Liquid rocket engine test spectral radiation thermodetector curve fitting method, computer and storage medium

Abstract

The invention discloses a liquid rocket engine test spectral radiation thermodetector curve fitting method, a computer and a storage medium, and aims to realize accurate processing of spectral radiation temperature measurement data according to the temperature measurement requirement of a liquid rocket engine. The method comprises the following steps: firstly, establishing an electric signal-brightness temperature corresponding relation, pre-dividing a measured temperature zone, fitting an electric signal-temperature curve by using a least square method, then introducing a genetic algorithm, solving an optimal brightness temperature range division mode, and finally, calculating the brightness temperature range according to the optimal temperature zone division mode and the fitted electric signal-brightness temperature curve. And the target true temperature and the emissivity under different wavelengths are solved, so that the measurement precision of the spectral radiation thermodetector is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the field of temperature measurement in liquid rocket engine tests, and particularly relates to a curve fitting method, a computer, and a storage medium for a spectral radiation thermometer in liquid rocket engine tests. Background Technique

[0002] During the test of a liquid rocket engine, the temperature of the outer wall of the engine combustion chamber is one of the important parameters to be measured. The temperature of the combustion chamber of a steadily operating engine can reach as high as 1000°C to 2000°C. By measuring the change in the combustion chamber temperature, the working performance of the engine can be timely and effectively reflected, and at the same time, it also provides an important criterion for emergency shutdown of the test. Currently, a single-point infrared pyrometer is usually used for non-contact temperature measurement of the high temperature generated during the test. However, the emissivity of the engine surface changes continuously during the test, and the infrared pyrometer cannot measure the true temperature of the combustion chamber wall in real time. Based on this, the most advanced method currently is to use spectral radiation thermometry, that is, according to the spectral radiation information at different wavelengths, collect the radiation brightness measurement information of the engine combustion chamber wall, and then obtain the true temperature and spectral emissivity of the combustion chamber through data processing.

[0003] For spectral radiation thermometry equipment, there are also certain differences in the measurement results using different calibration formulas. Currently, there is no clear curve fitting method for the temperature measurement curve of a spectral radiation thermometer. Therefore, how to accurately fit the temperature curve and improve the measurement accuracy of the spectral radiation thermometer is an urgent problem to be solved currently. Summary of the Invention

[0004] In view of this, the present invention provides a curve fitting method for a spectral radiation thermometer in liquid rocket engine tests, aiming to accurately measure the combustion chamber temperature using a spectral radiation thermometer during liquid rocket engine tests.

[0005] The technical solution of the present invention relates to a curve fitting method for a spectral radiation thermometer in liquid rocket engine tests: establishing the correspondence between temperature and electrical signal; using the genetic algorithm to divide the temperature range for the temperature measurement range of the spectral radiation thermometer and solve the optimal temperature range division method; for different temperature ranges, using different calibration formulas to fit the temperature measurement curve. The specific steps are as follows:

[0006] Step 1: Establish the correspondence between electrical signal and brightness temperature

[0007] Based on the electrical signals output by the spectral radiation thermometer at different temperatures, the correspondence between temperature and electrical signal can be obtained; specifically, the temperature value here is the brightness temperature of the spectral radiation thermometer.

[0008] Step 2: Obtain the brightness temperature range division method using the genetic algorithm

[0009] Step 2.1 Randomly divide the spectral radiation thermometer into n temperature zones, and take each division method as an individual in the genetic algorithm population;

[0010] Step 2.2 For each individual in the population, according to the established electrical signal-temperature correspondence in Step 1, use regression to fit the electrical signal-temperature curve, and calculate the correlation coefficient of the regression curve at the same time;

[0011] Step 2.3 Set the maximum number of generations of the genetic algorithm;

[0012] Step 2.4 Set the objective function of the genetic algorithm to maximize the correlation coefficient;

[0013] Step 2.5 Set the penalty function of the genetic algorithm so that the correlation coefficient of any one of the n temperature zones of an individual is not lower than a certain set threshold;

[0014] Step 2.6 Set the final fitness function of the genetic algorithm to consider both the objective function and the penalty function;

[0015] Step 2.7 Run the genetic algorithm, perform selection, crossover, and mutation operations, calculate the optimal individual, and use it as the optimal temperature zone division method;

[0016] Based on this, the optimal temperature zone division solved in Step 2.7 is obtained, and the electrical signal-brightness temperature curve of this division method has been fitted in Step 2.2.

[0017] Step 3: Calculate the true temperature based on the brightness temperature

[0018] Based on the established electrical signal-brightness temperature correspondence, further obtain the true temperature at different wavelengths 1 .

[0019] Since the brightness temperature is a function of the electrical signal, denoted as T′ = f(U), where T′ is the brightness temperature value and U is the output voltage value of the spectral radiation thermometer, and the electrical signal-brightness temperature correspondence is obtained by fitting in Step 2; for the i-th channel of the spectral radiation thermometer:

[0020]

[0021] where is a calibration constant that only depends on the wavelength and is independent of temperature, that is is related to the spectral responsivity of the detector, the transmittance of the optical element, the geometric size, and the first radiation constant at this wavelength; ε(λ i , T) is the target spectral emissivity at temperature T;

[0022] Using Wien's formula to replace Planck's law, Equation (1) can be rewritten as:

[0023]

[0024] Furthermore, for the emissivity ε and the true temperature T, there are some well-known assumed equations:

[0025] lnε(λ, T) = a + bλ (3)

[0026]

[0027] ε(λ, T) = a o + a i λ (5)

[0028]

[0029] ε(λ, T) = exp[-(a o + a1λ) 2 (7)

[0030] Substitute any one of equations (3) to (7) into equation (2), and the target true temperature and spectral emissivity can be obtained by solving the equation method.

[0031] A computer includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of a curve fitting method for a spectral radiation thermometer in a liquid rocket engine test.

[0032] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, it implements a curve fitting method for a spectral radiation thermometer in a liquid rocket engine test.

[0033] The beneficial effects of the present invention are as follows: According to the temperature measurement requirements of a liquid rocket engine, accurate processing of spectral radiation temperature measurement data is achieved. The temperature measurement range of the spectral radiation thermometer is pre-divided, the least squares method is used to fit the electrical signal-temperature curve, and by introducing a genetic algorithm, the optimal temperature range division method is solved. According to the optimal temperature range division method and the fitted electrical signal-bright temperature curve, the target true temperature and the emissivity at different wavelengths are solved, improving the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of this application. The schematic embodiments of the present invention and their descriptions are only used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0036] Figure 1 It is a schematic diagram of the steps of a curve fitting method for a spectral radiation thermometer in a liquid rocket engine test of the present invention;

[0037] Figure 2Schematic diagram of steps for obtaining the division method of brightness temperature range using genetic algorithm. Detailed implementation mode

[0038] The following will respectively combine the attached Figure 1 and the attached Figure 2 to give further explanations on a curve fitting method for a spectral radiation thermometer in a liquid rocket engine test involved in the present invention.

[0039] Example 1: Refer to Figure 1 、 Figure 2 to illustrate this implementation mode. In this example, the temperature fitting range of the spectral radiation thermometer is set to 800°C to 2000°C. The specific operation methods involved are as follows:

[0040] S1: Establish the relationship between electrical signal and brightness temperature

[0041] Calibrate the spectral radiation thermometer using a standard blackbody furnace. The calibration temperature range is 800°C to 2000°C. Operate according to JJG856-2015 "Verification Regulation of Working Radiation Thermometers". Based on the set temperature of the standard blackbody furnace and the output electrical signal value of the spectral radiation thermometer, establish the relationship between electrical signal and brightness temperature. In this example, the temperature calibration step size is set to 50°C;

[0042] Furthermore, in this example, the emissivity of the standard blackbody furnace is 0.999. Therefore, it is considered that the measured brightness temperature is consistent with the true temperature value of the blackbody furnace.

[0043] S2: Obtain the division method of brightness temperature range using genetic algorithm

[0044] S21: Randomly divide 800°C to 2000°C into 3 temperature zones. Each division method is an individual in the genetic algorithm population; Example: individual

[0045] S22: For each individual in the population, according to the relationship between electrical signal and temperature established in S1, use the least squares method to fit the electrical signal-brightness temperature curve and calculate the correlation coefficient R at the same time; Example: the electrical signal-brightness temperature curve of individual A1 The correlation coefficient of the electrical signal-brightness temperature curve of individual A1

[0046] S23: Set the maximum number of generations for the genetic algorithm. In this example, the number of generations is 50;

[0047] S24: Set the objective function to maximize the correlation coefficient R. Preferably, the interval of the correlation coefficient R is [0, 1];

[0048] S25: Set the penalty function so that the correlation coefficient R of each temperature zone of the individual is not less than 80%;

[0049] S26: The final fitness function is the objective function plus the penalty function;

[0050] S27: Run the genetic algorithm, perform selection, crossover, and mutation operations, and finally calculate the optimal individual, which is the optimal temperature zone division method. In this embodiment, the optimal temperature zone division method is A x1 =[800, 1400], A x2 =[1450, 1450], A x3 =[1450, 2000]. Further, since temperature zone A x2 coincides with A x3 the optimal temperature zone division method is A x1 =[800, 1400], A x2 =[1450, 2000];

[0051] Based on this, the optimal temperature zone division solved in step S27 is obtained. At the same time, the electrical signal - brightness temperature curve of this division method has been fitted in step S22.

[0052] S3: Calculate the true temperature based on the brightness temperature

[0053] Further, in this embodiment, since the emissivity of the standard blackbody furnace is 0.999, it is considered that the measured brightness temperature is consistent with the true temperature value of the blackbody furnace, and there is no need to further fit the true temperature curve.

[0054] Embodiment 2: Refer to Figure 1 、 Figure 2 to illustrate this embodiment. In this embodiment, the temperature fitting range of the spectral radiation thermometer is set to 1000°C to 1600°C. The specific operation methods involved are as follows:

[0055] S1: Establish the correspondence between the electrical signal and the brightness temperature

[0056] Use the outer wall of the combustion chamber of a certain type of liquid rocket engine as the radiation source, whose operating temperature range is 1000°C to 1600°C. Aim the spectral radiation thermometer at the outer wall of the combustion chamber of the liquid rocket engine, and at the same time use a standard radiation thermometer to aim at the outer wall of the combustion chamber of the liquid rocket engine, and their positions are symmetrical;

[0057] In this embodiment, the emissivity of the outer wall of the combustion chamber of the liquid rocket engine is unknown;

[0058] When the liquid rocket engine starts to work, according to the measured temperature of the standard radiation thermometer and the output electrical signal value of the spectral radiation thermometer, the correspondence between the electrical signal and the brightness temperature can be established.

[0059] S2: Use the genetic algorithm to obtain the brightness temperature range division method

[0060] S21: Randomly divide the range from 1000 °C to 1700 °C into 3 temperature zones, and each division method is an individual in the genetic algorithm population; set the temperature division step size to 20 °C. For example, an individual

[0061] S22: For each individual in the population, according to the established relationship between the electrical signal and temperature in S1, use the least squares method to fit the electrical signal - brightness temperature curve, and calculate the correlation coefficient R at the same time. For example, the electrical signal - brightness temperature curve of individual A2 The correlation coefficient of the electrical signal - brightness temperature curve of individual A1

[0062] S23: Set the maximum number of generations for the genetic algorithm. In this example, the number of generations is 50;

[0063] S24: Set the objective function to maximize the correlation coefficient R. Preferably, the range of the correlation coefficient R is [0, 1];

[0064] S25: Set the penalty function so that the correlation coefficient R of each temperature zone of the individual is not less than 80%;

[0065] S26: The final fitness function is the objective function plus the penalty function;

[0066] S27: Run the genetic algorithm, perform selection, crossover, and mutation operations, and finally calculate the optimal individual, which is the optimal temperature zone division method. In this embodiment, the optimal temperature zone division method is A y1 =[1000, 1180], A y2 =[1200, 1520], A y3 =[1520, 1600];

[0067] Based on this, the optimal temperature zone division solved in step S27 is obtained. At the same time, the electrical signal - brightness temperature curve of this division method has been fitted in step S22,

[0068] and the electrical signal - brightness temperature curve of this division method fitted in step S22.

[0069] S3: Calculate the true temperature based on the brightness temperature

[0070] Since the brightness temperature is a function of the electrical signal, therefore, denote T' = f(U), where T' is the brightness temperature value, U is the voltage value output by the spectral radiation thermometer, and T is the target true temperature value; the i-th channel of the spectral radiation thermometer satisfies:

[0071]

[0072] where is a calibration constant that only depends on the wavelength and is independent of temperature, that is It is related to the spectral responsivity of the detector, the transmittance of the optical element, the geometric size, and the first radiation constant at this wavelength; ε(λ i , T) is the target spectral emissivity at temperature T;

[0073] Using Wien's formula to replace Planck's law, Equation (8) can be rewritten as:

[0074]

[0075] In this embodiment, the spectral radiation thermometer has 3 measurement channels, namely i = 1, 2, 3;

[0076] Furthermore, for the emissivity ε and the true temperature T, there are some well-known hypothetical equations:

[0077] lnε(λ, T) = a + bλ (10)

[0078]

[0079] ε(λ, T)a o + a i λ (12)

[0080]

[0081] ε(λ, T) = exp[-(a o + a1λ) 2 (14)

[0082] In this embodiment, Equation (10) is used to calculate the true temperature and emissivity. For different radiation wavelengths λ i , the relationship between the true temperature and the bright temperature of the i-th channel is:

[0083]

[0084] Substituting Equation (10) into Equation (11), we get:

[0085]

[0086] Since the radiation wavelength λ i is a manually set value, through the measurement results of 3 measurement channels, the two variables a and b can be solved;

[0087] Then the expressions for the true temperature and spectral emissivity of the measured target are:

[0088]

[0089] where C2 is the second radiation constant and C2 = 14388 μmk, λ fThe wavelength value selected for the spectral radiation thermometer, T′ = f(U) is obtained from step S2, and then the true temperature T and the emissivity ε at each wavelength can be solved.

[0090] In summary, the above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A curve fitting method for a spectral radiation thermometer in a liquid rocket engine test, characterized in that, Including: Step 1: Establish the correspondence between the electrical signal and the brightness temperature; Step 2: Use the genetic algorithm to obtain the division method of the brightness temperature range; Step 3: Calculate the true temperature based on the brightness temperature. The obtaining of the division method of the brightness temperature range by using the genetic algorithm further includes Step 2.1: Randomly divide the spectral radiation thermometer into n temperature zones, and take each division method as an individual in the population of the genetic algorithm; Step 2.2: For each individual in the population, according to the established correspondence between the electrical signal and the temperature in Step 1, use regression to fit the electrical signal-temperature curve, and at the same time calculate the correlation coefficient of the regression curve; Step 2.3: Set the maximum number of generations of evolution of the genetic algorithm; Step 2.4: Set the objective function of the genetic algorithm to be the maximum correlation coefficient; Step 2.5: Set the penalty function of the genetic algorithm to be that the correlation coefficient of any one of the n temperature zones of the individual is not lower than a certain set threshold; Step 2.6: Set the final fitness function of the genetic algorithm to consider both the objective function and the penalty function; Step 2.7: Run the genetic algorithm, perform selection, crossover, and mutation operations, and calculate the optimal individual as the optimal temperature zone division method. Based on this, the optimal temperature zone division solved in Step 2.7 is obtained, and at the same time, the electrical signal-brightness temperature curve of this division method has been fitted in Step 2.

2.

2. The curve fitting method of the spectral radiation thermometer for liquid rocket engine tests as described in claim 1, wherein The establishment of the correspondence between the electrical signal and the brightness temperature further includes According to the electrical signals output by the spectral radiation thermometer at different temperatures, obtain the correspondence between the temperature and the electrical signal.

3. The curve fitting method of the spectral radiation thermometer for liquid rocket engine tests according to claim 1, characterized in that, The temperature value is the brightness temperature of the spectral radiation thermometer.

4. The curve fitting method of the spectral radiation thermometer for liquid rocket engine tests according to claim 1, wherein The calculation of the true temperature based on the brightness temperature further includes: According to the established correspondence between the electrical signal and the brightness temperature, further obtain the true temperature at different wavelengths, where the brightness temperature is a function of the electrical signal T′ = f(U), where T′ is the brightness temperature value and U is the voltage value output by the spectral radiation thermometer; For the i-th channel of the spectral radiation thermometer, there is: wherein is a calibration constant that depends only on wavelength and is independent of temperature, i.e., is related to the spectral responsivity of the detector at that wavelength, the transmittance of the optical element, the geometric dimensions, and the first radiation constant. T is the true temperature, and ε(λ i , T) is the target spectral emissivity at the true temperature T; Furthermore, for the emissivity ε and the true temperature T, there are some well-known hypothetical equations: lnε(λ, T) = a + bλ (2) ε(λ, T) = a o + a l λ (4) ε(λ, T) = exp[-(a o + a1λ) 2 (6) Substitute any one of equations (2) to (6) into equation (1), and the true temperature of the target and the spectral emissivity can be obtained by solving the equation method.

5. The curve fitting method of the spectral radiation thermometer for liquid rocket engine tests according to claim 1, wherein The formula (1) can be rewritten as:

6. A computer, characterized in that, Including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method according to any one of claims 1 to 5.

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