Aero-engine temperature measurement performance improvement method

Abstract

The application relates to an aero-engine temperature measurement performance improvement method, which comprises the following steps: analyzing the response characteristics of a temperature sensor to obtain the response error of the temperature sensor in the response process; analyzing the temperature measurement deviation of the temperature sensor to obtain the temperature measurement deviation of the temperature sensor; taking the time constant, the response error, the temperature measurement deviation and the sensor reliability as performance indexes, optimizing the structure of the temperature sensor to obtain a temperature sensor with an optimal structure; and establishing a dynamic parameterized compensation model based on the response error and the temperature measurement deviation of the temperature sensor with the optimal structure, and completing adaptive compensation of measurement errors through the dynamic parameterized compensation model. The application can improve the overall temperature measurement performance of the aero-engine.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of temperature measurement of an aero-engine, and particularly relates to a method for improving temperature measurement performance of an aero-engine. BACKGROUND

[0002] An aero-engine is the heart of an aircraft, and its advancement reflects the industrial level of a country. During ground tests of the aero-engine and service in flight, accurate measurement of airflow temperature of the aero-engine is of great significance for evaluating the performance of the aero-engine, state monitoring, fuel control and the like. Influenced by heat loss, incomplete stagnation and the like, when a high-temperature airflow temperature sensor is measured, there are many factors influencing the measurement results, and the influencing mechanism is complex, so the measurement error is often large, which causes great difficulty in the design of the airflow temperature sensor. Meanwhile, due to a certain mass of the temperature sensor, the temperature sensor has a certain thermal inertia, so the temperature sensor cannot immediately respond to the rapid change of the airflow temperature, and has a certain response lag. For a first-order system, a time constant is usually used to reflect the dynamic response capability thereof, although the temperature sensor does not necessarily belong to a first-order system, but for the convenience of research, the time constant is still used as a dynamic performance index of the airflow temperature sensor. Due to the harsh and changeable working conditions of the aero-engine in the service state, the measurement error and the 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

[0003] The present application relates to the technical field of temperature measurement of an aero-engine, and particularly relates to a method for improving temperature measurement performance of an aero-engine.

[0004] The technical solution adopted by the present application to solve the technical problem is as follows: a method for improving temperature measurement performance of an aero-engine is provided, comprising the following steps:

[0005] response error of the temperature sensor in the response process is obtained by analyzing the response characteristics of the temperature sensor;

[0006] temperature measurement deviation of the temperature sensor is obtained by analyzing the temperature measurement deviation of the temperature sensor;

[0007] the temperature sensor is structurally optimized by taking the time constant, the response error, the temperature measurement deviation and the sensor reliability as performance indexes, so that a temperature sensor with an optimal structure is obtained;

[0008] a dynamic parameterized compensation model is established based on the response error and the 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 error of the temperature sensor in the response process is obtained by analyzing the response characteristics of the temperature sensor, and specifically is:

[0010] The sensor model of the temperature sensor is established by using a finite element simulation software, and an engine working condition environment is simulated to cause a temperature step of the environment temperature of the sensor model, the dynamic response characteristics of the sensor model are analyzed, the time constant of the temperature sensor is obtained, and the response error of the temperature sensor in the response process is calculated based on the time constant.

[0011] The temperature measurement deviation of the temperature sensor is obtained by analyzing the temperature measurement deviation of the temperature sensor, and specifically is:

[0012] The sensor model of the temperature sensor is established by using a finite element simulation method, and different working condition environments in an engine service state are simulated to keep the environment temperature of the sensor model constant, the deviation of the sensor model from a theoretical value is analyzed, and the deviation is recorded as the temperature measurement deviation of the temperature sensor.

[0013] The different working condition environments in the engine service state are realized by changing the airflow velocity and / or the airflow pressure.

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

[0015] The temperature sensor is divided into an internal structure, an external stagnation cover and a shell package, and the comprehensive influence of the time constant, the response error, the temperature measurement deviation and the sensor reliability after optimization of the three parts is analyzed by using a finite element simulation software by controlling optimization variables, and the optimal structure optimization design is selected according to the overall optimization results of the four performance indexes of the time constant, the response error, the temperature measurement deviation and the sensor reliability.

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

[0017] The response error and the temperature measurement deviation are parameterized modeled by using a first-order response and a multi-order response function, the model is parameterized fitted according to the dynamic response characteristics of the temperature sensor with the optimal structure, a plurality of parameter variables are added in the fitted model in combination with the change law of the temperature measurement deviation, and the dynamic parameterized compensation model is established.

[0018] The dynamic parameterized compensation model is represented as: Y(x) = Y 12 (x) + Y 22 (x) + e*T0*Ma 2 +f*T v *h*L*(4*h / lambda / d) 1 / 2+ g*mu*omega*T v 4 wherein Y(x) is a dynamic parameterized compensation model, Y 12 (x) is a first-order parameterized compensation model, Y 22 (x) is a second-order response compensation model, e is a speed error compensation variable, T0 is an initial step temperature, Ma is a gas flow Mach number, f is a heat conduction error compensation variable, T v is a fixed flange stabilization, h is a surface heat exchange coefficient, L is a temperature measuring element length, lambda is a heat conduction coefficient, d is a temperature measuring element diameter, g is a radiation error compensation variable, mu is a temperature measuring element surface emissivity, and omega is a Stefan-Boltzmann constant.

[0019] Advantages

[0020] Compared with the prior art, the present application has the following advantages and positive effects: the present application analyzes the temperature sensor response characteristics, analyzes the temperature sensor temperature measurement deviation, optimizes the temperature sensor multivariable structure, and self-adapts the measurement error compensation, references the aero-engine service working condition environment, optimizes the temperature sensor design, evaluates the reliability, and self-adapts the measurement error compensation, forms the overall improvement of the aero-engine temperature measurement performance, thereby improving the aero-engine temperature measurement precision and reducing the response time, and ensuring the stability and reliability. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a schematic diagram of the temperature sensor multivariable structure optimization;

[0022] Figure 2 is a schematic diagram of the temperature sensor multivariable structure optimization;

[0023] Figure 3 is a temperature sensor structure optimization influence trend on the time constant and response error;

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

[0025] Figure 5 is a temperature sensor structure optimization influence trend on the temperature measurement deviation;

[0026] Figure 6 is a temperature sensor temperature measurement error self-adaptive compensation schematic diagram. DETAILED DESCRIPTION

[0027] The application will be further described in connection with the following specific embodiments. It should be understood that these embodiments are only used to illustrate the application and not used to limit the scope of the application. Furthermore, it should be understood that after reading the content of the application, those skilled in the art can make various modifications or changes to the application, and these equivalent forms also fall within the scope defined by the appended claims.

[0028] The embodiment of the application relates to an aero-engine temperature measurement performance improvement method, as shown in the figure, mainly including the following steps: Figure 1

[0029] Step 1: response characteristic analysis of the temperature sensor, to obtain the response error of the temperature sensor in the response process.

[0030] Because the temperature sensor has certain thermal inertia, the temperature sensor cannot immediately respond to the change of the airflow temperature when measuring the suddenly changed airflow temperature. In this step, a sensor model of the temperature sensor is established by using finite element simulation software, a fluid-structure-thermal coupling module in the software is used to simulate the aero-engine working condition environment, the exhaust condition after the turbine of a certain type of aero-engine is referred to, the airflow pressure is 200 KPa, the airflow speed is 0.5 Ma, the temperature step (for example, 300-400 DEG C, 400-500 DEG C, 600-750 DEG C) of the environment temperature of the sensor model is generated, the dynamic characteristic response curve of the sensor model is calculated, the dynamic characteristic response curve of the temperature sensor is obtained, the time point of 63.2% of the step temperature is taken as the time constant, and the response error of the time constant point in the response process is calculated.

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

[0032] The temperature measurement accuracy of the temperature sensor is influenced by the temperature sensing element material accuracy, the sensor structure heat conduction and the engine case heat radiation and other factors, and generally includes the sensor speed error, the radiation error and the heat conduction error. In this step, the sensor model of the temperature sensor is established by using the finite element simulation method, and the engine service state different working condition environment is simulated, that is, the aero-engine airflow pressure and airflow speed are changed to simulate, wherein the aero-engine airflow pressure parameter is set to 100 KPa-300 KPa, the airflow speed parameter is set to 0.2-0.5 Ma, the temperature of the environment of the temperature sensor is constant: 300 DEG C, 400 DEG C, 500 DEG C, 600 DEG C and 800 DEG C, the deviation of the measured temperature of the sensor model from 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 the influence of the airflow speed and the airflow pressure on the temperature measurement deviation is considered in the embodiment. ​

[0033] Step 3, the temperature sensor is optimized in structure with time constant, response error, temperature measurement deviation and sensor reliability as performance indexes, to obtain a temperature sensor with optimal structure.

[0034] To improve the dynamic response characteristics of the sensor, reduce the response error, reduce the temperature measurement deviation and improve the sensor reliability, the internal structure, the external stagnation cover and the shell packaging of the temperature sensor can be optimized. As shown in Figure 2 The internal structure optimization includes that the diameters of the odd wire welding points are respectively set as 1mm, 1.2mm, 1.4mm, 1.6mm, 1.8mm and 2mm, the diameters of the odd wires are respectively 0.2mm, 0.4mm, 0.5mm, 0.6mm, 0.8mm and 1mm, and the odd wire inclination angles are respectively 0°, 10°, 15°, 20°, 25° and 30°; the external stagnation cover optimization includes that the area ratios of the inlet and outlet are respectively 3, 2 and 1, the outlet shapes are respectively oval, circular and rectangular, and the length-diameter ratios of the stagnation cover are respectively 3, 6 and 7; and the sensor shell packaging optimization includes that the outer diameter of the shell changes in a single ladder type distribution, a double ladder type distribution and a uniform outer diameter.

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

[0036] As shown in Figure 3 , Figure 4 and Figure 5As shown in the figure, it can be concluded that the changes of the structure and size of the filament, the stagnation cover and the structural package have an impact on the four performance indicators, time constant, dynamic error, temperature measurement deviation and reliability. The larger the filament welding point, the larger the diameter and the smaller the filament 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 length-diameter ratio of the stagnation cover, 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. The time constant and the response error of the rectangular inlet and outlet are the smallest, and the temperature measurement deviation and the reliability MTTF value have no obvious change. When the diameter distribution of the external structural package is in a step distribution, the temperature sensor reliability MTTF value is higher. It can be concluded that in the optimization indicators of the filament and the stagnation cover, the reliability indicator MTTF value and the response characteristics and the measurement error have opposite trends. Therefore, the reliability decline problem caused by the optimization of the measurement error is compensated by the optimization of the external packaging structure.

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

[0038] After the optimization in step 3, the response error and the temperature measurement deviation still exist in the temperature sensor measurement process. In this step, a first-order response and a multi-order response function are used to parameterize the modeling of the response error and the temperature measurement deviation. The model parameterization fitting is performed according to the dynamic response characteristics of the temperature sensor with the optimal structure. A plurality of parameter variables are added in the fitted model in combination with the temperature measurement deviation variation law to establish a dynamic parameterized compensation model. The adaptive compensation of the measurement error is completed by using the dynamic parameterized compensation model, thereby comprehensively improving the temperature measurement performance of the aero-engine.

[0039] As shown in Figure 6 , 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), wherein 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, and the second-order response compensation model is Y 22 (x)=T0*(b1*(x-c1)*(x-d1))+T0, wherein b0, c0 and d0 are the second-order response fitting model parameters, and b1, c1 and d1 are the second-order response compensation model parameters. Considering the temperature measurement deviation forming factors, including speed error, heat conduction error and radiation error, the first-order parameterized model is optimized as wherein e is a velocity error compensation variable, Ma is a Mach number of the airflow, f is a thermal conduction error compensation variable, T v is a fixed flange stability, h is a surface heat exchange coefficient, L is a length of the temperature measuring element, lambda is a thermal conductivity, d is a diameter of the temperature measuring element, g is a radiation error compensation variable, mu is a surface emissivity of the temperature measuring element, omega is a Stefan-Boltzmann constant, and the 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, by means of temperature sensor response characteristic analysis, temperature sensor temperature measurement deviation analysis, temperature sensor multivariate structure optimization and measurement error adaptive compensation, and with reference to the service working condition environment of the aero-engine, the overall improvement of the temperature measurement performance of the aero-engine is formed from the temperature sensor design optimization, reliability evaluation and measurement error adaptive compensation, so as to improve the temperature measurement precision and reduce the response time of the aero-engine, and ensure the 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, multi-parameter structure optimization is performed on the temperature sensor to obtain the temperature sensor with the optimal structure; First-order response and multi-order response functions are used to perform parameterized modeling of response error and temperature measurement deviation. 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: A finite element simulation method is used to establish a sensor model of the temperature sensor, and different operating conditions under the engine service state 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: Different operating conditions of the engine under service conditions 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 optimized by multi-parameter structure optimization based on the time constant, response error, temperature measurement deviation and sensor reliability as performance indicators to obtain the temperature sensor with the optimal structure, specifically: The temperature sensor is divided into three parts: internal structure, external stagnation cover and shell packaging. Finite element simulation software is used to control the optimization variables to analyze the comprehensive impact of the optimization of the three parts on the time constant, response error, temperature measurement deviation and sensor reliability. 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, including: 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 fitted model in combination with the variation 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: Among them, 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 heat 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.

Images