CN108469281A - Two-phase Research on vortex signal processing based on EMD and Spectrum Correction - Google Patents
Two-phase Research on vortex signal processing based on EMD and Spectrum Correction Download PDFInfo
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- CN108469281A CN108469281A CN201810049784.5A CN201810049784A CN108469281A CN 108469281 A CN108469281 A CN 108469281A CN 201810049784 A CN201810049784 A CN 201810049784A CN 108469281 A CN108469281 A CN 108469281A
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F1/00—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
- G01F1/05—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using mechanical effects
- G01F1/20—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using mechanical effects by detection of dynamic effects of the flow
- G01F1/32—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by using mechanical effects by detection of dynamic effects of the flow using swirl flowmeters
- G01F1/325—Means for detecting quantities used as proxy variables for swirl
Abstract
The present invention relates to a kind of two-phase Research on vortex signal processing based on EMD and Spectrum Correction, including：Original time domain vortex signal is subjected to EMD decomposition；Calculate separately the auto-correlation function of each IMF components；The characteristics of being decayed according to auto-correlation function judges the mode separation k that noise plays a leading role with signal, and it is leading (IMF that IMF components, which are divided into noise,1~IMFk) and signal be leading (IMFk+1~IMFN) two parts；Leading signal IMF is accounted for noise1~IMFkCarry out wavelet soft-threshold filter；Reconstruct original signal obtains signal y (t) after denoising；To signal y (t) after denoising, the dominant frequency extraction accuracy of two-phase vortex street is improved by Spectrum Correction.
Description
Technical field
The invention belongs to two-phase flowmeter fields, are related to a kind of two-phase vortex street letter based on EMD filtering and Spectrum Correction
Number processing method.
Background technology
Two-phase flow is widely present in industrial production and daily life, wherein low liquid holdup operating mode is very common, such as day
Condensate is precipitated since operating mode changes in right gas exploitation, to form biphase gas and liquid flow (i.e. moisture) [1], and since heat damages
It loses, the stream-liquid two-phase flow (i.e. moist steam) [2] of steam generation condensation and formation.(flow is done for the parameter measurement of moisture and moist steam
Degree etc.) be process control, equipment safety operation important parameter.For example, in oil recovery by heating, to the high temperature and pressure of oil well injection
The mass dryness fraction and flow of moist steam, have a major impact [3] oil recovery efficiency and energy consumption；To the steam turbine of steam turbine and nuclear power station
In, steam quality seriously affects mechanical efficiency and leaf longevity [4].In addition, the accurate metering of moist steam and moisture is for pipeline
Transport, trade settlement has a major impact, be directly related to environmental protection, energy management and make full use of.
Vortex-shedding meter as a kind of velocity flowmeter, because its measurement range is wide, pressure drop is small, without moving part, resistance to height
The features such as warm high pressure, is widely used in moisture [5]-[6] and on-line measurement [7]-[8] of moist steam.Vortex-shedding meter may be used also
It is used with other kinds of flow meter, carries out measurement [9]-[10] of two-parameter (flow, mass dryness fraction).To improve vortex street frequency
Extraction accuracy, there has been proposed different signal processing methods, such as Kalman filtering [11], wavelet analysis [12], auto-correlation side
Method [13], Hilbert-Huang transformation [14] etc..
Above-mentioned signal processing method is measured both for monophasic fluid, has preferable effect for the processing of single-phase vortex signal
Fruit.However in two-phase flow measurement, influenced by discrete liquid phase, vortex signal amplitude reduces, quality declines, and the water that liquid phase generates
Kinetic noise generates together with vortex, and frequency and vortex street frequency are very close, therefore are very difficult to eliminate.In addition, utilizing
When FFT carries out frequency abstraction, fence effect caused by spectral leakage and algorithm caused by limited sampling point are discrete can all influence frequency
Rate extraction accuracy.Therefore, effectively feature extraction is carried out from small-signal, signal spectrum is rationally corrected, and is to improve
The key of two-phase signal reliability.
Bibliography
[1].ISO,“Measurement of Wet Gas Flow by Means of Pressure
Differential Devices Inserted in Circular Cross-section Conduits,”ISO,TR
11583,Switzerland,2012.
[2] .N Barton, A review of steam flowmeatering technology, London：NEL,
2004.
[3] Liu Yu texts, Xu Hong states thick oil heat production steam injection Efficiency Evaluations are studied [J] Liaoming Petrochemical Univ and are learned
Report, 2014,34 (3):62-66.
[4] Li Yan cutting edges of a knife or a sword, Wang Xinjun, Xu Tingxiang, wait in steam turbines the analysis of flowing wet steam humidity measuring method with
Compare [J] steam turbine technologies, 2000,42 (3):156-161.
[5].Hua C,Geng Y.Investigation on the swirlmeter performance in low
pressure wet gas flow[J].Measurement,vol 44(5),pp.881-887,2011.
[6].Stewart,D.The evaluation of dry gas meters in wet gas conditions,
DTI NMSD Flow Programme 1999-2002,NEL Report No 2002-100,Noverber 2002.
[7].Wade Mattar.Vortex shedding flowmeters a technology finally comes
of age,Technical Conference and EmergingTechnologiesConference,2004,454:631-
645.
[8].Measurement of fluid flow in pipes using vortex flowmeters,an
American National Standard, ASME MFC-6-2013, American Society of Mechanical
Engineers.
[9] .Agar J, Farchy D.Wet gas metering using dissimilar flow sensor：
theory and field trial results[A].SPE Annual Technical Conference[c].San
Antordo, Tx：2002,1-6.
[10].Li J,Wang C,Ding H,et al.Mass flowrate measurement of wet steam
using combined V-cone and vortex flowmeters[C]//Instrumentation and
Measurement Technology Conference.IEEE,2017:1-6.
[11].Shao C L,Xu K J,Shu Z P.Segmented Kalman Filter Based Antistrong
Transient Impact Method for Vortex Flowmeter[J].IEEE Transactions on
Instrumentation&Measurement,2017,PP(99):1-11.
[12].Laurantzon F,R,Segalini A,et al.Time-resolved measurements
with a vortex flowmeter in a pulsating turbulent flow using wavelet analysis
[J].Measurement Science & Technology,2010,21(12):123001.
[13].C.C.Hu,J.J.Miau,T.L.Chen,Determination of real-time vortex
shedding frequency by a DSP,J.Chin.Soc.Mech.Eng.27(3)(2006)335–342.
[14] Sun Bin, Zhou Hongliang, Zhang Hongjian, the Research on vortex signal processing for waiting to be converted based on Hilbert-Huang
[J] journal of Zhejiang university (engineering version), 2005,39 (6):801-804.
Invention content
The present invention provides a kind of two-phase vortex shedding flowmeter signal processing that can improve signal quality and frequency abstraction precision
Method.The present invention carries out EMD filtering to time domain vortex signal first, improves signal quality, is then carried out to dominant frequency spectral line accurate
Correction improves frequency abstraction precision, and finally improve two-phase vortex street measurement accuracy to reduce spectral leakage and truncated error.
For this purpose, the present invention adopts the following technical scheme that：
A kind of two-phase Research on vortex signal processing based on EMD and Spectrum Correction, includes the following steps：
1) original time domain vortex signal x (t) is subjected to EMD decomposition, obtains N number of IMF components；
2) auto-correlation function of each IMF components is calculated separately；
3) the characteristics of being decayed according to auto-correlation function judges the mode separation k that noise plays a leading role with signal, will
It is leading (IMF that IMF components, which are divided into noise,1~IMFk) and signal be leading (IMFk+1~IMFN) two parts；
4) leading signal IMF is accounted for noise1~IMFkWavelet soft-threshold filter is carried out, each component IMF after denoising is obtained1'
~IMFk'；
5) reconstruct original signal obtains signal y (t) after denoising；
6) to signal y (t) after denoising, the dominant frequency extraction accuracy of two-phase vortex street is improved by Spectrum Correction, method is as follows：
A. windowing process is carried out, and carries out Fast Fourier Transform (FFT) FFT；
B. spectrum peak spectral line in main lobe is determined, if its corresponding spectral line number is m, spectral line value is Y (m)；
C. n adjacent spectral line is found at left and right sides of peak value spectral line respectively；
D. the center of gravity of above-mentioned 2n+1 spectral line is calculated as correction frequency values, correction frequency values f0It is estimated as follows
Wherein, YiFor the corresponding spectral line value of i spectral lines, n is correction accuracy parameter, and the spectral line number for participating in correction is 2n+1, fs
For sample frequency, N is FFT transform sampling number.
E. correction signal amplitude A is estimated as follows
Wherein KtFor the energetic coefficient of restitution after windowed function, calculate as follows
Wherein y (t) and w (t) is respectively signal and window function after denoising.
Description of the drawings
Fig. 1：Vortex signal collecting flowchart figure
Fig. 2：Vortex signal frequency, Amplitude Estimation algorithm flow chart
Fig. 3：Direct FFT transform and this example processing method Contrast on effect, (a) direct FFT transform sample 1#；(b) this example is calculated
Method samples 1#；(c) direct FFT transform samples 2#；(d) this example algorithm samples 2#
Specific implementation mode
In conjunction with attached drawing and example, the present invention will be further described.
This example is a kind of application of the two-phase vortex street processing method based on EMD and Spectrum Correction in wet gas measurement.It is wet
Gas working condition pressure p=275~289kPa, gas phase flow rate Qv=10~25m3/ h, corresponding reynolds number Re=5.3 × 104~1.08 ×
105, liquid phase quality loading capacity φ=0~0.4, wherein φ=mL/mG, m representation quality flows, it is gentle that L and G respectively represent liquid phase
Phase.
Vortex street clock signal collecting flowchart is as shown in Figure 1：To detect vortex signal, flow signal is turned using piezoelectric probe
Turn to electric signal, original signal be subjected to charge amplification and voltage amplification by hardware circuit, and carry out bandpass filtering (f=200~
After 2500Hz), by NI-USB capture cards carry out data acquisition, sample frequency 20kHz, sampling number 131072, and by
Labview softwares are shown and are stored, and vortex street clock signal x (t) is obtained.
Signal processing based on EMD and Spectrum Correction is carried out to vortex street clock signal, is comprised the concrete steps that：
1) original signal x (t) is subjected to EMD decomposition, obtains several IMF components,Wherein N
For IMF component numbers, rcFor residual error；
2) auto-correlation function of each IMF components is calculated separatelyAnd carry out following normalizing
ChangeWherein τ indicates the time difference；
3) the characteristics of being decayed according to auto-correlation function judges the mode separation k that noise plays a leading role with signal, will
It is leading (IMF that IMF components, which are divided into noise,1~IMFk) and signal be leading (IMFk+1~IMFN)；
4) leading signal IMF is accounted for noise1~IMFkWavelet soft-threshold filter is carried out, each point of IMF after denoising is obtained1'~
IMFk'；
5) original signal is reconstructed,Y (t) is signal after denoising；
6) to signal y (t) after denoising, the dominant frequency extraction accuracy of two-phase vortex street is improved by Spectrum Correction.N=2 is chosen,
Namely 5 point calibrations are carried out, to improve correction accuracy.Method is as follows：
A. windowing process is carried out, the higher Hanning windows of main lobe energy is selected, to reduce energy leakage, and carries out FFT changes
It changes；
B. spectrum peak spectral line in main lobe is determined, if its corresponding spectral line number is m, spectral line value is Y (m)；
C. 2 adjacent spectral lines are found at left and right sides of peak value spectral line respectively；
D. the center of gravity of above-mentioned 5 spectral lines is calculated as correction frequency values, correction frequency values f0It is estimated as follows
Wherein, YiFor the corresponding spectral line value of i spectral lines, fsFor sample frequency, N is FFT transform sampling number.
E. correction signal amplitude A is estimated as follows
Wherein KtFor the energetic coefficient of restitution after windowed function, calculate as follows
Wherein y (t) is signal after denoising, and w (t) is Hanning window functions, corresponding recovery coefficient KtIt is 8/3.
To illustrate EMD filter effects in this example, clock signal progress denoising when to loading capacity φ=0.13, and and other
Filtering algorithm is compared, and includes wavelet filtering, moving average filtering and FIR low-pass filtering based on different basic functions, filtering
Contrast on effect is as shown in table 1, wherein SqFor frequency domain quality factor, Sq=10log10P0/Pr, wherein P0For (0.98~1.02) f
The spectrum energy of frequency range, PrFor residual spectrum energy, f is vortex street frequency；SNR is time domain signal-to-noise ratioMSE is mean square errorWherein, xiTo filter preceding original vortex street sequential letter
Number, yiFor filtered signal, N is signal length.
The denoising effect comparison (φ=0.13) of the different filtering algorithms of table 1
As it can be seen that moving average filtering and FIR low-pass filter effects are poor, this is because noise signal and vortex street frequency are very
It is close, both noise cannot effectively be filtered.In comparison, wavelet filtering effect is preferable, but since wavelet filtering is imitated
Fruit depends critically upon the selection of wavelet basis, and selects suitable wavelet basis relatively difficult.The filter effect based on EMD is most in this example
It is good, this is because it has the adaptive and irredundant characteristic of height, adaptive decomposition and filtering can be carried out according to by processing signal.
The validity of processing method to illustrate the invention, at the vortex street time-domain signal that is sampled twice in succession under the operating modes of φ=0.13
Reason, handling result as shown in figure 3, wherein f be extract vortex street frequency, PfFor vortex signal amplitude.As it can be seen that direct FFT transform
The frequency phase-difference 1.8% of the two, this error compared with vortex street typical accuracy (± 1%) are very big.After EMD is filtered, signal
Quality significantly improves, and the two correction frequency is very close.The vortex street frequency extracted through this example algorithm process, can represent φ
Vortex street eigenfrequency under=0.13 operating mode.
Claims (1)
1. a kind of two-phase Research on vortex signal processing based on EMD and Spectrum Correction, includes the following steps：
1) original time domain vortex signal x (t) is subjected to EMD decomposition, obtains N number of IMF components；
2) auto-correlation function of each IMF components is calculated separately；
3) the characteristics of being decayed according to auto-correlation function judges the mode separation k that noise plays a leading role with signal, by IMF points
It is leading (IMF that amount, which is divided into noise,1~IMFk) and signal be leading (IMFk+1~IMFN) two parts；
4) leading signal IMF is accounted for noise1~IMFkWavelet soft-threshold filter is carried out, each component IMF after denoising is obtained1'~
IMFk'；
5) reconstruct original signal obtains signal y (t) after denoising；
6) to signal y (t) after denoising, the dominant frequency extraction accuracy of two-phase vortex street is improved by Spectrum Correction, method is as follows：
A. windowing process is carried out, and carries out Fast Fourier Transform (FFT) FFT；
B. spectrum peak spectral line in main lobe is determined, if its corresponding spectral line number is m, spectral line value is Y (m)；
C. n adjacent spectral line is found at left and right sides of peak value spectral line respectively；
D. the center of gravity of above-mentioned 2n+1 spectral line is calculated as correction frequency values, correction frequency values f0It is estimated as follows
Wherein, YiFor the corresponding spectral line value of i spectral lines, n is correction accuracy parameter, and the spectral line number for participating in correction is 2n+1, fsTo adopt
Sample frequency, N are FFT transform sampling number；
E. correction signal amplitude A is estimated as follows
Wherein KtFor the energetic coefficient of restitution after windowed function, calculate as follows
Wherein y (t) and w (t) is respectively signal and window function after denoising.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109507072A (en) * | 2018-11-19 | 2019-03-22 | 北京大学 | A kind of fine particle turbulent flux measurement method |
| CN109974793A (en) * | 2019-04-22 | 2019-07-05 | 合肥工业大学 | A kind of signal processing method of magnetic vortex street flowmeter measurement gassiness the flow of conductive liquid |
| CN110186521A (en) * | 2019-05-31 | 2019-08-30 | 天津大学 | Vortex street moisture based on Wavelet Ridge feature extraction crosses reading compensation and flow-measuring method |
| CN110186522A (en) * | 2019-05-31 | 2019-08-30 | 天津大学 | Reading compensation and flow-measuring method are crossed in conjunction with the moisture of vortex street amplitude characteristic |
| CN111312291A (en) * | 2020-02-24 | 2020-06-19 | 厦门快商通科技股份有限公司 | Signal-to-noise ratio detection method, system, mobile terminal and storage medium |
| CN112926767A (en) * | 2021-01-27 | 2021-06-08 | 天津大学 | Annular fog flow gas phase apparent flow velocity prediction method based on particle swarm BP neural network |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109507072A (en) * | 2018-11-19 | 2019-03-22 | 北京大学 | A kind of fine particle turbulent flux measurement method |
| CN109507072B (en) * | 2018-11-19 | 2020-09-08 | 北京大学 | Fine particle turbulent flux measurement method |
| CN109974793A (en) * | 2019-04-22 | 2019-07-05 | 合肥工业大学 | A kind of signal processing method of magnetic vortex street flowmeter measurement gassiness the flow of conductive liquid |
| CN109974793B (en) * | 2019-04-22 | 2020-08-04 | 合肥工业大学 | Signal processing method for measuring flow of gas-containing conductive liquid by electromagnetic vortex shedding flowmeter |
| CN110186521A (en) * | 2019-05-31 | 2019-08-30 | 天津大学 | Vortex street moisture based on Wavelet Ridge feature extraction crosses reading compensation and flow-measuring method |
| CN110186522A (en) * | 2019-05-31 | 2019-08-30 | 天津大学 | Reading compensation and flow-measuring method are crossed in conjunction with the moisture of vortex street amplitude characteristic |
| CN110186521B (en) * | 2019-05-31 | 2020-09-04 | 天津大学 | Vortex street moisture over-reading compensation and flow measurement method based on wavelet ridge feature extraction |
| CN110186522B (en) * | 2019-05-31 | 2020-12-11 | 天津大学 | Moisture overreading compensation and flow measurement method combining vortex street amplitude characteristic |
| CN111312291A (en) * | 2020-02-24 | 2020-06-19 | 厦门快商通科技股份有限公司 | Signal-to-noise ratio detection method, system, mobile terminal and storage medium |
| CN112926767A (en) * | 2021-01-27 | 2021-06-08 | 天津大学 | Annular fog flow gas phase apparent flow velocity prediction method based on particle swarm BP neural network |
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Application publication date: 20180831 |