Satellite dynamic thermal control method based on plume imaging feedback

Abstract

The invention provides a satellite dynamic thermal control method based on plume imaging feedback, which belongs to a spacecraft thermal control technology, and comprises the following steps of: acquiring plasma plume radiation field distribution in a thruster starting process by utilizing multi-spectrum CMOS imaging, inverting corresponding plasma parameters and flow field velocity distribution, and sending the plasma parameters and the flow field velocity distribution into a thermal control module through a high-speed bus; judging heat flow distribution, and comparing the threshold set with a historical model to evaluate the overheat risk; and if the overheat risk exists, marking as thermal load sudden change, executing a thermal control strategy, adjusting thermal resistance, and changing heat dissipating capacity until the risk is removed. The thermal radiation change process of the electric thruster is associated with the overall thermal control of the satellite, the optical information of the plasma plume is collected by using an optical imaging method, and the corresponding plasma parameters and thermal field information are obtained through inversion, so that the thermal control function of the satellite is actively controlled; thermal control of satellite components and thermal control of the whole satellite are associated, and accurate satellite thermal control is achieved.

Description

Technical Field

[0001] The present invention relates to spacecraft thermal control technology, and in particular to a satellite dynamic thermal control method based on plume imaging feedback. Background Art

[0002] With the widespread application of aerospace electric propulsion technology in low-orbit communication constellations, attitude control, and north-south position maintenance missions, the focus of research on the characteristics of individual thrusters has gradually shifted to the study of the coupling characteristics of thrusters and satellites. The transient large heat flux caused by thruster state transitions such as ignition, shutdown, and restart can cause a sudden increase in the local or overall temperature of the satellite. Traditional passive thermal control methods, such as constant temperature coatings and passive heat absorption using single phase change materials, are difficult to respond to in a timely manner, which can easily lead to thermal runaway or thermal stress accumulation. Existing technologies often rely on empirical models or post-correction, lacking dynamic thermal control methods based on real-time operating conditions, and are unable to meet the operational requirements of high-precision and high-reliability electric propulsion satellites. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a satellite dynamic thermal control method based on plume imaging feedback. By real-time imaging of the thruster plume plasma radiation characteristics and plasma parameter inversion, phase change materials and adjustable thermal resistance components are driven to achieve dynamic compensation for sudden changes in thermal load of the satellite under transient conditions such as thruster ignition and restart.

[0004] The present invention is implemented through the following technical solution: a satellite dynamic thermal control method based on plume imaging feedback: the method specifically comprises the following steps: Step 1: Use a multi-spectral imager to continuously sample the plume radiation intensity at a high frame rate; Step 2: perform distortion correction, noise suppression, and dynamic range optimization on the captured image; Step 3: Based on the pre-processed multi-spectral image, the image solution model is used to quickly invert the two-dimensional plasma temperature field and velocity distribution, and extract key parameters; Step 4: Evaluate and control the current degree of thermal load mutation according to the preset temperature threshold and flow field distribution rules.

[0005] Furthermore, in step 1, a multi-spectral imaging device is pre-installed outside the thruster nozzle. The imaging device includes a CMOS sensor in the visible and near-infrared bands, and the imaging device and the thruster nozzle are arranged in the same plane, and the imaging field of view covers the entire plume area; When the thruster is started, the imaging device continuously collects plume radiation field images and transmits them to the pre-processing module.

[0006] Furthermore, in step 2, specifically: Perform distortion correction on the original image sequence to remove the fisheye effect of the lens; Apply dark current and flat-field correction algorithms to remove image sensor noise and uneven response; Adaptive filtering method is used to enhance the image and highlight the plume edge and hot spot area; The processed images are cached in timestamp order and marked with the corresponding thruster working status information.

[0007] Furthermore, in step 3, the key parameters include peak temperature, hot spot position and flow field direction.

[0008] Furthermore, in step 3, For each frame of enhanced image, the pixel radiation intensity value I(λ) is extracted by band, and the plasma temperature T(x,y) of each pixel is calculated using the plasma collision radiation model algorithm. At the same time, the local flow velocity vector field v(x,y) is inverted by combining multi-frame time series signals and using the particle image velocimetry algorithm. The obtained two-dimensional temperature field matrix and flow field vector data are sent to the thermal control strategy module through the high-speed bus.

[0009] Furthermore, in step 4, The maximum temperature and area of the hotspot are calculated based on the plasma temperature T(x,y). The direction and intensity distribution of the heat flow are determined based on the flow velocity v(x,y). The threshold sets for temperature and hotspot area are compared with the historical operating condition model to assess whether there is an overheating risk. If there is an overheating risk, the system is marked as in the "heat load mutation" state and thermal control is executed.

[0010] Furthermore, the thermal control is specifically performed as follows: Step 4.1: When it is determined that the safety range is exceeded, the predictive control method is called to comprehensively determine the required heat absorption and heat dissipation, as well as the phase change degree of the phase change material and the adjustable thermal resistance setting value; Step 4.2: Convert the control decision into specific execution instructions and send them to the phase change material driver and adjustable thermal resistance device respectively to change the thermal conductivity and insulation state, thereby achieving precise regulation of the heat flow of the heat dissipation panel or internal structure; In step 4.3, the actual effect is continuously fed back through the internal temperature and heat flow sensors, and the thermal model parameters are fine-tuned online. When the heat load returns to a safe range, the system automatically resets to standby mode.

[0011] A satellite dynamic thermal control system based on plume imaging feedback; The dynamic thermal control system includes an acquisition module, a preprocessing module, an inversion module and a thermal control strategy module: The acquisition module continuously samples the plume radiation intensity at a high frame rate through a multi-spectral imager; The preprocessing module performs distortion correction, noise suppression and dynamic range optimization on the collected image; The inversion module uses an image solution model to quickly invert the two-dimensional plasma temperature field and velocity distribution based on the pre-processed multi-spectral image and extract key parameters; The thermal control strategy module evaluates and controls the degree of sudden change in the current thermal load according to the preset temperature threshold and flow field distribution rules.

[0012] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0013] A computer-readable storage medium is used to store computer instructions, which implement the steps of the above method when executed by a processor.

[0014] Beneficial effects of the present invention Compared with the existing technology, the present invention links the thermal radiation change process of the electric thruster with the overall thermal control of the satellite, uses optical imaging methods to collect optical information of the plasma plume, and inverts the corresponding plasma parameters and thermal field information, thereby actively controlling the thermal control function of the satellite, overcoming the insensitivity of the existing passive control satellite thermal control method, and linking the thermal control of satellite components with the thermal control of the satellite as a whole, thereby realizing precise satellite thermal control. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the implementation steps of the dynamic thermal control system based on plume imaging feedback of the present invention; Figure 2 Schematic diagram of the phase change material / adjustable thermal resistance execution unit structure. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] The experimental methods used in the following examples are conventional methods unless otherwise specified. The materials, reagents, methods, and instruments used are conventional in the art and can be obtained commercially by those skilled in the art unless otherwise specified.

[0018] In the example, the specific process of the satellite dynamic thermal control method based on plume imaging feedback is as follows: using multi-spectral CMOS imaging to collect the plasma plume radiation field distribution during the thruster startup process, thereby inverting the corresponding plasma parameters and flow field velocity distribution, and sending them to the thermal control module through a high-speed bus to judge the heat flux distribution, and compare the threshold set with the historical model to evaluate the overheating risk; if there is an overheating risk, it is marked as a "thermal load mutation" and the thermal control strategy is executed to adjust the thermal resistance and change the heat dissipation until the risk is eliminated.

[0019] The present invention tightly couples thermal control execution with plume imaging feedback to form a closed-loop control chain of "monitoring-analysis-decision-execution". A satellite dynamic thermal control method based on plume imaging feedback is proposed. Specifically, the method includes the following steps: Step 1: Use a multi-spectral imager to continuously sample the plume radiation intensity at a high frame rate; A multi-spectral imaging device is pre-installed on the outside of the thruster nozzle. The imaging device includes a CMOS sensor in the visible and near-infrared bands, and the imaging device and the thruster nozzle are arranged in the same plane, and the imaging field of view covers the entire plume area; When the thruster is started, the imaging device continuously collects plume radiation field images and transmits them to the pre-processing module.

[0020] Step 2: perform distortion correction, noise suppression, and dynamic range optimization on the captured image; Perform distortion correction on the original image sequence to remove the fisheye effect of the lens; Apply dark current and flat-field correction algorithms to remove image sensor noise and uneven response; Adaptive filtering method is used to enhance the image and highlight the plume edge and hot spot area; The processed images are cached in timestamp order and marked with the corresponding thruster working status information.

[0021] Step 3: Based on the pre-processed multi-spectral image, the image solution model is used to quickly invert the two-dimensional plasma temperature field and velocity distribution, and extract key parameters; In step 3, the key parameters include peak temperature, hot spot position and flow field direction; For each frame of enhanced image, the pixel radiation intensity value I(λ) is extracted by band, and the plasma temperature T(x,y) of each pixel is calculated using a publicly available plasma collision radiation model algorithm. Simultaneously, the local velocity vector field v(x,y) is inverted using a particle image velocimetry algorithm combined with multi-frame time series signals. The obtained two-dimensional temperature field matrix and flow field vector data are sent to the thermal control strategy module through the high-speed bus.

[0022] Step 4: Evaluate and control the current degree of thermal load mutation according to the preset temperature threshold and flow field distribution rules.

[0023] The maximum temperature and area of the hotspot are calculated based on the plasma temperature T(x,y). The direction and intensity distribution of the heat flow are determined based on the flow velocity v(x,y). The pre-established threshold sets for temperature and hotspot area are compared with the historical operating condition model to assess whether there is an overheating risk. If there is an overheating risk, it is marked as a "heat load mutation" state and thermal control execution is initiated.

[0024] The thermal control is specifically performed as follows: Step 4.1: When it is determined that the safety range is exceeded, the predictive control method is called to comprehensively determine the required heat absorption and heat dissipation, as well as the phase change degree of the phase change material and the adjustable thermal resistance setting value; like Figure 2 As shown, the phase change material / adjustable thermal resistance execution unit structure consists of a heat dissipation panel, a phase change material, a driving circuit, and an adjustable thermal resistance.

[0025] Read the current satellite internal temperature and cooling panel status; In the closed-loop control system, T(x,y) and v(x,y) are inputted comprehensively to calculate the required heat absorption and heat dissipation. Step 4.2: Convert the control decision into specific execution instructions and send them to the phase change material driver and adjustable thermal resistance device respectively to change the thermal conductivity and insulation state, thereby achieving precise regulation of the heat flow of the heat dissipation panel or internal structure; Determine the phase change material participation range and phase change rate control signal based on the amount of heat absorbed and dissipated, and calculate the target thermal resistance value of the adjustable thermal resistor; Send phase change rate control commands to the PCM heating / cooling subsystem to achieve melting endothermicity or solidification exothermicity; Sending a target thermal resistance value instruction to the thermal resistance control unit; In step 4.3, the actual effect is continuously fed back through the internal temperature and heat flow sensors, and the thermal model parameters are fine-tuned online. When the heat load returns to a safe range, the system automatically resets to standby mode.

[0026] Monitor the actual heat conduction / insulation effect through temperature sensing elements and flow sensors, and send feedback data back to the thermal control strategy module; Repeat the above steps until the heat dissipation panel value drops below the threshold set, automatically reset the PCM and thermal resistance to the default standby state, and record all operating data and control actions for subsequent performance evaluation and algorithm optimization.

[0027] A satellite dynamic thermal control system based on plume imaging feedback; The dynamic thermal control system includes an acquisition module, a preprocessing module, an inversion module and a thermal control strategy module: The acquisition module continuously samples the plume radiation intensity at a high frame rate through a multi-spectral imager; The preprocessing module performs distortion correction, noise suppression and dynamic range optimization on the collected image; The inversion module uses an image solution model to quickly invert the two-dimensional plasma temperature field and velocity distribution based on the pre-processed multi-spectral image and extract key parameters; The thermal control strategy module evaluates and controls the degree of sudden change in the current thermal load according to the preset temperature threshold and flow field distribution rules.

[0028] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0029] A computer-readable storage medium is used to store computer instructions, which implement the steps of the above method when executed by a processor.

[0030] The memory in the embodiments of the present application can be volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM). It should be noted that memory of the methods described herein is intended to comprise, but not be limited to, these and any other suitable types of memory.

[0031] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired connection such as a coaxial cable, optical fiber, digital subscriber line (DSL), or wireless connection such as infrared, wireless, or microwave. The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium such as a floppy disk, hard disk, magnetic tape, an optical medium such as a high-density digital video disc (DVD), or a semiconductor medium such as a solid-state disc (SSD).

[0032] During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor or by instructions in the form of software. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it will not be described in detail here.

[0033] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above-described method embodiment can be completed by hardware integrated logic circuits in the processor or by software instructions. The above-described processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above-described method.

[0034] The above is a detailed introduction to the satellite dynamic thermal control method based on plume imaging feedback proposed in the present invention, and the principles and implementation methods of the present invention are explained. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A satellite dynamic thermal control method based on plume imaging feedback, characterized by: The method specifically comprises the following steps: Step 1: Use a multi-spectral imager to continuously sample the plume radiation intensity at a high frame rate; Step 2: perform distortion correction, noise suppression, and dynamic range optimization on the captured image; Step 3: Based on the pre-processed multi-spectral image, the image solution model is used to quickly invert the two-dimensional plasma temperature field and velocity distribution, and extract key parameters; Step 4: Evaluate and control the current degree of thermal load mutation according to the preset temperature threshold and flow field distribution rules.

2. The dynamic thermal control method according to claim 1, characterized in that: In step 1, a multi-spectral imaging device is pre-installed outside the thruster nozzle. The imaging device includes a CMOS sensor in the visible and near-infrared bands, and the imaging device and the thruster nozzle are arranged in the same plane, and the imaging field of view covers the entire plume area; When the thruster is started, the imaging device continuously collects plume radiation field images and transmits them to the pre-processing module.

3. The dynamic thermal control method according to claim 2, characterized in that: Specifically in step 2: Perform distortion correction on the original image sequence to remove the fisheye effect of the lens; Apply dark current and flat-field correction algorithms to remove image sensor noise and uneven response; Adaptive filtering method is used to enhance the image and highlight the plume edge and hot spot area; The processed images are cached in timestamp order and marked with the corresponding thruster working status information.

4. The dynamic thermal control method according to claim 3, characterized in that: In step 3, the key parameters include peak temperature, hot spot position and flow field direction.

5. The dynamic thermal control method according to claim 4, characterized in that: In step 3, For each frame of enhanced image, the pixel radiation intensity value I(λ) is extracted by band, and the plasma temperature T(x,y) of each pixel is calculated using the plasma collision radiation model algorithm. At the same time, the local flow velocity vector field v(x,y) is inverted by combining multi-frame time series signals and using the particle image velocimetry algorithm. The obtained two-dimensional temperature field matrix and flow field vector data are sent to the thermal control strategy module through the high-speed bus.

6. The dynamic thermal control method according to claim 5, characterized in that: In step 4, The maximum temperature and area of the hotspot are calculated based on the plasma temperature T(x,y). The direction and intensity distribution of the heat flow are determined based on the flow velocity v(x,y). The threshold sets for temperature and hotspot area are compared with the historical operating condition model to assess whether there is an overheating risk. If there is an overheating risk, the system is marked as in the "heat load mutation" state and thermal control is executed.

7. The dynamic thermal control method according to claim 6, characterized in that: The thermal control is specifically performed as follows: Step 4.1: When it is determined that the safety range is exceeded, the predictive control method is called to comprehensively determine the required heat absorption and heat dissipation, as well as the phase change degree of the phase change material and the adjustable thermal resistance setting value; Step 4.2: Convert the control decision into specific execution instructions and send them to the phase change material driver and adjustable thermal resistance device respectively to change the thermal conductivity and insulation state, thereby achieving precise regulation of the heat flow of the heat dissipation panel or internal structure; In step 4.3, the actual effect is continuously fed back through the internal temperature and heat flow sensors, and the thermal model parameters are fine-tuned online. When the heat load returns to a safe range, the system automatically resets to standby mode.

8. A satellite dynamic thermal control system based on plume imaging feedback, characterized by: The system is used to perform the dynamic thermal control method according to any one of claims 1 to 7; The dynamic thermal control system includes an acquisition module, a preprocessing module, an inversion module and a thermal control strategy module: The acquisition module continuously samples the plume radiation intensity at a high frame rate through a multi-spectral imager; The preprocessing module performs distortion correction, noise suppression and dynamic range optimization on the collected image; The inversion module uses an image solution model to quickly invert the two-dimensional plasma temperature field and velocity distribution based on the pre-processed multi-spectral image and extract key parameters; The thermal control strategy module evaluates and controls the degree of sudden change in the current thermal load according to the preset temperature threshold and flow field distribution rules.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium for storing computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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