CN117332214A - Surge alarm method based on wavelet transformation and frequency domain coherence function fusion - Google Patents
Surge alarm method based on wavelet transformation and frequency domain coherence function fusion Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
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Abstract
The invention provides a surge alarm method based on wavelet transformation and frequency domain coherence function fusion, which comprises the following steps: s is S 1 The method comprises the steps of performing section cutting and rolling refreshing on continuously collected pulsation pressure data through an analysis window with a fixed length, setting the length of the data analysis window and the refreshing step length of the analysis window, and analyzing initial signals in the window; s is S 2 Selecting a wavelet basis function, a wavelet transformation layer number N and a threshold value rule function, and performing N-level discrete wavelet transformation on data in the analysis window length L by using a Mallet algorithm; reconstructing the signal by inverse wavelet transform using the approximation component of the nth stage;S 3 linearly trending the reconstructed signal; s is S 4 Solving a time domain difference value of a signal in a current analysis window; s is S 5 Performing cyclic iterative computation; s is S 6 And respectively setting surge judgment thresholds of a time domain and a frequency domain to acquire alarm parameters. The invention realizes the high-precision analysis of the surge anomaly in the time-frequency domain double dimensions by fusing the wavelet transformation technology and the frequency domain coherence function.
Description
Technical Field
The invention relates to the field of gas turbine compressor test measurement, in particular to a surge alarm method based on wavelet transformation and frequency domain coherence function fusion.
Background
In the prior art, when the compressor enters surge, severe airflow oscillation can be generated, so that the multistage blades bear large exciting force for a long time, and when severe, the structure of the engine is damaged destructively, so that the multistage blades are one of important factors affecting test safety. In the test, it is necessary to identify the surge precisely and quickly at the first moment of its occurrence, so that the antiasthmatic measures are taken.
The surge alarm is to judge whether the compressor enters surge or not by comparing and analyzing the stable working state of the compressor and the difference of dynamic pressure characteristics of a flow field when the compressor enters surge. Dynamic pressure characteristic analysis is based on digital signal processing technology and generally comprises a time domain analysis method, a frequency domain analysis method and an analysis method combining time and frequency domains.
1. The time domain analysis method is based on the time sequence change of the direct measurement signal, and the algorithm is simple, but only focuses on the total signal change trend, and does not distinguish the components. Therefore, the prediction capability is limited, and the compression system can be identified only when a relatively obvious instability phenomenon of the compression system occurs.
2. The frequency domain analysis method is based on the principle that the frequency characteristics of the compressor under different working conditions and different instability forms can be determined by carrying out Fourier transform on the acquired signals with a certain length, and the frequency domain analysis method has stronger anti-interference capability on high-frequency noise, but has the problem that the positioning of surge time cannot be realized;
3. the time-frequency analysis method is a method which is applied more, and has time sequence positioning capability while realizing spectrum analysis. The common time-frequency analysis method is short-time Fourier transform, but the time domain and the frequency domain precision cannot be considered due to the limitation of a fixed window function, and the method is not suitable for abrupt signal analysis. The wavelet analysis can directly observe the time domain waveform of each frequency band, has high time domain identification capability on transient mutation, but has insufficient sensitivity on the change of specific frequency components in each frequency band under the condition of limited decomposition layer number.
It follows that the existing analytical methods have a number of problems:
1. the conventional time domain analysis is insensitive to the change of surge characteristic signals and has poor anti-interference capability;
2. the problem that the occurrence time of the surge mutation signal cannot be accurately captured in the conventional frequency domain analysis;
3. the problem that high-precision time domain identification and frequency domain identification capability cannot be guaranteed simultaneously in conventional time-frequency analysis, and the problem of how to identify small amplitude-frequency variation in a segmented frequency domain.
Therefore, the inventor designs a surge alarm method based on wavelet transformation and frequency domain coherence function fusion, so as to solve the technical problems.
Disclosure of Invention
The invention aims to overcome the defects that in the prior art, an analysis method is insensitive to signal change and has poor anti-interference capability, and the occurrence time of a surge mutation signal cannot be accurately captured, and provides a surge alarm method based on wavelet transformation and frequency domain coherence function fusion.
The invention solves the technical problems by the following technical proposal:
the surge alarm method based on wavelet transformation and frequency domain coherence function fusion is characterized by comprising the following steps of:
S 1 the method comprises the steps of performing section cutting and rolling refreshing on continuously collected pulsation pressure data through an analysis window with a fixed length, respectively setting the length L of the data analysis window and the refreshing step length of the analysis window as the length delta L of data volume, and marking an initial signal in the analysis window as X;
S 2 selecting a wavelet basis function, a wavelet transformation layer number N and a threshold value rule function, and performing N-level discrete wavelet transformation on data in the analysis window length L by using a Mallet algorithm; reconstructing the signal by inverse wavelet transform using the approximation component of the nth stage, denoted as X1;
S 3 counterweightCarrying out linear trending on the structural signal X1, and marking the trended signal as X2;
S 4 solving the time domain difference value of the signal X2 in the current analysis window and marking the time domain difference value as A t ；
S 5 Performing cyclic iterative computation;
S 6 respectively setting surge judgment threshold T of time domain and frequency domain thred 、C thred And acquiring an Alarm parameter Alarm.
According to one embodiment of the invention, the step S 4 Also comprises:
the analysis window slides forward by the data quantity length delta L, the data in the analysis window is updated, the updated signal is recorded as X2', and the time domain difference value is calculated again and is recorded as A t+1 ；
Wherein the time domain difference value A t The calculation formula is as follows:
wherein P is tmax And P tmin Respectively corresponding to the maximum value and the minimum value of the pulsating pressure signal in the analysis window at the moment t, P tmean For the average value of the pulsating pressure signal in the analysis window corresponding to time t, X represents the initial signal in the analysis window.
According to one embodiment of the present invention, with the step S 4 Synchronization, further comprising: the frequency domain coherence function of the current analysis window signal X2 and the updated signal X2' is calculated by the Welch method.
According to one embodiment of the invention, the frequency domain coherence function C xy The value interval is 0-1.
According to one embodiment of the invention, when the compressor is in stable operation, the power spectrums of the pulsating pressures of adjacent windows are similar, and the frequency domain coherence function is close to 1;
when the compressor enters surge, the pulsation pressure frequency spectrum is obviously changed, and the frequency domain coherence function is sharply reduced;
wherein,representing a frequency domain coherence function; p (P) xx , P yy The self-power spectral densities of adjacent analysis windows X2 and X2' signals respectively;cross power spectral densities for adjacent analysis windows X2 and X2' signals; x2 represents an analysis window signal; x2' represents an updated signal; m represents a data point; l represents the data analysis window length.
In accordance with one embodiment of the present invention,for adjacent analysis windows X2 and X2' signals, the self-power spectral density is calculated by the following formula:
；
；
representing the autocorrelation coefficients; l represents the data analysis window length; m represents a data point;a sine wave with a frequency m times w;representing frequency resolution; n represents a data position;
；
；
x2 represents an analysis window signal; x2' represents an updated signal;
cross-power spectral density for adjacent analysis windows X2 and X2' signals, the cross-power spectral density calculated by the following formula:
；
representing cross-correlation coefficients; l represents the data analysis window length; m represents a data point;a sine wave with a frequency m times w;representing frequency resolution; n represents a data position;
the method comprises the steps of carrying out a first treatment on the surface of the X2 represents an analysis window signal; x2' represents the updated signal.
According to one embodiment of the invention, the step S 5 Further comprises: defining a time domain judging parameter T;
；
a time domain judgment parameter representing the (i+1) th and (i) th time constitution;represents the extreme difference of the (i+1) th time;indicating the extreme difference of the ith time.
According to one embodiment of the invention, the step S 5 Further comprises: defining a frequency domain judging parameter C;
；
a frequency domain decision parameter representing the time t to t+1;representing the current time;
indicating that the coherence function at time t to t +1 is averaged over the analysis bandwidth.
According to one embodiment of the invention, the step S 5 Further comprises:
continuously and iteratively updating the analysis window, wherein the data volume length delta L is updated by the data of each analysis window, and the data length L is kept unchanged;
and calculating a time domain judging parameter T and a frequency domain judging parameter C of adjacent windows once every time data are updated.
According to one embodiment of the invention, the step S 6 Comprises the following steps:
when (when)The Alarm parameter alarm=0, and no Alarm is output;
when (when)The Alarm parameter alarm=0, and no Alarm is output;
when (when)Outputting surge Alarm by the Alarm parameter alarm=1;
a time domain judgment parameter representing the (i+1) th and (i) th time constitution;
T thred c represents a surge determination threshold in the time domain thred The surge determination threshold in the frequency domain is represented.
The invention has the positive progress effects that:
the surge alarm method based on wavelet transformation and frequency domain coherence function fusion has the following advantages:
1. by fusing a wavelet transformation technology and a frequency domain coherence function, the high-precision analysis of surge anomaly in two dimensions of a time domain and a frequency domain is realized, namely, the accurate capture of the timing mutation anomaly is realized while the surge anomaly has strong anti-interference capability in a complex engineering environment. Meanwhile, the accuracy of identifying the surge frequency domain is improved, and the defect of insufficient sensitivity to detailed change of amplitude-frequency components in the frequency domain based on wavelet transformation is overcome.
2. The rolling window method ensures continuous sampling analysis of data, takes time-frequency change characteristics between nearest adjacent windows as a judgment criterion, thereby ensuring high timeliness of monitoring the state of the air compressor, and moreover, long-term influence of historical reference data can be avoided by rolling calculation only by means of one analysis window.
3. The surge alarm method can be applied to surge alarm monitoring of aero-engines, gas turbine compressor components and complete machines, effectively improves test safety, and reduces model development risks and cost.
Drawings
The above and other features, properties and advantages of the present invention will become more apparent from the following description of embodiments taken in conjunction with the accompanying drawings in which like reference characters designate like features throughout the drawings, and in which:
FIG. 1 is a schematic diagram of an original signal containing high-frequency noise in a surge alarm method based on wavelet transform and frequency domain coherence function fusion.
Fig. 2 is a schematic diagram of signal and analysis window updating after wavelet transformation reconstruction in the surge alarm method based on wavelet transformation and frequency domain coherence function fusion.
FIG. 3 shows the frequency domain coherence function C of adjacent analysis windows in the surge alarm method based on wavelet transform and frequency domain coherence function fusion of the present invention xy Is a schematic diagram of (a).
FIG. 4 shows a time domain decision parameter T and a decision threshold T in the surge alarm method based on wavelet transform and frequency domain coherence function fusion of the present invention thred Is a schematic diagram of (a).
FIG. 5 shows a frequency domain decision parameter C and a decision threshold C in a surge alarm method based on wavelet transform and frequency domain coherence function fusion of the present invention thred Is a schematic diagram of (a).
Detailed Description
In order to make the above objects, features and advantages of the present invention more comprehensible, embodiments accompanied with figures are described in detail below.
Embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts.
Furthermore, although terms used in the present invention are selected from publicly known and commonly used terms, some terms mentioned in the present specification may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein.
Furthermore, it is required that the present invention is understood, not simply by the actual terms used but by the meaning of each term lying within.
As shown in fig. 1 to 5, the invention discloses a surge alarm method based on wavelet transformation and frequency domain coherence function fusion, which comprises the following steps:
step S 1 And aiming at continuously collected pulsation pressure data, performing section cutting and rolling refreshing through an analysis window with a fixed length, respectively setting the data volume length L of the data analysis window and the refreshing step length of the analysis window as the data volume length delta L, and marking an initial signal in the analysis window as X.
Step S 2 Selecting a Daubechies wavelet basis function, a wavelet transformation layer number N and a threshold rule function, and performing N-level discrete wavelet transformation on data in the analysis window length L by using a Malet algorithm; the signal is reconstructed by inverse wavelet transform using the approximation component of the nth stage, denoted as X1.
Step S 3 The reconstructed signal X1 is linearly dettrended to reduce the influence of the slowly varying signal or the dc component, and the dettrended signal is denoted as X2.
Step S 4 Solving the time domain difference value (corresponding time is marked as t) of the signal X2 in the current analysis window and marking as A t 。
Said step S 4 Also comprises:
the analysis window slides forward by the data quantity length delta L, the data in the analysis window is updated, the updated signal is recorded as X2', and the time domain difference value is calculated again and is recorded as A t+1 ；
Wherein, the time domain difference value A t The calculation formula is as follows:
wherein P is tmax And P tmin Respectively corresponding to the maximum value and the minimum value of the pulsating pressure signal in the analysis window at the time tValue, P tmean The time t corresponds to the average value of the pulsating pressure signal in the analysis window.
And said step S 4 Synchronization, further comprising: the frequency domain coherence function of the current analysis window signal X2 and the updated signal X2' is calculated by the Welch method.
The frequency domain coherence function C xy The value interval is 0-1.
When the compressor works stably, the power spectrums of the pulsating pressures of adjacent windows are similar, and the frequency domain coherence function is close to 1;
when the compressor enters surge, the pulsation pressure frequency spectrum is obviously changed, and the frequency domain coherence function is sharply reduced;
wherein,representing a frequency domain coherence function; p (P) xx , P yy The self-power spectral densities of adjacent analysis windows X2 and X2' signals respectively;for cross-power spectral densities of adjacent analysis window X2 and X2' signals, X2 represents the analysis window signal; x2' represents an updated signal; m represents a data point; l represents the data analysis window length.
For adjacent analysis windows X2 and X2' signals, the self-power spectral density is calculated by the following formula:
；
；
representing the autocorrelation coefficients; l represents the data analysis window length; m represents a data point;a sine wave with a frequency m times w;representing frequency resolution; n represents a data position;
；
；
x2 represents an analysis window signal; x2' represents the updated signal.
Cross-power spectral density for adjacent analysis windows X2 and X2' signals, the cross-power spectral density calculated by the following formula:
。
representing cross-correlation coefficients; l represents a data analysis windowPort length; m represents a data point;a sine wave with a frequency m times w;representing frequency resolution; n represents a data position;
the method comprises the steps of carrying out a first treatment on the surface of the X2 represents an analysis window signal; x2' represents the updated signal.
Step S 5 And performing loop iteration calculation.
Preferably, the step S 5 Further comprises: defining a time domain judging parameter T;
。
a time domain judgment parameter representing the (i+1) th and (i) th time constitution;represents the extreme difference of the (i+1) th time;indicating the extreme difference of the ith time.
Further, the step S 5 Further comprises: defining a frequency domain judging parameter C;
。
a frequency domain decision parameter representing the time t to t+1;representing the current time;indicating that the coherence function at time t to t +1 is averaged over the analysis bandwidth.
Further preferably, the step S 5 Further comprises:
and carrying out continuous iterative updating on the analysis window, wherein the data updating delta L of each analysis window is carried out, and the data length L is kept unchanged.
And calculating a time domain judging parameter T and a frequency domain judging parameter C of adjacent windows once every time data are updated.
For example, after i iterations, two parameter sets can be written as:
。
step S 6 Respectively setting surge judgment threshold T of time domain and frequency domain thred 、C thred And acquiring an Alarm parameter Alarm.
Preferably, whenThe Alarm parameter alarm=0, and no Alarm is output;
when (when)The Alarm parameter alarm=0, and no Alarm is output;
when (when)And outputting a surge Alarm by the Alarm parameter alarm=1.
A time domain judgment parameter representing the (i+1) th and (i) th time constitution;
T thred c represents a surge determination threshold in the time domain thred Representation ofSurge determination threshold in the frequency domain.
According to the step description of the method, the surge alarm method based on wavelet transformation and frequency domain coherence function fusion realizes the following innovation:
1. after wavelet transformation is carried out on an original signal, information reconstruction is carried out by using a designated level coarse wavelet coefficient, and high-frequency noise is removed;
2. performing high-precision analysis on two dimensions of a time domain and a frequency domain on the reconstruction signal by adopting a rolling window;
3. the time domain adopts a range method to analyze the range time sequence variation of adjacent windows; the frequency domain adopts a coherent function method to analyze the similarity of specific frequency spectrum components and amplitude values between adjacent windows and identify micro amplitude-frequency variation;
4. and when the range change of the adjacent window exceeds a set threshold and the frequency domain coherence function is lower than the set threshold, a surge alarm is sent out.
In summary, the surge alarm method based on wavelet transformation and frequency domain coherence function fusion has the following advantages:
1. by fusing a wavelet transformation technology and a frequency domain coherence function, the high-precision analysis of surge anomaly in two dimensions of a time domain and a frequency domain is realized, namely, the accurate capture of the timing mutation anomaly is realized while the surge anomaly has strong anti-interference capability in a complex engineering environment. Meanwhile, the accuracy of identifying the surge frequency domain is improved, and the defect of insufficient sensitivity to detailed change of amplitude-frequency components in the frequency domain based on wavelet transformation is overcome.
2. The rolling window method ensures continuous sampling analysis of data, takes time-frequency change characteristics between nearest adjacent windows as a judgment criterion, thereby ensuring high timeliness of monitoring the state of the air compressor, and moreover, long-term influence of historical reference data can be avoided by rolling calculation only by means of one analysis window.
3. The surge alarm method can be applied to surge alarm monitoring of aero-engines, gas turbine compressor components and complete machines, effectively improves test safety, and reduces model development risks and cost.
The above disclosure is intended to be illustrative only and not limiting to the present application to those skilled in the art. Although not explicitly described herein, various modifications, improvements, and adaptations of the present application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within this application, and therefore, such modifications, improvements, and modifications are intended to be within the spirit and scope of the exemplary embodiments of this application.
Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present application may be combined as suitable.
Likewise, it should be noted that in order to simplify the presentation disclosed herein and thereby aid in understanding one or more inventive embodiments, various features are sometimes incorporated into one embodiment, the drawings, or the description thereof, in the foregoing description of embodiments of the present application. This method of disclosure, however, is not intended to imply that more features than are presented in the claims are required for the subject application. Indeed, embodiments may have fewer than all of the features of a single embodiment disclosed above. In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.
Claims (10)
1. The surge alarm method based on wavelet transformation and frequency domain coherence function fusion is characterized by comprising the following steps of:
S 1 the method comprises the steps of performing section cutting and rolling refreshing on continuously collected pulsation pressure data through an analysis window with a fixed length, respectively setting the length L of the data analysis window and the refreshing step length of the analysis window as the length delta L of data volume, and marking an initial signal in the analysis window as X;
S 2 selecting a wavelet basis function, a wavelet transformation layer number N and a threshold value rule function, and performing N-level discrete wavelet transformation on data in the analysis window length L by using a Mallet algorithm; reconstructing the signal by inverse wavelet transform using the approximation component of the nth stage, denoted as X1;
S 3 linearly detrending the reconstructed signal X1, wherein the detrended signal is marked as X2;
S 4 solving the time domain difference value of the signal X2 in the current analysis window and marking the time domain difference value as A t ；
S 5 Performing cyclic iterative computation;
S 6 respectively setting surge judgment threshold T of time domain and frequency domain thred 、C thred And acquiring an Alarm parameter Alarm.
2. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 1, wherein said step S 4 Also comprises:
the analysis window slides forward by the data quantity length delta L, the data in the analysis window is updated, the updated signal is recorded as X2', and the time domain difference value is calculated again and is recorded as A t+1 ；
Wherein the time domain difference value A t The calculation formula is as follows:
wherein P is tmax And P tmin Respectively corresponding to the maximum value and the minimum value of the pulsating pressure signal in the analysis window at the moment t, P tmean For the average value of the pulsating pressure signal in the analysis window corresponding to time t, X represents the initial signal in the analysis window.
3. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 2, wherein said step S 4 Synchronization, further comprising: the frequency domain coherence function of the current analysis window signal X2 and the updated signal X2' is calculated by the Welch method.
4. A surge alarm method based on wavelet transform and frequency domain coherence function fusion as defined in claim 3, wherein said frequency domain coherence function C xy The value interval is 0-1.
5. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 4, wherein when the compressor is in stable operation, the power spectrum of the pulsating pressure of adjacent windows is similar, and the frequency domain coherence function is close to 1;
when the compressor enters surge, the pulsation pressure frequency spectrum is obviously changed, and the frequency domain coherence function is sharply reduced;
wherein,representing a frequency domain coherence function; p (P) xx , P yy The self-power spectral densities of adjacent analysis windows X2 and X2' signals respectively;cross power spectral densities for adjacent analysis windows X2 and X2' signals; x2 represents an analysis window signal; x2' represents an updated signal; m represents a data point; l represents the data analysis window length.
6. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 5,for adjacent analysis windows X2 and X2' signals, the self-power spectral density is calculated by the following formula:
；
；
representing the autocorrelation coefficients; l represents the data analysis window length; m represents a data point; />A sine wave with a frequency m times w; />Representing frequency resolution; n represents a data position;
；
；
x2 represents an analysis window signal; x2' represents an updated signal;
cross-power spectral density for adjacent analysis windows X2 and X2' signals, the cross-power spectral density calculated by the following formula:
；
representing cross-correlation coefficients; l represents the data analysis window length; m represents a data point; />A sine wave with a frequency m times w; />Representing frequency resolution; n represents a data position;
the method comprises the steps of carrying out a first treatment on the surface of the X2 represents an analysis window signal; x2' represents the updated signal.
7. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 1, wherein said step S 5 Further comprises: defining a time domain judging parameter T;
；
a time domain judgment parameter representing the (i+1) th and (i) th time constitution;
represents the extreme difference of the (i+1) th time; />Indicating the extreme difference of the ith time.
8. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 1, wherein said step S 5 Further comprises: defining a frequency domain judging parameter C;
；
a frequency domain decision parameter representing the time t to t+1; />Representing the current time;
indicating that the coherence function at time t to t +1 is averaged over the analysis bandwidth.
9. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 1, wherein said step S 5 Further comprises:
continuously and iteratively updating the analysis window, wherein the data volume length delta L is updated by the data of each analysis window, and the data length L is kept unchanged;
and calculating a time domain judging parameter T and a frequency domain judging parameter C of adjacent windows once every time data are updated.
10. The surge alarm method based on wavelet transform and frequency domain coherence function fusion of claim 1, wherein said step S 6 Comprises the following steps:
when (when)The Alarm parameter alarm=0, and no Alarm is output;
when (when)The Alarm parameter alarm=0, and no Alarm is output;
when (when)Outputting surge Alarm by the Alarm parameter alarm=1;
a time domain judgment parameter representing the (i+1) th and (i) th time constitution;
T thred c represents a surge determination threshold in the time domain thred The surge determination threshold in the frequency domain is represented.
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