Method, device and equipment for measuring gas temperature in aero-engine disc cavity

Abstract

The application relates to the technical field of data processing, and discloses an aero-engine rotating disc cavity gas temperature measurement method and device, which comprises the following steps: acquiring actual measurement data and simulation data of an aero-engine under multiple preset working conditions; optimizing model parameters of a preset simulation model based on stator wall surface actual measurement temperature; quantifying uncertainty of the optimized preset simulation model; obtaining an uncertainty range of simulated disc cavity gas temperature and an uncertainty range of simulated rotor temperature; constructing a compensation model; optimizing the compensation model based on the actual measurement data and the simulation data; and outputting a target disc cavity gas temperature based on the optimized compensation model. The method optimizes the preset simulation model, constructs a compensation model considering the physical mechanisms of heat conduction and radiation, and optimizes the compensation model by using the actual measurement data and the simulation data under multiple preset working conditions, so that the accuracy of disc cavity gas temperature measurement is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically to a method and apparatus for measuring the gas temperature inside the rotating disk cavity of an aero-engine. Background Technology

[0002] Accurate measurement of the gas temperature in the turbine disk cavity of an aero-engine is crucial for assessing the lifespan of hot-end components, optimizing the cooling system, and ensuring safe operation. The disk cavity typically refers to the narrow space formed in front of and behind the turbine disk, where the gas temperature is extremely high and its distribution is complex.

[0003] In related technologies, thermocouples are commonly used to measure the gas temperature inside a rotating disk cavity. The installation position and insertion depth of the thermocouple have a significant impact on the results; improper installation can introduce substantial errors. Under the specific high-temperature, high-speed rotating environment of the disk cavity, measurement errors become even more complex. Thermal radiation error is a major problem. The thermocouple measuring node is simultaneously exposed between the high-temperature rotor and the high-temperature stator, and the net radiative heat exchange causes the temperature at the measuring point to deviate significantly from the actual gas temperature. Due to the confined space of the disk cavity, the thermocouple is usually fixed to the stator wall and extends a certain distance into the disk cavity. Heat is conducted along the thermocouple wire to the measuring point, causing measurement deviations. Therefore, improving the measurement accuracy of the gas temperature inside the rotating disk cavity of an aero-engine is a pressing issue that needs to be addressed. Summary of the Invention

[0004] In view of this, the present invention provides a method for measuring the gas temperature inside the rotating disk cavity of an aero-engine, so as to solve the problem of insufficient accuracy in measuring the gas temperature inside the rotating disk cavity of an aero-engine.

[0005] In a first aspect, the present invention provides a method for measuring the gas temperature in the disk cavity of an aero-engine, the method comprising: Acquire measured and simulated data of the aero-engine under multiple preset operating conditions. The measured data includes at least the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity. The simulated data includes at least the simulated temperature of the gas in the disk cavity and the simulated temperature of the rotor. The simulated data is calculated by a preset simulation model. The model parameters of the preset simulation model are optimized based on the measured temperature of the stator wall, and the uncertainty of the optimized preset simulation model is quantified to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature. A compensation model is constructed, which includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is constructed based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity. The radiation error term is constructed based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity. Based on the measured and simulated data, the compensation model is optimized. Based on the optimized compensation model, the target disk cavity gas temperature is output.

[0006] In one optional implementation, optimizing the model parameters of the preset simulation model based on the measured temperature of the stator wall includes: The boundary conditions of the preset simulation model are calibrated based on the measured temperature of the stator wall. Under the calibrated boundary conditions, the input parameters of the preset simulation model are adjusted until the deviation between the simulated stator wall temperature output by the preset simulation model and the measured stator wall temperature meets the preset convergence condition.

[0007] In one optional implementation, the uncertainty quantification of the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature includes: The input parameters in the preset simulation model are sampled to obtain the sampling results. The input parameters include at least the inflow turbulence intensity and the heat transfer coefficient. The influence of the sampling results on the simulated disk cavity gas temperature and the simulated rotor temperature is quantified to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature.

[0008] In one optional implementation, the construction of the compensation model includes: Based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, a thermal conductivity error term is constructed. Based on the uncertainty range of the simulated rotor temperature, the measured temperature of the gas in the disk cavity, and the measured temperature of the stator wall, a radiation error term is constructed; The compensation model is constructed based on the thermal conductivity error term and the radiation error term.

[0009] In one alternative implementation, the compensation model is determined according to the following formula:

[0010] in, Represents the compensation model. This represents the measured temperature of the stator wall. This represents the thermal conductivity error term. Indicates the radiation error term; The thermal conductivity error term is determined according to the following formula:

[0011] in, This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. Indicates the thermal conductivity correction factor; The radiation error term is determined according to the following formula:

[0012] in, This represents the range of uncertainty in the simulated rotor temperature. , Indicates the simulated rotor temperature. This represents the uncertainty in the simulated rotor temperature. This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. This represents the first radiative heat correction factor. This represents the second radiative heat correction factor.

[0013] In one optional implementation, optimizing the compensation model based on the measured data and simulated data includes: A first optimization objective and a second optimization objective are set. The first optimization objective is used to ensure that the gas temperature output by the compensation model is within the uncertainty range of the simulated disk cavity gas temperature. The second optimization objective is used to ensure that the gas temperature output by the compensation model satisfies the preset energy balance equation. Solve for the first optimization objective and the second optimization objective to obtain the thermal conductivity correction coefficient, the first radiative heat correction coefficient and the second radiative heat correction coefficient of the compensation model.

[0014] In one optional implementation, the step of outputting the target disk cavity gas temperature based on the optimized compensation model includes: Obtain the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity corresponding to the current operating condition; The measured temperature of the stator wall and the measured temperature of the gas in the disk cavity are input into the optimized compensation model to calculate the target gas temperature in the disk cavity.

[0015] The method for measuring the gas temperature in the disk cavity of an aero-engine provided in this embodiment includes acquiring measured and simulated data of the aero-engine under multiple preset operating conditions; optimizing the model parameters of a preset simulation model based on the measured temperature of the stator wall; quantifying the uncertainty of the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature; constructing a compensation model; optimizing the compensation model based on the measured and simulated data; and outputting the target disk cavity gas temperature based on the optimized compensation model. This method optimizes the preset simulation model, constructs a compensation model that simultaneously considers the physical mechanisms of heat conduction and radiation, and optimizes the compensation model using measured and simulated data under multiple preset operating conditions. This expands the measurement error into a high-confidence estimate with a confidence interval, resulting in a more accurate output of the target disk cavity gas temperature and improving the accuracy of disk cavity gas temperature measurement.

[0016] Secondly, the present invention provides a measuring device for the gas temperature in the disk cavity of an aero-engine, the device comprising: The data acquisition module is used to acquire measured data and simulated data of the aero-engine under multiple preset operating conditions. The measured data includes at least the measured temperature of the stator wall and the measured temperature of the disk gas. The simulated data includes at least the simulated disk gas temperature and the simulated rotor temperature. The simulated data is calculated by a preset simulation model. The parameter optimization module is used to optimize the model parameters of the preset simulation model based on the measured temperature of the stator wall, and to perform uncertainty quantification on the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature. The model building module is used to build a compensation model, which includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is built based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, and the radiation error term is built based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity. The model optimization module is used to optimize the compensation model based on the measured data and the simulated data; The temperature output module is used to output the target disk cavity gas temperature based on the optimized compensation model.

[0017] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for measuring the gas temperature of the aero-engine disk cavity as described in the first aspect or any corresponding embodiment.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for measuring the gas temperature in the disk cavity of an aero-engine as described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a schematic flowchart of a method for measuring the gas temperature in the disk cavity of an aero-engine according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the test of gas temperature and wall temperature in the disk cavity of an aircraft engine according to an embodiment of the present invention; Figure 3 This is a structural block diagram of a device for measuring the gas temperature in the disk cavity of an aero-engine according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Accurate measurement of gas temperature in the turbine disk cavity of an aero-engine is crucial for assessing the lifespan of hot-end components, optimizing the cooling system, and ensuring safe operation. The disk cavity typically refers to the narrow space formed in front of and behind the turbine disk, where the gas temperature is extremely high and its distribution is complex. However, due to the confined space, structural obstructions, and high-speed rotation of the disk cavity, direct gas measurement using sensors (e.g., thermocouples) faces multiple interferences. Because the thermocouple exchanges heat with the stator wall through its mounting base, the temperature at the measuring point deviates from the actual gas temperature, resulting in thermal conduction errors. The thermocouple is also affected by radiative heat transfer from both the high-temperature rotor and the high-temperature stator wall, leading to radiation errors.

[0023] Computational Fluid Dynamics (CFD) refers to the technology of using numerical methods to solve the governing equations of fluid mechanics (e.g., the Navier-Stokes equations) and perform computer simulations of physical phenomena such as flow, heat transfer, and combustion. In related technologies, CFD models can be used to calculate the spatial distribution of gas temperature, rotor temperature, and wall heat transfer coefficient within the engine disk, providing reference information for the entire flow field for temperature compensation. However, due to uncertainties in turbulence models and boundary condition inputs, CFD results often exhibit systematic biases. Based on this, this invention provides a method for measuring the gas temperature within an aero-engine disk. By using multi-source data and real-time compensation, temperature measurement errors caused by heat conduction and radiation are eliminated. Furthermore, measured data from the stator wall are used to comprehensively scale and correct the CFD systematic errors. Combined with multi-state test data, the accuracy and adaptability of the model under all operating conditions are improved, ultimately achieving reliable real-time monitoring of the gas temperature within the disk.

[0024] According to an embodiment of the present invention, a method for measuring the gas temperature in the disk cavity of an aircraft engine is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] This embodiment provides a method for measuring the gas temperature in the disk cavity of an aero-engine. Figure 1 This is a flowchart of a method for measuring the gas temperature in the disk cavity of an aero-engine according to an embodiment of the present invention, as shown below. Figure 1 As shown, the process includes the following steps: Step S101: Obtain measured and simulated data of the aero-engine under multiple preset operating conditions.

[0026] The measured data includes at least the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, while the simulated data includes at least the simulated temperature of the gas in the disk cavity and the simulated rotor temperature. The simulated data is calculated from a preset simulation model. Multiple preset operating conditions refer to various operating states that may occur during the actual operation or testing of the aero-engine, such as different speeds and different power outputs.

[0027] The measured temperature of the stator wall can be obtained by a temperature sensor (e.g., a thermocouple) pre-installed at a specific location on the engine stator wall (e.g., at a radius corresponding to the rotating disk cavity height). This measured temperature reflects the true thermal state of the stator wall. The measured temperature of the gas in the disk cavity can be obtained by a temperature sensing element inserted deep into the disk cavity. Figure 2 As shown, the measured temperature of the stator wall is Figure 2 Temperature measuring points on the wall of the mirror The measured temperature of the gas in the disk cavity was Figure 2 Gas temperature measuring point in the middle plate cavity .

[0028] The preset simulation model can be a numerical simulation model built based on computational fluid dynamics (CFD), which can be used to simulate the flow and heat transfer process in the disk cavity. The simulated disk cavity gas temperature and simulated rotor temperature are calculated through the preset simulation model.

[0029] Step S102: Optimize the model parameters of the preset simulation model based on the measured temperature of the stator wall, and quantify the uncertainty of the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature.

[0030] The model parameters of the preset simulation model are adjusted by using the measured temperature of the stator wall, so that the output of the optimized preset simulation model in terms of stator wall temperature is closer to the measured value, thereby reducing the systematic bias of the model. The model parameters may include boundary condition parameters and physical model parameters. Among them, the boundary condition parameters may include inlet flow rate, inlet temperature, outlet temperature, and outlet pressure, while the physical model parameters may include empirical constants in the turbulence model.

[0031] In some optional implementations, initial values ​​of model parameters can be set based on engineering experience or reference data, and a preset simulation model can be run to obtain the simulated stator wall temperature. Then, the simulated stator wall temperature is compared with the measured stator wall temperature, and the deviation between the two is calculated. According to the direction and magnitude of the deviation, the model parameters are adjusted by single-variable or multi-variable coupling, the model is run again, and the comparison is repeated. The above iterative process is repeated until the deviation between the simulated stator wall temperature and the measured stator wall temperature meets the preset convergence condition (e.g., the deviation is less than a set threshold). The model parameters obtained at this time are the optimized model parameters. The optimized preset simulation model is closer to the measured value in terms of the output of the stator wall temperature.

[0032] Building upon this, and considering the inherent uncertainties in the model input parameters (e.g., inflow conditions, physical properties, etc.), this step further quantifies the uncertainty of the optimized preset simulation model. For example, by using sampling methods, it analyzes how the uncertainty of the input parameters is transmitted to the output results, thereby obtaining the uncertainty ranges of the simulated disk gas temperature and the simulated rotor temperature. The uncertainty range reflects the confidence interval of the model's prediction results, rather than a single deterministic value.

[0033] Step S103: Construct a compensation model.

[0034] The compensation model includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is constructed based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, while the radiation error term is constructed based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity.

[0035] Separate error terms, thermal conductivity and radiation, are constructed. The thermal conductivity error term characterizes the measurement deviation caused by thermal conduction of the thermocouple by the difference between the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity. The radiation error term characterizes the measurement deviation caused by radiative heat transfer of the thermocouple by simulating the uncertainty range of the rotor temperature and the measured temperature of the gas in the disk cavity.

[0036] Step S104: Optimize the compensation model based on measured data and simulated data.

[0037] The compensation model includes multiple correction coefficients, the values ​​of which affect the accuracy of the compensation results. The coefficients in the compensation model are optimized based on measured and simulated data. The optimization objective can be to ensure that the compensated gas temperature is consistent with the information provided by the simulated data (e.g., the uncertainty range of the simulated gas temperature in the disk cavity), and / or to ensure that the compensated gas temperature satisfies physical laws such as energy conservation at the system level, thereby obtaining model coefficients with good generalization performance under multiple operating conditions.

[0038] Step S105: Based on the optimized compensation model, output the target disk cavity gas temperature.

[0039] After optimizing the compensation model, for any operating condition that has been optimized or other operating conditions that have not been optimized, the measured temperature of the stator wall and the measured temperature of the disk gas under that operating condition are obtained. The measured temperature of the stator wall and the measured temperature of the disk gas are input into the optimized compensation model. The optimized compensation model calculates the disk gas temperature after compensation for thermal conduction error and radiation error, and outputs it as the target disk gas temperature under that operating condition.

[0040] The method for measuring the gas temperature in the disk cavity of an aero-engine provided in this embodiment includes acquiring measured and simulated data of the aero-engine under multiple preset operating conditions; optimizing the model parameters of a preset simulation model based on the measured temperature of the stator wall; quantifying the uncertainty of the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature; constructing a compensation model; optimizing the compensation model based on the measured and simulated data; and outputting the target disk cavity gas temperature based on the optimized compensation model. This method optimizes the preset simulation model, constructs a compensation model that simultaneously considers the physical mechanisms of heat conduction and radiation, and optimizes the compensation model using measured and simulated data under multiple preset operating conditions. This expands the measurement error into a high-confidence estimate with a confidence interval, resulting in a more accurate output of the target disk cavity gas temperature and improving the accuracy of disk cavity gas temperature measurement.

[0041] In some optional implementations, step S102 above includes: Step S201: Calibrate the boundary conditions of the preset simulation model based on the measured temperature of the stator wall.

[0042] The boundary conditions of the preset simulation model include parameters such as inlet flow rate, inlet temperature, and outlet pressure. Since these boundary conditions may have measurement errors or uncertainties during actual engine operation, directly using design values ​​or empirical values ​​will lead to deviations between the model output and the actual physical process. The measured stator wall temperature is used as a calibration benchmark to calibrate the boundary conditions. For example, experimental measurement data or reliable reference values ​​can be used to set the inlet flow rate and inlet temperature. If measured data is lacking, the boundary conditions are corrected through back-calculation or sensitivity analysis to ensure that the simulated stator wall temperature output by the model is close to the measured stator wall temperature.

[0043] Step S202: Under the calibrated boundary conditions, adjust the input parameters of the preset simulation model until the deviation between the simulated stator wall temperature output by the preset simulation model and the measured stator wall temperature meets the preset convergence condition.

[0044] After boundary condition calibration is completed, this step further adjusts the physical model parameters of the preset simulation model. The physical model parameters include at least the empirical constants from the turbulence model, such as those in... k - ε Turbulence model involves C μ , C ε1 , C ε2Equal coefficients. Specifically, an iterative parameter tuning method is adopted. Initial values ​​of model parameters can be set based on engineering experience or reference data. The preset simulation model is run to obtain the simulated stator wall temperature. Then, the simulated stator wall temperature is compared with the measured stator wall temperature, and the deviation between the two is calculated. According to the direction and magnitude of the deviation, the model parameters are adjusted by single-variable or multi-variable coupling, the model is run again, and the comparison is repeated. The above iterative process is repeated until the deviation between the simulated stator wall temperature and the measured stator wall temperature meets the preset convergence condition (for example, the deviation is less than a set threshold). The model parameters obtained at this time are the optimized model parameters. The optimized preset simulation model is closer to the measured value in terms of stator wall temperature output.

[0045] In some optional implementations, step S102 above includes: Step S203: Sample the input parameters in the preset simulation model to obtain the sampling results.

[0046] The input parameters include at least the inflow turbulence intensity and the heat transfer coefficient. The inflow turbulence intensity reflects the intensity of the airflow turbulence entering the disk cavity, while the heat transfer coefficient characterizes the heat exchange capacity between the wall and the fluid.

[0047] Optionally, the Latin hypercube sampling method can be used to sample the input parameters. During the sampling process, based on engineering experience or the statistical characteristics of measured data, reasonable value ranges and probability distributions (such as normal distribution or uniform distribution) are set for the incoming flow turbulence intensity and heat transfer coefficient, respectively. Multiple sets of sampling points are generated within this range as the sampling results.

[0048] Step S204: Quantify the impact of sampling results on the simulated disk cavity gas temperature and the simulated rotor temperature to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature.

[0049] For each set of sampling results (i.e., each set of input parameter combinations) generated in step S203, the optimized preset simulation model is run to obtain the corresponding simulated disk gas temperature and simulated rotor temperature outputs, forming an output sample set. Based on this, sensitivity analysis or surrogate model techniques are used to quantify the impact of input parameter uncertainties on the output results. For example, a response surface surrogate model can be constructed to approximate the mapping relationship between input parameters and output responses. Then, based on the Monte Carlo method or analytical propagation method, the uncertainty distribution of the output results can be derived from the uncertainty distribution of the input parameters, obtaining the uncertainty of the disk gas temperature and the uncertainty of the rotor temperature, and thus the uncertainty range of the simulated disk gas temperature and the uncertainty range of the simulated rotor temperature.

[0050] Specifically, the uncertainty range of the simulated disk cavity gas temperature is: Uncertainty range of simulated rotor temperature ,in, This indicates the simulated gas temperature in the disk cavity. The uncertainty in the temperature of the gas in the disk cavity. Indicates the simulated rotor temperature. This represents the uncertainty of the rotor temperature.

[0051] In some optional implementations, step S103 above includes: Step S301: Based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, construct a thermal conductivity error term.

[0052] Step S302: Based on the uncertainty range of the simulated rotor temperature, the measured temperature of the gas in the disk cavity, and the measured temperature of the stator wall, a radiation error term is constructed. Step S303: Construct a compensation model based on the thermal conductivity error term and the radiation error term.

[0053] Specifically, the compensation model is determined according to the following formula:

[0054] in, Represents the compensation model. This represents the measured temperature of the stator wall. This represents the thermal conductivity error term. Indicates the radiation error term; The thermal conductivity error term is determined according to the following formula:

[0055] in, This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. Indicates the thermal conductivity correction factor; The radiation error term is determined according to the following formula:

[0056] in, This represents the range of uncertainty in the simulated rotor temperature. , Indicates the simulated rotor temperature. This represents the uncertainty in the simulated rotor temperature. This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. This represents the first radiative heat correction factor. This represents the second radiative heat correction factor.

[0057] In some alternative implementations, step S104 includes: Step S401: Set the first optimization objective and the second optimization objective.

[0058] The first optimization objective is to ensure that the gas temperature output by the compensation model is within the uncertainty range of the simulated disk cavity gas temperature, and the second optimization objective is to ensure that the gas temperature output by the compensation model satisfies the preset energy balance equation.

[0059] The first optimization objective focuses on the consistency between the compensation result and the CFD simulation information, requiring the compensated gas temperature to fall within the uncertainty range of the simulated disk cavity gas temperature. The second optimization objective focuses on the physical rationality of the compensation result at the system level, requiring the compensated gas temperature to satisfy the preset energy balance equation. The energy balance equation is the macroscopic energy conservation relationship of the disk cavity air system, established for example based on the enthalpy values ​​of the inlet and outlet, and the heat dissipation of the disk cavity wall. Substituting the compensated gas temperatures under multiple operating conditions into this equation requires minimizing the closure error of the system's energy balance.

[0060] Specifically, the gas temperature after compensation under multiple states can be... (States i=1 to n) Substituting into the macroscopic energy balance equation of the disk-cavity air system, we get:

[0061] in, The temperature of the imported gas; The mass flow rate of the disk cavity can be calculated from a preset simulation model; This is the specific heat capacity of air at constant pressure (which can be a function of temperature). The total heat absorbed through the wall of the disk cavity can be calculated using a preset simulation model.

[0062] Step S402: Solve for the first optimization objective and the second optimization objective to obtain the thermal conductivity correction coefficient, the first radiative heat correction coefficient and the second radiative heat correction coefficient of the compensation model.

[0063] The first and second optimization objectives are solved collaboratively. Multi-objective optimization algorithms can be used during the solution process, such as the weighted summation method to transform the two objectives into a single-objective optimization problem, or the Pareto optimization method to find a solution set that achieves a relatively optimal state for both objectives. During the optimization process, the thermal conductivity correction coefficient, the first radiative heat correction coefficient, and the second radiative heat correction coefficient are used as design variables. The positional relationship between the uncertainty range of the compensated gas temperature and the simulated disk cavity gas temperature is used as the evaluation index for the first optimization objective, and the closure error of the energy balance equation is used as the evaluation index for the second optimization objective. Through iterative search, the coefficient values ​​that simultaneously satisfy or achieve optimal balance for both optimization objectives are obtained. The coefficients obtained after optimization are the parameters of the compensation model, including the thermal conductivity correction coefficient, the first radiative heat correction coefficient, and the second radiative heat correction coefficient.

[0064] In some alternative implementations, step S105 includes: Step S501: Obtain the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity corresponding to the current operating condition.

[0065] The current operating condition can be one of the preset operating conditions that have already participated in the compensation model optimization, or it can be other operating conditions that have not participated in the optimization. For any operating condition that requires measuring the gas temperature in the disk cavity, the measured temperature of the stator wall under that operating condition is collected by a temperature sensor that is pre-installed at a specific position on the engine stator wall, and the measured temperature of the gas in the disk cavity under that operating condition is collected by a temperature measuring element such as a thermocouple that extends into the disk cavity.

[0066] Step S502: Input the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity into the optimized compensation model to calculate the target gas temperature in the disk cavity.

[0067] The actual temperature of the gas in the disk cavity after compensation is:

[0068] in, This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. Indicates the thermal conductivity correction factor. This represents the first radiative heat correction factor. This represents the second radiative heat correction factor. This indicates the range of uncertainty in the simulated rotor temperature.

[0069] For other state temperature corrections where the results of the pre-set simulation model calculation are lacking, the rotor wall and disk cavity gas temperatures are obtained using the temperature ratio method based on adjacent state temperatures, i.e.:

[0070] In this context, superscript A indicates other states that lack the calculation results of the preset simulation model, while superscript B indicates existing states that have the calculation results of the preset simulation model.

[0071] use The compensated gas temperature in the disk cavity is obtained, which is the target gas temperature in the disk cavity.

[0072] Furthermore, the target disk cavity gas temperature includes the best estimate of the disk cavity gas temperature. Confidence interval And a reliability evaluation. The optimal estimate of the gas temperature in the disk cavity represents the point estimate of the gas temperature calculated using the optimized compensation model. The confidence interval integrates information from the uncertainty propagation of the preset simulation model, the residuals of model coefficient optimization, and the energy balance closure error. The total uncertainty is... Uncertainty synthesis methods can be used for calculation.

[0073] This embodiment also provides a device for measuring the gas temperature in the disk cavity of an aircraft engine. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0074] This embodiment provides a device for measuring the gas temperature in the disk cavity of an aero-engine, such as... Figure 3 As shown, it includes: The data acquisition module is used to acquire measured data and simulated data of the aero-engine under multiple preset operating conditions. The measured data includes at least the measured temperature of the stator wall and the measured temperature of the disk gas. The simulated data includes at least the simulated disk gas temperature and the simulated rotor temperature. The simulated data is calculated by a preset simulation model. The parameter optimization module is used to optimize the model parameters of the preset simulation model based on the measured temperature of the stator wall, and to perform uncertainty quantification on the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature. The model building module is used to build a compensation model, which includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is built based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, and the radiation error term is built based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity. The model optimization module is used to optimize the compensation model based on the measured data and the simulated data; The temperature output module is used to output the target disk cavity gas temperature based on the optimized compensation model.

[0075] In some optional implementations, the parameter optimization module includes: A condition calibration unit is used to calibrate the boundary conditions of the preset simulation model based on the measured temperature of the stator wall. The parameter adjustment unit is used to adjust the input parameters of the preset simulation model under the calibrated boundary conditions until the deviation between the simulated stator wall temperature output by the preset simulation model and the measured stator wall temperature meets the preset convergence condition.

[0076] In some optional implementations, the parameter optimization module includes: The parameter sampling unit is used to sample the input parameters in the preset simulation model to obtain the sampling results. The input parameters include at least the inflow turbulence intensity and the heat transfer coefficient. A quantization sampling unit is used to quantify the influence of the sampling results on the simulated disk cavity gas temperature and the simulated rotor temperature, so as to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature.

[0077] In some alternative implementations, the model building module includes: A thermal conductivity error term construction unit is used to construct a thermal conductivity error term based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity; The radiation error term construction unit is used to construct the radiation error term based on the uncertainty range of the simulated rotor temperature, the measured temperature of the disk cavity gas, and the measured temperature of the stator wall. The compensation model is constructed based on the thermal conductivity error term and the radiation error term.

[0078] In some alternative implementations, the compensation model is determined according to the following formula:

[0079] in, Represents the compensation model. This represents the measured temperature of the stator wall. This represents the thermal conductivity error term. Indicates the radiation error term; The thermal conductivity error term is determined according to the following formula:

[0080] in, This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. Indicates the thermal conductivity correction factor; The radiation error term is determined according to the following formula:

[0081] in, This represents the range of uncertainty in the simulated rotor temperature. , Indicates the simulated rotor temperature. This represents the uncertainty in the simulated rotor temperature. This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. This represents the first radiative heat correction factor. This represents the second radiative heat correction factor.

[0082] In some optional implementations, the model optimization module includes: The target setting unit is used to set a first optimization target and a second optimization target. The first optimization target is used to ensure that the gas temperature after compensation output by the compensation model is within the uncertainty range of the simulated disk cavity gas temperature. The second optimization target is used to ensure that the gas temperature after compensation output by the compensation model satisfies the preset energy balance equation. The objective solving unit is used to solve the first optimization objective and the second optimization objective to obtain the thermal conductivity correction coefficient, the first radiative heat correction coefficient and the second radiative heat correction coefficient of the compensation model.

[0083] In some alternative implementations, the temperature output module includes: The temperature acquisition unit is used to acquire the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity corresponding to the current operating condition. The temperature output unit is used to input the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity into the optimized compensation model to calculate the target gas temperature in the disk cavity.

[0084] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0085] In this embodiment, the device for measuring the gas temperature in the engine disk cavity is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0086] This invention also provides a computer device having the above-described device for measuring the gas temperature in the disk cavity of an aero-engine.

[0087] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 4 Take a processor 10 as an example.

[0088] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0089] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0090] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0091] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0092] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0093] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0094] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0095] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for measuring the gas temperature in the disk cavity of an aero-engine, characterized in that, The method includes: Acquire measured and simulated data of the aero-engine under multiple preset operating conditions. The measured data includes at least the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity. The simulated data includes at least the simulated temperature of the gas in the disk cavity and the simulated temperature of the rotor. The simulated data is calculated by a preset simulation model. The model parameters of the preset simulation model are optimized based on the measured temperature of the stator wall, and the uncertainty of the optimized preset simulation model is quantified to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature. A compensation model is constructed, which includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is constructed based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity. The radiation error term is constructed based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity. Based on the measured and simulated data, the compensation model is optimized. Based on the optimized compensation model, the target disk cavity gas temperature is output.

2. The method according to claim 1, characterized in that, The optimization of the model parameters of the preset simulation model based on the measured temperature of the stator wall includes: The boundary conditions of the preset simulation model are calibrated based on the measured temperature of the stator wall. Under the calibrated boundary conditions, the input parameters of the preset simulation model are adjusted until the deviation between the simulated stator wall temperature output by the preset simulation model and the measured stator wall temperature meets the preset convergence condition.

3. The method according to claim 2, characterized in that, The uncertainty quantification of the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature includes: The input parameters in the preset simulation model are sampled to obtain the sampling results. The input parameters include at least the inflow turbulence intensity and the heat transfer coefficient. The influence of the sampling results on the simulated disk cavity gas temperature and the simulated rotor temperature is quantified to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature.

4. The method according to claim 1, characterized in that, The construction of the compensation model includes: Based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, a thermal conductivity error term is constructed. Based on the uncertainty range of the simulated rotor temperature, the measured temperature of the gas in the disk cavity, and the measured temperature of the stator wall, a radiation error term is constructed; The compensation model is constructed based on the thermal conductivity error term and the radiation error term.

5. The method according to claim 4, characterized in that, The compensation model is determined according to the following formula: in, Represents the compensation model. This represents the measured temperature of the stator wall. This represents the thermal conductivity error term. Indicates the radiation error term; The thermal conductivity error term is determined according to the following formula: in, This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. Indicates the thermal conductivity correction factor; The radiation error term is determined according to the following formula: in, This represents the range of uncertainty in the simulated rotor temperature. , Indicates the simulated rotor temperature. This represents the uncertainty in the simulated rotor temperature. This represents the measured temperature of the stator wall. This represents the measured temperature of the stator wall. This represents the first radiative heat correction factor. This represents the second radiative heat correction factor.

6. The method according to claim 1, characterized in that, The optimization of the compensation model based on the measured data and simulated data includes: A first optimization objective and a second optimization objective are set. The first optimization objective is used to ensure that the gas temperature output by the compensation model is within the uncertainty range of the simulated disk cavity gas temperature. The second optimization objective is used to ensure that the gas temperature output by the compensation model satisfies the preset energy balance equation. Solve for the first optimization objective and the second optimization objective to obtain the thermal conductivity correction coefficient, the first radiative heat correction coefficient and the second radiative heat correction coefficient of the compensation model.

7. The method according to claim 6, characterized in that, The optimized compensation model outputs the target disk cavity gas temperature, including: Obtain the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity corresponding to the current operating condition; The measured temperature of the stator wall and the measured temperature of the gas in the disk cavity are input into the optimized compensation model to calculate the target gas temperature in the disk cavity.

8. A device for measuring the gas temperature in the disk cavity of an aero-engine, characterized in that, The device includes: The data acquisition module is used to acquire measured data and simulated data of the aero-engine under multiple preset operating conditions. The measured data includes at least the measured temperature of the stator wall and the measured temperature of the disk gas. The simulated data includes at least the simulated disk gas temperature and the simulated rotor temperature. The simulated data is calculated by a preset simulation model. The parameter optimization module is used to optimize the model parameters of the preset simulation model based on the measured temperature of the stator wall, and to perform uncertainty quantification on the optimized preset simulation model to obtain the uncertainty range of the simulated disk cavity gas temperature and the uncertainty range of the simulated rotor temperature. The model building module is used to build a compensation model, which includes a thermal conductivity error term and a radiation error term. The thermal conductivity error term is built based on the measured temperature of the stator wall and the measured temperature of the gas in the disk cavity, and the radiation error term is built based on the uncertainty range of the simulated rotor temperature and the measured temperature of the gas in the disk cavity. The model optimization module is used to optimize the compensation model based on the measured data and the simulated data; The temperature output module is used to output the target disk cavity gas temperature based on the optimized compensation model.

9. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for measuring the gas temperature in the disk cavity of an aero-engine as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the method for measuring the gas temperature in the engine disk cavity as described in any one of claims 1 to 7.

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