Accumulation algorithm for discriminating flow instability of gas compressor and analysis system thereof

Abstract

The invention relates to the technical field of aero-engines, and discloses an accumulation algorithm for discriminating flow instability of a gas compressor and an analysis system thereof.The change rate of dynamic pressure of an outlet of the gas compressor is extracted according to the characteristics of the outlet pressure when the gas compressor surges, the change rate of the outlet pressure is corrected by considering external noise when the gas compressor runs, and the flow instability of the gas compressor is discriminated. Obtaining a correction value of the outlet pressure change rate; according to the correction value of the outlet pressure change rate, the compressor outlet pressure change accumulation amount is counted through an integral accumulation and algorithm, the problem of false alarm caused by sensor failure is solved, online steady-state and transition-state real-time detection can be achieved by designing a preset detection threshold, and stable and safe work of an engine is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of aeroengines and discloses an accumulation algorithm for identifying compressor flow instability and an analysis system thereof. Background Art

[0002] Stall and surge are two types of flow instability phenomena often encountered in aircraft engine tests. Once the engine has flow instability, it cannot be exited in time. At the least, it will cause the engine to suddenly shut down, resulting in a sharp deterioration in engine performance. At the worst, it will cause the compressor blades to vibrate violently and break, resulting in damage to the entire engine and causing serious accidents. The anti-surge system of the previous engine failed to reliably identify the surge state, and often relied on manual monitoring of pulsating pressure changes to determine the engine's operating status. There are problems such as long alarm lag time and slow control response. Due to the high cost and long cycle of engine development, once an accident occurs, not only will the economic loss be huge, but it will also greatly delay the engine development process.

[0003] The compressor outlet pressure can reflect the state of the compressor more quickly than other parameters, and it is also easier to measure. Therefore, the compressor outlet pressure is usually used as the input signal, and the features are extracted through the relevant algorithm to identify whether the compressor is unstable. At present, the energy method, wavelet analysis method, traveling wave energy method / correlation function method and probability density method are usually used. Usually, a threshold is set. When the compressor is close to an unstable state, the characteristic coefficient used for detection changes suddenly. When the threshold is exceeded, it is determined that the compressor has entered an unstable state. This type of method only explains how to identify the aerodynamic instability signal of the engine with obvious characteristics from the perspective of data processing, without too much connection with the actual test signal. Considering reliability and real-time performance, these identification methods have a positive effect on analyzing the mechanism of aerodynamic instability and suppressing its hazards. However, the distinction between real signals and sensor fault signals is insufficient, and false alarms often occur. Summary of the invention

[0004] The purpose of the present invention is to provide an accumulation algorithm and an analysis system for identifying compressor flow instability, which can solve the false alarm problem caused by sensor failure. By designing a preset detection threshold, online steady-state and transition state real-time detection can be achieved to ensure stable and safe operation of the engine.

[0005] In order to achieve the above technical effects, the technical solution adopted by the present invention is:

[0006] An accumulation algorithm for identifying compressor flow instability includes:

[0007] Set the compressor outlet dynamic pressure signal sampling rate, detection window width, and step length to collect the compressor outlet dynamic pressure signal;

[0008] According to the collected dynamic pressure signal of the compressor outlet, the average value of the compressor outlet pressure in each detection window is analyzed and obtained;

[0009] According to the average value of the outlet pressure corresponding to each detection window, the outlet pressure change rate is analyzed and obtained;

[0010] According to the external noise when the compressor is in operation, the outlet pressure change rate is corrected to obtain a corrected value of the outlet pressure change rate;

[0011] According to the correction value, the cumulative amount of changes in the compressor outlet pressure is counted. If the cumulative amount of changes is greater than or equal to a preset detection threshold of the cumulative amount, it is determined that the compressor is unstable; otherwise, it is determined that the compressor is in a stable working state.

[0012] Furthermore, the detection window width is 10-50 ms, the step length is 1-10 ms, and the preset detection threshold value range is 5-12.

[0013] Furthermore, using S i =β-x i-j , i analyzes and obtains the outlet pressure change rate correction value S detected to the i-th detection window i ; where x i-j , i is the outlet pressure change rate between the ith detection window and the ijth detection window, β is the noise introduced from the outside, and the value range of β is -3 to 0, excluding 0.

[0014] Furthermore, after the detection of the i-th detection window is completed, the cumulative change of the compressor outlet pressure B i according to It is obtained by analysis, where μ is the cumulative loss, γ is the cumulative gain, and both μ and γ are positive integers.

[0015] In order to achieve the above technical effects, the present invention also provides an analysis system for identifying compressor flow instability, comprising:

[0016] A data acquisition module is used to collect the dynamic pressure signal at the compressor outlet according to the set sampling rate, detection window width and step length of the dynamic pressure signal at the compressor outlet;

[0017] The data analysis module is used to analyze and obtain the average value of the compressor outlet pressure in each detection window according to the collected compressor outlet dynamic pressure signal; and to analyze and obtain the outlet pressure change rate according to the average value of the outlet pressure corresponding to each detection window;

[0018] A data correction module, used to correct the outlet pressure change rate according to the external noise when the compressor is in operation, so as to obtain a correction value of the outlet pressure change rate;

[0019] The discrimination output module is used to collect statistics on the cumulative change of the compressor outlet pressure according to the correction value. If the cumulative change is greater than or equal to the preset detection threshold of the cumulative amount, it is judged that the compressor is unstable; otherwise, it is judged that the compressor is in a stable working state.

[0020] Furthermore, the detection window width is 10-50 ms, the step length is 1-10 ms, and the preset detection threshold value range is 5-12.

[0021] Furthermore, using S i =β-x i-j，i Analyze and obtain the outlet pressure change rate correction value S detected to the i-th detection window i ; where x i-j，i is the outlet pressure change rate between the ith detection window and the ijth detection window, β is the noise introduced by the outside world, and the value range of β is -3 to 0, excluding 0.

[0022] Furthermore, after the detection of the i-th detection window is completed, the cumulative change of the compressor outlet pressure B i according to It is obtained by analysis, where μ is the cumulative loss, γ is the cumulative gain, and both μ and γ are positive integers.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention extracts the rate of change of the dynamic pressure at the compressor outlet according to the characteristics of the outlet pressure during compressor surge, and corrects the rate of change of the outlet pressure by taking into account the external noise during the operation of the compressor, so as to obtain a corrected value of the rate of change of the outlet pressure; according to the magnitude of the corrected value of the rate of change of the outlet pressure, an integral cumulative sum algorithm is used to perform statistics on the accumulated amount of the compressor outlet pressure change, so as to solve the problem of false alarms caused by sensor failure, and by designing a preset detection threshold, online steady-state and transition state real-time detection can be realized to ensure stable and safe operation of the engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of the cumulative algorithm for identifying compressor flow instability in Example 1 or 2;

[0025] Figure 2 The structure diagram of the analysis system for identifying compressor flow instability in Example 1;

[0026] Figure 3 The curve diagram of the original data of the dynamic pressure at the compressor outlet in Example 2 over time

[0027] Figure 4 This is a data curve diagram of the cumulative change of conventional outlet pressure in Example 2 after being processed by the algorithm;

[0028] Figure 5A curve diagram showing the cumulative change of the compressor outlet pressure obtained by using the cumulative algorithm of the present invention in Example 2;

[0029] Among them, 1. Data acquisition module; 2. Data analysis module; 3. Data correction module; 4. Judgment output module. DETAILED DESCRIPTION

[0030] The present invention is further described in detail below in conjunction with the embodiments and drawings. However, it should not be understood that the scope of the above subject matter of the present invention is limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

[0031] Example 1

[0032] See also Figure 1 , Figure 2 , an accumulation algorithm for identifying compressor flow instability, including:

[0033] Set the compressor outlet dynamic pressure signal sampling rate, detection window width, and step length to collect the compressor outlet dynamic pressure signal;

[0034] According to the collected dynamic pressure signal of the compressor outlet, the average value of the compressor outlet pressure in each detection window is analyzed and obtained;

[0035] According to the average value of the outlet pressure corresponding to each detection window, the outlet pressure change rate is analyzed and obtained;

[0036] According to the external noise when the compressor is in operation, the outlet pressure change rate is corrected to obtain a corrected value of the outlet pressure change rate;

[0037] According to the correction value, the cumulative amount of changes in the compressor outlet pressure is counted. If the cumulative amount of changes is greater than or equal to a preset detection threshold of the cumulative amount, it is determined that the compressor is unstable; otherwise, it is determined that the compressor is in a stable working state.

[0038] In this embodiment, according to the characteristics of the outlet pressure during compressor surge, the rate of change of the dynamic pressure at the compressor outlet (i.e., the first-order derivative of the dynamic pressure with respect to time) is extracted, and the outlet pressure change rate is corrected by taking into account the external noise when the compressor is in operation, so as to obtain a corrected value of the outlet pressure change rate; according to the magnitude of the corrected value of the outlet pressure change rate, an integral cumulative sum algorithm is used to perform statistics on the cumulative amount of the compressor outlet pressure change, in order to solve the problem of false alarms caused by sensor failure, and by designing a preset detection threshold, online steady-state and transition state real-time detection can be achieved, thereby ensuring stable and safe operation of the engine.

[0039] Based on the same inventive concept, this embodiment also provides an analysis system for identifying compressor flow instability, including:

[0040] The data acquisition module 1 is used to collect the dynamic pressure signal at the compressor outlet according to the set sampling rate, detection window width and step length of the dynamic pressure signal at the compressor outlet;

[0041] Data analysis module 2 is used to analyze and obtain the average value of the compressor outlet pressure in each detection window according to the collected compressor outlet dynamic pressure signal; and to analyze and obtain the outlet pressure change rate according to the average value of the outlet pressure corresponding to each detection window;

[0042] A data correction module 3 is used to correct the outlet pressure change rate according to the external noise when the compressor is in operation, so as to obtain a correction value of the outlet pressure change rate;

[0043] The judgment output module 4 is used to collect statistics on the cumulative change of the compressor outlet pressure according to the correction value. If the cumulative change is greater than or equal to the preset detection threshold of the cumulative amount, it is judged that the compressor is unstable, otherwise it is judged that the compressor is in a stable working state.

[0044] Example 2

[0045] See also Figure 1 , Figure 3 , Figure 4 and Figure 5 This embodiment takes a certain type of compressor as an example to explain in detail the cumulative algorithm process for identifying compressor flow instability of the present invention, which specifically includes the following steps:

[0046] Step 1, setting the compressor outlet dynamic pressure signal sampling rate, detection window width, and step length, and collecting the compressor outlet dynamic pressure signal;

[0047] In this embodiment, the compressor outlet dynamic pressure signal sampling rate Fs = 10 kHz, the calculation window width Twin = 25 ms, the detection step length Tstep = 5 ms, and the detection threshold Bth = 10. The detection signal adopts the compressor outlet static pressure dynamic signal.

[0048] Step 2: Analyze and obtain the average value of the compressor outlet pressure in each detection window according to the collected compressor outlet dynamic pressure signal;

[0049] Step 3: Analyze and obtain the outlet pressure change rate according to the average outlet pressure corresponding to each detection window;

[0050] In this embodiment, the outlet pressure change rate between the i-th detection window and the ij-th detection window is Where P i is the average outlet pressure of the ith detection window, P i-jis the average outlet pressure of the ijth detection window, j is the number of interval windows, and the value range of j in this embodiment is 1 to 10.

[0051] Step 4, correcting the outlet pressure change rate according to the external noise when the compressor is in operation, to obtain a corrected value of the outlet pressure change rate;

[0052] In this embodiment, S i =β-x i-j，i Analyze and obtain the outlet pressure change rate correction value S detected to the i-th detection window i ; where x i-j，i is the outlet pressure change rate between the ith detection window and the ijth detection window, β is the noise introduced by the outside world, and the value range of β is -3 to 0, excluding 0; in this embodiment, the value of β is -1.

[0053] Step 5: According to the correction value, the cumulative amount of change of the compressor outlet pressure is counted;

[0054] In this embodiment, after the detection of the i-th detection window is completed, the cumulative change of the compressor outlet pressure B i according to It is obtained by analysis, where μ is the cumulative loss, γ is the cumulative gain, and both μ and γ are positive integers.

[0055] Step 6: Compare and judge.

[0056] If the cumulative amount of the change is greater than or equal to a preset detection threshold of the cumulative amount, it is determined that the compressor is unstable and an alarm signal may be issued by the alarm system; otherwise, it is determined that the compressor is in a stable working state.

[0057] like Figure 3-Figure 5 As shown, Figure 3 This is a graph showing the change of the original data of the dynamic pressure at the outlet of this type of compressor over time. Figure 4 This is the data curve after the original data is processed by the conventional outlet pressure change accumulation and algorithm. Figure 5 The cumulative curve of the compressor outlet pressure change obtained by using the cumulative algorithm of the present invention. Figure 3 Contains sensor failure data and compressor surge data. The sensor failure occurred before 5 seconds, and surge occurred after 6 seconds. Figure 4 , Figure 5 The middle dotted line is the detection threshold under the corresponding algorithm. Figure 4 , Figure 5The data curve in shows that the conventional outlet pressure change accumulation and algorithm cannot identify the fault of short-term sensor failure, resulting in false alarm. The method in this paper can effectively solve the false alarm problem caused by sensor failure, and can successfully capture the instability characteristics after the real surge occurs, thus improving the reliability of the pressure change rate aerodynamic instability detection method.

[0058] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An accumulation algorithm for identifying compressor flow instability, characterized in that: include: Set the compressor outlet dynamic pressure signal sampling rate, detection window width, and step length to collect the compressor outlet dynamic pressure signal; According to the collected dynamic pressure signal of the compressor outlet, the average value of the compressor outlet pressure in each detection window is analyzed and obtained; According to the average value of the outlet pressure corresponding to each detection window, the outlet pressure change rate is analyzed and obtained; According to the external noise when the compressor is in operation, the outlet pressure change rate is corrected to obtain a corrected value of the outlet pressure change rate; According to the correction value, the cumulative amount of changes in the compressor outlet pressure is counted. If the cumulative amount of changes is greater than or equal to a preset detection threshold of the cumulative amount, it is determined that the compressor is unstable; otherwise, it is determined that the compressor is in a stable working state.

2. The cumulative algorithm for identifying compressor flow instability according to claim 1 is characterized in that: The detection window width is 10 to 50 ms, the step length is 1 to 10 ms, and the preset detection threshold range is 5 to 12.

3. The cumulative algorithm for identifying compressor flow instability according to claim 1, characterized in that: Using S i =β-x i-j , i Analyze and obtain the outlet pressure change rate correction value S detected to the i-th detection window i ; where x i-j , i is the outlet pressure change rate between the ith detection window and the ijth detection window, β is the noise introduced by the outside world, and the value range of β is -3 to 0, excluding 0.

4. The cumulative algorithm for identifying compressor flow instability according to claim 3, characterized in that: After the i-th detection window is completed, the cumulative change of the compressor outlet pressure B i according to It is obtained by analysis, where μ is the cumulative loss, γ is the cumulative gain, and both μ and γ are positive integers.

5. An analysis system for identifying compressor flow instability, characterized in that: include: A data acquisition module is used to collect the dynamic pressure signal at the compressor outlet according to the set sampling rate, detection window width and step length of the dynamic pressure signal at the compressor outlet; The data analysis module is used to analyze and obtain the average value of the compressor outlet pressure in each detection window according to the collected compressor outlet dynamic pressure signal; and to analyze and obtain the outlet pressure change rate according to the average value of the outlet pressure corresponding to each detection window; A data correction module, used to correct the outlet pressure change rate according to the external noise when the compressor is in operation, so as to obtain a correction value of the outlet pressure change rate; The discrimination output module is used to collect statistics on the cumulative change of the compressor outlet pressure according to the correction value. If the cumulative change is greater than or equal to the preset detection threshold of the cumulative amount, it is judged that the compressor is unstable; otherwise, it is judged that the compressor is in a stable working state.

6. The analysis system for identifying compressor flow instability according to claim 5, characterized in that: The detection window width is 10 to 50 ms, the step length is 1 to 10 ms, and the preset detection threshold range is 5 to 12.

7. The analysis system for identifying compressor flow instability according to claim 5, characterized in that: Using S i =β-x i-j , i Analyze and obtain the outlet pressure change rate correction value S detected to the i-th detection window i ; where x i-j , i is the outlet pressure change rate between the ith detection window and the ijth detection window, β is the noise introduced by the outside world, and the value range of β is -3 to 0, excluding 0.

8. The analysis system for identifying compressor flow instability according to claim 7, characterized in that: After the i-th detection window is completed, the cumulative change of the compressor outlet pressure B i according to It is obtained by analysis, where μ is the cumulative loss, γ is the cumulative gain, and both μ and γ are positive integers.

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