Active sensing laser protection composite material and design method thereof

Abstract

The application discloses an active sensing laser protection composite material and a design method thereof, and belongs to the technical field of composite materials.The composite material is a woven reinforced resin-based composite material, and structural forms include but are not limited to orthogonal three-way, 2.5D and fine woven puncture.The composite material is embedded with a temperature sensor array and a built-in ceramic tube array.The composite material is connected with a single-chip microcomputer through a cooling medium storage pump.The single-chip microcomputer is connected with the ceramic tube array, and the flow of the cooling medium in the ceramic tube array is adjusted in real time through a control algorithm.The application adopts the active sensing laser protection composite material and the design method thereof, perceives the temperature field of the composite material through embedding a platinum resistance temperature sensor array, combines a physical information neural network algorithm to inversely calculate the laser irradiation position, energy density and temperature field change in real time, intelligently adjusts the cooling flow, and provides efficient laser protection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of composite materials, in particular to an active sensing laser protection composite material and a design method thereof. BACKGROUND

[0002] With the continuous development of laser technology, laser weapons, as a new type of high-energy weapon, have been widely used in military, aerospace and other fields. Laser weapons can accurately attack targets through high-power laser beams, but they can easily cause damage to equipment or personnel, especially high-temperature damage to surface materials. Traditional laser protection techniques mainly rely on the thermal physical properties of materials, such as absorption, reflection and heat dissipation characteristics. However, these methods often have certain limitations, such as being unable to dynamically adjust when the laser intensity changes, or being unable to respond to rapid changes in thermal load in a timely manner, thereby making it difficult to provide continuous and effective protection.

[0003] In recent years, composite materials have been widely used in aerospace, military equipment and protection fields due to their excellent mechanical properties and thermal stability. However, in the case of high laser radiation intensity, the thermal management capability of composite materials is still limited, especially in the case of rapid thermal loading and transient heat flux density changes, traditional passive thermal management methods are difficult to meet the protection requirements. Therefore, how to achieve more precise heat flow control in composite materials has become an important issue to improve laser protection capability. SUMMARY

[0004] The purpose of the present application is to provide an active sensing laser protection composite material and a design method thereof, which can perceive the temperature field of the composite material by embedding a platinum resistance temperature sensor array, and combine a physical information neural network algorithm to real-time inverse the laser irradiation position, energy density and temperature field changes, thereby intelligently adjusting the cooling flow and providing efficient laser protection.

[0005] To achieve the above purpose, the present application provides an active sensing laser protection composite material, which is a woven reinforced resin-based composite material, and the structural form includes but is not limited to orthogonal three-way, 2.5D and fine woven puncture. The composite material is embedded with a temperature sensor array and a built-in ceramic tube array, and the composite material is connected with a single-chip microcomputer through a cooling medium storage pump.

[0006] Preferably, the temperature sensor array is a platinum resistance array, which is located inside the composite material. The platinum resistance array is located at a position about 5mm from the surface inside the composite material. The platinum resistance sensor can perceive temperature changes by measuring resistance changes and feed back real-time temperature data to the control system to accurately monitor temperature changes on the surface of the composite material.

[0007] Preferably, the ceramic tube array is a silicon carbide high-temperature-resistant ceramic tube array, the ceramic tube material includes high-temperature-resistant and high-strength materials such as silicon carbide, alumina, etc., the ceramic tube array realizes the cooling function through the conduction of a liquid or gas cooling medium, and the cooling medium includes but is not limited to water, carbon dioxide, helium, nitrogen, etc.

[0008] Preferably, the single-chip microcomputer stores a preset laser protection control strategy, and a control algorithm is running in the single-chip microcomputer in real time.

[0009] Preferably, the ceramic tube array is connected with the single-chip microcomputer through the cooling medium storage pump, the single-chip microcomputer adjusts the flow of the cooling medium in real time through the control algorithm, and transports the cooling medium to the surface of the composite material through the ceramic tube array, so as to ensure that the surface temperature of the material is maintained within a safe range and avoid material damage or performance degradation caused by overheating.

[0010] Preferably, the training process of the control algorithm includes the following steps:

[0011] S1, data preparation, input temperature sensor array position, actual temperature data and geometric characteristics of the composite material, define training data set and test data set;

[0012] S2, create a physical information neural network (PINN) model;

[0013] S3, define a physical information loss function based on the heat conduction equation;

[0014] S4, define a sensor loss function to calculate the error between the network output temperature and the actual temperature data of the temperature sensor array;

[0015] S5, define a sweating amount function to calculate the sweating amount, calculate the local temperature rise and the laser heat flow according to the temperature field predicted by the physical information neural network model, and calculate the required sweating amount according to the temperature increment and the heat flux density;

[0016] S6, adjust the flow of the cooling medium in the ceramic tube array according to the sweating amount, input the calculated sweating amount into the ceramic tube array, control the flow of the cooling medium, adjust the sweating amount according to the real-time temperature, and ensure that the surface temperature is within a safe range;

[0017] S7, training and optimization, use gradient descent method (such as Adam optimizer) to optimize the physical information loss and the sensor loss, minimize the loss, use back propagation to update the weights of the neural network;

[0018] S8, after the training is completed, use the trained model to predict a new temperature field and calculate the corresponding sweating amount, and output the predicted temperature distribution and the recommended sweating amount.

[0019] Preferably, the formula of the physical information loss function of step S3 is as follows:

[0020]

[0021] wherein, is a physical information error term, is a data error term, λ PDE and λ data are hyperparameters that weigh the importance of the two error terms.

[0022] Preferably, the formula of the sensor loss function of step S4 is as follows:

[0023]

[0024] wherein N is the number of temperature sensors, T pred,i is the temperature predicted by the model at the position of the i-th temperature sensor, T sensor,i is the actual temperature measured by the i-th temperature sensor.

[0025] Preferably, the formula of the sweating amount function in step S6 is as follows:

[0026] Sweating amount = f(temperature increment, heat flux density);

[0027] A design method of an active sensing laser protection composite material, comprising the following steps:

[0028] Step 1, selecting a woven reinforced resin-based composite material, the structure form including orthogonal three-way, 2.5D and fine woven piercing, such composite material structure can effectively improve the mechanical strength and thermal stability, suitable for the thermal protection demand under high strength laser environment;

[0029] Step 2, embedding platinum resistance array temperature sensor in the composite material, the temperature sensor array is located at the position 5mm away from the surface inside the composite material, and the temperature is sensed by resistance change;

[0030] Step 3, using the temperature points sensed by the temperature sensor array, combining the control algorithm based on physical information neural network written independently, real-time inversion of temperature field, laser striking position and laser energy density;

[0031] Step 4, writing the trained control algorithm into the single-chip microcomputer, and real-time controlling the sweating amount of the ceramic pipe array in the composite material through the single-chip microcomputer;

[0032] Step 5, realizing sweating cooling through the silicon carbide ceramic pipe array; selecting appropriate cooling medium;

[0033] Step 6, using the control algorithm to adjust the cooling effect according to the actual situation, and regulating and controlling the sweating amount to realize laser protection.

[0034] Therefore, the present invention, employing the above-mentioned active laser-sensing protective composite material and its design method, has the following beneficial effects:

[0035] (1) By embedding a platinum array temperature sensor in the composite material to sense the temperature field under the action of laser in real time, and combining the physical information neural network algorithm to invert the laser heat flux density and transient temperature distribution, the changes of laser radiation can be monitored in real time.

[0036] (2) By using the active sweating cooling method of the ceramic tube array built into the composite material, the sweating flow rate of the ceramic tube array is intelligently adjusted according to the algorithm, thereby effectively improving the thermal management capability of the composite material and realizing active protection under continuous laser irradiation.

[0037] (3) It not only has significant advantages in improving the thermal protection performance of composite materials, but its intelligent control method can adjust the cooling strategy in real time according to the actual laser radiation situation, ensuring continuous and effective protection in complex and dynamic laser environments, and has broad application prospects.

[0038] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the design method of an active laser-sensing protective composite material according to the present invention. Detailed Implementation

[0040] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0041] Example

[0042] like Figure 1 As shown, an active laser-sensing protective composite material and its design method include the following steps:

[0043] Step 1: Select braided reinforced resin matrix composite material. The structural forms include orthogonal triaxial, 2.5D and fine braided puncture. This composite material structure can effectively improve mechanical strength and thermal stability, and is suitable for thermal protection requirements in high-intensity laser environments. The composite material has a built-in ceramic tube array, which is connected to a microcontroller through a cooling medium storage pump.

[0044] Step 2, embed platinum resistance array temperature sensors in the composite material, the temperature sensor array is located inside the composite material 5mm away from the surface, the temperature is sensed by resistance change, the platinum resistance sensor can sense temperature change by measuring resistance change and feedback real-time temperature data to the control system to accurately monitor the temperature change of the composite material surface.

[0045] The temperature sensor array can cover different areas of the composite material through accurate temperature sensing and distribution, to monitor the temperature change of the laser irradiation area in real time and provide accurate data support for subsequent cooling control.

[0046] Step 3, use the temperature points sensed by the temperature sensor array, combined with the self-written control algorithm based on physical information neural network, to real-time inverse temperature field, laser striking position and laser energy density.

[0047] The control algorithm can calculate the thermal effect of the laser and the spatial distribution of the material temperature based on the laser irradiation conditions and the thermal response of the material, to provide decision basis for cooling control. The control algorithm improves the accuracy and efficiency of laser protection by continuously obtaining data feedback from the sensor array.

[0048] The training process of the control algorithm includes the following steps:

[0049] S1, data preparation, input temperature sensor array position, actual temperature data and composite material geometric characteristics, define training data set and test data set.

[0050] S2, create a physical information neural network (PINN) model, which consists of multiple fully connected layers, the activation function of each fully connected layer uses tanh activation function, the number of layers and the number of neurons in each layer are hyperparameters, define the input of the network (position x), the input x passes through multiple fully connected layers in turn through forward propagation to the output layer, and the output layer outputs the temperature T without activation function.

[0051] S3, define the physical information loss function based on the heat conduction equation;

[0052] The formula satisfied by the heat conduction equation is:

[0053]

[0054] Where T pred is the predicted temperature, t is the time, x is the position coordinate, and a is the thermal diffusivity.

[0055] The formula of the physical information error term is as follows:

[0056]

[0057] The formula of the data error term is as follows:

[0058]

[0059] where T sensor is the actual measured temperature of the temperature sensor.

[0060] The formula of the physical information loss function is as follows:

[0061]

[0062] where λ PDE and λ data are hyperparameters that weigh the importance of the two error terms.

[0063] S4, define the sensor loss function to calculate the error between the output temperature of the network and the actual temperature data of the temperature sensor array.

[0064] The formula of the sensor loss function is as follows:

[0065]

[0066] where N is the number of temperature sensors, T pred,i is the temperature predicted by the model at the i-th temperature sensor location, T sensor,i is the actual temperature measured by the i-th temperature sensor.

[0067] S5, define the sweating amount function to calculate the sweating amount, according to the temperature field predicted by the physical information neural network model, calculate the local temperature rise and the laser heat flow; according to the temperature increment and the heat flux density, calculate the required sweating amount.

[0068] The temperature increment T increase = T pred -T threshold , T threshold is the temperature threshold.

[0069] The formula of the sweating amount function is sweating amount = f(temperature increment, heat flux density).

[0070] In this embodiment, it is assumed that the heat flux density is proportional to the absolute value of the temperature, and the formula for defining the heat flux density is H = |T pred |, in actual application, the heat flux density will depend on a more complex physical model.

[0071] Therefore, in this embodiment, the formula of the sweating amount function is as follows:

[0072] Sweating amount = 0.1 * T increase * H, while limiting the sweating amount between 0 and 1.

[0073] S6、According to the amount of sweating, adjust the flow of cooling medium in the ceramic tube array, input the calculated sweating amount into the ceramic tube array, control the flow of cooling medium, adjust the sweating amount according to the real-time temperature, and ensure that the surface temperature is within a safe range.

[0074] S7、Training and optimization, using gradient descent method to optimize physical information loss and sensor loss, minimizing loss, in this embodiment, using Adam optimizer, using back propagation to update the weights of neural network;

[0075] S8、After training, use the trained model to predict new temperature field and calculate corresponding sweating amount, output predicted temperature distribution and recommended sweating amount.

[0076] Step 4, write the trained control algorithm into the single-chip microcomputer, and control the sweating amount of the ceramic tube array in the composite material in real time through the single-chip microcomputer.

[0077] The control algorithm runs in real time in the single-chip microcomputer. The single-chip microcomputer stores a preset laser protection control strategy, and adjusts the control parameters according to real-time data, and then controls the sweating amount. The single-chip microcomputer is connected to the ceramic tube array in the composite material through a cooling medium storage pump, and the flow of cooling medium is adjusted in real time through the control algorithm, and is transported to the surface of the composite material through the ceramic tube array, so as to ensure that the surface temperature of the material is maintained within a safe range, and avoid damage or performance degradation of the material due to overheating.

[0078] Step 5, realize sweating cooling through silicon carbide ceramic tube array; select appropriate cooling medium.

[0079] The ceramic tube material includes high-temperature-resistant and high-strength materials such as silicon carbide and alumina, which can operate stably in high-temperature environment and maintain good heat conduction and thermal resistance performance. The ceramic tube array has good heat resistance and mechanical strength, and can be used in high-power laser protection process.

[0080] The ceramic tube array realizes cooling function through the conduction of liquid or gas cooling medium, and the cooling medium includes but is not limited to water, carbon dioxide, helium, nitrogen, etc. The selection of cooling medium is adjusted according to different laser environments, composite material types and protection requirements, so as to effectively reduce the surface temperature of the material.

[0081] Step 6, use the control algorithm to adjust the cooling effect according to the actual situation, and adjust the sweating amount to realize laser protection.

[0082] Therefore, the application adopts the active sensing laser protection composite material and the design method, which not only has a significant advantage in improving the heat protection performance of the composite material, but also can adjust the cooling strategy in real time according to the actual laser radiation condition, ensure the continuous and effective protection effect in the complex and dynamic laser environment, and has a wide application prospect.

[0083] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, but not to limit them, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can still be modified or replaced by equivalents, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. An actively sensing laser protection composite material, characterized in that: The composite material is a woven reinforced resin-based composite material, and the structural form includes orthogonal three-way, 2.5D and fine woven piercing; the composite material is embedded with an array of temperature sensors and an array of built-in ceramic tubes; and the composite material is connected with a single-chip microcomputer through a cooling medium storage pump; The single-chip microcomputer stores a preset laser protection control strategy, and a control algorithm is run in the single-chip microcomputer in real time; The training process of the control algorithm includes the following steps: S1, data preparation, input temperature sensor array position, actual temperature data and composite material geometric characteristics, define training data set and test data set; S2, create a physical information neural network model; S3, define a physical information loss function based on the heat conduction equation; S4, define a sensor loss function, calculate the error between the network output temperature and the actual temperature data of the temperature sensor array; S5, define a sweating amount function to calculate the sweating amount, according to the temperature field predicted by the physical information neural network model, calculate the local temperature rise and laser heat flow; according to the temperature increment and heat flux density, calculate the required sweating amount; S6, adjust the cooling medium flow rate in the ceramic tube array according to the sweating amount, input the calculated sweating amount into the ceramic tube array, control the flow rate of the cooling medium, adjust the sweating amount according to the real-time temperature, and ensure that the surface temperature is within a safe range; S7, training and optimization, use gradient descent method to optimize physical information loss and sensor loss, minimize loss, use back propagation to update the weights of the neural network; S8, after the training is completed, use the trained model to predict the new temperature field and calculate the corresponding sweating amount, output the predicted temperature distribution and recommended sweating amount.

2. The actively sensing laser protection composite material of claim 1, wherein: The temperature sensor array is a platinum resistance array, which is arranged inside the composite material at a position 5mm away from the surface.

3. The actively sensing laser protection composite material of claim 1, wherein: The ceramic tube array is a high-temperature-resistant silicon carbide ceramic tube array, which realizes the cooling function through the conduction of liquid or gas cooling medium.

4. The actively sensing laser protection composite material of claim 1, wherein: The ceramic tube array is connected with the single-chip microcomputer through the cooling medium storage pump, and the single-chip microcomputer adjusts the flow rate of the cooling medium in real time through the control algorithm and transports it to the surface of the composite material through the ceramic tube array.

5. The actively sensing laser protection composite material of claim 1, wherein, The formula of the physical information loss function of step S3 is as follows: where, is the physical information error term, is the data error term, λ PDE and λ data is a hyperparameter that balances the importance of the two error terms.

6. The actively sensing laser protection composite material of claim 1, wherein, The formula of the sensor loss function of step S4 is as follows: where N is the number of temperature sensors, T pred,i is the predicted temperature at the i-th temperature sensor location, T sensor,i is the actual temperature measured by the i-th temperature sensor.

7. The actively sensing laser protection composite material of claim 1, wherein, The formula of the sweating amount function in step S6 is as follows: Sweating amount = f(temperature increment, heat flux density).

8. A method of designing an active sensing laser protection composite material according to any one of claims 1 to 7, characterized in that, The method comprises the following steps: Step 1, select a woven reinforced resin-based composite material, and the structural form includes orthogonal three-way, 2.5D and fine woven piercing; Step 2, embed a platinum resistance array temperature sensor in the composite material, and the temperature sensor array is located at a position 5mm away from the surface inside the composite material, and the temperature is sensed by resistance change; Step 3, use the temperature points sensed by the temperature sensor array, combine the self-written control algorithm based on the physical information neural network, and real-time inverse the temperature field, laser striking position and laser energy density; Step 4, write the trained control algorithm into the single-chip microcomputer, and control the sweating amount of the ceramic tube array in the composite material in real time through the single-chip microcomputer; Step 5, sweat cooling through silicon carbide ceramic tube array; select appropriate cooling medium; Step 6, use control algorithm to adjust cooling effect according to actual situation, and regulate sweat amount to realize laser protection.

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