Method and device for calibrating surface infrared emissivity of magnesium alloy plate under warm condition

Abstract

The invention provides a magnesium alloy plate surface infrared emissivity calibration method and device under a warm condition, and relates to the technical field of material performance testing. A probe is adjusted to a target scale, and a laser indicating lamp is used for auxiliary positioning; driving the infrared temperature measurement probe to move to a detection position, and regulating and controlling the inclination angle of the sample; the temperature is controlled through a cast aluminum heating plate; collecting data at different temperatures, distances and angles, training a neural network, and establishing an emissivity fitting model; and completing calibration based on a model rule. The device comprises a distance measuring module, an angle adjusting module, a heating module and a control monitoring module. Through combination of a mechanical structure and an intelligent algorithm, rapid matching of temperature, angle and distance parameters is realized, closed-loop control is realized, a neural network analysis technology is integrated, limitation of traditional single parameter calibration is overcome, calibration precision of emissivity in a complex temperature change environment is improved, and the method is suitable for laboratories and industrial scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material performance testing, and in particular to a method and device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions. BACKGROUND

[0002] As a typical warm-sensitive material, the uniformity and stability of the temperature field during hot tensile and forming processes of magnesium-lithium alloys are extremely demanding. A slight deviation in temperature can significantly change the plastic deformation capacity, flow stress characteristics and microstructure evolution of the material, and further lead to problems such as cracks, wrinkles or size precision out-of-tolerance in the formed parts. In the field of material forming, the warm condition generally refers to a temperature range between room temperature and high temperature. For most metal materials, the specific values may vary slightly depending on the type of material. The core feature is that it is different from cold processing at room temperature and different from hot processing near or above the recrystallization temperature. It is a processing condition that relies on temperature regulation to improve material plasticity and reduce forming difficulty.

[0003] In hot tensile experiments, accurate temperature monitoring is a key element to ensure the reliability of material mechanical property testing. The infrared temperature measurement technology has become the main measurement method due to its non-contact and real-time nature. However, the accuracy of infrared temperature measurement is highly dependent on the emissivity parameter of the target object surface, especially for low-emissivity bright metal materials such as magnesium alloy and aluminum alloy. The surface reflection characteristics can significantly interfere with the collection of infrared thermal radiation signals, resulting in temperature measurement errors. Therefore, accurate determination of the surface emissivity of magnesium alloy is the key to achieving closed-loop temperature control.

[0004] Currently, the determination and calibration of magnesium alloy emissivity face many challenges. First, in the hot tensile experiment site, it is very difficult to adjust the emissivity parameter in real time. The traditional method requires repeated trial and error to match the emissivity, which not only consumes time but also consumes a large number of test pieces. Second, in the low temperature range of 50-150℃, the surface emissivity of magnesium alloy is usually less than 0.3. The reflection interference of background thermal radiation is intensified, and the fluctuation factors of temperature measurement distance and angle make it difficult for a single compensation method to adapt to complex working conditions. Finally, existing constant temperature ovens or resistance heating devices have low heating efficiency and limited physical space, which cannot provide a stable dynamic temperature field for infrared temperature measurement, further limiting the efficiency of emissivity calibration. In addition, the traditional emissivity calibration method relies on empirical formula fitting, which lacks physical consistency under variable temperature conditions.

[0005] In these circumstances, if there is no effective calibration device and method for the surface emissivity of magnesium alloy, it will have a wide range of impacts. Therefore, a new emissivity calibration device and method is needed to address the above deficiencies. SUMMARY

[0006] In order to solve the above-mentioned deficiencies of the prior art, the purpose of the present application is to provide a method and device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions, which only integrates a heating element and an infrared temperature measurement module, has a compact heating system structure, fast heating speed, small occupied space, and can adapt to the efficient heating of special-shaped test pieces, synchronously collects data through a real-time thermal monitoring device of a heating plate and an infrared non-contact temperature measurement, and combines a deep learning model to construct a multi-parameter coupled infrared temperature measurement data set covering emissivity, temperature measurement distance, angle, and background temperature, thereby breaking through the limitations of traditional single-factor compensation and having high temperature measurement robustness.

[0007] Specifically, in one aspect, the present application provides a method for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions, comprising the following steps: S1: adjusting the height of the ball screw to the same longitudinal height as the position to be measured; S2: turning on the laser indicator light and the infrared temperature measurement probe arranged on the ball screw sliding table, and driving the ball screw with the servo motor to move the infrared temperature measurement probe to the position to be measured; S3: rotating the cast aluminum heating plate and changing its inclination angle, so that the angle sensor displays the target angle; S4: starting the heating system, inputting the target temperature on the heating control panel, and starting the temperature rise of the cast aluminum heating plate until the cast aluminum heating plate reaches the target temperature; S5: simultaneously collecting the distance between the infrared temperature measurement probe and the position to be measured, and the angle data of the cast aluminum heat insulation plate under different temperature conditions, and using the collected distance and angle data set to train the existing basic neural network system; S6: analyzing the training output results to make the error between the predicted value and the true value of the training set meet the preset error condition; S7: using the trained neural network system to input the target distance between the infrared temperature measurement probe and the position to be measured, and the target angle data of the cast aluminum heat insulation plate, to complete the infrared emissivity calibration of the magnesium alloy sheet surface.

[0008] Preferably, in step S2, the collimation characteristics of the laser are used to project a light spot to capture the target position of the infrared temperature measurement probe and determine the specific coordinates of the target position in space: ; ; In the formula, P=P(Px, Py, Pz) is the target three-dimensional space coordinates of the magnesium alloy plate surface point to be measured, that is, the actual measurement position of the infrared probe, L=L(Lx, Ly, Lz) is the installation position of the laser indicator on the sliding table, which is determined by the ball screw drive, d=d(dx, dy, dz) is the normalized direction vector of the laser indicator light beam, representing the collimated projection direction of the laser, I=I(Ix, Iy, Iz) is the installation position of the infrared temperature measurement probe on the sliding table, v=v(vx, vy, vz) is the normalized detection direction vector of the infrared temperature measurement probe, indicating the aiming direction of the probe optical axis, and k is the straight line distance from the laser source to the target point on the surface of the magnesium alloy plate.

[0009] Preferably, in step S6, the preset error condition of the error between the predicted value of the training set and the true value includes NRMSE<0.1, determining that the model is in the first state, determining that the model is in the second state.

[0010] In another aspect, the present application provides a calibration device for a magnesium alloy plate surface infrared emissivity calibration method, which comprises a distance measuring module, an angle adjusting module, a heating module and a control monitoring module. The distance measuring module comprises a ball screw, a servo motor, an infrared temperature measurement probe and a laser indicator. The servo motor is installed on the ball screw, and the ball screw is provided with a sliding table. The infrared temperature measurement probe and the laser indicator are installed on the sliding table.

[0011] The angle adjusting module comprises a hand wheel and a worm gear reducer. The heating module comprises a fixed clamp, a heat insulation plate and an aluminum alloy heating plate. The aluminum alloy heating plate is arranged on the heat insulation plate, and the fixed clamp is arranged on the heat insulation plate. The aluminum alloy heating plate is connected with the worm gear reducer through a rotating support. The hand wheel is connected with the worm gear reducer. An angle sensor is arranged on the aluminum alloy heating plate.

[0012] The control monitoring module comprises a screw sensor, a heating plate temperature sensor and an infrared temperature sensor. The screw sensor is arranged at the first end of the control monitoring module. The heating plate temperature sensor is arranged at the middle position of the control monitoring module. The infrared temperature sensor is arranged at the second end of the control monitoring module.

[0013] Preferably, the distance measuring module, the angle adjusting module and the heating module are all installed on a support frame. The support frame is composed of profiles connected with each other. The profiles are connected with each other by angle pieces.

[0014] Preferably, the rotating support is installed on the support frame through a bearing seat.

[0015] Preferably, the fixed clamp is arranged in a U shape. The first side edge and the second side edge of the fixed clamp are respectively provided with clamping assemblies.

[0016] Preferably, the clamping assembly comprises a movable clamping plate, adjusting screws and a rotating rod, two adjusting screws are arranged on the first side and the second side of the fixed clamp respectively, the movable clamping plate is arranged on the adjusting screws, and the first end of the adjusting screw is provided with the rotating rod.

[0017] Further, preferably, the distance measuring module, the angle adjusting module and the heating module are arranged at the first end of the support frame, and the control and monitoring module is arranged at the second end of the support frame.

[0018] Compared with the prior art, the present application has the following advantages: 1. The servo motor is configured, which has the characteristics of high precision and fast response speed, can accurately control the movement of the device, ensures stable operation under different working conditions, provides stable power support for accurate measurement of the surface infrared emissivity of the light alloy sheet, and guarantees the stability and reliability of the experimental or production process.

[0019] 2. The ball screw, speed reducer and rotating shaft components are installed, the transmission efficiency is high, the positioning accuracy is accurate, the accurate linear motion can be realized, different working requirements can be matched, the device has strong applicability, meets various measurement scenes, and the overall performance and measurement accuracy of the device are improved through the cooperation of the components.

[0020] 3. The OLED display arranged on the bottom side can detect the position and state of the device in real time, so that the operator can master the equipment operation at any time, and potential problems can be found in time and adjusted.

[0021] 4. Compared with the traditional scheme, only the heating element and the infrared temperature measurement module are integrated, the heating system structure is compact, a large constant temperature environment box is not needed, the heating speed is fast, the occupied space is small, and the heating of special-shaped test pieces can be adapted.

[0022] 5. The real-time thermal monitoring device and the infrared non-contact temperature measurement are synchronized data acquisition through the heating plate, and a multi-parameter coupled infrared temperature measurement data set covering emissivity, temperature measurement distance, angle and background temperature is constructed by combining a deep learning model, thereby breaking through the limitations of traditional single factor compensation.

[0023] 6. The trained and optimized model can directly output dynamic emissivity calibration values, avoid frequent parameter adjustment and test piece waste during the experiment, significantly improve the temperature measurement robustness under complex working conditions, and provide reliable protection for the precise closed-loop control of the magnesium alloy hot stretching temperature field. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The flow chart of the magnesium alloy plate surface infrared emissivity calibration method under the warm condition of the present application; Figure 2It is a structure schematic view of the calibration device for the infrared emissivity calibration method of the magnesium alloy sheet under the warm condition of the application. Figure 3 It is a schematic view of the distance measuring device of the application. Figure 4 It is a partial schematic view of the angle adjusting device of the application. Figure 5 It is a schematic view of the control monitoring mechanism of the application. Figure 6 It is an architecture diagram of the DFNN neural network model of the application. DETAILED DESCRIPTION

[0025] Hereinafter, the embodiments of the application will be described with reference to the accompanying drawings.

[0026] Specifically, in one aspect, the application provides an infrared emissivity calibration method for a magnesium alloy sheet under a warm condition, as shown in Figure 1 and Figure 2 , comprising the following steps: S1: Adjust the height of the ball screw 10 to reach the same longitudinal height as the position to be measured.

[0027] S2: Turn on the laser indicator 16 and the infrared temperature measuring probe 9 arranged on the sliding table 15 of the ball screw 10, and drive the ball screw 10 with the servo motor 11 to move the infrared temperature measuring probe 9 to the desired position to be measured.

[0028] S3: Rotate the cast aluminum heating plate 7 and change its inclination angle, so that the angle sensor 13 displays the target angle parameter.

[0029] S4: Start the heating system, input the target temperature on the heating control panel 21, and the cast aluminum heating plate 7 starts to heat until the cast aluminum heating plate 7 reaches the target temperature.

[0030] S5: Under different temperature conditions, simultaneously collect the distance between the infrared temperature measuring probe 9 and the position to be measured, and the angle data of the cast aluminum heat insulation plate 7, and use the collected distance and angle data set to train the existing basic neural network system.

[0031] S6: Analyze the training output results, so that the prediction value of the training set and the true value error meet the preset error condition.

[0032] S7: Use the trained neural network system to input the target distance between the infrared temperature measuring probe 9 and the position to be measured, and the target angle data of the cast aluminum heat insulation plate 7, to complete the infrared emissivity calibration of the magnesium alloy sheet surface.

[0033] Further, in step S2, a precise light spot is projected by using the collimation characteristics of the laser, the target position of the infrared temperature measuring probe 9 is captured, and the specific coordinates of the target in space are determined by combining the geometric triangulation principle: ; ; In the formula, P=P(Px, Py, Pz) is the target three-dimensional space coordinates of the magnesium alloy plate surface point to be measured, i.e. the actual measured position of the infrared; L=L(Lx, Ly, Lz) is the installation position of the laser indicator 16 on the platform, which is determined by the ball screw 10 drive; d=d(dx, dy, dz) is the normalized direction vector of the light beam emitted by the laser indicator 16, representing the collimation projection direction of the laser; I=I(Ix, Iy, Iz) is the installation position of the infrared temperature measuring probe 9 on the sliding table 15; v=v(vx, vy, vz) is the normalized detection direction vector of the infrared temperature measuring probe 9, indicating the aiming direction of the probe optical axis; k is the straight line distance from the laser source to the target point on the surface of the magnesium alloy plate.

[0034] In step S6, the preset error condition of the error between the prediction value and the true value of the training set includes NRMSE<0.1, determining that the model is in the first state, determining that the model is in the second state. Wherein, the model in the first state means that the model is in an excellent state; the model in the second state means that the model is in an invalid state.

[0035] Wherein, the error between the prediction value and the true value of the training set satisfies the following conditions: ; In the formula, is the standard deviation of the target variable, is the normalized root mean square error, and MSE is the mean square error.

[0036] In addition, the error between the prediction value and the true value is summarized as a loss function for measuring the current good or bad of the model. By calculating the gradient, the direction of the weight adjustment is indicated, and each update of the weight is driven. The ultimate goal is to make the prediction value output by the model more and more close to the corresponding true value as a whole.

[0037] On the other hand, the present application provides a calibration device for calibrating the infrared emissivity of the magnesium alloy plate surface under warm conditions, such as Figures 2-5As shown, it comprises a distance measuring module 24, an angle adjusting module 25, a heating module 26 and a control monitoring module 27, the distance measuring module 24 comprises a ball screw 10, a servo motor 11, an infrared temperature measuring probe 9 and a laser indicator 16, the servo motor 11 is installed at the second end of the ball screw 10, a sliding table 15 is arranged on the ball screw 10, the first side of the sliding table 15 is installed with the infrared temperature measuring probe 9, and the second side of the sliding table 15 is installed with the laser indicator 16.

[0038] The angle adjusting module 25 comprises a hand wheel 3 and a worm gear reducer 4, the heating module 26 comprises a fixed clamp 5, an insulating plate 6 and an aluminum casting heating plate 7, the aluminum casting heating plate 7 is arranged at the first side of the insulating plate 6, the fixed clamp 5 is arranged at the second side of the insulating plate 6 and is arranged as a U-shaped plate, the aluminum casting heating plate is connected with the output shaft of the worm gear reducer 4 through a rotating support 14, the hand wheel is connected with the input shaft of the worm gear reducer 4, and an angle sensor 13 is arranged at the middle position of the second side of the aluminum casting heating plate 7.

[0039] The control detection module 27 comprises a screw sensor 20, a heating plate temperature sensor 21 and an infrared temperature sensor 22, the first end of the control detection module 27 is the screw sensor 21, which is used for monitoring the calibration distance of the infrared temperature measuring probe on the screw rod and the measured position, the middle position of the control detection module 27 is provided with the heating plate temperature sensor 22, which is used as the main means for inputting temperature and monitoring the overall temperature environment, and the second end of the control detection module 27 is the infrared temperature sensor 23, which is used for monitoring the temperature of the measured position, judging whether the temperature of the measured position is consistent with the predetermined temperature of the heating plate, and calibrating the infrared emissivity.

[0040] Further, the distance measuring module 24, the angle adjusting module 25 and the heating module 26 are all installed on the profile 1 and the longitudinal profile 2, and the profile 1 and the longitudinal profile 2 are connected through the corner piece 8. The rotating support 14 is installed on the support frame profile 1 through the bearing seat 20. The fixed clamp 5 is arranged in a U shape, and the first side and the second side of the fixed clamp 5 are respectively provided with clamping assemblies 28. The clamping assembly 28 comprises a movable clamp plate 17, an adjusting screw 18 and a rotating rod 19, the adjusting screw 18 is provided with two, which are respectively arranged at the first side and the second side of the fixed clamp 5, the movable clamp plate 17 is arranged at the second end of the adjusting screw 18, and the first end of the adjusting screw 18 is provided with the rotating rod 19. The control monitoring module 27 is arranged at the second end of the support frame profile 1 and the longitudinal profile 2.

[0041] In step S5, as shown in the figure, Figure 6 The neural network system is composed of an input layer, a hidden layer and an output layer: 1. Input layer: receiving feature vector .

[0042] 2. Hidden Layers: Each layer undergoes linear transformations and non-linear activations. The output of layer 1 is: ; in, This is the activation function.

[0043] 3. Output layer.

[0044] Specifically, such as Figures 2-5 As shown, in this infrared emissivity calibration device for magnesium alloy sheet surfaces suitable for warm and hot environments, the main frame is constructed from profiles. A stable profile frame structure is formed through the tight fit of profiles 1 of varying lengths and corner fittings 8. Key components are installed inside the mechanism, including a ball screw 10, a worm gear reducer 4, and a rotating support 14. Specifically, the profile 1 is designed with corner fittings 8 for mounting the ball screw 10, ensuring a tight fit and secure fixation. The drive mechanism is equipped with a servo motor 11 and a handwheel 3. The first end of the worm gear reducer 4 is connected to the rotating support 14, while the handwheel 3 is used for precise control of rotation.

[0045] The cast aluminum heating plate 7 serves as the heating element. Four precision threaded holes are machined on both sides of the cast aluminum heating plate 7. It is fixed to the rotating bracket 14 and can rotate together with it. The rotating bracket 14 is fixed to the longitudinal profile 2. To achieve real-time monitoring and precise adjustment of the measured distance and position, the device integrates a laser indicator light 16, an infrared temperature sensor 9, and a distance sensor 12. The infrared temperature sensor 9 and the laser indicator light 16 are fixed on the slide table 15 of the ball screw 10, arranged flush. Furthermore, through the coordinated operation of the rotating bracket 14, the fixing clamp 5, and the angle sensor 13, the fixing and angle control of the alloy sheet can be effectively achieved.

[0046] like Figure 5 As shown, the control and detection module 27 of the present invention controls and monitors the status of the present invention, and responds to relevant data in real time to ensure stable operation and problem feedback during use.

[0047] The alloy sheet after pre-treatment is fixed on the clamp 5, and is close to the cast aluminum heating plate 7, and rotates with the rotating support 14, to ensure good thermal contact and electrical insulation between the sample and the rotating support 14 of the cast aluminum heating plate 7. Start the heating system, the cast aluminum heating plate 7 has alloy heating wires, when the current passes through these heating wires, heat will be generated, and will be uniformly transmitted to the surface of the cast aluminum heating plate 7, and through the mode of heat conduction, the required temperature is reached. The servo motor 11 controls the feeding movement of the ball screw 10 to realize the measured distance, and adjusts and reaches the calibration temperature according to the required temperature condition. The laser indicator light 16 and the infrared temperature measuring probe 9 are aligned with the measured area, the optical system converges the infrared radiation energy of the target in the field of view, the infrared temperature measuring probe 9 as the core component can convert the infrared radiation into an electric signal, the signal processing circuit is responsible for amplifying and filtering the electric signal, and then the worm gear reducer 4 is adjusted and stabilized to collect data under different conditions, integrate the data set, and accurately find the matching infrared emissivity under the current conditions through the neural network training method.

[0048] The implementation of the embedded system of the application includes the following key steps: Time domain feature smoothing processing: ; Sliding window width Second.

[0049] Network parameter quantization acceleration: 8-bit fixed-point encoding is performed on the weight matrix: ; Adaptive incremental learning: When the real-time error Trigger update: ; Learning rate The number of new samples.

[0050] The above-described embodiments only describe the preferred embodiments of the application, and do not limit the scope of the application, and various modifications and improvements to the technical solutions of the application made by those skilled in the art without departing from the design spirit of the application shall fall within the protection scope of the claims of the application.

Claims

1. A method for calibrating the surface infrared emissivity of a magnesium alloy sheet under warm conditions, characterized by: It comprises the following steps: S1: adjust the height of the ball screw to the same longitudinal height as the position to be measured; S2: turn on the laser indicator and infrared temperature probe arranged on the ball screw sliding table, and drive the ball screw with the servo motor to move the infrared temperature probe to the position to be measured; S3: rotate the cast aluminum heating plate and change its inclination angle, so that the angle sensor displays the target angle; S4: start the heating system, input the target temperature on the heating control panel, and the cast aluminum heating plate starts to heat until the target temperature is reached; S5: under different temperature conditions, the distance between the infrared temperature probe and the position to be measured, and the angle data of the cast aluminum heat insulation plate are collected at the same time, and the collected distance and angle data are used to train the existing basic neural network system; S6: analyze the training output results, so that the prediction error of the training set and the true value meets the preset error condition; S7: using the trained neural network system, input the target distance between the infrared temperature probe and the position to be measured, and the target angle data of the cast aluminum heat insulation plate, complete the infrared emissivity calibration of the magnesium alloy sheet surface.

2. The method for calibrating the surface infrared emissivity of a magnesium alloy sheet at a warm temperature according to claim 1, characterized in that: In step S2, the collimating property of laser is used to project a light spot, and the target position of the infrared temperature probe is captured to determine the specific coordinates of the target position in space: ； ； In the formula, P=P(Px, Py, Pz) is the target three-dimensional space coordinates of the magnesium alloy plate surface to be measured, that is, the actual measurement position of the infrared probe, L=L(Lx, Ly, Lz) is the installation position of the laser indicator on the sliding table, which is determined by the ball screw drive, d=d(dx, dy, dz) is the normalized direction vector of the laser indicator light beam, representing the collimating projection direction of the laser, I=I(Ix, Iy, Iz) is the installation position of the infrared temperature probe on the sliding table, v=v(vx, vy, vz) is the normalized detection direction vector of the infrared temperature probe, indicating the aiming direction of the probe optical axis, and k is the straight line distance from the laser source to the target point on the magnesium alloy plate surface.

3. The method for calibrating the surface infrared emissivity of a magnesium alloy sheet at a warm temperature according to claim 1, characterized in that: In step S6, the preset error condition of the error between the predicted value of the training set and the true value includes NRMSE < 0.1, determining that the model is in the first state, determining that the model is in the second state.

4. A calibration device for the calibration method of the infrared emissivity of the surface of a magnesium alloy sheet under warm conditions according to one of claims 1 to 3, characterized in that it comprises: It comprises a distance measuring module, an angle adjusting module, a heating module and a control monitoring module; The distance measuring module comprises a ball screw, a servo motor, an infrared temperature probe and a laser indicator, the servo motor is installed on the ball screw, the ball screw is provided with a sliding table, and the infrared temperature probe and the laser indicator are installed on the sliding table; The angle adjusting module comprises a hand wheel and a worm gear reducer, the heating module comprises a fixed clamp, a heat insulation plate and a cast aluminum heating plate, the cast aluminum heating plate is arranged on the heat insulation plate, the fixed clamp is arranged on the heat insulation plate, the cast aluminum heating plate is connected with the worm gear reducer through a rotating support, the hand wheel is connected with the worm gear reducer, and an angle sensor is arranged on the cast aluminum heating plate; The control detection module comprises a lead screw sensor, a heating plate temperature sensor and an infrared temperature sensor, the lead screw sensor is arranged at the first end of the control detection module, the heating plate temperature sensor is arranged at the middle position of the control detection module, and the infrared temperature sensor is arranged at the second end of the control detection module.

5. The calibration device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions according to claim 4, characterized in that: The distance measuring module, the angle adjusting module and the heating module are all installed on the support frame, the support frame is composed of profiles connected with each other, and the profiles are connected with angle pieces.

6. The calibration device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions according to claim 4, characterized in that: The rotating support is installed on the support frame through a bearing seat.

7. The calibration device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions according to claim 4, characterized in that: The fixing clamp is in a U shape, and the first side and the second side of the fixing clamp are respectively provided with clamping assemblies.

8. The calibration device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions according to claim 7, characterized in that: The clamping assembly comprises a movable clamping plate, an adjusting screw and a rotating rod, two adjusting screws are arranged on the first side and the second side of the fixing clamp respectively, the movable clamping plate is arranged on the adjusting screw, and the first end of the adjusting screw is provided with the rotating rod.

9. The calibration device for calibrating the surface infrared emissivity of a magnesium alloy plate under warm conditions according to claim 4, characterized in that: The distance measuring module, the angle adjusting module and the heating module are arranged at the first end of the support frame, and the control monitoring module is arranged at the second end of the support frame.

Images