CN105181031A - Vortex flowmeter based on multi-sensor information fusion - Google Patents
Vortex flowmeter based on multi-sensor information fusion Download PDFInfo
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- CN105181031A CN105181031A CN201510259001.2A CN201510259001A CN105181031A CN 105181031 A CN105181031 A CN 105181031A CN 201510259001 A CN201510259001 A CN 201510259001A CN 105181031 A CN105181031 A CN 105181031A
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Abstract
The invention discloses a vortex flowmeter based on multi-sensor information fusion. The vortex flowmeter has functions of effectively inhibiting an interference of a strong periodic vibration noise in a piezoelectric transducer signal, extracting a useful vortex signal from the piezoelectric transducer signal and accurately measuring the flow speed of fluid. The vortex flowmeter is characterized in that a temperature sensor and a differential pressure sensor with high vibration resistance are added on a traditional piezoelectric vortex flowmeter; the temperature sensor can be used for compensating the temperature drifts of the piezoelectric transducer and the differential pressure sensor; a multi-sensor data fusion algorithm based on an unscented Kalman Filter is used; Data fusion between an average value of the differential pressure which is output by the differential pressure sensor and a frequency of a piezoelectric signal that is obtained by the piezoelectric sensor is performed. The precision in locking a digital bandpass filter is improved. The vortex flowmeter has advantages of improving a measured signal-to-noise ratio of the vortex signal, improving vibration resistance of the piezoelectric vortex flowmeter, reducing a measurement lower limit of a least flow speed, enlarging a measuring range ratio, etc.
Description
Technical field
The present invention relates to the Research on vortex signal processing based on Multi-information acquisition in vortex shedding flow meter, belong to fluid flux measurement technology field.
Background technology
Flow metering takies consequence as the important component part of detection technique in economic development.In all eurypalynous flow instruments, vortex shedding flow meter realizes flow measurement according to " Karman vortex street " principle famous in fluid mechanics, in certain reynolds number range, the frequency that vortex is separated is proportional to the mean flow rate of fluids within pipes, thus obtains the flow velocity of fluid by vortex signal frequency and then obtain the flow of fluid.Because vortex shedding flow meter has non mechanical movable, go for the measurement of medium, the pressure loss is little, and measuring accuracy is high, output signal frequency and the advantage such as flow is directly proportional, be widely used in the fields such as light industry, chemical industry, electric power, metallurgy, municipal service.
Piezoelectric vortex flowmeter is the most traditional is also the most frequently used vortex shedding flow meter, because piezoelectric sensor has the advantages such as response is fast, signal is strong, technique good, cost of manufacture is low, is used widely in traditional stress-type vortex street flowmeter.
But traditional piezoelectric vortex flowmeter is just analyzed the mixed signal that piezoelectric crystal exports, there are two large shortcomings in actual use: one is that piezoelectric sensor is very responsive to mechanical vibration, also just result in the not vibration resistance of piezoelectric vortex flowmeter.Two is under extraneous very noisy Vibration Condition, the intensity of noise signal is higher than the intensity of useful vortex signal, the frequency values that traditional Research on vortex signal processing obtains and the real frequency value difference of vortex signal larger, therefore the filter effect of digital band-pass filter is also very poor, so the precision of the vortex signal frequency values finally recorded is very low.
Kalman filtering is called as optimization autoregression data processing algorithm, and Kalman filter designs in time domain, and be applicable to multidimensional situation.Divided without useful and useless by the signal of Kalman filter process, the object of filtering to estimate all processed signals.Based on above advantage, Kalman filtering is widely used in the every field of national defense industry.In non-linear Kalman filtering, Unscented kalman filtering (UnscentedKalmanFilter) algorithm application is the most extensive, compares general non-linear Kalman filtering, has the advantages such as calculated amount is little, practicality of being more convenient for.
Summary of the invention
The object of the invention is to occur the shortcomings such as poor, the lower limit flow of vibration resistance is high, range ratio is little for traditional piezoelectric vortex flowmeter when extraneous very noisy vibration interference, propose a kind of flux of vortex street based on Multi-information acquisition and take into account Research on vortex signal processing.The method can improve the signal to noise ratio (S/N ratio) that vortex signal is measured, and strengthens the vibration resistance of piezoelectric vortex flowmeter, reduces minimum flow velocity measurement lower limit, widens range ratio.
The object of the invention is to be achieved through the following technical solutions: a kind of vortex shedding flow meter based on Multi-information acquisition, comprise piezoelectric sensor and differential pressure pick-up, the anode of described differential pressure pick-up is placed on the fluoran stream surface of bluff body inside, and negative terminal is placed on the downstream of bluff body; The difference of the total pressure that what described differential pressure pick-up two ends were experienced is on bluff body fluoran stream surface and the static pressure in bluff body downstream, obtains the mean value of differential pressure before and after bluff body
the measurement impact of outside noise vibration on differential pressure pick-up is less, therefore
variance less,
to square being directly proportional of fluid density and rate of flow of fluid, can be expressed as:
Wherein C
pfor pressure coefficient; ρ is fluid density; U is rate of flow of fluid.
Described piezoelectric sensor is placed on the downstream of bluff body, exports the piezoelectric signal under the fluid oscillation and outside noise vibration acting in conjunction produced by Karman vortex street principle; Analysis of spectrum carried out to piezoelectric signal and carry out float level cutting in time domain, obtaining the frequency values f of piezoelectric signal, can be expressed as:
f＝k·U(4)
Wherein k is meter constant; U is rate of flow of fluid.
Piezoelectric sensor detects extraneous vibration and measures rate of flow of fluid, and therefore vibration interference is very sensitive to external world for piezoelectric sensor, and the variance of f is larger.
Further, described vortex shedding flow meter also comprises temperature sensor, the temperature value that described temperature sensor records be used for compensate for poor pressure sensor and piezoelectric sensor temperature drift.
Utilize above-mentioned vortex shedding flow meter to carry out a method for rate of flow of fluid measurement, comprise the following steps:
Step one: differential pressure pick-up records the mean value of differential pressure before and after bluff body
Step 2: the differential pressure signal separately differential pressure pick-up recorded
carry out UKF filtering, obtain a preliminary flow speed value u, according to formula f
p=ku, converts this flow speed value and obtains the frequency f of vortex signal
p, wherein k is meter constant.
To differential pressure signal
when carrying out UKF filtering, system state vector
Wherein d ρ is the first differential of density, and du is the first differential of speed.
Step 3: the vortex signal collected piezoelectric sensor carries out analysis of spectrum and float level cutting, peak-peak in record spectrogram, secondary peak value, the frequency values f that the third and fourth peak value is corresponding
n(n=1,2,3,4).
Step 4: if f
nmiddle existence and f
p, namely there is f in the frequency values be more or less the same
n(n=1,2,3,4) make | f
n-f
p| during < Δ f, at f
nin find out and f
pthe most close one the net result f be worth as piezoelectric signal analysis of spectrum, namely at f
nfind out a frequency values in (n=1,2,3,4) to make | f
n-f
p| value minimum, then perform step 5; If f
nall values all with f
pdifference is comparatively large, namely as | f
n-f
p| time>=Δ f (n=1,2,3,4), do not perform step 5, directly by f
pas the center frequency value f of bandpass filter
0.The concrete value of Δ f can be demarcated in industry spot and be obtained.
Step 5: structure Federated Filters.Differential pressure signal
uKF filtering and the UKF filtering of frequency signal f as two subfilters of Federated Filters, try to achieve last flow speed value U according to this Federated Filters, and then according to formula (2) frequency of conversion f
0.
When UKF filtering is carried out to frequency signal f, system state vector
Step 6: by vortex signal frequency values f
0centre frequency as narrow bandwidth digital band-pass filter arranges the coefficient of digital band-pass filter, re-use this digital band-pass filter and digital band pass filtering is carried out to the piezoelectric signal that piezoelectric sensor exports, obtain the stable vortex signal containing minute quantity clutter;
Step 7: the stable vortex signal that step 6 obtains is the sinusoidal signal containing minute quantity noise, is used Schmidt trigger vortex signal to be converted to the square-wave signal of same frequency, is obtained the frequency values f of stable vortex signal by the frequency values measuring square wave
m, calculate the flow velocity U of fluid, i.e. U=f
m/ k, k are meter constant.
The invention has the beneficial effects as follows, adopt Unscented kalman filtering (UnscentedKalmanFilter, UKF) measured value of algorithm to differential pressure pick-up and piezoelectric sensor carries out data fusion, in extraneous very noisy vibration interference situation, still can obtain a digital band-pass filter center frequency value close with true vortex signal frequency values, improve the filter effect of digital band-pass filter, obtain stable vortex signal.Traditional vortex shedding flow meter is directly using the centre frequency of frequency values corresponding for top in piezoelectric signal spectrogram as wide bandwidth digital band-pass filter, compared with traditional piezoelectric vortex flowmeter, the Research on vortex signal processing of the Multi-information acquisition that the present invention proposes, the signal to noise ratio (S/N ratio) that vortex signal is measured can be improved, strengthen the vibration resistance of piezoelectric vortex flowmeter, reduce minimum flow velocity measurement lower limit, widen range ratio.
Accompanying drawing explanation
The multisensor vortex flowmeter system structural drawing that Fig. 1 provides for the embodiment of the present invention;
The schematic diagram of the Research on vortex signal processing of the Multi-information acquisition that Fig. 2 provides for the embodiment of the present invention;
In figure,
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention; technical scheme in the embodiment of the present invention is clearly and completely described; obviously; described embodiment is only a part of embodiment of the present invention; based on the every other embodiment that embodiment provided by the invention obtains not making creative work, all belong to the scope of protection of the invention.
As shown in Figure 1, the vortex shedding flow meter based on Multi-information acquisition that the embodiment of the present invention provides, forms primarily of piezoelectric sensor 4, differential pressure pick-up 3 and temperature sensor 5.Bluff body 1 is that the gradient is less, drift angle triangular prism bluff body forward.Piezoelectric sensor 4 is placed on the downstream of bluff body 1, exports the piezoelectric signal under the fluid oscillation and outside noise vibration acting in conjunction produced by Karman vortex street principle; The anode 2a of differential pressure pick-up 3 is placed on the fluoran stream surface of bluff body 1 inside, and negative terminal 2b is placed on the downstream of bluff body 1, the difference of the total pressure that what differential pressure pick-up 3 two ends were experienced is on bluff body 1 fluoran stream surface and the static pressure in bluff body 1 downstream; Differential pressure pick-up 3 can select the PX81D0-005DI of OMEGA company, and the differential pressure pick-up of this model is high precision small-range differential pressure pick-up; Temperature sensor can select the PRTF-10-1-100-1/8-12-E of OMEGA company.
As shown in Figure 2, the Research on vortex signal processing of the Multi-information acquisition that the embodiment of the present invention provides, the differential pressure mean value that first the method records differential pressure pick-up 3 and the piezoelectric signal frequency values that piezoelectric sensor 4 records carry out Fusion, the frequency values of piezoelectric signal is restrained to the frequency values of useful vortex signal, and then obtains a stable vortex signal frequency values f
0, f
0as the centre frequency of narrow bandwidth digital band-pass filter.
Narrow bandwidth digital band-pass filter is designed to 2 rank IIR digital band-pass filters, by centre frequency f
0the coefficient of narrow bandwidth digital band-pass filter can be calculated, re-use this digital band-pass filter and digital band pass filtering is carried out to the piezoelectric signal that piezoelectric sensor exports.Due to the smaller bandwidth of digital band-pass filter, most noise signal is decayed, obtain the stable vortex signal containing minute quantity clutter.By stablizing the frequency values of vortex signal after the filtering of measurement digital band pass, calculating the flow velocity of fluid, ensure that the degree of accuracy of flow measurement.When very noisy vibrates, by above measuring process, can the stability of guaranteed flow measurement and the precision of measurement.
Claims (3)
1. the vortex shedding flow meter based on Multi-information acquisition disposal route, it is characterized in that, comprise piezoelectric sensor (4) and differential pressure pick-up (3), the anode (2a) of described differential pressure pick-up (3) is placed on the inner fluoran stream surface of bluff body (1), and negative terminal (2b) is placed on the downstream of bluff body (1); The difference of the total pressure that what described differential pressure pick-up (3) two ends were experienced is on bluff body (1) fluoran stream surface and the static pressure in bluff body (1) downstream, obtains the mean value of differential pressure before and after bluff body (1)
to fluid density and rate of flow of fluid square product be directly proportional, can be expressed as:
Wherein C
pfor pressure coefficient; ρ is fluid density; U is rate of flow of fluid;
Described piezoelectric sensor (4) is placed on the downstream of bluff body (1), exports the piezoelectric signal under the fluid oscillation and outside noise vibration acting in conjunction produced by Karman vortex street principle; Carry out analysis of spectrum to piezoelectric signal and carry out float level cutting in time domain, obtain the frequency values f of piezoelectric signal, f is directly proportional to rate of flow of fluid, can be expressed as:
f＝k·U(2)
Wherein k is meter constant; U is rate of flow of fluid.
2. a kind of vortex shedding flow meter based on Multi-information acquisition according to claim 1, it is characterized in that, also comprise temperature sensor (5), the temperature value that described temperature sensor (5) records be used for compensate for poor pressure sensor (3) and piezoelectric sensor (4) temperature drift.
3. utilize vortex shedding flow meter described in claim 1 to carry out a method for rate of flow of fluid measurement, it is characterized in that, comprise the following steps:
Step one: differential pressure pick-up (3) records the mean value of differential pressure before and after bluff body
Step 2: the differential pressure signal separately differential pressure pick-up (3) recorded
carry out UKF filtering, obtain a flow speed value u, according to formula f
p=ku, converts this flow speed value and obtains the frequency f of vortex signal
p, wherein k is meter constant;
Step 3: the vortex signal collected piezoelectric sensor (4) carries out analysis of spectrum and float level cutting, peak-peak in record spectrogram, secondary peak value, the frequency values f that the third and fourth peak value is corresponding
n(n=1,2,3,4);
Step 4: if f
nmiddle existence and f
p, namely there is f in the frequency values be more or less the same
n(n=1,2,3,4) make | f
n-f
p| during < Δ f, at f
nin find out and f
pthe most close one the net result f be worth as piezoelectric signal analysis of spectrum, namely at f
nfind out a frequency values in (n=1,2,3,4) to make | f
n-f
p| value minimum, then perform step 5; If f
nall values all with f
pdifference is comparatively large, namely as | f
n-f
p| time>=Δ f (n=1,2,3,4), do not perform step 5, directly by f
pas the center frequency value f of bandpass filter
0;
Step 5: structure Federated Filters: differential pressure signal
uKF filtering and the UKF filtering of frequency signal f as two subfilters of Federated Filters, try to achieve last flow speed value U according to this Federated Filters, and then according to formula (2) frequency of conversion f
0;
Step 6: by vortex signal frequency values f
0centre frequency as narrow bandwidth digital band-pass filter arranges the coefficient of digital band-pass filter, re-use this digital band-pass filter and digital band pass filtering is carried out to the piezoelectric signal that piezoelectric sensor (4) exports, obtain the stable vortex signal containing minute quantity clutter;
Step 7: the frequency values f of the stable vortex signal obtained by measuring process six
m, calculate the flow velocity U of fluid, i.e. U=f
m/ k, k are meter constant.
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Cited By (7)
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| CN105571659A (en) * | 2016-01-21 | 2016-05-11 | 中国计量学院 | Vortex frequency stochastic resonance control and detection method based on standard deviation |
| CN105737909A (en) * | 2016-02-23 | 2016-07-06 | 合肥工业大学 | Anti-instantaneous-impact-interference signal processing method and system for vortex shedding flowmeter based on Kalman filtering |
| CN108287007A (en) * | 2017-01-09 | 2018-07-17 | 山东省水利勘测设计院 | A kind of intelligent water-level instrumentation based on Data fusion technique |
| CN111426353A (en) * | 2020-04-08 | 2020-07-17 | 中国民用航空飞行学院 | Accurate flow obtaining device and method |
| CN113167609A (en) * | 2018-12-14 | 2021-07-23 | 恩德斯+豪斯流量技术股份有限公司 | Measuring system for measuring flow parameters of a fluid flowing in a pipe |
| CN116202584A (en) * | 2023-05-05 | 2023-06-02 | 河南新航流量仪表有限公司 | Vibration-resistant vortex shedding flowmeter |
| CN117007144A (en) * | 2023-10-07 | 2023-11-07 | 成都睿宝电子科技有限公司 | High-precision thermal type gas mass flowmeter and zeroing method thereof |
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Cited By (13)
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| CN105571659A (en) * | 2016-01-21 | 2016-05-11 | 中国计量学院 | Vortex frequency stochastic resonance control and detection method based on standard deviation |
| CN105737909A (en) * | 2016-02-23 | 2016-07-06 | 合肥工业大学 | Anti-instantaneous-impact-interference signal processing method and system for vortex shedding flowmeter based on Kalman filtering |
| WO2017143649A1 (en) * | 2016-02-23 | 2017-08-31 | 合肥工业大学 | Kalman filter-based vortex flowmeter anti-transient shock interference signal processing method and system |
| CN105737909B (en) * | 2016-02-23 | 2018-07-13 | 合肥工业大学 | The signal processing method and system of the anti-transient impact interference of vortex-shedding meter based on Kalman filtering |
| US10876869B2 (en) | 2016-02-23 | 2020-12-29 | Hefei University Of Technology | Kalman filter based anti-transient-impact-vibration-interference signal processing method and system for vortex flowmeter |
| CN108287007A (en) * | 2017-01-09 | 2018-07-17 | 山东省水利勘测设计院 | A kind of intelligent water-level instrumentation based on Data fusion technique |
| CN113167609B (en) * | 2018-12-14 | 2024-05-24 | 恩德斯+豪斯流量技术股份有限公司 | Measuring system for measuring a flow parameter of a fluid flowing in a pipe |
| CN113167609A (en) * | 2018-12-14 | 2021-07-23 | 恩德斯+豪斯流量技术股份有限公司 | Measuring system for measuring flow parameters of a fluid flowing in a pipe |
| CN111426353A (en) * | 2020-04-08 | 2020-07-17 | 中国民用航空飞行学院 | Accurate flow obtaining device and method |
| CN116202584A (en) * | 2023-05-05 | 2023-06-02 | 河南新航流量仪表有限公司 | Vibration-resistant vortex shedding flowmeter |
| CN117007144A (en) * | 2023-10-07 | 2023-11-07 | 成都睿宝电子科技有限公司 | High-precision thermal type gas mass flowmeter and zeroing method thereof |
| CN117007144B (en) * | 2023-10-07 | 2023-12-15 | 成都睿宝电子科技有限公司 | High-precision thermal type gas mass flowmeter and zeroing method thereof |
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