Explosion field dual temperature measurement time constant ratio solving method based on genetic algorithm

Abstract

The invention provides an explosion field dual temperature measurement time constant ratio solving method based on a genetic algorithm. The explosion field dual temperature measurement time constant ratio solving method comprises the steps of 1, preprocessing a test signal; 2, calculating the value range of the time constant ratio K of each moment; step 3, genetic algorithm population initialization; step four, individual fitness calculation: step 401, compensating the resampled test signal obtained in the step 103 by using each individual in the population of the genetic algorithm; step 402, performing Fourier transform on each group of individual compensation results obtained in the step 401; and step 403, removing low-frequency components in the frequency spectrum of each group of individual compensation results after transformation obtained in the step 402, taking absolute values of amplitudes of high-frequency components in the frequency spectrum, and summing the absolute values to obtain individual fitness. 5, generating a new population; and step 6, carrying out iterative solution. Compared with a traditional method for compensating by utilizing a constant time-constant ratio, the method has the advantages that the time-varying characteristic of the time constant of the thermocouple under the influence of an explosion environment is considered, the time-constant ratio K is solved moment by moment, and the problem of compensation result distortion can be effectively solved.

Description

Technical Field

[0001] The invention belongs to the technical field of damage testing, relates to explosives and warhead power testing, and particularly relates to a method for solving the time constant ratio of double-couple temperature measurement in an explosion field based on a genetic algorithm. Background Art

[0002] Thermobaric and fuel-air explosive warheads possess significant thermal damage capabilities, making them crucial for striking targets deep within tunnels and underground fortifications. Accurately measuring the explosion temperature field is crucial for characterizing the power of these warheads.

[0003] Thermocouple temperature measurement is the primary method for explosion field temperature testing, and insufficient dynamic performance is one of the key issues restricting the accuracy of thermocouple temperature measurement. The dual-couple compensation temperature measurement method uses mutual compensation between thermocouple test results to restore the true temperature, which can effectively compensate for the shortcomings of insufficient dynamic performance of thermocouples. This method has been applied and verified in high-temperature airflow testing of internal combustion engines, and its scenario is similar to that of explosion fields. Therefore, it has also been introduced for application in explosion field temperature testing. Its core principle is: two thermocouples with different performance are arranged at the same measuring point, and the ratio K of their time constants is introduced to eliminate the time constant term in the heat transfer relationship. Then, the dual-couple compensation formula is derived to realize the conversion of test results to true temperature.

[0004] It's generally assumed that thermocouples have stable performance, with the time constant ratio K remaining constant during testing. Pre-calibration methods are used to determine the value of K. However, actual application in explosion fields has revealed that due to the harsh testing environment, the thermocouple surface can become damaged and contaminated by erosion from detonation products, sand, and other debris. This causes the time constant ratio K to change over time, leading to significant distortion in compensation results. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm, so as to solve the technical problem that the distortion of the solution result of the time constant ratio K of double-couple temperature measurement in explosion field in the existing technology needs to be further reduced.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm, the method comprising the following steps:

[0008] Step 1: Test signal preprocessing:

[0009] Step 101: Obtain a valid test signal:

[0010] The pressure signals of thermocouple 1 and thermocouple 2 measured in the test are converted into temperature signals, zero drift is removed, and the signal segment of interest is intercepted to finally obtain a test signal; the test signal includes signal 1 corresponding to thermocouple 1 and signal 2 corresponding to thermocouple 2.

[0011] Step 102: Test signal noise reduction:

[0012] The test signal obtained in step 101 is subjected to signal noise reduction to obtain a noise-reduced test signal.

[0013] Step 103: resampling the test signal:

[0014] The noise-reduced test signal obtained in step 102 is resampled to obtain a resampled test signal.

[0015] Step 2: Calculate the value range of the time constant ratio K at each moment:

[0016] The range of the time constant ratio K at each moment is K real (τ)∈[K min (τ), K max (τ)], where: K min (τ)=max[K by_t1 (τ), K by_t2 (τ)],K max (τ) = kK min (τ);

[0017] Where:

[0018] K real (τ) represents the true value of the time constant ratio K at time τ;

[0019] K min (τ) represents the minimum possible value of the time constant ratio K at time τ;

[0020] K max (τ) represents the maximum possible value of the time constant ratio K at time τ;

[0021] k represents the amplification factor, k>1.

[0022] Step 3: Initialize the genetic algorithm population:

[0023] Within the value range of the time constant ratio K at each moment obtained in step 2, the time constant ratio K(τ) at each moment is initialized, and multiple groups of K(τ) are obtained in the form of n preferred individuals + m random individuals to form the initial population of the genetic algorithm.

[0024] Step 4: Calculation of individual fitness:

[0025] Step 401 : Use each individual in the population of the genetic algorithm to compensate the resampled test signal obtained in step 103 , and obtain compensation results for each group of individuals.

[0026] In step 401, the compensation method is:

[0027]

[0028] Where:

[0029] t i (τ) represents the compensation result temperature value of the i-th group individual at time τ;

[0030] K i (τ) represents the value of the time constant ratio of the individuals in group i at time τ;

[0031] t1 represents the temperature test result of signal 1;

[0032] t2 represents the temperature test result of signal 2;

[0033] τ represents the time point;

[0034] t1(τ) represents the temperature test result of signal 1 at time τ;

[0035] t2(τ) represents the temperature test result of signal 2 at time τ;

[0036] K i (τ) represents the i-th group of individuals at time τ.

[0037] Step 402 , performing Fourier transform on each group of individual compensation results obtained in step 401 to obtain transformed individual compensation results for each group.

[0038] Step 403 , remove the low-frequency components in the spectrum of each group of individual compensation results obtained in step 402 , take the absolute values of the amplitudes of the high-frequency components in the spectrum and sum them to obtain the individual fitness.

[0039] Step 5: Generate a new population:

[0040] According to the individual fitness obtained in step 4, individuals are naturally selected, recombined and mutated to form a new population.

[0041] Step 6, iterative solution:

[0042] Repeat steps 4 and 5 until the solution is completed; take the individual with the highest fitness as the optimal value of the time constant ratio K at each moment.

[0043] The present invention also has the following technical features:

[0044] The specific process of step 2 is:

[0045] Step 201: Read the peak time point τ1 and peak point t of signal 1. 1_max ; Read the peak time point τ2 and peak point t of signal 2 2_max .

[0046] Step 202: Based on the τ1 and t obtained in step 201, 1_max , find the time constant C2(τ1) of signal 2 at the corresponding moment; according to τ2 and t obtained in step 201 2_max , find the time constant C1(τ2) of signal 1 at the corresponding moment.

[0047] Step 203: Compensate the test result of signal 2 according to C2(τ1) and the heat transfer equation obtained in step 202 to obtain the true temperature value t at time τ of signal 2. g_by_t2 (τ); According to C1(τ2) and the heat transfer equation obtained in step 202, the test result of signal 1 is compensated to obtain the true temperature value t at time τ of signal 1 compensated g_by_t1 (τ).

[0048] Step 204, according to the t obtained in step 203 g_by_t2 (τ), and inversely calculate the time constant C of thermocouple 1 at each moment 1_by_t2 (τ); t obtained in step 203 g_by_t1 (τ), and inversely calculate the time constant C of thermocouple 1 at each moment 2_by_t1 (τ).

[0049] Step 205: Based on the C obtained in step 204 1_by_t2 (τ) and C2(τ1) obtained in step 202, a set of possible values K of the time constant ratio K at time τ is obtained by_t2 (τ); according to C obtained in step 204 2_by_t1 (τ) and C1(τ2) obtained in step 202, we can get another set of possible values K of the time constant ratio K at time τ. by_t1 (τ).

[0050] Step 206: Based on the K obtained in step 205 by_t2 (τ) and K by_t1 (τ) Calculate the range of the time constant ratio K at each moment.

[0051] Compared with the prior art, the present invention has the following technical effects:

[0052] (I) Compared with the traditional method of using a constant time constant ratio for compensation, the present invention takes into account the time-varying characteristics of the thermocouple time constant under the influence of an explosive environment and proposes to solve the time constant ratio K moment by moment, which can effectively solve the problem of distortion of the compensation result.

[0053] (II) The present invention introduces a genetic algorithm to solve the time constant ratio, which can effectively improve the solution efficiency.

[0054] (III) The present invention innovatively proposes a method for determining the range of time constant ratios at each moment, which can significantly reduce the number of samples to be solved and effectively avoid falling into local optimality.

[0055] (IV) The present invention innovatively proposes an individual fitness evaluation method based on spectrum analysis, which can effectively solve the optimal time constant ratio at each moment.

[0056] (V) The present invention can solve the time constant ratio K moment by moment to improve the accuracy of double-couple compensation temperature measurement in the explosion field, and support the characterization and evaluation of the thermal damage capability of thermobaric and fuel-air explosive warheads. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a diagram of a double-even test signal used in an embodiment of the present invention.

[0058] Figure 2 2 is a diagram showing the signal noise reduction result according to an embodiment of the present invention.

[0059] Figure 3 This is the effect diagram when the test signal without noise reduction and resampling is compensated using the traditional method.

[0060] Figure 4 This is the effect diagram when the test signal after noise reduction and resampling is compensated using the traditional method.

[0061] Figure 5 1 is a diagram of the double-couple temperature measurement compensation result of an embodiment of the present invention.

[0062] The specific contents of the present invention are further explained in detail below with reference to the embodiments. DETAILED DESCRIPTION

[0063] It should be noted that, unless otherwise specified, all components and equipment in the present invention are components and equipment known in the prior art.

[0064] In the present invention, when a double couple is used for temperature testing, the two thermocouples are respectively referred to as thermocouple 1 and thermocouple 2, the corresponding time constants are respectively referred to as time constant 1 (symbol C1) and time constant 2 (symbol C2), and the corresponding temperature test results at each moment are respectively referred to as signal 1 (symbol t1(τ)) and signal 2 (symbol t2(τ)).

[0065] Specific embodiments of the present invention are given below. It should be noted that the present invention is not limited to the following specific embodiments, and all equivalent modifications made on the basis of the technical solution of this application fall within the protection scope of the present invention.

[0066] Example:

[0067] This embodiment provides a method for solving the time constant ratio of double-couple temperature measurement in an explosion field based on a genetic algorithm, the method comprising the following steps:

[0068] Step 1: Test signal preprocessing:

[0069] Step 101: Obtain a valid test signal:

[0070] The pressure signals of thermocouple 1 and thermocouple 2 measured in the test are converted into temperature signals, zero drift is removed, and the signal segment of interest is intercepted to finally obtain a test signal; the test signal includes signal 1 corresponding to thermocouple 1 and signal 2 corresponding to thermocouple 2.

[0071] In step 101, during the interception process, the flat signal segment before the starting point is removed, and the peak points of signal 1 and signal 2 are retained, and the interception time lengths of signal 1 and signal 2 are the same.

[0072] In this embodiment, the test signal is finally obtained as follows: Figure 1 shown.

[0073] Step 102: Test signal noise reduction:

[0074] The test signal obtained in step 101 is subjected to signal denoising by using a fourth-order Butterworth low-pass filter and locally weighted regression (LOESS) to obtain a denoised test signal.

[0075] In step 102, the cutoff frequency of the fourth-order Butterworth low-pass filter is not lower than the response frequency of the corresponding thermocouple.

[0076] In this embodiment, the cutoff frequency of the fourth-order Butterworth low-pass filter is 160 Hz, which meets the requirement that the cutoff frequency is not lower than the response frequency of the thermocouple. The time constant of the thermocouple used in this embodiment is greater than 1 ms, and its response frequency f c Calculated based on the thermocouple time constant C, both are less than 160Hz.

[0077]

[0078] The noise reduction result in this embodiment is as follows Figure 2 shown.

[0079] Step 103: resampling the test signal:

[0080] The test signal after noise reduction obtained in step 102 is resampled, with a sampling rate not less than 30 Hz.

[0081] In this embodiment, the test signal is resampled at 2000 Hz, and a total of 5000 data points are obtained, which meets the requirement that the sampling rate is not less than 30 Hz.

[0082] In this embodiment, the final result obtained in step 101 is Figure 1 When the test signal shown is directly compensated using the traditional constant time constant ratio, the compensation result is as follows: Figure 3 As shown, the compensation result is severely distorted and difficult to recognize.

[0083] Step 2: Calculate the value range of the time constant ratio K at each moment:

[0084] Step 201: Read the peak time point τ1 and peak point t of signal 1. 1_max ; Read the peak time point τ2 and peak point t of signal 2 2_max .

[0085] Step 202: Based on the τ1 and t obtained in step 201, 1_max , find the time constant C2(τ1) of signal 2 at the corresponding moment; according to τ2 and t obtained in step 201 2_max , find the time constant C1(τ2) of signal 1 at the corresponding moment.

[0086] In step 202, the C2(τ1) calculation formula is:

[0087]

[0088] Where:

[0089] C2(τ1) represents the time constant of signal 2 at the peak point of signal 1;

[0090] τ represents the time point;

[0091] τ1 represents the peak time point of signal 1;

[0092] t2(τ1) represents the temperature test result of signal 2 at the time when the peak point of signal 1 corresponds to;

[0093] t2 represents the temperature test result of signal 2.

[0094] In step 202, the calculation formula of C1(τ2) is:

[0095]

[0096] Where:

[0097] C1(τ2) represents the time constant of signal 1 at the peak point of signal 2;

[0098] τ represents the time point;

[0099] τ2 represents the peak time point of signal 2;

[0100] t1(τ2) represents the temperature test result of signal 1 at the time when the peak point of signal 2 corresponds to;

[0101] t1 represents the temperature test result of signal 1.

[0102] Step 203: Compensate the test result of signal 2 according to C2(τ1) and the heat transfer equation obtained in step 202 to obtain the true temperature value t at time τ of signal 2. g_by_t2 (τ); According to C1(τ2) and the heat transfer equation obtained in step 202, the test result of signal 1 is compensated to obtain the true temperature value t at time τ of signal 1 compensated g_by_t1 (τ).

[0103] In step 203, the temperature true value t at time τ obtained by compensating the signal 2 is g_by_t2 (τ) is calculated as follows:

[0104]

[0105] Where:

[0106] t g_by_t2 (τ) represents the true temperature value at time τ compensated by signal 2;

[0107] t2(τ) represents the temperature test result of signal 2 at time τ.

[0108] In step 203, the temperature true value t at time τ obtained by compensating the signal 1 is g_ny_t1 (τ) is calculated as follows:

[0109]

[0110] Where:

[0111] t g_by_t1 (τ) represents the true temperature value at time τ compensated by signal 1;

[0112] t1(τ) represents the temperature test result of signal 1 at time τ.

[0113] Step 204, according to the t obtained in step 203 g_by_t2 (τ), and inversely calculate the time constant C of thermocouple 1 at each moment 1_by_t2 (τ); t obtained in step 203 g_by_t1(τ), and inversely calculate the time constant C of thermocouple 1 at each moment 2_by_t1 (τ).

[0114] In step 204, the time constant C of the thermocouple 1 at each moment is 1_by_t2 The calculation formula for (τ) is:

[0115]

[0116] In step 204, the time constant C of the thermocouple 2 at each moment is 2_by_t1 The calculation formula for (τ) is:

[0117]

[0118] Step 205: According to the C obtained in step 204 1_by_t2 (τ) and C2(τ1) obtained in step 202, a set of possible values K of the time constant ratio K at time τ is obtained by_t2 (τ); according to C obtained in step 204 2_by_t1 (τ) and C1(τ2) obtained in step 202, we can get another set of possible values K of the time constant ratio K at time τ. by_t1 (τ).

[0119] In step 205, the possible values K of the set of time constants K at time τ are by_t2 The calculation formula for (τ) is:

[0120]

[0121] In step 205, the possible values K of the other set of time constants K at time τ are by_t1 The calculation formula for (τ) is:

[0122]

[0123] Step 206: Based on the K obtained in step 205 by_t2 (τ) and K by_t1 (τ) Calculate the range of the time constant ratio K at each moment.

[0124] In step 206, the value range of the time constant ratio K at each moment is K real (τ)∈[K min (τ), K max (τ)], where: K min (τ)=max[K by_t1 (τ), K by_t2 (τ)],K max (τ) = kK min (τ);

[0125] Where:

[0126] K real (τ) represents the true value of the time constant ratio K at time τ;

[0127] K min (τ) represents the minimum possible value of the time constant ratio K at time τ;

[0128] K max (τ) represents the maximum possible value of the time constant ratio K at time τ;

[0129] k represents the amplification factor, k>1; when the thermocouple is close to the explosion point and is greatly affected by the explosion field, the value should be larger, otherwise it should be smaller; k usually has a value range of (1,10], and in this embodiment, the value is 5.

[0130] Step 3: Initialize the genetic algorithm population:

[0131] Within the value range of the time constant ratio K at each moment obtained in step 2, the time constant ratio K(τ) at each moment is initialized, and multiple groups of K(τ) are obtained in the form of n preferred individuals + m random individuals to form the initial population of the genetic algorithm.

[0132] In this embodiment, the population size is 400, n is 300, and m is 100. The specific method is as follows:

[0133] In step 3, the method for generating the preferred individual is:

[0134] K i (τ)=[1-(i-1)w]K min (τ)+(i-1)wK max (τ);

[0135] Where:

[0136] K i (τ) represents the i-th group of individuals at time τ;

[0137] i represents the sequence number of the preferred individual, i = 1, 2, 3…, n;

[0138] n represents the number of preferred individuals; in this embodiment, b is 300;

[0139] w represents the weight coefficient, (i-1)w=1;

[0140] K min (τ) represents the minimum possible value of the time constant ratio K at time τ;

[0141] K max (τ) represents the maximum possible value of the time constant ratio K at time τ;

[0142] In step 3, the method for generating random individuals is: generating m individuals by random sampling.

[0143] In this embodiment, m is 100.

[0144] Step 4: Calculation of individual fitness:

[0145] In this embodiment, the sum of the absolute values of the amplitudes of the high-frequency components of the compensation results is used as the basis for fitness evaluation. The lower the value, the higher the fitness.

[0146] Step 401 : Use each individual in the population of the genetic algorithm to compensate the resampled test signal obtained in step 103 , and obtain compensation results for each group of individuals.

[0147] In step 401, the compensation method is:

[0148]

[0149] Where:

[0150] t i (τ) represents the compensation result temperature value of the i-th group individual at time τ;

[0151] K i (τ) represents the value of the time constant ratio of the individuals in group i at time τ;

[0152] t1 represents the temperature test result of signal 1;

[0153] t2 represents the temperature test result of signal 2;

[0154] τ represents the time point;

[0155] t1(τ) represents the temperature test result of signal 1 at time τ;

[0156] t2(τ) represents the temperature test result of signal 2 at time τ;

[0157] K i (τ) represents the i-th group of individuals at time τ.

[0158] Step 402 , performing Fourier transform on each group of individual compensation results obtained in step 401 to obtain transformed individual compensation results for each group.

[0159] Step 403 , remove the low-frequency components in the spectrum of each group of individual compensation results obtained in step 402 , take the absolute values of the amplitudes of the high-frequency components in the spectrum and sum them to obtain the individual fitness.

[0160] In step 403, the method for selecting the boundary line between the high-frequency component and the low-frequency component is:

[0161]

[0162] Where:

[0163] f represents the minimum value of the dividing line between high-frequency components and low-frequency components;

[0164] C ideal Indicates the time constant that can be achieved after compensation.

[0165] In this embodiment, C ideal Less than 1ms, so f is taken as 160Hz.

[0166] Compensation performance comparison test:

[0167] The final result of step 101 is Figure 1 When the test signal shown is directly compensated using the traditional constant time constant ratio, the compensation result is as follows: Figure 3 As shown, the compensation result is severely distorted and difficult to recognize.

[0168] The final result of step 101 is Figure 1 The test signal shown in FIG. 1 is subjected to noise reduction in step 102 and resampling in step 103 to obtain a resampled test signal. When the conventional method of using a constant time constant ratio is used for compensation, the compensation result is as follows: Figure 4 As shown, relative Figure 3 In terms of noise reduction and resampling, the compensation result obtained by using traditional methods has greatly alleviated the oscillation phenomenon, but there is still a large distortion and it cannot be clearly identified.

[0169] The final result of step 101 is Figure 1 The test signal shown in FIG. 1 is subjected to noise reduction in step 102 and resampling in step 103 to obtain a resampled test signal. When the resampled test signal obtained in step 103 is compensated using the method of steps 2 to 6 in this embodiment, the compensation result is as follows: Figure 5 As shown, from Figure 5 It can be seen that compared with traditional methods, the method of the present invention can effectively avoid distortion of compensation results, restore the true temperature, and realize the application of double-pair compensation technology in explosion field temperature testing.

[0170] Step 5: Generate a new population:

[0171] According to the individual fitness obtained in step 4, individuals are naturally selected, recombined and mutated to form a new population.

[0172] Step 501, natural selection:

[0173] Individuals in the population are sorted from highest to lowest fitness, and low-fitness individuals are eliminated. The elimination ratio can be selected based on the actual situation. Generally speaking, when the thermocouple is close to the explosion point and is greatly affected by the explosion, the elimination ratio should be lower, while when it is not, it can be higher. In actual operation, it is recommended to use a ratio of 1 / 4 to 3 / 4; in this embodiment, the elimination ratio is 3 / 4.

[0174] Step 502, reorganization:

[0175] Randomly select two individuals from the surviving individuals as parents, and randomly select one of the time constant ratios of the two parents at each moment as the time constant ratio of the corresponding moment of the offspring. Repeat this process until the sum of the number of offspring and the number of surviving individuals meets the population size requirement.

[0176] Step 503, mutation:

[0177] A random value is superimposed on the time constant ratio of each individual in the population at each moment to achieve population variation. The range of the random value is related to the number of iterations. The higher the iteration number, the smaller the range should be. After superposition, if the time constant ratio at a certain moment exceeds the range of the time constant ratio at that moment, the value should be reselected within the range. This embodiment iterates a total of 200 times. The range of values within 100 times is [-0.005, 0.005], the range of values from 100 to 150 times is [-0.0025, 0.0025], and the range of values from 150 to 200 times is [-0.001, 0.001].

[0178] Step 6, iterative solution:

[0179] Repeat steps 4 and 5 until the solution is completed; take the individual with the highest fitness as the optimal value of the time constant ratio K at each moment.

[0180] In step 6, the solution completion signs include the following three types and their combinations:

[0181] First, the number of iterations reaches the set maximum number.

[0182] Second, the optimal individual does not change after multiple rounds of iterations, which means that the solution converges.

[0183] Third, within the range of time constant ratio values at each moment, the permutations and combinations of time constant ratio values have been completely traversed.

[0184] In this embodiment, the first form is adopted for solution control, and the maximum number of iterations is set to 200.

[0185] It has been verified that the present invention can realize the moment-by-moment solution of the time constant ratio, thereby improving the accuracy of the double-couple compensation temperature measurement method in the explosion field, and supporting the characterization and evaluation of the thermal damage capability of the warhead.

Claims

1. A method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm, the method comprising the following steps: Step 1: Test signal preprocessing: Step 101: Obtain a valid test signal: Convert the pressure signals of thermocouple 1 and thermocouple 2 measured in the test into temperature signals, remove zero drift, intercept the signal segment of interest, and finally obtain a test signal; the test signal includes signal 1 corresponding to thermocouple 1 and signal 2 corresponding to thermocouple 2; Its characteristics are: Step 102: Test signal noise reduction: Performing signal noise reduction on the test signal obtained in step 101 to obtain a noise-reduced test signal; Step 103: resampling the test signal: Resampling the noise-reduced test signal obtained in step 102 to obtain a resampled test signal; Step 2: Calculate the value range of the time constant ratio K at each moment: The range of the time constant ratio K at each moment is K real (τ)∈[K min (τ), K max (τ)], where: K min (τ)=max[K by_t1 (t),K by_t2 (τ)], K max (τ)=kK min (t); Where: K real (τ) represents the true value of the time constant ratio K at time τ; K min (τ) represents the minimum possible value of the time constant ratio K at time τ; K max (τ) represents the maximum possible value of the time constant ratio K at time τ; k represents the amplification factor, k>1; Step 3: Initialize the genetic algorithm population: Initialize the time constant ratio K(τ) at each moment within the value range of the time constant ratio K obtained in step 2, and obtain multiple groups of K(τ) in the form of n preferred individuals + m random individuals to form the initial population of the genetic algorithm; Step 4: Calculation of individual fitness: Step 401, using each individual in the population of the genetic algorithm to compensate the resampled test signal obtained in step 103, to obtain compensation results for each group of individuals; In step 401, the compensation method is: Where: t i (τ) represents the compensation result temperature value of the i-th group individual at time τ; K i (τ) represents the value of the time constant ratio of the individuals in group i at time τ; t1 represents the temperature test result of signal 1; t2 represents the temperature test result of signal 2; τ represents the time point; t1(τ) represents the temperature test result of signal 1 at time τ; t2(τ) represents the temperature test result of signal 2 at time τ; K i (τ) represents the i-th group of individuals at time τ; Step 402, performing Fourier transform on each group of individual compensation results obtained in step 401 to obtain transformed individual compensation results for each group; Step 403 , remove the low-frequency components in the spectrum of each group of individual compensation results obtained in step 402 , take the absolute values of the amplitudes of the high-frequency components in the spectrum and sum them to obtain the individual fitness.

2. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm according to claim 1, characterized in that: In step 101, during the interception process, the flat signal segment before the starting point is removed, and the peak points of signal 1 and signal 2 are retained, and the interception time lengths of signal 1 and signal 2 are the same.

3. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm according to claim 1, characterized in that: The specific process of step 2 is: Step 201: Read the peak time point τ1 and peak point t of signal 1. 1_max ; Read the peak time point τ2 and peak point t of signal 2 2_max ; Step 202: Based on the τ1 and t obtained in step 201, 1_max , find the time constant C2(τ1) of signal 2 at the corresponding moment; according to τ2 and t obtained in step 201 2_max , find the time constant C1(τ2) of signal 1 at the corresponding moment; Step 203: Compensate the test result of signal 2 according to C2(τ1) and the heat transfer equation obtained in step 202 to obtain the true temperature value t at time τ of signal 2. g_by_t2 (τ); According to C1(τ2) and the heat transfer equation obtained in step 202, the test result of signal 1 is compensated to obtain the true temperature value t at time τ of signal 1 compensated g_by_t1 (τ); Step 204: According to the t obtained in step 203 g_by_t2 (τ), and inversely calculate the time constant C of thermocouple 1 at each moment 1_by_t2 (τ); t obtained in step 203 g_by_t1 (τ), and inversely calculate the time constant C of thermocouple 1 at each moment 2_by_t1 (τ); Step 205: According to the C obtained in step 204 1_by_t2 (τ) and C2(τ1) obtained in step 202, a set of possible values K of the time constant ratio K at time τ is obtained by_t2 (τ); according to C obtained in step 204 2_by_t1 (τ) and C1(τ2) obtained in step 202, we can get another set of possible values K of the time constant ratio K at time τ. by_t1 (τ); Step 206: Based on the K obtained in step 205 by_t2 (τ) and K by_t1 (τ) Calculate the range of the time constant ratio K at each moment.

4. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm as claimed in claim 3, characterized in that: In step 202, the C2(τ1) calculation formula is: Where: C2(τ1) represents the time constant of signal 2 at the peak point of signal 1; τ represents the time point; τ1 represents the peak time point of signal 1; t2(τ1) represents the temperature test result of signal 2 at the time when the peak point of signal 1 corresponds to; t2 represents the temperature test result of signal 2; In step 202, the calculation formula of C1(τ2) is: Where: C1(τ2) represents the time constant of signal 1 at the peak point of signal 2; τ represents the time point; τ2 represents the peak time point of signal 2; t1(τ2) represents the temperature test result of signal 1 at the time when the peak point of signal 2 corresponds to; t1 represents the temperature test result of signal 1.

5. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm as claimed in claim 3, characterized in that: In step 203, the temperature true value t at time τ obtained by compensating the signal 2 is g_by_t2 (τ) is calculated as follows: Where: t g_by_t2 (τ) represents the true temperature value at time τ compensated by signal 2; t2(τ) represents the temperature test result of signal 2 at time τ; In step 203, the temperature true value t at time τ obtained by compensating the signal 1 is g_by_t1 (τ) is calculated as follows: Where: t g_by_t1 (τ) represents the true temperature value at time τ compensated by signal 1; t1(τ) represents the temperature test result of signal 1 at time τ.

6. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm as claimed in claim 3, characterized in that: In step 204, the time constant C of the thermocouple 1 at each moment is 1_by_t2 The calculation formula for (τ) is: In step 204, the time constant C of the thermocouple 2 at each moment is 2_by_t1 The calculation formula for (τ) is:

7. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm as claimed in claim 3, characterized in that: In step 205, the possible values K of the set of time constants K at time τ are by_t2 The calculation formula for (τ) is: In step 205, the possible values K of the other set of time constants K at time τ are by_t1 The calculation formula for (τ) is:

8. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm according to claim 1, characterized in that: In step 3, the method for generating the preferred individual is: K i (τ)=[1-(i-1)w]K min (τ)+(i-1)wK max (t); Where: K i (τ) represents the i-th group of individuals at time τ; i represents the sequence number of the preferred individual, i = 1, 2, 3…, n; n represents the number of preferred individuals; w represents the weight coefficient, (i-1)w=1; K min (τ) represents the minimum possible value of the time constant ratio K at time τ; K max (τ) represents the maximum possible value of the time constant ratio K at time τ; In step 3, the method for generating random individuals is: generating m individuals by random sampling.

9. The method for solving the time constant ratio of double-couple temperature measurement in explosion fields based on a genetic algorithm as claimed in claim 1, wherein in step 403, the method for selecting the dividing line between the high-frequency component and the low-frequency component is: Where: f represents the minimum value of the dividing line between high-frequency components and low-frequency components; C ideal Indicates the time constant that can be achieved after compensation.

10. The method for solving the time constant ratio of double-couple temperature measurement in explosion field based on genetic algorithm according to claim 1, characterized in that: The method further includes: Step 5: Generate a new population: According to the individual fitness obtained in step 4, individuals are subjected to natural selection, recombination and mutation to form a new population; Step 6, iterative solution: Repeat steps 4 and 5 until the solution is completed; take the individual with the highest fitness as the optimal value of the time constant ratio K at each moment.

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