Digital wind tunnel balance temperature effect compensation method

Abstract

The invention discloses a digital wind tunnel balance temperature effect compensation method, which comprises the following steps: constructing a steady-state zero drift compensation function, a steady-state sensitivity drift compensation function and a dynamic temperature gradient influence compensation function, and compensating a wind tunnel balance model based on each compensation function to obtain a wind tunnel balance temperature effect compensation model; the temperature measurement module is installed on the wind tunnel balance, and debugging of the temperature measurement module is completed; finishing static calibration of the wind tunnel balance; and putting the wind tunnel balance into a high-low temperature box for experiment, obtaining experiment data based on the temperature measurement module, and substituting the experiment data into the wind tunnel balance temperature effect compensation model to obtain the load value of each component of the wind tunnel balance after compensation. According to the method, the original wind tunnel balance model is corrected by using the temperature data, so that the purpose of compensating the temperature effect of the wind tunnel balance is achieved, the influence of the temperature effect on the measurement of the wind tunnel balance is effectively reduced, and the measurement accuracy of the wind tunnel balance is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of static calibration of wind tunnel balances, and in particular relates to a temperature effect compensation method for a digital wind tunnel balance. Background Art

[0002] A wind tunnel balance is a multi-component force measuring device that can decompose and accurately measure the forces and moments acting on the model along the axis. It is the core equipment for aerodynamic measurement in wind tunnel experiments. Before each balance is officially put into use, it needs to be statically calibrated to obtain the balance formula. The accuracy of the calibration directly affects the accuracy and uncertainty of the balance measurement, as well as the quality of the wind tunnel experiment data, and is an important indicator of the wind tunnel balance.

[0003] Normally, there is a fixed correspondence between the voltage signal increment of the balance and the applied load. However, when the wind tunnel experiment time is relatively long, there is high-temperature and high-pressure airflow flowing through the internal flow field, and the jet drop pressure ratio is simulated, the heat of the flow field will be transferred to the balance through heat conduction and other means, causing the balance temperature to change significantly and produce a temperature effect. If it cannot be effectively corrected, it will cause a large experimental error, seriously affecting the credibility and availability of the experimental data. Summary of the invention

[0004] The technology of the present invention solves the problem: overcomes the shortcomings of the prior art and provides a method for compensating the temperature effect of a digital wind tunnel balance. By adding a compensation function to the original wind tunnel balance formula, the steady-state zero drift, steady-state sensitivity drift and dynamic temperature gradient influence of the wind tunnel balance caused by temperature changes are corrected, which is of great significance in practical applications.

[0005] In order to solve the above technical problems, the present invention discloses a digital wind tunnel balance temperature effect compensation method, comprising:

[0006] The piecewise cubic Hermite interpolation method is used to construct the steady-state zero drift compensation function and the steady-state sensitivity drift compensation function.

[0007] The random forest algorithm is used to construct a dynamic temperature gradient impact compensation function;

[0008] Based on the steady-state zero drift compensation function, steady-state sensitivity drift compensation function and dynamic temperature gradient influence compensation function, the wind tunnel balance model is compensated to obtain the wind tunnel balance temperature effect compensation model.

[0009] Install the temperature measurement module on the wind tunnel balance and complete the debugging of the temperature measurement module to ensure that the temperature data collection and transmission functions of the temperature measurement module are normal;

[0010] Complete static calibration of the wind tunnel balance;

[0011] The wind tunnel balance is placed in a high and low temperature box for experiments. Based on the temperature measurement module, the experimental data are obtained and substituted into the wind tunnel balance temperature effect compensation model to obtain the load values ​​of each component of the wind tunnel balance after compensation.

[0012] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the temperature measurement module includes multiple temperature sensors for real-time acquisition of the surface temperature of various parts of the wind tunnel balance, and performs A / D conversion to transmit the temperature data to the computer in the form of digital signals.

[0013] In the above-mentioned digital wind tunnel balance temperature effect compensation method,

[0014] The steady-state zero drift compensation function characterizes the change of zero voltage value with temperature; the zero voltage value of the wind tunnel balance at different temperatures is predicted by the steady-state zero drift compensation function, so as to realize the compensation of the steady-state zero drift of the wind tunnel balance model;

[0015] Steady-state sensitivity drift compensation function, used to realize compensation for the steady-state sensitivity drift of the wind tunnel balance model;

[0016] The dynamic temperature gradient compensation function is used to compensate for the dynamic temperature gradient influence of the wind tunnel balance model.

[0017] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the steady-state zero drift compensation function is constructed in the following way:

[0018] Under the condition of no load, the zero-point voltage value of the wind tunnel balance at different steady-state temperatures is collected and interpolated using the piecewise cubic Hermite interpolation method to obtain the steady-state zero-point drift compensation function f. 0 (T):

[0019]

[0020] Among them, α i-1 (T), α i (T), β i-1 (T) and β i (T) represents the four cubic polynomial basis functions constructed, y i represents the zero-point voltage value at the i-th temperature measurement point, and T represents the wind tunnel balance temperature.

[0021] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the steady-state sensitivity drift compensation function is constructed in the following way:

[0022] A 5kg weight was loaded on the wind tunnel balance at different steady-state temperatures. When the temperature change of the wind tunnel balance was less than 0.05°, voltage data was collected. The voltage increment of the wind tunnel balance before and after loading was calculated. The loading and unloading of the weight was repeated several times, and the average value of the voltage increment was taken as the voltage increment at the steady-state temperature.

[0023] Using the wind tunnel balance model, calculate the load value at each temperature measurement point; add the compensation value to the main coefficient to compensate for the error between the calculated load value and the actual applied load value, so that the error between the calculated load value and the actual applied load value is less than 0.0001kgf, and record the compensation value at each temperature measurement point;

[0024] According to the compensation values ​​at different temperature measurement points, the piecewise cubic Hermite interpolation method is used to construct a third-order polynomial steady-state sensitivity drift compensation function f s (T):

[0025]

[0026] Among them, λ i-1 (T), λ i (T), η i-1 (T) and η i (T) represent the four constructed cubic polynomial basis functions.

[0027] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the dynamic temperature gradient influence compensation function is constructed in the following way:

[0028] Place the wind tunnel balance in a high and low temperature box, and collect temperature data and zero-point voltage when the wind tunnel balance temperature changes within a certain range;

[0029] According to the steady-state zero-point drift compensation function, the influence of the steady-state temperature effect on the zero-point voltage is removed, and the zero-point voltage error caused by the dynamic temperature gradient is obtained;

[0030] According to the temperature data and the zero-point voltage error caused by the dynamic temperature gradient, multiple regression tree models are constructed based on the random forest algorithm to obtain the dynamic temperature gradient influence compensation function f g (T).

[0031] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the regression tree model is in the form of a binary tree.

[0032] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the regression tree model uses the residual sum of squares SSR of the model predicted zero-point voltage error as a node splitting method to determine the splitting characteristics and threshold of each node of the regression tree.

[0033] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the wind tunnel balance model is expressed as follows:

[0034]

[0035] Among them, F i represents the load value of the i-th component of the wind tunnel balance, α i represents the intercept term, a i represents the main coefficient, It represents the first-order interference correction coefficient of the j-th component load on the i-th component, It represents the interference correction coefficient of the second-order square term and the cross term of each component load on the i-th component, ΔU i Represents the output voltage increment of the i-th component of the balance.

[0036] In the above-mentioned digital wind tunnel balance temperature effect compensation method, the wind tunnel balance temperature effect compensation model is expressed as follows:

[0037]

[0038] Among them, U i Represents the voltage output value of the i-th component.

[0039] The present invention has the following advantages:

[0040] (1) The present invention discloses a method for compensating the temperature effect of a digital wind tunnel balance, which can use the surface temperature data measured by the digital wind tunnel balance and perform temperature compensation on the static calibration of the wind tunnel balance based on this information to improve the measurement accuracy of the wind tunnel balance.

[0041] (2) The present invention discloses a method for compensating temperature effects of a digital wind tunnel balance. By constructing a steady-state zero drift compensation function, a steady-state sensitivity drift compensation function and a dynamic temperature gradient influence compensation function, three temperature effects of steady-state zero drift, steady-state sensitivity drift and dynamic temperature gradient influence are compensated to improve the measurement accuracy of the wind tunnel balance.

[0042] (3) The present invention discloses a method for compensating the temperature effect of a digital wind tunnel balance. The method performs compensation based on a balance formula and corrects the output voltage increment and the principal term coefficient. The corrected balance formula can reduce the error caused by the temperature effect to improve the measurement accuracy of the wind tunnel balance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of a method for compensating temperature effect of a digital wind tunnel balance in an embodiment of the present invention;

[0044] Figure 2 is a schematic diagram of a steady-state zero drift compensation function in an embodiment of the present invention;

[0045] Figure 3 is a schematic diagram of a steady-state sensitivity drift compensation function in an embodiment of the present invention;

[0046] Figure 4 is a schematic diagram of compensation results of a steady-state sensitivity drift compensation function in an embodiment of the present invention;

[0047] Figure 5 It is a schematic diagram of a dynamic temperature gradient influence compensation function in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments disclosed in the present invention will be further described in detail below with reference to the accompanying drawings.

[0049] Reference Figure 1 In this embodiment, the digital wind tunnel balance temperature effect compensation method includes:

[0050] Step 1: Use piecewise cubic Hermite interpolation method to construct steady-state zero drift compensation function and steady-state sensitivity drift compensation function.

[0051] In this embodiment, the steady-state zero drift compensation function characterizes the change of the zero voltage value with temperature; the steady-state zero drift compensation function is used to predict the zero voltage value of the wind tunnel balance at different temperatures, thereby realizing compensation for the steady-state zero drift of the wind tunnel balance model. The steady-state sensitivity drift compensation function is used to realize compensation for the steady-state sensitivity drift of the wind tunnel balance model.

[0052] Preferably, the steady-state zero drift compensation function can be constructed in the following manner:

[0053] Under the condition of no load, the zero-point voltage value of the wind tunnel balance at different steady-state temperatures is collected and interpolated using the piecewise cubic Hermite interpolation method to obtain the steady-state zero-point drift compensation function f. 0 (T):

[0054]

[0055] Among them, α i-1 (T), α i (T), β i-1 (T) and β i (T) represents the four cubic polynomial basis functions constructed, y i represents the zero-point voltage value at the i-th temperature measurement point, and T represents the wind tunnel balance temperature.

[0056] Preferably, the steady-state sensitivity drift compensation function can be constructed in the following manner:

[0057] A 5kg weight was loaded on the wind tunnel balance at different steady-state temperatures. Voltage data was collected when the temperature change of the wind tunnel balance was less than 0.05°. The voltage increment of the wind tunnel balance before and after loading was calculated. The loading and unloading of the weight was repeated multiple times, and the average value of the voltage increment was taken as the voltage increment at steady-state temperature.

[0058] Using the wind tunnel balance model, calculate the load value at each temperature measurement point.

[0059] Due to the steady-state temperature effect, there will be a large error between the calculated load value and the actual applied load value. Therefore, a compensation value is added to the main coefficient to compensate for the error between the calculated load value and the actual applied load value, so that the error between the calculated load value and the actual applied load value is less than 0.0001kgf, and the compensation value at each temperature measurement point is recorded.

[0060] According to the compensation values ​​at different temperature measurement points, the piecewise cubic Hermite interpolation method is used to construct a third-order polynomial steady-state sensitivity drift compensation function f s (T):

[0061]

[0062] Among them, λ i-1 (T), λ i (T), η i-1 (T) and η i (T) represent the four constructed cubic polynomial basis functions.

[0063] Step 2: Use the random forest algorithm to construct a dynamic temperature gradient impact compensation function.

[0064] In this embodiment, the dynamic temperature gradient impact compensation function is used to compensate for the dynamic temperature gradient impact of the wind tunnel balance model.

[0065] Preferably, the dynamic temperature gradient impact compensation function can be constructed in the following manner:

[0066] The wind tunnel balance is placed in a high and low temperature box, and the temperature data and zero-point voltage are collected when the wind tunnel balance temperature changes within a certain range.

[0067] According to the steady-state zero-point drift compensation function, the influence of the steady-state temperature effect on the zero-point voltage is removed, and the zero-point voltage error caused by the dynamic temperature gradient is obtained.

[0068] According to the temperature data and the zero-point voltage error caused by the dynamic temperature gradient, multiple regression tree models are constructed based on the random forest algorithm to obtain the dynamic temperature gradient influence compensation function f g(T). The regression tree model is in the form of a binary tree; when constructing the regression tree model, the residual sum of squares (SSR) of the model prediction zero-point voltage error is used as the node splitting method to determine the splitting characteristics and threshold of each node of the regression tree.

[0069] Step 3: Based on the steady-state zero drift compensation function, the steady-state sensitivity drift compensation function and the dynamic temperature gradient influence compensation function, the wind tunnel balance model is compensated to obtain a wind tunnel balance temperature effect compensation model.

[0070] In this embodiment, the original wind tunnel balance model before compensation is expressed as follows:

[0071]

[0072] Among them, F i represents the load value of the i-th component of the wind tunnel balance, α i represents the intercept term, a i represents the main coefficient, It represents the first-order interference correction coefficient of the j-th component load on the i-th component, It represents the interference correction coefficient of the second-order square term and the cross term of each component load on the i-th component, ΔU i Represents the output voltage increment of the i-th component of the balance.

[0073] The temperature effect compensation model of the wind tunnel balance obtained after compensation is expressed as follows:

[0074]

[0075] Among them, U i Represents the voltage output value of the i-th component.

[0076] Step 4: Install the temperature measurement module on the wind tunnel balance and complete the debugging of the temperature measurement module to ensure that the temperature data collection and transmission functions of the temperature measurement module are normal.

[0077] In this embodiment, the temperature measurement module includes a plurality of temperature sensors for collecting the surface temperature of various parts of the wind tunnel balance in real time, performing A / D conversion, and transmitting the temperature data to the computer in the form of digital signals.

[0078] Step 5, complete the static calibration of the wind tunnel balance.

[0079] Step 6: Place the wind tunnel balance in a high and low temperature box for experiment, obtain experimental data based on the temperature measurement module, substitute the experimental data into the wind tunnel balance temperature effect compensation model, and obtain the load value of each component of the wind tunnel balance after compensation.

[0080] Based on the above embodiment, a specific example is described below.

[0081] (1) Install the temperature measurement module on the wind tunnel balance and debug the temperature data acquisition and transmission functions so that it can collect the surface temperature of various parts of the wind tunnel balance in real time through multiple temperature sensors, perform A / D conversion, and transmit the temperature data to the computer in the form of digital signals.

[0082] (2) Install the wind tunnel balance on the balance calibration stand, complete the static calibration, and determine the wind tunnel balance model.

[0083] (3) Construct a steady-state zero drift compensation function. Place the wind tunnel balance in a high and low temperature chamber, collect the zero voltage values ​​of the balance at five steady-state temperatures: -30°C, -10°C, 10°C, 30°C, and 50°C, and perform piecewise cubic Hermite interpolation to obtain a steady-state zero drift compensation function, as shown in Figure 2 shown.

[0084] (4) Check the prediction accuracy of the steady-state zero drift compensation function. A test experiment was conducted, and the test temperature was selected at 4 measurement points, namely -20℃, 0℃, 20℃, and 40℃, to test the interpolation accuracy. The results are shown in Table 1 below:

[0085]

[0086] Table 1. Schematic diagram of the test results of the steady-state zero drift compensation function

[0087] (5) Construct a steady-state sensitivity drift compensation function. Place the wind tunnel balance in a high and low temperature chamber, and select 5 groups of steady-state temperature measurement points, namely -30℃, -10℃, 10℃, 30℃ and 50℃. Measure the voltage increment after applying a 5kg weight at each temperature measurement point, repeat 9 times, remove the maximum and minimum values, calculate the average value of the remaining 7 groups of voltage increments, and use the average value as the voltage increment at the temperature measurement point. Calculate the voltage increment at the 5 temperature measurement points, and use the original wind tunnel balance formula to calculate the load value at each temperature measurement point. Due to the steady-state temperature effect, there will be a large error between the calculated load value and the applied load value. Add a compensation value to the main coefficient to compensate for the error so that the error is less than 0.0001kgf. Record the compensation value at each temperature measurement point, and then use the piecewise cubic Hermite interpolation algorithm for interpolation to construct the steady-state sensitivity drift compensation function of the main coefficient, as follows: Figure 3 shown.

[0088] (6) To verify the prediction accuracy of the steady-state sensitivity drift compensation function, eight temperature measurement points were selected, including -20°C, -5°C, 0°C, 5°C, 15°C, 25°C, 35°C, and 45°C. At each temperature measurement point, the voltage increment of the 5kg weight was measured using the same method, and then the load value was calculated using the compensated balance formula, as shown in Table 2 and Figure 4 As shown:

[0089]

[0090]

[0091] Table 2, schematic diagram of the correction results of the steady-state sensitivity drift compensation function

[0092] (7) Construct a dynamic temperature gradient error compensation function. Place the wind tunnel balance in a high and low temperature box, wrap one end of the wind tunnel balance with multiple layers of plastic film, and leave the other end untreated, so that the thermal conductivity at both ends of the wind tunnel balance is different. The temperature change range is designed to be 50℃~-30℃ and -30℃~50℃. During the temperature change, record the zero point voltage signal of the balance and the readings of each temperature sensor every 1 minute, and repeat 3 times.

[0093] (8) The steady-state sensitivity drift compensation function constructed in step (3) is used to remove the influence of the steady-state zero-point drift, and the remaining zero-point voltage error is caused by the influence of the dynamic temperature gradient.

[0094] (9) Select the random forest algorithm to construct the dynamic temperature gradient compensation function and establish the relationship between the balance temperature and the zero voltage error. Randomly select 80% of the samples as training samples and 20% of the samples as test samples. The number of regression trees is set to 10. During the training process, each tree randomly extracts 80% of the training samples with replacement for training. The training features are all features without removal. The minimum number of samples is 20. The node splitting method selects the SSR indicator. After the training is completed, the model (dynamic temperature gradient compensation function) is tested with the test samples, as shown in the following figure. Figure 5 shown.

[0095] (10) The final wind tunnel balance temperature effect compensation model is obtained:

[0096]

[0097] It should be noted that the embodiment of the present invention only takes the resistance component as an example to introduce the implementation steps of the method of the present invention. It is worth noting that the method can also be applied to temperature compensation of other components. The interpolation method used in the embodiment of the present invention is the piecewise cubic Hermite interpolation method. It is worth noting that other interpolation methods, such as Lagrange interpolation and cubic spline interpolation, are also applicable. The machine learning algorithm used in the embodiment of the present invention is the random forest algorithm. It is worth noting that other machine learning algorithms, such as the convolutional neural network algorithm, are also applicable.

[0098] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

[0099] The contents not described in detail in the specification of the present invention belong to the common knowledge of the professionals in this field.

Claims

1. A digital wind tunnel balance temperature effect compensation method, characterized in that: include: The piecewise cubic Hermite interpolation method is used to construct the steady-state zero drift compensation function and the steady-state sensitivity drift compensation function. The random forest algorithm is used to construct a dynamic temperature gradient impact compensation function; Based on the steady-state zero drift compensation function, steady-state sensitivity drift compensation function and dynamic temperature gradient influence compensation function, the wind tunnel balance model is compensated to obtain the wind tunnel balance temperature effect compensation model. Install the temperature measurement module on the wind tunnel balance and complete the debugging of the temperature measurement module to ensure that the temperature data collection and transmission functions of the temperature measurement module are normal; Complete static calibration of the wind tunnel balance; The wind tunnel balance is placed in a high and low temperature box for experiments. Based on the temperature measurement module, the experimental data are obtained and substituted into the wind tunnel balance temperature effect compensation model to obtain the load values ​​of each component of the wind tunnel balance after compensation.

2. The digital wind tunnel balance temperature effect compensation method according to claim 1 is characterized in that: The temperature measurement module includes multiple temperature sensors, which are used to collect the surface temperature of various parts of the wind tunnel balance in real time, perform A / D conversion, and transmit the temperature data to the computer in the form of digital signals.

3. The digital wind tunnel balance temperature effect compensation method according to claim 1 is characterized in that: The steady-state zero drift compensation function characterizes the change of zero voltage value with temperature; the zero voltage value of the wind tunnel balance at different temperatures is predicted by the steady-state zero drift compensation function, so as to realize the compensation of the steady-state zero drift of the wind tunnel balance model; Steady-state sensitivity drift compensation function, used to realize compensation for the steady-state sensitivity drift of the wind tunnel balance model; The dynamic temperature gradient compensation function is used to compensate for the dynamic temperature gradient influence of the wind tunnel balance model.

4. The digital wind tunnel balance temperature effect compensation method according to claim 1 is characterized in that: The steady-state zero drift compensation function is constructed as follows: Under the condition of no load, the zero-point voltage value of the wind tunnel balance at different steady-state temperatures is collected and interpolated using the piecewise cubic Hermite interpolation method to obtain the steady-state zero-point drift compensation function f0(T): Among them, α i-1 (T), α i (T), β i-1 (T) and β i (T) represents the four cubic polynomial basis functions constructed, y i represents the zero-point voltage value at the i-th temperature measurement point, and T represents the wind tunnel balance temperature.

5. The digital wind tunnel balance temperature effect compensation method according to claim 4 is characterized in that: The steady-state sensitivity drift compensation function is constructed as follows: A 5kg weight was loaded on the wind tunnel balance at different steady-state temperatures. When the temperature change of the wind tunnel balance was less than 0.05°, voltage data was collected. The voltage increment of the wind tunnel balance before and after loading was calculated. The loading and unloading of the weight was repeated several times, and the average value of the voltage increment was taken as the voltage increment at the steady-state temperature. Using the wind tunnel balance model, calculate the load value at each temperature measurement point; Add the compensation value to the main coefficient to compensate for the error between the calculated load value and the actual applied load value, so that the error between the calculated load value and the actual applied load value is less than 0.0001kgf, and record the compensation value at each temperature measurement point; According to the compensation values ​​at different temperature measurement points, the piecewise cubic Hermite interpolation method is used to construct a third-order polynomial steady-state sensitivity drift compensation function f s (T): Among them, λ i-1 (T), λ i (T), η i-1 (T) and η i (T) represent the four constructed cubic polynomial basis functions.

6. The digital wind tunnel balance temperature effect compensation method according to claim 5 is characterized in that: The dynamic temperature gradient impact compensation function is constructed as follows: Place the wind tunnel balance in a high and low temperature box, and collect temperature data and zero-point voltage when the wind tunnel balance temperature changes within a certain range; According to the steady-state zero-point drift compensation function, the influence of the steady-state temperature effect on the zero-point voltage is removed, and the zero-point voltage error caused by the dynamic temperature gradient is obtained; According to the temperature data and the zero-point voltage error caused by the dynamic temperature gradient, multiple regression tree models are constructed based on the random forest algorithm to obtain the dynamic temperature gradient influence compensation function f g (T).

7. The digital wind tunnel balance temperature effect compensation method according to claim 6 is characterized in that: The regression tree model is in the form of a binary tree.

8. The digital wind tunnel balance temperature effect compensation method according to claim 6 is characterized in that: The regression tree model uses the residual sum of squares (SSR) of the model's predicted zero-point voltage error as a node splitting method to determine the splitting characteristics and thresholds of each node in the regression tree.

9. The digital wind tunnel balance temperature effect compensation method according to claim 6 is characterized in that: The wind tunnel balance model is expressed as follows: Among them, F i represents the load value of the i-th component of the wind tunnel balance, α i represents the intercept term, a i represents the main coefficient, It represents the first-order interference correction coefficient of the j-th component load on the i-th component, It represents the interference correction coefficient of the second-order square term and the cross term of each component load on the i-th component, ΔU i Represents the output voltage increment of the i-th component of the balance.

10. The digital wind tunnel balance temperature effect compensation method according to claim 9 is characterized in that: The wind tunnel balance temperature effect compensation model is expressed as follows: Among them, U i Represents the voltage output value of the i-th component.

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