Method for improving temperature measurement performance of aero-engine

Abstract

The invention relates to a method for improving temperature measurement performance of an aero-engine, and the method comprises the following steps: carrying out the response characteristic analysis of a temperature sensor, and obtaining a response error of the temperature sensor in a response process; performing temperature measurement deviation analysis on the temperature sensor to obtain the temperature measurement deviation of the temperature sensor; performing structure optimization on the temperature sensor by taking the time constant, the response error, the temperature measurement deviation and the reliability of the sensor as performance indexes to obtain the temperature sensor with the optimal structure; and establishing a dynamic parameterization compensation model based on the response error and the temperature measurement deviation of the temperature sensor with the optimal structure, and completing the self-adaptive compensation of the measurement error through the dynamic parameterization compensation model. The overall temperature measurement performance of the aero-engine can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aero-engine temperature measurement, and in particular to a method for improving the temperature measurement performance of an aero-engine. Background Art

[0002] The aircraft engine is the heart of the aircraft, and its advancement reflects the industrial level of a country. In the ground test of the aircraft engine and the process of equipment flight service, the accurate measurement of its airflow temperature is of great significance for evaluating the performance, status monitoring and fuel control of the aircraft engine. Affected by factors such as heat transfer loss and incomplete stagnation, the high-temperature airflow temperature sensor has many factors affecting the measurement results and complex influencing mechanisms when measuring. Therefore, the measurement error is often large, which makes the design of the airflow temperature sensor very difficult; at the same time, due to the certain mass of the temperature sensor, it has a certain thermal inertia, which makes the temperature sensor unable to respond immediately to the rapid change of the airflow temperature, but has a certain response lag. For the first-order system, the response time constant is usually used to reflect its dynamic response ability. Although the temperature sensor does not necessarily belong to the first-order system, for the convenience of studying the problem, the time constant is still used as the dynamic performance indicator of the airflow temperature sensor at home and abroad. Due to the harsh and changeable working conditions of the aircraft engine in the flight service state, the measurement error and dynamic response lag often coexist, and under the working conditions of vibration and high temperature, higher requirements are put forward for the reliability measurement of the temperature sensor. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a method for improving the temperature measurement performance of an aircraft engine, which can improve the temperature measurement accuracy and reliability of the aircraft engine and reduce the response time.

[0004] The technical solution adopted by the present invention to solve the technical problem is: to provide a method for improving the temperature measurement performance of an aircraft engine, comprising the following steps:

[0005] Analyze the response characteristics of the temperature sensor and obtain the response error of the temperature sensor during the response process;

[0006] Perform temperature measurement deviation analysis on the temperature sensor to obtain the temperature measurement deviation of the temperature sensor;

[0007] Taking time constant, response error, temperature measurement deviation and sensor reliability as performance indicators, the temperature sensor is structurally optimized to obtain a temperature sensor with an optimal structure;

[0008] A dynamic parameterized compensation model is established based on the response error and temperature measurement deviation of the temperature sensor with the optimal structure, and adaptive compensation of the measurement error is completed through the dynamic parameterized compensation model.

[0009] The response characteristic analysis of the temperature sensor is performed to obtain the response error of the temperature sensor during the response process, specifically:

[0010] Finite element simulation software is used to establish a sensor model of the temperature sensor, and the engine operating environment is simulated to cause the ambient temperature of the sensor model to produce a temperature step. The dynamic response characteristics of the sensor model are analyzed to obtain the time constant of the temperature sensor, and the response error of the temperature sensor during the response process is calculated based on the time constant.

[0011] The temperature measurement deviation analysis of the temperature sensor is performed to obtain the temperature measurement deviation of the temperature sensor, which is specifically:

[0012] The sensor model of the temperature sensor is established by using the finite element simulation method, and different working conditions under the service state of the engine are simulated to keep the ambient temperature of the sensor model constant. The deviation between the sensor model and the theoretical value is analyzed, and the deviation is recorded as the temperature measurement deviation of the temperature sensor.

[0013] The different operating conditions of the engine under service are achieved by changing the airflow velocity and / or airflow pressure.

[0014] The temperature sensor is structurally optimized with time constant, response error, temperature measurement deviation and sensor reliability as performance indicators to obtain a temperature sensor with an optimal structure, specifically:

[0015] The temperature sensor is divided into three parts: internal structure, external hysteresis cover and shell packaging. Finite element simulation software is used to control the optimization variables to analyze the comprehensive influence of the three parts on the time constant, response error, temperature measurement deviation and sensor reliability after optimization. The optimal structural optimization design is selected according to the overall optimization results of the four performance indicators of time constant, response error, temperature measurement deviation and sensor reliability.

[0016] The dynamic parameterized compensation model is established based on the response error and temperature measurement deviation of the temperature sensor with the optimal structure, specifically:

[0017] First-order response and multi-order response functions are used to parameterize the response error and temperature measurement deviation. The model is parameterized and fitted according to the dynamic response characteristics of the temperature sensor with the optimal structure. Multiple parameter variables are added to the fitting model in combination with the changing law of temperature measurement deviation to establish a dynamic parameterized compensation model.

[0018] The dynamic parameterized compensation model is expressed as: Y(x)=Y 12 (x)+Y 22 (x)+e*T0*Ma 2 +f*T v *h*L*(4*h / λ / d) 1 / 2+g*μ*ω*T v 4 , where Y(x) is the dynamic parameterized compensation model, Y 12 (x) is the first-order parameterized compensation model, Y 22 (x) is the second-order response compensation model, e is the speed error compensation variable, T0 is the initial step temperature, Ma is the airflow Mach number, f is the thermal conductivity error compensation variable, T v is the stability of the fixed flange, h is the surface heat transfer coefficient, L is the length of the temperature measuring element, λ is the thermal conductivity, d is the diameter of the temperature measuring element, g is the radiation error compensation variable, μ is the surface emissivity of the temperature measuring element, and ω is the Stefan-Boltzmann constant.

[0019] Beneficial Effects

[0020] Due to the adoption of the above-mentioned technical scheme, the present invention has the following advantages and positive effects compared with the prior art: the present invention analyzes the response characteristics of the temperature sensor, analyzes the temperature measurement deviation of the temperature sensor, optimizes the multivariable structure of the temperature sensor and adaptively compensates for the measurement error, and refers to the service working conditions of the aircraft engine. From the aspects of temperature sensor design optimization, reliability evaluation and adaptive compensation of measurement errors, the overall improvement of the temperature measurement performance of the aircraft engine is formed, thereby improving the temperature measurement accuracy of the aircraft engine, reducing the response time, and ensuring stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The schematic diagram of the method for improving the temperature measurement performance of aircraft engines;

[0022] Figure 2 Schematic diagram of multivariable structural optimization of temperature sensor;

[0023] Figure 3 The influence trend of temperature sensor structure optimization on time constant and response error;

[0024] Figure 4 The influence trend of temperature sensor structure optimization on the reliability index MTTF value;

[0025] Figure 5 The influence trend of temperature sensor structure optimization on temperature measurement deviation;

[0026] Figure 6 This is the schematic diagram of the adaptive compensation of the temperature sensor's temperature measurement error. DETAILED DESCRIPTION

[0027] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0028] The embodiment of the present invention relates to a method for improving the temperature measurement performance of an aircraft engine, such as Figure 1 As shown, it is mainly divided into: response characteristic analysis of temperature sensor, temperature measurement deviation analysis, optimization of temperature sensor structure and adaptive compensation, which specifically includes the following steps:

[0029] Step 1: Analyze the response characteristics of the temperature sensor to obtain the response error of the temperature sensor during the response process.

[0030] Since the temperature sensor has a certain thermal inertia, it cannot immediately respond to the change of the airflow temperature when measuring the sudden change of the airflow temperature. In this step, the sensor model of the temperature sensor is established by finite element simulation software, and the fluid-solid thermal coupling module in the software is used to simulate the working environment of the aircraft engine. With reference to the exhaust working conditions after the turbine of a certain type of aircraft engine, the airflow pressure is 200KPa and the airflow velocity is 0.5Ma, so that the ambient temperature of the sensor model produces a temperature step (for example, 300-400℃, 400-500℃, 600-750℃), and the dynamic characteristic response curve of the sensor model is calculated. The dynamic characteristic response curve is the dynamic characteristic response curve of the temperature sensor, and the time point when the step temperature reaches 63.2% is used as the time constant, and the response error of the time constant point in the response process is calculated.

[0031] Step 2: Analyze the temperature measurement deviation of the temperature sensor to obtain the temperature measurement deviation of the temperature sensor.

[0032] The temperature measurement accuracy of the temperature sensor is affected by factors such as the accuracy of the material of the temperature sensing element, the heat conduction of the sensor structure, and the thermal radiation of the engine casing, and generally includes sensor speed error, radiation error, and thermal conduction error. This step uses the finite element simulation method to establish the sensor model of the temperature sensor, and simulates different working conditions of the engine service state, that is, by changing the airflow pressure and airflow velocity of the aircraft engine for simulation, wherein the airflow pressure parameter of the aircraft engine is set to 100KPa~300KPa, and the airflow velocity parameter is set to 0.2~0.5Ma, and then the temperature of the temperature sensor environment is constant: 300℃, 400℃, 500℃, 600℃ and 800℃, and the deviation between the measured temperature of the sensor model and the theoretical value under different working conditions is analyzed, and the deviation is the temperature deviation of the temperature sensor. It is not difficult to find that this embodiment takes into account the influence of airflow velocity and airflow pressure on the temperature measurement deviation.

[0033] Step 3, taking the time constant, response error, temperature measurement deviation and sensor reliability as performance indicators, optimizing the structure of the temperature sensor to obtain a temperature sensor with an optimal structure.

[0034] In order to improve the dynamic response characteristics of the sensor, reduce the response error, reduce the temperature measurement deviation and improve the reliability of the sensor, the internal structure, external hysteresis cover and shell packaging of the temperature sensor can be optimized. Figure 2 As shown, the internal structure optimization includes the diameter settings of the even wire welding point are 1mm, 1.2mm, 1.4mm, 1.6mm, 1.8mm and 2mm respectively, the even wire diameters are 0.2mm, 0.4mm, 0.5mm, 0.6mm, 0.8mm and 1mm respectively, and the even wire inclination angles are 0°, 10°, 15°, 20°, 25° and 30° respectively; the external stagnation cover optimization includes the inlet and outlet area ratios are 3, 2 and 1 respectively, the outlet shapes are elliptical, circular and rectangular respectively, and the aspect ratios of the stagnation cover are 3, 6 and 7 respectively; the sensor shell packaging optimization includes the change of the outer diameter of the shell: single-step distribution, double-step distribution and uniform outer diameter.

[0035] In this step, the finite element simulation software is used to control the optimization variables to analyze the comprehensive impact of the three parts on the time constant, response error, temperature measurement deviation and sensor reliability after optimization, and the optimal structural optimization design is selected according to the overall optimization results of the four performance indicators of time constant, response error, temperature measurement deviation and sensor reliability. Among them, the sensor reliability is based on the calculation of the minimum fatigue life of the sensor after structural optimization by the nCode Designlife module in the finite element analysis software, and the inverse of the minimum fatigue life is set as the MTTF value, which can be used as the sensor reliability.

[0036] like Figure 3 , Figure 4 and Figure 5As shown in the figure, it can be concluded that the changes in the structure and size of the even wire, stagnation cover and structural packaging have an impact on the four performance indicators of time constant, dynamic error, temperature measurement deviation and reliability. The larger the even wire welding point, the larger the diameter and the smaller the even wire inclination angle, the larger the time constant, the larger the response error, the larger the temperature measurement deviation, and the higher the reliability MTTF value. The larger the aspect ratio of the stagnation cover and the smaller the area ratio of the inlet and outlet, the smaller the time constant, the smaller the response error, the smaller the temperature measurement deviation, and the smaller the reliability MTTF value. Among them, the time constant and response error of the rectangular inlet and outlet are the smallest, and the temperature measurement deviation and reliability MTTF value do not change significantly. When the diameter distribution of the external structural packaging is a step-type distribution, the reliability MTTF value of the temperature sensor is higher. It can be concluded that in the optimization indicators of the even wire and the stagnation cover, the reliability indicator MTTF value shows an opposite trend with the response characteristics and measurement error. Therefore, the reliability degradation caused by the optimization of the measurement error can be compensated by optimizing the external packaging structure.

[0037] Step 4: establishing a dynamic parameterized compensation model based on the response error and temperature measurement deviation of the temperature sensor with the optimal structure, and completing the adaptive compensation of the measurement error through the dynamic parameterized compensation model.

[0038] After the temperature sensor is optimized in step 3, there are still response errors and temperature measurement deviations in the measurement process. In this step, the response error and temperature measurement deviation are parameterized and modeled using first-order response and multi-order response functions. The model is parameterized and fitted according to the dynamic response characteristics of the temperature sensor with the optimal structure. In combination with the change law of the temperature measurement deviation, multiple parameter variables are added to the fitted model to establish a dynamic parameterized compensation model. The dynamic parameterized compensation model is then used to complete the adaptive compensation of the measurement error, thereby comprehensively improving the temperature measurement performance of the aircraft engine.

[0039] like Figure 6 As shown in the figure, the first-order, second-order or high-order parameterized model fitting is performed through the dynamic response characteristics of the temperature sensor. The first-order parameterized fitting model is Y 11 (x) = 2*T0-T0*exp(a0*x), the compensation model is Y 12 (x) = 2*T0-T0*exp(a1*x), where T0 is the initial step temperature, a0 is the first-order response fitting model parameter, and a1 is the first-order response compensation model parameter; the second-order response fitting model is Y 21 (x) = T0*(b0*(x-c0)*(x-d0))+T0, the second-order response compensation model is Y 22 (x) = T0*(b1*(x-c1)*(x-d1))+T0, where b0, c0, d0 are the second-order response fitting model parameters, and b1, c1, d1 are the second-order response compensation model parameters. Considering the factors that cause temperature measurement deviation, including velocity error, thermal conductivity error, and radiation error, the first-order parameterized model is optimized as follows: Among them, e is the speed error compensation variable, Ma is the airflow Mach number, f is the thermal conduction error compensation variable, T v is the stability of the fixed flange, h is the surface heat transfer coefficient, L is the length of the temperature measuring element, λ is the thermal conductivity, d is the diameter of the temperature measuring element, g is the radiation error compensation variable, μ is the surface emissivity of the temperature measuring element, and ω is the Stefan-Boltzmann constant, whose value is 5.67*10 -8 (m 2 ·K 4 ). Therefore, the temperature sensor measurement error adaptive compensation model is:

[0040]

[0041] It is not difficult to find that the present invention, through temperature sensor response characteristic analysis, temperature sensor temperature measurement deviation analysis, temperature sensor multivariable structure optimization and adaptive compensation of measurement errors, refers to the aircraft engine service working conditions, from temperature sensor design optimization, reliability evaluation and adaptive compensation of measurement errors, to form an overall improvement in the temperature measurement performance of the aircraft engine, thereby improving the temperature measurement accuracy of the aircraft engine, reducing the response time, and ensuring stability and reliability.

Claims

1. A method for improving the temperature measurement performance of an aircraft engine, characterized in that: The following steps are involved: Analyze the response characteristics of the temperature sensor and obtain the response error of the temperature sensor during the response process; Perform temperature measurement deviation analysis on the temperature sensor to obtain the temperature measurement deviation of the temperature sensor; Taking time constant, response error, temperature measurement deviation and sensor reliability as performance indicators, the temperature sensor is structurally optimized to obtain a temperature sensor with an optimal structure; A dynamic parameterized compensation model is established based on the response error and temperature measurement deviation of the temperature sensor with the optimal structure, and adaptive compensation of the measurement error is completed through the dynamic parameterized compensation model.

2. The method for improving the temperature measurement performance of an aircraft engine according to claim 1, characterized in that: The response characteristic analysis of the temperature sensor is performed to obtain the response error of the temperature sensor during the response process, specifically: Finite element simulation software is used to establish a sensor model of the temperature sensor, and the engine operating environment is simulated to cause the ambient temperature of the sensor model to produce a temperature step. The dynamic response characteristics of the sensor model are analyzed to obtain the time constant of the temperature sensor, and the response error of the temperature sensor during the response process is calculated based on the time constant.

3. The method for improving the temperature measurement performance of an aircraft engine according to claim 1, characterized in that: The temperature measurement deviation analysis of the temperature sensor is performed to obtain the temperature measurement deviation of the temperature sensor, which is specifically: The sensor model of the temperature sensor is established by using the finite element simulation method, and different working conditions under the service state of the engine are simulated to keep the ambient temperature of the sensor model constant. The deviation between the sensor model and the theoretical value is analyzed, and the deviation is recorded as the temperature measurement deviation of the temperature sensor.

4. The method for improving the temperature measurement performance of an aircraft engine according to claim 3, characterized in that: The different operating conditions of the engine under service are achieved by changing the airflow velocity and / or airflow pressure.

5. The method for improving the temperature measurement performance of an aircraft engine according to claim 1, characterized in that: The temperature sensor is structurally optimized with time constant, response error, temperature measurement deviation and sensor reliability as performance indicators to obtain a temperature sensor with an optimal structure, specifically: The temperature sensor is divided into three parts: internal structure, external hysteresis cover and shell packaging. Finite element simulation software is used to control the optimization variables to analyze the comprehensive influence of the three parts on the time constant, response error, temperature measurement deviation and sensor reliability after optimization. The optimal structural optimization design is selected according to the overall optimization results of the four performance indicators of time constant, response error, temperature measurement deviation and sensor reliability.

6. The method for improving the temperature measurement performance of an aircraft engine according to claim 1, characterized in that: The dynamic parameterized compensation model is established based on the response error and temperature measurement deviation of the temperature sensor with the optimal structure, specifically: First-order response and multi-order response functions are used to parameterize the response error and temperature measurement deviation. The model is parameterized and fitted according to the dynamic response characteristics of the temperature sensor with the optimal structure. Multiple parameter variables are added to the fitting model in combination with the changing law of temperature measurement deviation to establish a dynamic parameterized compensation model.

7. The method for improving the temperature measurement performance of an aircraft engine according to claim 6, characterized in that: The dynamic parameterized compensation model is expressed as: Y(x) = Y 12 (x) + Y 22 (x) + e * T0 * Ma 2 + f * T v * h * L * (4 * h / λ / d) 1 / 2 + g * μ * ω * T v 4 , where, Y(x) is a dynamic parameterized compensation model, Y 12 (x) is the first-order parameterized compensation model, Y 22 (x) is the second-order response compensation model, e is the speed error compensation variable, T0 is the initial step temperature, Ma is the airflow Mach number, f is the thermal conductivity error compensation variable, T v is the stability of the fixed flange, h is the surface heat transfer coefficient, L is the length of the temperature measuring element, λ is the thermal conductivity, d is the diameter of the temperature measuring element, g is the radiation error compensation variable, μ is the surface emissivity of the temperature measuring element, and ω is the Stefan-Boltzmann constant.

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