Method for analyzing performance of arc heater by using test database

Abstract

A method for analyzing the performance of an arc heater by using a test database comprises the following steps: (1) establishing the test database, and automatically acquiring operating parameters and test data of the arc heater from a control machine and a test machine respectively; (2) correlating the operating parameters and the test data of the arc heater by taking the test train number as a correlation quantity; (3) determining key variables influencing the performance of the arc heater, such as parameters such as the operation time, the operation current value, the operation voltage value, the working gas flow and the mixing chamber pressure of the arc heater, and performing summary statistics on all related parameters by utilizing a database platform; (4) taking the same type of arc heater as a research object, screening all related test data, performing statistical analysis on key variable data and input parameters, and drawing into a graph to obtain an electrode life graph, a volt-ampere characteristic graph and an enthalpy pressure characteristic graph of the arc heater; and (5) along with the increase of the test data volume, continuously expanding the atlas to obtain a numerical solution of the key variable representing the performance of the arc heater along with the change of the input parameter.

Description

Technical Field

[0001] The invention relates to the field of aerodynamic thermal environment ground simulation test. Background Art

[0002] Arc heaters are the core equipment for ground simulation test research on thermal protection of aerospace vehicles at home and abroad, and are an important means to solve the ground assessment of thermal protection of hypersonic vehicles such as missiles, recoverable satellites, and manned spacecraft return capsules. At present, there are more and more domestic model missions and more and more complex trajectories, which require arc heaters to have a wider range of simulation capabilities. The operating power, enthalpy value, and total pressure of the equipment span from extremely low states to extremely high states. This requires us to fully study and explore the performance of arc heaters, master the relationship between heater performance parameters and input quantities, and meet the needs of new model tests.

[0003] At present, we do not have an accurate grasp of the performance parameters of various types of heaters, and cannot predict the flow field parameters under different input conditions in advance. We have to use probes and sensors to measure and confirm the flow field state each time, which affects the test efficiency. Therefore, we hope to obtain the heater operation performance map by statistically analyzing the test state parameters, and by continuously filling in the data of the performance map, we can achieve an accurate prediction of the test state, which can not only improve the test efficiency but also guide the improvement of heater performance. Summary of the invention

[0004] The technology of the present invention solves the problem: Overcoming the shortcomings of the prior art, a method for analyzing the performance of an arc heater using a test database is provided. The method utilizes a database platform to combine the operating parameters of the arc heater with the test data to obtain a key variable map characterizing the performance of the heater, thereby realizing the study of the heater performance.

[0005] The technical solution of the present invention is a method for analyzing the performance of an arc heater using a test database, comprising the following steps:

[0006] A test database is established based on the arc heater operating parameter data and test data; the operating parameters are the arc heater operating data, including main gas flow, cold gas flow, current value, voltage value, and operating time; the test data are the flow field parameters of the arc heater, including heat flux, arc chamber pressure, mixing chamber pressure, and total temperature;

[0007] Based on the test database, the arc heater operating parameter data and the test data are correlated with each other using the test vehicle number as a correlation quantity;

[0008] Identify key variables that characterize the performance of the arc heater, including arc heater electrode operating time, heater operating voltage, total enthalpy, and total pressure; and classify and count all key variables using the test database;

[0009] The same type of arc heater is taken as the research object, all relevant test data are screened from the classification statistical results, and the key variable data and input parameters are statistically analyzed and plotted into a spectrum to obtain the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph; the spectrum is used to obtain the numerical solution of the key variables characterizing the performance of the arc heater as the input parameters change;

[0010] The input parameters include gas flow rate, given current value, throat size, and throat nozzle size.

[0011] Preferably, the test data obtained from subsequent tests are re-entered into the test database for processing to expand the map.

[0012] Preferably, the arc heater operating parameter data and test data are obtained from the control machine and the test machine respectively; the control machine is used to control the input parameters of the arc heater and monitor and record the operating data of the heater during the test; the test machine is used to measure and record the flow field parameters of the arc heater, and adjust the flow field parameters of the test machine by changing the input parameters of the control machine to achieve simulation of the aerodynamic thermal environment.

[0013] Preferably, the control machine and the test machine are two independent network systems, and the data of the two systems can only be associated through the test vehicle number.

[0014] A system for analyzing arc heater performance using a test database, including:

[0015] A database establishment module is used to establish a test database according to the arc heater operation parameter data and test data; the operation parameters are the operation data of the arc heater, including the main gas flow rate, the cold gas flow rate, the current value, the voltage value, and the operation time; the test data are the flow field parameters of the arc heater, including the heat flux, the arc chamber pressure, the mixing chamber pressure, and the total temperature;

[0016] A correlation module, based on the test database, correlates the arc heater operation parameter data and the test data with each other using the test vehicle number as a correlation quantity;

[0017] A classification statistics module is used to clearly identify key variables that characterize the performance of the arc heater, including arc heater electrode operating time, heater operating voltage, total enthalpy, and total pressure; and to perform classification statistics on all key variables;

[0018] The learning module takes the same type of arc heater as the research object, screens all relevant test data from the classification statistical results, takes two parameters of gas flow, given current value, throat size, and nozzle size as input variables, uses neural network for training, associates the input variables with key variables, and gradually increases the number of input variables until the deviation between the calculated results obtained after training and the measured data meets the requirements; statistically analyzes the key variable data and the input parameters, draws a graph, and obtains the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph; uses the graph to obtain the numerical solution of the key variables that characterize the performance of the arc heater as the input parameters change.

[0019] Preferably, the database establishment module obtains the arc heater operating parameter data and test data from the control machine and the test machine; the control machine controls the input parameters of the arc heater and monitors and records the operating data of the heater during the test; the test machine measures and records the flow field parameters of the arc heater, and adjusts the flow field parameters of the test machine by changing the input parameters of the control machine to achieve simulation of the aerodynamic thermal environment.

[0020] A computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method when executed by a processor.

[0021] A device for analyzing the performance of an arc heater using a test database comprises a memory, a processor and a computer program stored in the memory and executable on the processor. The steps of the method are implemented when the processor executes the computer program.

[0022] The advantages of the present invention compared with the prior art are as follows:

[0023] (1) By statistically analyzing a large amount of test data, a heater performance map is obtained. Based on the heater performance map, accurate prediction of the heater output parameters under different input conditions is achieved, thereby improving the test and debugging efficiency.

[0024] (2) By analyzing a large amount of test data, the performance of the same type of arc heaters with different structural sizes can be analyzed, which helps to optimize the design of the arc heater. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 Statistical methods for experimental databases.

[0026] Figure 2 Develop methods for heater performance mapping. DETAILED DESCRIPTION

[0027] like Figure 1 As shown, this is the test data statistical method of the present invention, Figure 2 To establish the performance map method of the present invention, the following is combined with Figure 1 , Figure 2 The implementation process of the method of the present invention is specifically introduced as follows:

[0028] (1) Establish a test database, and obtain the arc heater operating parameter data and test data from the control machine and the test machine respectively. The operating parameters include main gas flow, cold gas flow, current value, voltage value, and operating time. The test data include heat flux, arc chamber pressure, mixing chamber pressure, total temperature, etc. The control machine controls the input parameters of the arc heater and monitors and records the operating data of the heater during the test. The test machine measures and records the flow field parameters of the arc heater, and adjusts the flow field parameters of the test machine by changing the input parameters of the control machine to simulate the aerodynamic thermal environment. The control machine and the test machine are two independent network systems, and the data of the two systems can only be associated through the test vehicle number.

[0029] (2) After the test database captures the test data, the arc heater operating parameter data and the test data are correlated with each other using the test train number as the correlation quantity. All relevant test data can be queried and processed according to the train number. The operating parameters are stored in the form of a database, and the test parameters are stored in Excel format. Finally, they are converted into a unified database file through the test database;

[0030] (3) Clarify the key variables that characterize the performance of the arc heater, such as the arc heater electrode operating time, heater operating voltage, total enthalpy, total pressure and other parameters, and use the database platform to classify and count all relevant parameters. The classification and statistics criteria are classified by level. The first level is the data related to the same type of heater, the second level is the data related to the same type of arc heating with the same throat size, and the third level is the data related to the same type of arc heating with the same throat size and the same nozzle size;

[0031] (4) Taking the same type of arc heater as the research object, all relevant test data were screened, and the key variable data and input parameters were statistically analyzed (input parameters include gas flow, given current value, throat size, nozzle size, etc.). Through the neural network algorithm, they were associated with arc voltage value, arc chamber pressure, airflow enthalpy value, operating time, test probe surface heat flux, etc. (according to operating experience, arc voltage and arc chamber pressure are related to gas flow, current value, throat size, airflow enthalpy value is related to current value, throat size, and weakly related to gas flow, operating time is related to arc chamber pressure and given current value, and heat flux is related to airflow enthalpy value, arc chamber pressure, and nozzle size). After data training, the corresponding relationship was obtained, and two input variables were initially considered. The number of calculation variables was gradually increased according to the calculation accuracy until the deviation between the calculation result and the measurement result was less than 10%. The graph was drawn to obtain the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph;

[0032] (5) As the amount of experimental data increases, the spectrum is continuously expanded to obtain the numerical solution of the key variables characterizing the performance of the arc heater as the input parameters change.

[0033] The heater performance map is composed of a number of discrete points. Through a large amount of data, an envelope diagram of the heater performance can be obtained. On this basis, the key variables of the heater can be predicted and the equipment can be improved.

[0034] The present invention also provides a system for analyzing the performance of an arc heater using a test database, comprising:

[0035] A database establishment module is used to establish a test database according to the arc heater operation parameter data and test data; the operation parameters are the operation data of the arc heater, including the main gas flow rate, the cold gas flow rate, the current value, the voltage value, and the operation time; the test data are the flow field parameters of the arc heater, including the heat flux, the arc chamber pressure, the mixing chamber pressure, and the total temperature;

[0036] A correlation module, based on the test database, correlates the arc heater operation parameter data and the test data with each other using the test vehicle number as a correlation quantity;

[0037] A classification statistics module is used to clearly identify key variables that characterize the performance of the arc heater, including arc heater electrode operating time, heater operating voltage, total enthalpy, and total pressure; and to perform classification statistics on all key variables;

[0038] The learning module takes the same type of arc heater as the research object, screens all relevant test data from the classification statistical results, takes two parameters of gas flow, given current value, throat size, and nozzle size as input variables, uses neural network for training, associates the input variables with key variables, and gradually increases the number of input variables until the deviation between the calculated results obtained after training and the measured data meets the requirements; statistically analyzes the key variable data and the input parameters, draws a graph, and obtains the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph; uses the graph to obtain the numerical solution of the key variables that characterize the performance of the arc heater as the input parameters change.

[0039] The database establishment module obtains the arc heater operating parameter data and test data from the control machine and the test machine; the control machine is used to control the input parameters of the arc heater and monitor and record the operating data of the heater during the test; the test machine is used to measure and record the flow field parameters of the arc heater, and adjust the flow field parameters of the test machine by changing the input parameters of the control machine to achieve simulation of the aerodynamic thermal environment.

[0040] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0041] The present invention also provides a device for analyzing the performance of an arc heater using a test database, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0042] Parts not described in detail in the present invention belong to common knowledge of those skilled in the art.

Claims

1. A method for analyzing the performance of an arc heater using a test database, characterized in that The following steps are involved: A test database is established based on the arc heater operating parameter data and test data; the operating parameters are the arc heater operating data, including main gas flow, cold gas flow, current value, voltage value, and operating time; the test data are the flow field parameters of the arc heater, including heat flux, arc chamber pressure, mixing chamber pressure, and total temperature; Based on the test database, the arc heater operating parameter data and the test data are correlated with each other using the test vehicle number as a correlation quantity; Identify key variables that characterize the performance of the arc heater, including arc heater electrode operating time, heater operating voltage, total enthalpy, and total pressure; and classify and count all key variables using the test database; The same type of arc heater is taken as the research object, all relevant test data are screened from the classification statistical results, and the key variable data and input parameters are statistically analyzed and plotted into a spectrum to obtain the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph; the spectrum is used to obtain the numerical solution of the key variables characterizing the performance of the arc heater as the input parameters change; The input parameters include gas flow rate, given current value, throat size, and throat nozzle size.

2. The method according to claim 1, characterized in that: The test data obtained from subsequent tests were re-entered into the test database for processing and expansion of the map.

3. The method according to claim 1, characterized in that: The arc heater operating parameter data and test data are obtained from the control machine and the test machine respectively; the control machine is used to control the input parameters of the arc heater and monitor and record the operating data of the heater during the test; the test machine is used to measure and record the flow field parameters of the arc heater, and adjust the flow field parameters of the test machine by changing the input parameters of the control machine to achieve simulation of the aerodynamic thermal environment.

4. The method according to claim 3, characterized in that: The control machine and the test machine are two independent network systems, and the data of the two systems can only be linked through the test vehicle number.

5. A system for analyzing the performance of arc heaters using a test database, characterized in that include: A database establishment module is used to establish a test database based on the arc heater operation parameter data and test data; The operating parameters are the operating data of the arc heater, including the main gas flow, cold gas flow, current value, voltage value, and operating time; the test data are the flow field parameters of the arc heater, including heat flux, arc chamber pressure, mixing chamber pressure, and total temperature; A correlation module, based on the test database, correlates the arc heater operation parameter data and the test data with each other using the test vehicle number as a correlation quantity; A classification statistics module is used to clearly identify key variables that characterize the performance of the arc heater, including arc heater electrode operating time, heater operating voltage, total enthalpy, and total pressure; and to perform classification statistics on all key variables; The learning module takes the same type of arc heater as the research object, screens all relevant test data from the classification statistical results, takes two parameters of gas flow, given current value, throat size, and nozzle size as input variables, uses neural network for training, associates the input variables with key variables, and gradually increases the number of input variables until the deviation between the calculated results obtained after training and the measured data meets the requirements; statistically analyzes the key variable data and the input parameters, draws a graph, and obtains the arc heater electrode life graph, volt-ampere characteristic graph, and enthalpy-pressure characteristic graph; uses the graph to obtain the numerical solution of the key variables that characterize the performance of the arc heater as the input parameters change.

6. The system according to claim 5, characterized in that: The database establishment module obtains the arc heater operating parameter data and test data from the control machine and the test machine; the control machine is used to control the input parameters of the arc heater and monitor and record the operating data of the heater during the test; the test machine is used to measure and record the flow field parameters of the arc heater, and adjust the flow field parameters of the test machine by changing the input parameters of the control machine to achieve simulation of the aerodynamic thermal environment.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

8. A device for analyzing the performance of an arc heater using a test database, 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, the steps of the method according to any one of claims 1 to 4 are implemented.

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