Method and system for measuring temperature and emissivity of high-temperature material

Abstract

The invention provides a method and system for measuring the temperature and emissivity of a high-temperature material, and relates to the technical field of non-contact measurement, the method comprises the following steps: collecting spectral data of the high-temperature material, and carrying out radiation correction on the spectral data; in a spectral range of the spectral data, selecting an emission degree value En and a wavelength value lambda n of NC spectral channels; constructing a target function based on En and lambda n; calculating a numerical solution of the emissivity epsilon n for the target function by adopting an iterative calculation method; calculating a temperature intermediate value by using a numerical solution of epsilon n; the final temperature TOP of the high-temperature material is calculated through the temperature intermediate value; and calculating the emissivity epsilon obj (lambda, TOP) of the high-temperature material by using TOP. In addition, the invention also provides a measuring system which comprises an optical lens, a Fourier spectrometer, a laser, a servo turntable and a data acquisition processor. According to the method, a large amount of spectral data of the spectral channels can be processed in real time, the measurement efficiency and the measurement precision are improved, and the measurement system can realize non-contact measurement of the temperature and the emissivity of the high-temperature material.

Description

Technical Field

[0001] The invention belongs to the field of non-contact measurement, and in particular relates to a method and a system for measuring the temperature and emissivity of a high-temperature material. Background Art

[0002] Temperature is a key physical quantity that indicates the degree of hotness or coldness of a target, and plays an important role in describing the radiation characteristics of a target. Temperature measurement methods include contact temperature measurement and non-contact temperature measurement. Contact temperature measurement methods represented by thermocouple temperature measurement and temperature indicator temperature measurement require direct contact with the surface of the target to measure the temperature, so they have the defects of narrow temperature measurement range and affect the stability of the temperature field on the target surface, which limits the use of this type of technology. For non-contact temperature measurement, compared with single-band temperature measurement and two-color temperature measurement, multi-spectral temperature measurement acts on the spectral data collected for the target, measures the target temperature, and can simultaneously obtain the target emissivity. This temperature measurement method can be measured without destroying the target surface, thereby significantly expanding the temperature measurement distance. At the same time, it has the characteristics of simple operation, fast response speed, and wide temperature measurement range. It can be applied to the temperature and emissivity measurement of high-temperature materials, and has important value in the application directions of aircraft thermal state monitoring and petrochemical refining monitoring.

[0003] According to Planck's law, the target radiation energy is determined by the target temperature and emissivity. Therefore, the core of multi-spectral thermometry is to calculate the target temperature and emissivity through the known radiation wavelength and radiation energy. Traditional multi-spectral radiation thermometry usually relies on establishing a relationship model between the target emissivity and wavelength. The accuracy of the solution is highly dependent on the established emissivity-wavelength relationship model. In actual testing, it is difficult to establish an accurate emissivity and wavelength relationship model due to the unclear target radiation characteristics and the complexity of the emissivity distribution.

[0004] In recent years, researchers have proposed using optimization iterative methods such as gradient projection to act on the objective function constructed by spectral data to invert and calculate the target temperature and emissivity. These methods do not rely on the relationship model between emissivity and wavelength, but require Wien approximation of the objective function and the use of a reference temperature model. Wien approximation is often more effective for high-temperature spectral data in shortwave bands, but these methods cannot randomly process spectral data in arbitrary radiation bands. In addition, these methods are usually only applicable to data from a small number of spectral channels, and the computational efficiency is low when processing data containing a large number of spectral channels, making it difficult to meet real-time measurement requirements. Summary of the invention

[0005] In view of the above problems, the present invention proposes a method for measuring the temperature and emissivity of high-temperature materials. The present invention adopts a multi-spectral temperature measurement method in non-contact temperature measurement, collects spectral data through a Fourier spectrometer, and performs iterative calculations based on the data to obtain the temperature and emissivity of the high-temperature material. The temperature measurement method provided by the present invention is highly efficient, the results are more accurate, and the emissivity of the high-temperature material can be obtained.

[0006] The technical solution adopted by the present invention is as follows:

[0007] A method for measuring temperature and emissivity of a high temperature material comprises the following steps:

[0008] Step 1: Collect spectral data of high temperature materials;

[0009] Step 2: performing radiation correction on the spectral data;

[0010] Step 3: Select N within the spectral range of the spectral data. C The radiance E of the spectral channel n and wavelength λ n ;

[0011] Step 4: Based on the radiance E n and the wavelength value λ n , construct the objective function according to Planck's law

[0012]

[0013] Where c1 is Planck's first constant, c2 is Planck's second constant;

[0014] Step 5: For the objective function constructed in step 4, use the iterative calculation method to calculate the selected N C The emissivity ε of the spectral channels n Numerical solution of ;

[0015] Step 6: Using the emissivity ε n Numerical solution to calculate the intermediate temperature of high temperature materials;

[0016] Step 7: Calculate the final temperature T of the high temperature material using the intermediate temperature value OP ;

[0017] Step 8: Using the Final Temperature T of the High Temperature Material OP Calculate the emissivity ε of high temperature materials obj (λ,T OP ).

[0018] Furthermore, in step 3, select N C The radiance E of the spectral channel n and wavelength λn The method is:

[0019] In the spectral range of the spectral data, calculate the maximum spectral radiance E hMax and the minimum value E hMin , respectively select the corresponding radiance value

[0020]

[0021] Get N C The radiance value E of the spectral channel n and wavelength λ n .

[0022] Furthermore, in step 5, the specific calculation steps of the iterative algorithm used are:

[0023] N C The emissivity ε of the spectral channels n Make a vector Random initialization is performed according to the following expression:

[0024]

[0025] is a vector generated by random initialization, us is the upper limit of the search range, and its value is 1, ls is the lower limit of the search range, and its value is 0, and R1 is a vector composed of variable values ​​uniformly distributed between 0 and 1; according to the random initialization process, multiple vectors are generated to form a group as the initial input of the algorithm;

[0026] Substitute each vector in the generated population into the following formula in turn to iterate and calculate the intermediate solution:

[0027]

[0028] Among them, the parameters pn and rand are random numbers between 0 and 1. is the newly generated intermediate solution, is the candidate solution for the current iteration t, r1, r2, r3 and r4 are the indices of four vectors randomly drawn from the current population, and is a vector of random numbers between 0 and 1, the value range of parameter δ is 0.1-1.0, the value range of scaling parameter χ is 0.7-2.1, and β is the scaling factor, which is calculated as follows:

[0029]

[0030] vector The elements of are random numbers drawn from a normal distribution function with a mean of 0 and a standard deviation of 0, t is the current number of iterations, and T max is the maximum number of times the function is calculated;

[0031] V I is an adaptive adjustment factor, and its calculation expression is

[0032] V I =β×r -1 P -1 (β,1),

[0033] r is a uniformly distributed random number between 0 and 1. -1 is the inverse of r, which is used as the search operator in the entire optimization process. -1 is the incomplete inverse gamma function corresponding to the variable β;

[0034] Will Substitute the objective function to calculate the function value, and update the vector solutions in the population and the current global optimal solution according to the following expression, namely:

[0035]

[0036] Among them, y t+1 represents the updated solution in the population, y g represents the global optimal solution;

[0037] In each iteration, the objective function is calculated according to the above rules and the parameter y is updated. g When the algorithm iterative calculation meets the termination condition, the iterative calculation ends and the global optimal solution y is output g , the y g The objective function The solution is N C The emissivity ε of each spectral channel n Numeric value.

[0038] Furthermore, in step 5, the parameter and The mathematical expressions are:

[0039]

[0040] The value of parameter k is randomly generated between constants k1 and k2. The values ​​of k1 and k2 are 3.52 and 3.89 respectively. The mathematical expression of k is:

[0041] k=k1+R1(k2-k1),

[0042] R1 is a random number uniformly distributed between 0 and 1;

[0043] parameter and The calculation expression is:

[0044]

[0045] is a solution randomly selected from the output population after the tth iteration, is the optimal solution in the population after the tth iteration, is the current global optimal solution, and the calculation expression of norm(·) for the vector is:

[0046]

[0047] Among them, d represents the dimension of each variable in the group, is the normalized input vector, y j Then it is the data of the jth dimension in the input vector;

[0048] parameter The calculation expression is:

[0049]

[0050] represents the input vector, Y mean Represents the average value of each vector in the current group, expressed as:

[0051]

[0052] N is the number of vectors in the group.

[0053] Furthermore, the condition for terminating the algorithm iteration calculation is to set the number of iterations T max , the current number of iterations t satisfies:

[0054] t>T max ,

[0055] Or the objective function value satisfies:

[0056]

[0057] Among them, δ is the threshold for terminating the iteration.

[0058] Further, in step 6, the specific steps of calculating the intermediate temperature value are: N calculated in step 5 C The emissivity ε of each spectral channel n Substitute the value into the following formula to calculate the temperature value T on the selected spectral channel C :

[0059]

[0060] Then take the average temperature value T of each spectral channel O :

[0061]

[0062] T O This is the calculated intermediate temperature value.

[0063] Furthermore, in step 7, the final temperature T of the high temperature material is calculated using the intermediate temperature value. OP The specific steps are: follow the processing flow from step 3 to step 6, and repeat the spectral data processing N S times, calculate N S The middle temperature value T Oi (i=1,2,...,N s ), exclude one of the values ​​one by one, and calculate the remaining N s -1 standard deviation of the values, and get N s The standard deviation of the group values ​​is selected, and the group with the smallest standard deviation value is selected. According to the N s -1 the middle temperature value, calculate the average value, and use this value as the final temperature T of the high temperature material OP .

[0064] Further, in step 8, the final temperature T of the high temperature material is calculated using step 7. OP According to Planck's law, the temperature of each spectral channel λ is calculated as T OP The blackbody radiance E b (λ,T OP ):

[0065]

[0066] E b (λ,T OP ) and high temperature material measurement radiance E obj (λ,T OP ) is divided by the emissivity ε of each spectral channel. obj (λ,T OP ):

[0067]

[0068] The present invention also provides a high temperature material temperature and emissivity measurement system, comprising:

[0069] Optical lenses for collecting radiant energy from high-temperature materials; and

[0070] A Fourier spectrometer, comprising a data input terminal and a data output terminal, wherein the data input terminal is connected to the optical lens to receive the radiation energy collected by the optical lens; the Fourier spectrometer is used to generate spectrum data from the radiation energy; and

[0071] A laser, arranged on the Fourier spectrometer, for indicating a spectrum collection area, wherein the laser emission direction of the laser is parallel to the optical axis of the optical lens; and

[0072] A servo turntable, the Fourier spectrometer is arranged on the servo turntable, and the servo turntable is used to adjust the angle at which the Fourier spectrometer receives energy; and

[0073] A data acquisition processor is connected to the data output terminal. The data acquisition processor receives the spectral data transmitted by the Fourier spectrometer, and uses the above-mentioned high-temperature material temperature and emissivity measurement method to process the spectral data, inversely calculates the temperature and emissivity of the high-temperature material, and displays them.

[0074] Furthermore, the data acquisition processor is a computer.

[0075] Compared with the prior art, the present invention has the following beneficial effects:

[0076] The present invention realizes the long-distance non-contact measurement of temperature and emissivity of high-temperature materials. Without relying on the target emissivity and wavelength relationship model, it completes the inversion calculation of temperature and emissivity of randomly acquired high-temperature material spectral data. It does not use Wien approximation to construct the objective function. It can effectively act on spectral data with a large number of spectral channels and improves the measurement accuracy, so it has a wide range of applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0078] Figure 1 is a schematic diagram of the structure of a high temperature material temperature and emissivity measurement system in one embodiment of the present invention;

[0079] Figure 2 is a flow chart of a method for measuring temperature and emissivity of a high temperature material in one embodiment of the present invention;

[0080] Figure 3is a spectral radiance distribution curve of a standard black body with a spectral range of 8.0 μm-12.0 μm and a temperature of 325° C. used for inversion calculation in one embodiment of the present invention;

[0081] Figure 4 It is a theoretical emissivity curve and a calculated emissivity curve corresponding to the spectral radiation data of a standard black body with a spectral range of 8.0 μm-12.0 μm and a temperature of 325° C. calculated in one embodiment of the present invention.

[0082] In the figure, 1. optical lens; 2. Fourier spectrometer; 3. laser; 4. servo turntable; 5. data acquisition processor. DETAILED DESCRIPTION

[0083] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0084] Embodiment 1

[0085] Embodiment 1 of the present invention provides a method for measuring the temperature and emissivity of a high temperature material, and its control flow chart is as follows: Figure 2 As shown, the specific steps include:

[0086] Step 1: Collect spectral data of high temperature materials;

[0087] Step 2: performing radiation correction on the spectral data;

[0088] Step 3: Calculate the maximum spectral radiance E within the spectral range of the multispectral data hMax and the minimum value E hMin , respectively select the corresponding radiance value as:

[0089]

[0090] Then we can get N C The radiance value E of the spectral channel n and wavelength λ n .

[0091] Step 4: Based on the N obtained in step 3 C The radiance value E of the spectral channel n and wavelength λ n , construct the objective function according to Planck's law:

[0092]

[0093] Among them, c1 is Planck's first constant, and its value is 3.7418×10 -16 W·m 2 , c2 is Planck's second constant, and its value is 1.4398×10 -2 m.K.

[0094] Step 5: The objective function constructed in step 4 is processed by iterative calculation method. The specific calculation process is as follows:

[0095] N C The emissivity value ε of each spectral channel n Make a vector Random initialization is performed according to the following expression:

[0096]

[0097] is a vector generated by random initialization, us and ls are the upper and lower limits of the search range, and R1 is a vector composed of variable values ​​uniformly distributed between 0 and 1. According to the emissivity theory, the numerical range of the emissivity is 0 to 1, so the values ​​of us and ls are 1 and 0, respectively. According to the above random initialization process, multiple vectors are generated and grouped into a group as the initial input of the algorithm.

[0098] Substitute each vector in the group generated by the above process into the following formula in turn to iterate and calculate the intermediate solution:

[0099]

[0100] Among them, the parameters pn and rand are random numbers between 0 and 1. is the newly generated intermediate solution, is the candidate solution for the current iteration t, and r1, r2, r3, and r4 are the indices of four vectors randomly drawn from the current population. and is a vector of random numbers between 0 and 1. The value range of parameter δ is 0.1-1.0, which is set to 0.2 in this calculation. The value range of scaling parameter χ is 0.7-2.1, which is set to 1.0 in this calculation. β is the scaling factor, and its calculation formula is:

[0101]

[0102] vector The elements of are random numbers drawn from a normal distribution with a mean of 0 and a standard deviation of 0, t is the current number of iterations, and T max This is the maximum number of times the function is calculated.

[0103] V I is an adaptive adjustment factor, and its calculation expression is

[0104] V I =β×r -1 P -1 (β,1), (6)

[0105] r is a uniformly distributed random number between 0 and 1. -1 is the inverse of r, which is used as the search operator in the entire optimization process. -1 is the incomplete inverse gamma function corresponding to the variable β.

[0106] parameter and The mathematical expressions are:

[0107]

[0108] The value of parameter k is randomly generated between constants k1 and k2. The values ​​of k1 and k2 are 3.52 and 3.89 respectively. The mathematical expression of k is:

[0109] k=k1+R1(k2-k1), (10)

[0110] R1 is a random number uniformly distributed between 0 and 1.

[0111] parameter and The calculation expression is:

[0112]

[0113] is a solution randomly selected from the output population after the tth iteration, and is the optimal solution in the population after the tth iteration, is the current global optimal solution, and the calculation expression of norm(·) for the vector is:

[0114]

[0115] Among them, d represents the dimension of each variable in the group, is the normalized input vector, y j It is the data of the jth dimension in the input vector.

[0116] parameter The calculation expression is:

[0117]

[0118] represents the input vector, Y mean Represents the average value of each vector in the current group, expressed as:

[0119]

[0120] N is the number of vectors in the group.

[0121] Will Substitute the objective function to calculate the function value, and update the vector solutions in the population and the current global optimal solution according to the following expression, namely:

[0122]

[0123] Among them, y t+1 represents the updated solution in the population, y g represents the global optimal solution.

[0124] Set the number of iterations T max , in each iteration, the objective function is calculated according to the above rules and the parameter y is updated g The condition for the algorithm to terminate iterative calculation is that the current number of iterations t satisfies:

[0125] t>T max , (19)

[0126] Or the objective function value satisfies:

[0127]

[0128] Among them, δ is the threshold for iteration termination, and its value is a minimum value.

[0129] The global optimal solution x output by iteration g The objective function The solution is N C The emissivity ε of the spectral channels n Numeric value.

[0130] Step 6: Substitute the N calculated in step 5 C The emissivity ε of the spectral channels n Substitute the value into the following formula to calculate the temperature value T on the selected spectral channel C :

[0131]

[0132] Then take the average temperature value T of each spectral channel O :

[0133]

[0134] TO This is the calculated intermediate temperature value.

[0135] Step 7: Repeat the process from step 3 to step 6 to process the spectral data N times. S times, calculate N S The middle temperature value T Oi (i=1,2,...,N S ). After eliminating one of the values ​​one by one, calculate the remaining N s -1 standard deviation of the value. According to the above method, we can get N S The standard deviation of the group values, select the group N with the smallest standard deviation value S -1 intermediate temperature value, calculate the average value, and use this value as the final temperature T of the high temperature material OP .

[0136] Step 8: Use step 7 to calculate the final temperature T of the high temperature material OP According to Planck's law, the temperature of each spectral channel λ is calculated as T OP The blackbody radiance E b (λ,T OP ):

[0137]

[0138] E b (λ,T OP ) and high temperature material radiance E obj (λ,T OP ) is divided by the emissivity ε of each spectral channel. obj (λ,T OP ), which is the emissivity of high temperature materials ε obj (λ,T OP ):

[0139]

[0140] The present invention also verifies the measurement method of the temperature and emissivity of the above-mentioned high-temperature material based on the standard black body spectral data with a spectral range of 8.0μm-12.0μm and a temperature of 325°C. The spectral radiance distribution of the standard black body is shown in the figure, and the temperature and emissivity of the standard black body are calculated through the spectral data.

[0141] The calculated emissivity curve of the standard blackbody spectral radiation data with a spectral range of 8.0μm-12.0μm and a temperature of 325℃ was calculated and compared with the theoretical emissivity curve. Figure 4 .

[0142] Embodiment 2

[0143] Embodiment 2 of the present invention provides a system for measuring temperature and emissivity of high temperature materials, such as Figure 1 As shown, the measurement system can be used to perform the above-mentioned method for measuring the temperature and emissivity of the high-temperature material. The measurement system includes an optical lens 1 for collecting the radiation energy of the high-temperature material;

[0144] and a Fourier spectrometer 2, comprising a data input terminal and a data output terminal, wherein the data input terminal is connected to the optical lens 1 to receive the radiation energy collected by the optical lens 1; the Fourier spectrometer 2 is used to generate spectrum data from the radiation energy;

[0145] and a laser 3 for indicating a spectrum collection area, the laser 3 being arranged on the Fourier spectrometer 2, for example, the laser 3 can be mounted on the body of the Fourier spectrometer 2 by threaded connection, gluing, etc.; after calibration, the laser emission direction of the laser 3 is parallel to the optical axis of the optical lens 1;

[0146] and a servo turntable 4, the Fourier spectrometer 2 is arranged on the servo turntable 4, and the angle at which the Fourier spectrometer 2 receives energy can be adjusted by adjusting the pitch and rotation angles of the servo turntable 4;

[0147] And a data acquisition processor 5 is connected to the data output terminal. The data acquisition processor 5 receives the spectral data transmitted by the Fourier spectrometer 2, and uses the measurement method of the temperature and emissivity of the high-temperature material described above to process the spectral data, inversely calculates the temperature and emissivity of the high-temperature material, and displays it. The data acquisition processor 5 can be a computer.

[0148] The measurement system can complete the long-distance non-contact temperature and emissivity measurement of high-temperature materials. The specific measurement process is: adjust the pitch and rotation angles of the servo turntable 4, turn on the laser 3 to indicate the position of the long-distance high-temperature material, and make the optical lens 1 point to the high-temperature material. After turning off the laser 3, the Fourier spectrometer 2 receives the radiation energy of the high-temperature material collected by the optical lens 1 to complete the spectrum collection, and transmits the spectrum data to the data acquisition processor 5. The measurement method of the temperature and emissivity of the high-temperature material described above is used, and the spectrum data is processed by the data acquisition processor 5 to complete the temperature and emissivity measurement of the high-temperature material.

[0149] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0150] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for measuring temperature and emissivity of high temperature materials, characterized in that: The following steps are involved: Step 1: Collect spectral data of high temperature materials; Step 2: performing radiation correction on the spectral data; Step 3: Select N within the spectral range of the spectral data. C The radiance value E of the spectral channel n and wavelength λ n ; Step 4: Based on the radiance value E n and the wavelength value λ n , construct the objective function according to Planck's law Where c1 is Planck's first constant, c2 is Planck's second constant; Step 5: For the objective function constructed in step 4, use the iterative calculation method to calculate the selected N C The emissivity ε of the spectral channels n Numerical solution of ; Step 6: Using the emissivity ε n Numerical solution to calculate the intermediate temperature of high temperature materials; Step 7: Calculate the final temperature T of the high temperature material using the intermediate temperature value OP ; Step 8: Using the Final Temperature T of the High Temperature Material OP Calculate the emissivity ε of high temperature materials obj (λ,T OP ).

2. A method for measuring temperature and emissivity of high temperature materials according to claim 1, characterized in that: In step 3, select N C The radiance value E of the spectral channel n and wavelength λ n The method is: In the spectral range of the spectral data, calculate the maximum spectral radiance E hMax and the minimum value E hMin , respectively select the corresponding radiance value Get N C The radiance value E of the spectral channel n and wavelength λ n .

3. The method for measuring the temperature and emissivity of a high temperature material according to claim 1, characterized in that: In step 5, the specific calculation steps of the iterative algorithm used are: N C The emissivity ε of the spectral channels n Make a vector Random initialization is performed according to the following expression: is a vector generated by random initialization, us is the upper limit of the search range, and its value is 1, ls is the lower limit of the search range, and its value is 0, and R1 is a vector composed of variable values ​​uniformly distributed between 0 and 1; according to the random initialization process, multiple vectors are generated to form a group as the initial input of the algorithm; Substitute each vector in the generated population into the following formula in turn to iterate and calculate the intermediate solution: Among them, the parameters pn and rand are random numbers between 0 and 1. is the newly generated intermediate solution, is the candidate solution for the current iteration t, r1, r2, r3 and r4 are the indices of four vectors randomly drawn from the current population, and is a vector of random numbers between 0 and 1, the value range of parameter δ is 0.1-1.0, the value range of scaling parameter χ is 0.7-2.1, and β is the scaling factor, which is calculated as follows: vector The elements of are random numbers drawn from a normal distribution function with a mean of 0 and a standard deviation of 0, t is the current number of iterations, and T max is the maximum number of times the function is calculated; V I is an adaptive adjustment factor, and its calculation expression is V I =β×r -1 P -1 (b,1), r is a uniformly distributed random number between 0 and 1. -1 is the inverse of r, which is used as the search operator in the entire optimization process. -1 is the incomplete inverse gamma function corresponding to the variable β; Will Substitute the objective function to calculate the function value, and update the vector solutions in the population and the current global optimal solution according to the following expression, namely: Among them, y t+1 represents the updated solution in the population, y g represents the global optimal solution; In each iteration, the objective function is calculated according to the above rules and the parameter y is updated. g When the algorithm iterative calculation meets the termination condition, the iterative calculation ends and the global optimal solution y is output g , the y g The objective function The solution is N C The emissivity ε of each spectral channel n Numeric value.

4. A method for measuring temperature and emissivity of a high temperature material according to claim 3, characterized in that: In step 5, the parameters and The mathematical expressions are: The value of parameter k is randomly generated between constants k1 and k2. The values ​​of k1 and k2 are 3.52 and 3.89 respectively. The mathematical expression of k is: k=k1+R1(k2-k1), R1 is a random number uniformly distributed between 0 and 1; parameter and The calculation expression is: is a solution randomly selected from the output population after the tth iteration, is the optimal solution in the population after the tth iteration, is the current global optimal solution, and the calculation expression of norm(·) for the vector is: Among them, d represents the dimension of each variable in the group, is the normalized input vector, y j Then it is the data of the jth dimension in the input vector; parameter The calculation expression is: represents the input vector, Y mean Represents the average value of each vector in the current group, expressed as: N is the number of vectors in the group.

5. A method for measuring temperature and emissivity of high temperature materials according to claim 4, characterized in that: The condition for terminating the algorithm iteration calculation is to set the number of iterations T max , the current number of iterations t satisfies: t>T max , Or the objective function value satisfies: Among them, δ is the threshold for terminating the iteration.

6. A method for measuring temperature and emissivity of high temperature materials according to claim 5, characterized in that: In step 6, the specific steps for calculating the intermediate temperature value are: N calculated in step 5 C The emissivity ε of each spectral channel n Substitute the value into the following formula to calculate the temperature value T on the selected spectral channel C : Then take the average temperature value T of each spectral channel O : T O This is the calculated intermediate temperature value.

7. A method for measuring temperature and emissivity of high temperature materials according to claim 6, characterized in that: In step 7, the final temperature T of the high temperature material is calculated using the intermediate temperature value. OP The specific steps are: follow the processing flow from step 3 to step 6, and repeat the spectral data processing N S times, calculate N S The middle temperature value T Oi (i=1,2,...,N s ), exclude one of the values ​​one by one, and calculate the remaining N s -1 standard deviation of the values, and get N s The standard deviation of the group values ​​is selected, and the group with the smallest standard deviation value is selected. According to the N s -1 the middle temperature value, calculate the average value, and use this value as the final temperature T of the high temperature material OP .

8. A method for measuring temperature and emissivity of high temperature materials according to claim 7, characterized in that: In step 8, the final temperature T of the high temperature material is calculated using step 7. OP According to Planck's law, the temperature of each spectral channel λ is calculated as T OP The blackbody radiance E b (λ,T OP ): E b (λ,T OP ) and high temperature material measurement radiance E obj (λ,T OP ) is divided by the emissivity ε of each spectral channel. obj (λ,T OP ):

9. A high temperature material temperature and emissivity measurement system, characterized in that: include: Optical lens, used to collect radiation energy from high-temperature materials; and A Fourier spectrometer, comprising a data input terminal and a data output terminal, wherein the data input terminal is connected to the optical lens to receive the radiation energy collected by the optical lens; the Fourier spectrometer is used to generate spectrum data from the radiation energy; and A laser, arranged on the Fourier spectrometer, for indicating a spectrum collection area, and the laser emission direction of the laser is parallel to the optical axis of the optical lens; and A servo turntable, on which the Fourier spectrometer is arranged, and the servo turntable is used to adjust the angle at which the Fourier spectrometer receives energy; and A data acquisition processor is connected to the data output terminal, and receives the spectral data transmitted by the Fourier spectrometer, and uses the measurement method of the temperature and emissivity of the high-temperature material as described in any one of claims 1 to 8 to process the spectral data, inversely calculates the temperature and emissivity of the high-temperature material, and displays them.

10. A temperature and emissivity measurement system according to claim 9, characterized in that: The data acquisition processor is a computer.

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