A method, medium, and apparatus for heating boundary adaptive delay recognition

Abstract

The application discloses a heating boundary self-adaptive delay identification method, medium and equipment, relates to an identification analysis method for directly determining time delay required by each identification step by using characteristic information contained in internal temperature test data of a heatproof material or a heat measuring sensor, and further obtaining a surface heat boundary parameter of the material or the sensor, and belongs to the technical field of aircraft heat protection design.The application considers the influence of factors such as a heat boundary parameter, heat properties of a heatproof material and a measuring point position on material temperature response delay, and identification calculation is carried out by using a time delay parameter suitable for the factors, so that the identification precision of the heat identification analysis problem is improved, the identification analysis deviation is reduced, and more reliable test data for aircraft heat protection design is provided.The application has the characteristics of high conformity to an engineering actual physical process, high analysis efficiency and small identification deviation, and can provide a reliable implementation approach for aircraft flight or ground test heat data analysis.

Description

Technical Field

[0001] This application relates to an adaptive delay identification method for heating boundaries, belonging to the field of aircraft thermal protection design technology. Background Technology

[0002] Thermal boundary identification and analysis of heat-resistant materials or thermal sensors is a technical method and approach to obtain the surface thermal boundary parameters of specific materials or structures by using temperature response data of the thermal protection structure, heat-resistant materials, or thermal sensors on the aircraft surface under heating environments such as aerodynamic heating and irradiation heating, and employing parameter identification principles and techniques. Generally, it refers to the identification and analysis process of obtaining the surface temperature or heat flux boundary of materials or sensors using internal temperature test data of the heat-resistant materials or thermal sensors. Especially in application environments with relatively harsh heating boundaries, conventional thermal or temperature measurement equipment cannot withstand localized high temperatures. The method of obtaining internal temperature data through embedded temperature measurement points and then identifying the surface thermal boundary has become an important technical approach for obtaining the thermal boundary parameters of aircraft heat-resistant materials or structures. However, using embedded temperature for thermal boundary identification requires considering the impact of the delay in the heat transfer process inside the sensor. That is, there is a certain time lag between the change in the internal temperature response of the material and the change in the surface thermal boundary parameters. The magnitude of this time lag is closely related to factors such as the material's thermal boundary, the material's thermal properties, and the location of the internal and external temperature measurement points, and it has a significant impact on the identification calculation results. In traditional thermal identification analysis methods, the influence of heat transfer delay on the thermal identification calculation results is generally addressed by artificially assigning a time delay before the identification calculation. This method has good application results when solving problems with relatively small heat transfer delays, but it cannot meet the application requirements of thermal identification problems with relatively large heat transfer delays or large changes in heat transfer delays over time, and it also has a certain degree of arbitrariness. Summary of the Invention

[0003] The technical problem solved by this application is to overcome the shortcomings of the prior art and provide an adaptive delay identification method for heating boundaries, which solves the analysis needs of thermal identification problems with relatively large heat transfer delay or large changes in heat transfer delay over time, thereby providing an effective, reliable and feasible implementation approach for the identification and analysis of internal temperature measurement data and surface thermal boundary parameters of heat-resistant materials or thermal sensors.

[0004] The technical solution of this application is: an adaptive delay identification method for heating boundaries, comprising:

[0005] Acquire temperature data from inside heat-resistant materials or thermal sensors;

[0006] The entire time period for heat flow identification is specified, and an adaptive delay analysis uncertainty parameter and several identification steps are given. In each identification step, the heat transfer delay time of the temperature measurement point inside the material is adaptively determined, and the heat flow identification calculation of the current identification step is realized by combining the temperature measurement data. The heat flow identification calculation is repeated throughout the entire time period to obtain the heat flow identification results throughout the entire time period, and the identification temperature is calculated based on the heat flow identification results throughout the entire time period.

[0007] Adjust the uncertainty parameters of the adaptive delay analysis, repeat the identification temperature calculation, and stop only when the identification temperature calculation result meets the preset requirements to obtain the heat flow identification result for the specified time period.

[0008] Furthermore, in the nth identification step, the heat transfer delay time of the temperature measurement point inside the material is adaptively determined, including:

[0009] Using q 0 ~q n-1 As a thermal boundary condition, calculate the initial temperature field T of the current identification step. c n-1 n is an integer not less than 1; when n = 1, the initial temperature field T is given. c 0 The value of q, and let q 0 =q 1 ;q n This is the heat flow identification result corresponding to the nth identification step;

[0010] The interpolation calculation results of the temperature measurement data are iteratively optimized to obtain the temperature measurement data changing over time that meets the preset error accuracy requirements. The time delay t of the current identification step is then calculated in conjunction with the adaptive delay analysis uncertainty parameter. d n .

[0011] Furthermore, the iterative optimization of the temperature measurement data interpolation calculation results includes:

[0012] Given a time deviation Δt, using temperature measurement data T ta Input values ​​are used to interpolate and calculate t. n t n -Δt and t n The temperature values ​​at time +Δt are denoted as: T ta1 T ta2 and T ta3 ;

[0013] Using T ta1 T ta2 and T ta3 Calculate the changes in temperature measurement data over time;

[0014] Change the time deviation Δt and repeatedly calculate the temperature measurement data over time until the average value of the temperature measurement data over time is less than the preset error accuracy requirement range.

[0015] Furthermore, the temperature measurement data that changes over time includes:

[0016] Furthermore, the time delay t of the current identification step d n For t d n =t n-1 +t d0 + Among them, t d0 t is the initial value for the delayed analysis. dcoe1 and t dcoe2 To identify and calculate the adaptive time delay coefficient; the adaptive delay analysis uncertainty parameter includes t d0 , td coe1 and td coe2 .

[0017] Furthermore, in the nth identification step, the heat flow identification calculation for the current identification step is performed by combining the temperature measurement data, including:

[0018] t n-1 As the starting moment, the temperature field T c n-1 As the initial temperature field, take Perform different q n Calculate the ablation thermal response of the material under the given input conditions to obtain the comparison temperature;

[0019] t n-1 Time to t d n Input temperature value at any time Using the target temperature and the comparison temperature as the target temperature, q is iteratively calculated and updated. n Complete the heat flow identification calculation for the current identification step;

[0020] Where n is an integer not less than 1; q n This is the heat flow identification result corresponding to the nth identification step.

[0021] Furthermore, the calculation of the identified temperature based on the heat flow identification results over the entire time period includes:

[0022] Using the full time period t 0 ~t N Heat flow identification results q 0 ~q NAs a thermal boundary parameter, the calculated identification temperature T over the entire time period is obtained through calculation and analysis. c 0 ~T c N .

[0023] Furthermore, the temperature calculation result meets the preset requirements, including: the temperature calculation result T over the entire time period. c 0 ~T c N With temperature measurement data T ta 0 ~T ta N The relative error between them meets the preset requirements.

[0024] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the adaptive delay identification method for heating boundaries.

[0025] A heating boundary adaptive delay identification device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the heating boundary adaptive delay identification method.

[0026] The advantages of this application compared to existing technologies are:

[0027] (1) Compared with the method of directly giving a fixed time delay, the present invention uses the first-order partial derivative of temperature and the second-order partial derivative of temperature as input parameters for determining the time delay, which can reflect the influence of factors such as material thermal boundary, material thermal properties, and internal and external temperature measurement point positions on the heat transfer delay of internal temperature measurement points of the material. This is more in line with the actual physical process in engineering, and has better identification and calculation accuracy and stronger engineering application value.

[0028] (2) Compared with other methods such as thermal response process trial calculation to determine the heat transfer delay time of each temperature measurement point inside the material at different times, the present invention uses the temperature gradient and the second-order partial derivative of temperature as input parameters for determining the time delay, which has higher analysis efficiency and does not introduce other uncertain factors or the coupling effect of parameters. Attached Figure Description

[0029] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0030] Figure 1 The theoretical true values ​​of the thermal environment parameters are used for identification and analysis.

[0031] Figure 2 The measured temperature is used as the input for identification and analysis.

[0032] Figure 3 This is a comparison of the identification and analysis results of this invention with the analysis results of directly given fixed time delay and the true value of heat flow.

[0033] Figure 4 (a) and Figure 4 (b) is Figure 3 A magnified view of a portion of the image;

[0034] Figure 5 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0035] To better understand the above technical solutions, the technical solutions of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0036] The following description, in conjunction with the accompanying drawings, provides a more detailed explanation of an adaptive delay identification method for heating boundaries provided in this application. Specific implementation may include: using internal temperature measurement data from heat-resistant materials or thermal sensors as direct input; extracting relevant information from the input temperature data related to factors such as the material's thermal boundary, material thermal properties, and the locations of internal and external temperature measurement points; establishing an adaptive method for determining heat transfer delay time based on the characteristics of the input temperature response data; and then iteratively optimizing the uncertainty parameters in the adaptive delay identification analysis using an optimization algorithm to obtain surface thermal boundary parameters of the heat-resistant material or thermal sensor that meet the accuracy and error requirements of thermal identification analysis. Figure 5 Specifically, it includes the following steps:

[0037] Step (1): Identify and analyze specific requirements based on the thermal boundary parameters of the heat-resistant material or the thermal sensor surface, and give a certain time step Δt starting from the initial moment. ip The thermal boundary parameters at each time step are identified and analyzed. The time step number for the identification calculation is denoted as n, and the thermal boundary parameter identification result for each time step is denoted as q. n The total number of steps required for calculation is denoted as N;

[0038] Step (2): Use the identification result q obtained from calculation step 0 to calculation step n-1 before the current identification calculation step n. 0 ~q n-1As a thermal boundary condition, the initial temperature field T of the current identification step is calculated. c n-1 If n=1, then the initial temperature field T is directly given. c 0 The value of q, and let q 0 =q 1 ;

[0039] Step (3): Given a small time deviation Δt, the current identification time t is obtained by interpolation based on the measured temperature value over time. n and t n -Δt time and t n The temperature response values ​​at time +Δt are denoted as follows: and Among them, the small time deviation Δt needs to be greater than the minimum time interval of the input measured temperature value, which can generally be 1 to 5 times the minimum time interval of the input measured temperature value;

[0040] Step (4): Use the calculated current identification time t n and t n -Δt time and t n The temperature response value at time +Δt is used to approximate the first-order partial derivative of the input temperature over time at the current time: And second-order partial derivatives:

[0041] Step (5): Change the value of Δt, and repeat steps (3) and (4) until the result is obtained after multiple calculations. Value and The average value variation is less than the required accuracy range for numerical estimation of the first and second partial derivatives of temperature;

[0042] Step (6): Estimate the first and second partial derivatives of temperature using the input temperature value. These two parameters are used to characterize the specific influence of factors such as material thermal boundary, material thermal properties, and the location of internal and external temperature measurement points on the heat transfer delay of the internal temperature measurement points of the material. The specific method is as follows: Define the initial value t for delay analysis. d0 And the adaptive coefficient td for identifying and calculating time delay. coe1 and td coe2 , and given t d0 , td coe1 and td coe2 Initialize the values ​​and calculate the time delay for the current identification step:

[0043] Step (7): t n-1 As the starting moment, the temperature field T cn-1 As the initial temperature field, q n The value is used as the time t corresponding to calculation step n-1. n-1 The thermal boundary conditions for all subsequent moments are taken as follows: q n Perform different q n Calculation of the thermal response of material ablation under given input conditions;

[0044] Step (8): t n-1 Time to t d n Input temperature value at any time As the target temperature, q is iteratively updated using conventional optimization methods. n The current identification calculation step is performed to obtain a heat flux value q that meets the deviation requirements. n The value completes the calculation and analysis of the current identification calculation step;

[0045] Step (9): Repeat steps (2) to (8) to complete the heat flow identification calculation for all identification calculation steps and obtain the total time period t. 0 ~t N Heat flow identification results q 0 ~q N Using q 0 ~q N Using the thermal boundary parameter, the ablation thermal response of the material is calculated, and the identification temperature T is obtained over the entire time period. c 0 ~T c N ;

[0046] Step (10): Calculate the temperature T at all times. c 0 ~T c N Compared with the measured temperature input T ta 0 ~T ta N The relative error d% between them serves as a quantitative basis for judging the current accuracy of the identification calculation;

[0047] Step (11): Change t d0 , td coe1 and td coe2 The value of t is obtained by repeating steps (2) to (10). d0 , td coe1 and td coe2 The relative error d% corresponding to the value is calculated, and the t is iteratively updated using an optimization algorithm. d0 , td coe1 and td coe2The value is calculated until the relative error d% reaches the expected accuracy requirement.

[0048] Example

[0049] The solution provided in this application embodiment specifically includes the following steps:

[0050] Step (1): Data processing

[0051] Taking the surface heat flow identification and analysis process of a typical heat-resistant material as an example, the temperature response data at a depth of 3.0 mm inside the material under typical thermal environment parameter inputs were calculated using the heat-resistant structure ablation thermal response model. The emissivity of the material is 0.3–0.8, the thermal conductivity is 0.5–5.0 W / m / K, and the density is 400–600 kg / m³. 3 Its specific heat capacity is 1700-1800 J / kg / K.

[0052] like Figure 1 As shown, the heat flux in the above typical thermal environment parameters is taken as the theoretical true heat flux q. _ref In the figure, Hr represents the enthalpy of recovery, and Pe represents the pressure; both are thermal boundary input parameters for calculating the thermal response of the heat-resistant material. Figure 2 As shown, the temperature response data obtained from the above calculations is used as the input temperature data T for identification analysis. ta The time interval for this data is 0.1s. Starting from the initial moment, a given identification calculation time step Δt is used. ip =0.5s, the time step number is denoted as n, and the thermal boundary parameter identification result corresponding to each time step is denoted as q. n The total number of steps required for calculation is denoted as N = 76;

[0053] Step (2): Initial temperature field analysis

[0054] The identification result q obtained from calculation step 0 to calculation step n-1 before the current identification calculation step n is used. 0 ~q n-1 As a thermal boundary condition, the initial temperature field T of the current identification step is calculated. c n-1 For the first calculation step n=1, the initial temperature field T is directly given. c 0 The value of q is 300K, and let q 0 =q 1 ;

[0055] Step (3): Input temperature interpolation

[0056] Given a small time deviation Δt, the minimum time interval greater than the input measured temperature value must be met, i.e., Δt ≥ 0.1s. The current identification time t is obtained using an interpolation method. nt n -Δt time and t n The temperature response values ​​at time +Δt are denoted as follows: and

[0057] Step (4): Input the first and second partial derivatives of temperature for analysis.

[0058] Using a given Δt value, and t n t n -Δt and t n The temperature response value at time +Δt is used to approximate the first-order partial derivative of temperature change with time: And second-order partial derivatives:

[0059] Step (5): Iterative optimization of first-order and second-order partial derivatives of temperature

[0060] Change the value of Δt, for example, by randomly selecting a value within the range of [0.1 to 0.5], and repeat steps (3) and (4) until the result is obtained after multiple calculations. Value and The average value changes less than the required error accuracy range, for example, " Value and The average rate of change of the value is ≤1.0%;

[0061] Step (6): Adaptive Delay Analysis

[0062] Define the initial value t for the delay analysis d0 And the adaptive coefficient td for identifying and calculating time delay. coe1 and td coe2 And give an initial value, such as t d0 =2.0s, td coe1 =0.02s 2 / K 2 and td coe2 =0.01s 2 / K, calculates the time delay of the current identification step:

[0063] Step (7): Thermal response analysis

[0064] t n-1 As the starting moment, the temperature field T c n-1 As the initial temperature field, the identified object q is used n The value is used as the time t corresponding to calculation step n-1. n-1 The thermal boundary conditions for all subsequent moments are taken as follows: q nPerform different q n Calculation of the thermal response of material ablation under given input conditions;

[0065] Step (8): Thermal boundary identification and analysis

[0066] t n-1 Time to t d n Input temperature value at any time As the target temperature, combined with different q n The temperature calculation results under the given input conditions are obtained using conventional optimization methods, such as the bisection method and Newton's iteration method. The q is iteratively updated. n The current identification calculation step is performed to obtain the heat flux value q that meets the deviation requirements. n Values, for example, requiring "q during iteration". n The value variation range is ≤0.01W / m 2 ”;

[0067] Step (9): Time step progression

[0068] Repeat steps (2) to (8) to complete the heat flow identification calculation for all identification calculation steps, and obtain the total time period t. 0 ~t N Heat flow identification results q 0 ~q N Using q 0 ~q N Using the thermal boundary parameter, the ablation thermal response of the material is calculated, and the identification temperature T is obtained over the entire time period. c 0 ~T c N ;

[0069] Step (10): Deviation Statistics

[0070] Statistical analysis of temperature calculation results T at all times c 0 ~T c N Compared with the measured temperature input T ta 0 ~T ta N The relative error d% is used as a quantitative basis for judging the current identification calculation accuracy. The general form of the relative error d% is:

[0071]

[0072] Step (11): Adaptive Delay Parameter Optimization

[0073] Change t d0 , tdcoe1 and td coe2 The value of t is obtained by repeating steps (2) to (10). d0 , td coe1 and td coe2 The relative error d% corresponding to the value is calculated, and the t is iteratively updated using an optimization algorithm. d0 , td coe1 and td coe2 The value is calculated until the relative error d% reaches the expected accuracy requirement, such as "d% ≤ ​​1%".

[0074] Figure 3 The paper presents a comparison between the identification analysis result “newq_cal.(W / m2)” obtained by the analysis method of this invention under the current input parameters of the example, the analysis result “oldq_cal.(W / m2)” obtained by directly giving a fixed time delay, and the true heat flux “q_ref.(W / m2)”. Figure 4 Given Figure 3 The magnified view of the part can more clearly reflect the degree of improvement of the analysis results of the present invention compared with the analysis method with a given fixed time delay.

[0075] The average relative error is defined as the average of the absolute values ​​of the relative errors of the identification results relative to the theoretical true value at each time step, i.e.:

[0076]

[0077] For the current example, quantitative statistical analysis shows that, with all other parameters such as the identification time step being exactly the same, the average relative error De.% of the present invention is reduced by 37.2% compared to the traditional method.

[0078] This invention is applicable, but not limited to, the identification and analysis of heat flow boundary and temperature boundary parameters changing over time on the surface of various heat-resistant materials, heat-resistant structures, and temperature-measuring heat flow sensors.

[0079] This application provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform... Figure 5 The method described.

[0080] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0081] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0085] The contents not described in detail in this application specification are common knowledge to those skilled in the art.

Claims

1. A method for adaptive delay identification of heating boundaries, characterized in that, include: Acquire temperature data from inside heat-resistant materials or thermal sensors; Specify the entire time period for heat flow identification, give the adaptive delay analysis uncertainty parameters and several identification steps, adaptively determine the heat transfer delay time of the temperature measurement point inside the material in each identification step, and combine the temperature measurement data to realize the heat flow identification calculation of the current identification step. The heat flow identification calculation is repeated throughout the entire time period to obtain the heat flow identification results for the entire time period, and the identification temperature is calculated based on the heat flow identification results for the entire time period. Adjust the uncertainty parameters of the adaptive delay analysis, repeat the identification temperature calculation, and stop only when the identification temperature calculation result meets the preset requirements to obtain the heat flow identification result for the specified time period. No. In each identification step, the heat transfer delay time of the temperature measurement point inside the material is adaptively determined, including: use ~ As a thermal boundary condition, calculate the initial temperature field of the current identification step. ; It is an integer not less than 1; At that time, given the initial temperature field The value of , and let ; For the first The heat flow identification results corresponding to each identification step; The interpolation calculation results of the temperature measurement data are iteratively optimized to obtain the temperature measurement data changing over time that meets the preset error accuracy requirements. The time delay of the current identification step is then calculated by combining the adaptive delay analysis uncertainty parameters. ; The iterative optimization of the temperature measurement data interpolation calculation results includes: Given time deviation Using temperature measurement data Input values ​​for interpolation calculation , and The temperature values ​​at each moment are recorded as follows: , and ; use , and Calculate the changes in temperature measurement data over time; Changing the time deviation Repeatedly calculate the temperature measurement data over time until the average value of the temperature measurement data over time is less than the preset error accuracy requirement range; The temperature measurement data changing over time includes: , ; The time delay of the current identification step for ;in, These are the initial values ​​for the delayed analysis. and To identify and calculate the adaptive time delay coefficient; the adaptive delay analysis uncertainty parameters include , and .

2. The adaptive delay identification method for heating boundaries according to claim 1, characterized in that, No. In each identification step, the heat flow identification calculation for the current identification step is achieved by combining the temperature measurement data, including: Will As the starting moment, the temperature field As the initial temperature field, take to carry out different Calculate the ablation thermal response of the material under the given input conditions to obtain the comparison temperature; Will Time to Input temperature value at any time Using the target temperature as the benchmark temperature, the system iteratively calculates and updates the temperature based on the benchmark temperature and the comparison temperature. Complete the heat flow identification calculation for the current identification step; in, It is an integer not less than 1; For the first The heat flow identification results corresponding to each identification step.

3. The adaptive delay identification method for heating boundaries according to claim 1, characterized in that, The calculation of the identification temperature based on the heat flow identification results over the entire time period includes: Use the entire time period ~ Heat flow identification results ~ As a thermal boundary parameter, the calculation and analysis yielded the identification temperature results over the entire time period. ~ .

4. The adaptive delay identification method for heating boundaries according to claim 3, characterized in that, The temperature calculation results must meet the preset requirements, including: temperature calculation results over the entire time period. ~ With temperature measurement data ~ The relative error between them meets the preset requirements.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the adaptive delay identification method for heating boundaries as described in any one of claims 1 to 4.

6. A heating boundary adaptive delay identification device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the heating boundary adaptive delay identification method as described in any one of claims 1 to 4.

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