Aero-engine dynamic temperature data real-time correction and repair calculation method

Abstract

The application belongs to the field of aero-engines, and particularly relates to a real-time correction and repair calculation method for dynamic temperature data of an aero-engine. The method comprises the following steps: step one, correcting the dynamic temperature data, including: S1.1, performing digital filtering processing on the dynamic temperature data; S1.2, performing dynamic error correction on the dynamic temperature data; and step two, repairing bad point data in the dynamic temperature data. The real-time correction and repair calculation method for the dynamic temperature data of the aero-engine not only solves the problem of real-time correction of the dynamic temperature data in an experimental site, but also solves the problem of repairing damaged temperature measuring points through an algorithm.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of aero-engines, and particularly relates to a real-time correction and repair calculation method for dynamic temperature data of an aero-engine. BACKGROUND

[0002] Factors affecting the stability margin of the engine include, among others, total temperature distortion of the inlet air, which has an important influence on the stability of the engine. For example, severe weather, maneuvering flight, high-temperature tail plume of a missile launched by an aircraft, and high-temperature steam ejected by a carrier catapult, etc., can all cause temperature distortion at the inlet of the engine, thereby reducing the surge margin of the engine. In order to study the influence of total temperature distortion of the inlet air on the stability of the engine, in the temperature distortion test, high-temperature gas needs to be continuously injected without stopping the engine, which requires a calculation method for real-time online correction and repair of multi-point dynamic temperature field data.

[0003] Firstly, the prior art basically does not consider the signal-to-noise ratio requirement and dynamic response requirement required by dynamic signal processing, and the accuracy of the corrected data cannot be guaranteed to a great extent. Secondly, for the bad temperature points appearing in the test, the prior art basically adopts a post-handling removal scheme, which makes the data unable to be processed in real time by a computer processing system on site, resulting in a lack of automatic real-time processing capability for dynamic temperature data processing, thereby increasing the time cost and labor cost of test point repair under the condition of controllable accuracy requirement, and seriously affecting the test and experiment efficiency.

[0004] Therefore, it is desirable to have a technical solution to overcome or at least alleviate at least one of the aforementioned deficiencies of the prior art. SUMMARY

[0005] The purpose of the present application is to provide a real-time correction and repair calculation method for dynamic temperature data of an aero-engine to solve at least one problem existing in the prior art.

[0006] The technical solution of the present application is as follows:

[0007] A real-time correction and repair calculation method for dynamic temperature data of an aero-engine, comprising:

[0008] Step one, correcting dynamic temperature data, comprising:

[0009] S1.1, performing digital filtering processing on the dynamic temperature data;

[0010] S1.2, performing dynamic error correction on the dynamic temperature data;

[0011] Step two, repairing bad point data in the dynamic temperature data.

[0012] In at least one embodiment of the present application, in S1.1, the digital filtering processing on the dynamic temperature data comprises:

[0013] S1.1.1, using a Chebyshev low-pass digital filter to perform digital filtering processing on the dynamic temperature data;

[0014] S1.1.2, performing weighted average filtering processing on the dynamic temperature data.

[0015] In at least one embodiment of the present application, in S1.1.1, the amplitude-frequency calculation model of the Chebyshev low-pass digital filter is:

[0016]

[0017] n-order Chebyshev polynomial is:

[0018]

[0019]

[0020] Wherein, ε is the fluctuation coefficient, ω is the input frequency, and ω0 is the cutoff frequency.

[0021] In at least one embodiment of the present application, in S1.1.2, the weighted average filtering calculation model is:

[0022]

[0023] C1+C2+C3+...+C n =1

[0024] 0<C1<C2<C3<...<C n

[0025] Wherein, C i is the weight constant, and i is larger Distance present moment is closer.

[0026] In at least one embodiment of the present application, in S1.2, the dynamic error correction on the dynamic temperature data comprises:

[0027] Based on the dynamic error correction model, the dynamic error correction on the dynamic temperature data is performed, and the dynamic error correction model is:

[0028]

[0029] Wherein, T t is the corrected actual temperature value at time t, T n is the transient indication temperature value at time t, τ(λ) is the thermal inertia time constant, T n The temperature data of the five points before and after the transient temperature rise rate.

[0030] In at least one embodiment of the present application, in step two, the bad point data in the dynamic temperature data is repaired, including:

[0031] Search for valid temperature measurement points from above the bad point radially, determine whether there are valid temperature measurement points above the bad point radially, if yes, assign the valid temperature measurement point data above the bad point radially to a first variable, if not, assign 0 to the first variable;

[0032] Determine whether there are valid temperature measurement points below the bad point radially, if yes, assign the valid temperature measurement point data below the bad point radially to a second variable, if not, assign 0 to the second variable;

[0033] Determine whether there are valid temperature measurement points in the same ring surface clockwise direction of the bad point, if yes, assign the valid temperature measurement point data in the same ring surface clockwise direction of the bad point to a third variable, if not, assign 0 to the third variable;

[0034] Determine whether there are valid temperature measurement points in the same ring surface counterclockwise direction of the bad point, if yes, assign the valid temperature measurement point data in the same ring surface counterclockwise direction of the bad point to a fourth variable, if not, assign 0 to the fourth variable;

[0035] According to the first variable, the second variable, the third variable, the fourth variable and the bad point data repair model, the repaired temperature value is calculated.

[0036] In at least one embodiment of the present application, the bad point data repair model is:

[0037]

[0038] Wherein, T hxf is the repaired temperature value, p is the number of temperature measurement points participating in the repair calculation in the radial direction, q is the number of temperature measurement points participating in the repair calculation in the circumferential direction, t ri is the valid temperature data of the bad point in the radial direction, t wi is the valid temperature data of the bad point in the circumferential direction, W ri is the reciprocal of the straight-line distance in physical space between the temperature measurement point participating in the repair calculation in the radial direction and the bad point, W wj is the reciprocal of the straight-line distance in physical space between the temperature measurement point participating in the repair calculation in the circumferential direction and the bad point, and m is the dimension number.

[0039] Wherein, p≤2, q≤2, when the radial and circumferential temperature measurement points participate in the repair calculation, m=2; when only the radial or only the circumferential temperature measurement points participate in the repair calculation, m=1.

[0040] The present application has at least the following beneficial technical effects:

[0041] The real-time correction and repair calculation method for the dynamic temperature data of the aero-engine of the application solves the problems of signal-to-noise ratio and dynamic response requirement through signal processing of the dynamic temperature, solves the problem of data correction accuracy, and realizes real-time repair of the bad temperature points through a data logic algorithm, thereby solving the problem of automatic real-time processing of the dynamic temperature data. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The bad point data repair flowchart is an embodiment of the application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical scheme and advantages of the application clearer, the technical scheme of the embodiments of the application will be described in more detail below in combination with the drawings of the embodiments of the application. In the drawings, the same or similar notations represent the same or similar elements or elements with the same or similar functions throughout. The described embodiments are part of the embodiments of the application, not all of the embodiments. The embodiments described below by reference to the drawings are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application. The embodiments of the application will be described in detail below in combination with the drawings.

[0044] In the description of the application, it should be understood that the terms "center", "longitudinal", "transverse", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the scope of protection of the application.

[0045] The drawings will be described below in combination with the Figure 1 The application will be further described in detail.

[0046] The application provides a real-time correction and repair calculation method for dynamic temperature data of an aero-engine, comprising the following steps:

[0047] Step one, correcting the dynamic temperature data, comprising:

[0048] S1.1, performing digital filtering processing on the dynamic temperature data;

[0049] S1.2, performing dynamic error correction on the dynamic temperature data;

[0050] Step two, bad data in dynamic temperature data is repaired.

[0051] The collected original dynamic temperature data has large noise, in order to make the dynamic temperature signal meet the premise condition of certain signal-to-noise ratio, the collected original dynamic temperature data must be processed by two-step denoising.

[0052] In the preferred embodiment of the application, first, S1.1.1, the Chebyshev low-pass digital filter is used for digital filtering processing of dynamic temperature data. By using the Chebyshev low-pass digital filter with good phase frequency performance, the collected useless high-frequency signal is removed, in this embodiment, the amplitude frequency calculation model of the Chebyshev low-pass digital filter is:

[0053]

[0054] The nth order Chebyshev polynomial is:

[0055]

[0056]

[0057] Wherein, ε is the fluctuation coefficient, ω is the input frequency, ω0 is the cutoff frequency

[0058] Second, S1.1.2, the dynamic temperature data is processed by weighted average filtering. Using weighted average filtering algorithm, the signal-to-noise ratio of low frequency band is further improved while ensuring the response speed of dynamic temperature signal. When calculating, a buffer area is established to store n times sampling data in turn, and the earliest sampled data is removed every time a new data is sampled. At the same time, in order to increase the weight of new sampling data in recursive average, so as to improve the system response speed, different weights are given to the data at different times, the closer to the present time, the greater the weight. In this embodiment, the weighted average filtering calculation model is:

[0059]

[0060] C1+C2+C3+...+C n =1

[0061] 0<C1<C2<C3<...<C n

[0062] Wherein, C i is the weight constant, the greater i is, the closer to the present time.

[0063] Because thermocouples inherently possess thermal inertia, when the airflow temperature changes, the change at the thermocouple measuring end lags behind the change in airflow temperature in time. Therefore, dynamic error correction needs to be applied to the measured dynamic temperature data, which has undergone two-step filtering. In a preferred embodiment of this application, S1.2, the dynamic error correction of the dynamic temperature data includes:

[0064] Dynamic error correction is performed on dynamic temperature data based on a dynamic error correction model. The dynamic error correction model is as follows:

[0065]

[0066] Among them, T t T represents the corrected actual temperature value at time t. n Let λ be the transient indicated temperature value at time t, and τ(λ) be the thermal inertia time constant. For T n Transient temperature rise rate at 5 points before and after.

[0067] The real-time correction and repair calculation method for dynamic temperature data of aero-engines in this application allows for the repair of temperature defects by software algorithms when a test thermocouple is damaged, provided that a certain level of test accuracy is met. The repair algorithm performs repair calculations from both radial and circumferential spatial dimensions.

[0068] Specifically, such as Figure 1 As shown, the process of repairing bad data in dynamic temperature data includes:

[0069] Starting from radially upwards from the defective point, search for effective temperature measurement points. Determine whether there are effective temperature measurement points radially upwards from the defective point. If yes, assign the data of the effective temperature measurement point radially upwards from the defective point to the first variable. Otherwise, assign 0 to the first variable.

[0070] Determine whether there is a valid temperature measurement point radially below the defective point. If yes, assign the valid temperature measurement point data radially below the defective point to the second variable; otherwise, assign 0 to the second variable.

[0071] Determine whether there are valid temperature measurement points in the clockwise direction of the same ring surface around the defective point. If yes, assign the valid temperature measurement point data in the clockwise direction of the same ring surface around the defective point to the third variable. If no, assign 0 to the third variable.

[0072] Determine whether there are valid temperature measurement points in the counterclockwise direction of the same ring surface around the defective point. If yes, assign the data of the valid temperature measurement points in the counterclockwise direction of the same ring surface around the defective point to the fourth variable. If no, assign 0 to the fourth variable.

[0073] Based on the first variable, second variable, third variable, fourth variable, and the bad pixel data repair model, the repaired temperature value is calculated.

[0074] The damaged galvanic couple data is removed and replaced with the repaired temperature value, thereby repairing the bad point data.

[0075] In this embodiment, the bad point data repair model is:

[0076]

[0077] wherein T hxf is the repaired temperature value, p is the number of temperature measuring points participating in the repair calculation in the radial direction, q is the number of temperature measuring points participating in the repair calculation in the circumferential direction, t ri is the effective radial temperature data of the bad point, t wi is the effective circumferential temperature data of the bad point, W ri is the reciprocal of the physical space straight-line distance between the temperature measuring point participating in the repair calculation in the radial direction and the bad point, W wj is the reciprocal of the physical space straight-line distance between the temperature measuring point participating in the repair calculation in the circumferential direction and the bad point, and m is the dimension number.

[0078] wherein p≤2, q≤2, when the radial and circumferential temperature measuring points both participate in the repair calculation, m=2; when only the radial or only the circumferential temperature measuring points participate in the repair calculation, m=1.

[0079] The aviation engine dynamic temperature data real-time correction and repair calculation method of the present application can realize the automatic real-time correction and repair of dynamic temperature data in a computer processing system, realize the intelligent and automatic processing level of dynamic temperature data in the test process, can greatly improve the test efficiency, and reduce the time cost and labor cost of measuring point repair under the condition that the precision requirement is controllable.

[0080] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for real-time correction and repair of dynamic temperature data of an aeroengine, characterized in that, The application relates to a dynamic temperature data processing method, which comprises the following steps: Step one, correcting dynamic temperature data, which comprises the following steps: S1.1, performing digital filtering processing on the dynamic temperature data; S1.2, performing dynamic error correction on the dynamic temperature data; Step two, repairing bad point data in the dynamic temperature data, which comprises the following steps: searching for effective temperature measuring points above the bad point in the radial direction, judging whether the effective temperature measuring points exist above the bad point in the radial direction, if yes, assigning the data of the effective temperature measuring points above the bad point in the radial direction to a first variable, if not, assigning 0 to the first variable; judging whether the effective temperature measuring points exist below the bad point in the radial direction, if yes, assigning the data of the effective temperature measuring points below the bad point in the radial direction to a second variable, if not, assigning 0 to the second variable; judging whether the effective temperature measuring points exist in the clockwise direction of the same ring surface of the bad point, if yes, assigning the data of the effective temperature measuring points in the clockwise direction of the same ring surface of the bad point to a third variable, if not, assigning 0 to the third variable; judging whether the effective temperature measuring points exist in the counterclockwise direction of the same ring surface of the bad point, if yes, assigning the data of the effective temperature measuring points in the counterclockwise direction of the same ring surface of the bad point to a fourth variable, if not, assigning 0 to the fourth variable; calculating the repaired temperature value according to the first variable, the second variable, the third variable, the fourth variable and a bad point data repairing model; the bad point data repairing model is as follows: Wherein, T hxf is the repaired temperature value, p is the number of temperature measuring points participating in the repair calculation in the radial direction, q is the number of temperature measuring points participating in the repair calculation in the circumferential direction, t ri is the effective temperature data of the bad point in the radial direction, t wj is the effective temperature data of the bad point in the circumferential direction, W ri is the reciprocal of the straight-line distance in physical space between the temperature measuring point participating in the repair calculation in the radial direction and the bad point, W wj is the reciprocal of the straight-line distance in physical space between the temperature measuring point participating in the repair calculation in the circumferential direction and the bad point, and m is the dimension number. wherein, p<=2, q<=2, when the radial and circumferential temperature measuring points participate in the repairing calculation, m=2; when only the radial or only the circumferential temperature measuring points participate in the repairing calculation, m=1.

2. The gas turbine engine dynamic temperature data real-time correction and cure calculation method of claim 1, wherein, In S1.1, the digital filtering processing on the dynamic temperature data comprises the following steps: S1.1.1, adopting a Chebyshev low-pass digital filter to perform digital filtering processing on the dynamic temperature data; S1.1.2, performing weighted average filtering processing on the dynamic temperature data.

3. The gas turbine engine dynamic temperature data real-time correction and repair calculation method of claim 2, wherein, In S1.1.1, the amplitude-frequency calculation model of the Chebyshev low-pass digital filter is as follows: n-th Chebyshev polynomial is: wherein, epsilon is a fluctuation coefficient, omega is an input frequency, and omega0 is a cutoff frequency.

4. The gas turbine engine dynamic temperature data real-time correction and repair calculation method of claim 3, wherein, In S1.1.2, the weighted average filtering calculation model is as follows: C1 + C2 + C3 +... + C n = 1 0 < C1 < C2 < C3 <... < C n where C i is a weight constant, and i is larger the closer the distance is to the present time.

5. The gas turbine engine dynamic temperature data real-time correction and repair calculation method of claim 4, wherein, In S1.2, the dynamic error correction on the dynamic temperature data comprises the following steps: performing dynamic error correction on the dynamic temperature data based on a dynamic error correction model, and the dynamic error correction model is as follows: Wherein, T t is the actual temperature value after correction at time t, T n is the transient indication temperature value at time t, τ(λ) is the thermal inertia time constant, is the T n temperature data of the previous and next 5 points transient temperature rise rate.

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