computer-readable media other than a computer-readable storage media, which can communicate, propagate, or transport a program for use by being connected to an instruction execution system, apparatus, or device. The program code located on the computer-readable media can be propagated through any appropriate medium, including radio, cable, fiber optic cable, radio frequency signal, or similar media, or any combination of the above media.

[0139] The basic concepts have been described above. Obviously, for those skilled in the art, the above invention disclosure is only an example and does not constitute a limitation to the present application. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to the present application. Such modifications, improvements, and corrections are proposed in the present application, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of the present application.

[0140] At the same time, the present application uses specific terms to describe the embodiments of the present application. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification is not necessarily referring to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the present application can be appropriately combined.

[0141] In some embodiments, numbers are used to describe components and the quantity of attributes. It should be understood that such numbers used in the description of embodiments are, in some examples, modified by the modifiers "about", "approximate" or "substantially". Unless otherwise specified, "about", "approximate" or "substantially" indicate that the said numbers are allowed to have a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and such approximate values may vary according to the characteristics required by individual embodiments. In some embodiments, numerical parameters should consider the specified significant digits and adopt the method of retaining general digits. Although the numerical ranges and parameters used in some embodiments of the present application to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

Claims

1. An optimization design method for an infrared lamp array used in spacecraft thermal tests, comprising: Constructing an initial infrared lamp array, the initial infrared lamp array including m rows and n columns, with a row spacing between adjacent infrared lamps in each row, a column spacing between adjacent infrared lamps in each column, and a height of each infrared lamp from the irradiated surface, where m and n are positive integers greater than or equal to 1; Using a first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height, the objective function of the first optimization algorithm including the non-uniformity of the heat flux distribution of the infrared lamp array, and the condition for stopping the iteration including that the non-uniformity of the heat flux distribution is less than a first target value; Dividing the irradiated surface in the spacecraft thermal test into multiple rectangular basic irradiated surfaces, and constructing the initial infrared lamp array for the rectangular basic irradiated surfaces; And Constructing the initial infrared lamp array for each of the rectangular basic irradiated surfaces in sequence, and using the first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height; obtaining the total heat flux distribution non-uniformity according to the non-uniformity of the heat flux distribution of each rectangular basic irradiated surface; using a second optimization algorithm to perform optimization iterative calculations on the current parameters of each rectangular basic irradiated surface, and the condition for stopping the iteration including that the total heat flux distribution non-uniformity is less than a second target value.

2. The optimization design method according to claim 1, characterized in that The constraint conditions of the first optimization algorithm include that the row spacing and the column spacing gradually decrease from the center of the infrared lamp array to the periphery, and the height gradually decreases from the center of the infrared lamp array to the periphery.

3. The optimization design method according to claim 1, characterized in that In the step of constructing the initial infrared lamp array, it further includes: setting an initial row spacing of the row spacing and an initial column spacing of the column spacing based on engineering experience.

4. The optimization design method according to claim 1, characterized in that The first optimization algorithm includes a particle swarm optimization algorithm.

5. The optimization design method according to claim 1, characterized in that, In the step of using the first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height, it further includes: setting a row spacing limit, a column spacing limit, and / or a height limit; determining whether the row spacing exceeds the row spacing limit, determining whether the column spacing exceeds the column spacing limit, and / or determining whether the height exceeds the height limit; when it exceeds, making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit.

6. The optimization design method according to claim 5, wherein The step of making the row spacing within the row spacing limit, making the column spacing within the column spacing limit, and / or making the height within the height limit includes: When x > x max , let x = 2 * x max - x; When x < x min , set x = 2 * x min - x; where x represents the row pitch, the column pitch, or the height, and x min , x max represent the maximum and minimum values among the row pitch limit, the column pitch limit, or the height limit, respectively.

7. The optimization design method according to claim 1, wherein In the step of using the first optimization algorithm to perform optimization iterative calculations on the row spacing, the column spacing, and the height, it further includes: when the number of iterations is greater than a preset threshold and the non-uniformity of the heat flux distribution is not less than the first target value, reconstructing the initial infrared lamp array into a second infrared lamp array, the area of the second infrared lamp array being equal to that of the initial infrared lamp array, the second infrared lamp array including m + 1 rows and n columns, or the second infrared lamp array including m rows and n + 1 columns.

8. The optimization design method according to claim 1, wherein It further includes: Divide the initial infrared lamp array into four quadrants. The step of performing optimization iteration calculations on the row spacing, column spacing, and height using the first optimization algorithm includes: Selecting one of the four quadrants as the target quadrant, and performing optimization iteration calculations on the row spacing, column spacing, and height of the infrared lamps in the target quadrant.

9. The optimization design method according to claim 1, wherein The shape of the irradiated surface includes any one or a combination of multiple of rectangle, L-shape, concave shape, and convex shape.

10. An optimized design system for an infrared lamp array used in spacecraft thermal tests, characterized in that, Comprising: A lamp array construction module for constructing an initial infrared lamp array, the initial infrared lamp array including m rows and n columns, with a row spacing between adjacent infrared lamps in each row, a column spacing between adjacent infrared lamps in each column, and a height of each infrared lamp from the irradiated surface, where m and n are both positive integers greater than or equal to 1; A lamp array uniformity optimization module for performing optimization iteration calculations on the row spacing, column spacing, and height using the first optimization algorithm, the objective function of the first optimization algorithm including the non-uniformity of the heat flux distribution of the infrared lamp array, and the conditions for stopping iteration including that the non-uniformity of the heat flux distribution is less than a first target value, and dividing the irradiated surface in the spacecraft thermal test into multiple rectangular basic irradiated surfaces, and constructing the initial infrared lamp array for the rectangular basic irradiated surfaces. Construct the initial infrared lamp array for each of the rectangular basic irradiated surfaces in sequence, and perform optimization iteration calculations on the row spacing, column spacing, and height using the first optimization algorithm; Obtain the total heat flux distribution non-uniformity based on the heat flux distribution non-uniformity of each rectangular basic irradiated surface; Perform optimization iteration calculations on the current parameters of each rectangular basic irradiated surface using the second optimization algorithm, and the conditions for stopping iteration include that the total heat flux distribution non-uniformity is less than a second target value.

11. The optimization design system according to claim 10, characterized in that, It further includes a visualization module for displaying the heat flux distribution of the initial infrared lamp array.

12. An optimization design device for an infrared lamp array used in a spacecraft thermal test, comprising: A memory for storing instructions executable by a processor; A processor for executing the instructions to implement the method according to any one of claims 1-9.

13. A computer-readable medium storing computer program code, the computer program code implementing the method according to any one of claims 1-9 when executed by a processor.

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