CN102269333A - Method for eliminating pipe blockage acoustic signal strong interference by utilizing frequency domain self-adaptive filtering - Google Patents

Abstract

The invention relates to a method for eliminating pipe blockage acoustic signal strong interference by utilizing frequency domain self-adaptive filtering, The method comprises the following steps: (1) a main sensor is arranged in a pipeline, a reference sensor is arranged on the part close to a pump, and simultaneously a sound wave signal is collected; (2) the sound wave signals of the main sensor and the reference sensor sound wave are inputted a monitoring system; (3) a frequency domain spectrum of the inputted low-frequency sound wave signal is extracted; (4) the estimation is carried out on frequency domain spectrum of the signal, and the threshold value is set; (5) when the spectrum is higher than the threshold value, and an adaptive filter is started to eliminate the strong interference spectrum; and (6) the inverse fourier transform is utilized, thereby obtaining low-frequency blockage echo signal after the strong interference signal is eliminated. The system adopts a disturb-counteracted filter, the frequency domain spectrum adopts an adaptive algorithm to gradually iterative update, the required data-storing volume is smaller, thereby greatly improving the response time of the system; the system provided by the invention has the advantages that the construction is convenient, the reliability of the system is strong, the detection speed is rapid, therefore, the normal production run of the pipeline can not be influenced, and the blockage state of the oil gas pipeline is monitored in on-line manner.

Description

A kind of frequency domain adaptive filtering is eliminated the strongly disturbing method of line clogging acoustic signal

Technical field

The present invention relates to the removing method that oil and gas pipes stops up high reject signal in the monitoring equipment.

Background technique

Crude oil that China produces is higher waxy crude oil of condensation point and sticky heavy crude more than 80%, so its conveying exists and mobile relevant potential safety hazard always.If the wax component in the crude oil contacts with cryogenic object, will separate out and condense, can blocking pipe when serious.

Therefore, find that in time it is the key that ensures the submarine pipeline safe operation that the mobile sexual abnormality of submarine pipeline prevents trouble before it happens.Submarine pipeline stops up flow abnormalities such as leakage that monitoring technology helps in time finding and handle that submarine pipeline takes place and obstruction, is to ensure the critical technological means of submarine pipeline safe operation.At present, submarine pipeline obstruction monitoring technology means relatively lack.

Low-frequency sound wave has the advantages that the decay brief biography is broadcast distance, is the important means of carrying out flowing state monitoring in the pipeline.Utilize acoustic emission apparatus emission low-frequency sound wave based on the line clogging monitoring system of sound wave, and use sonic sensor that the low frequency echo signal of line clogging point reflection is converted to electrical signal, be transferred to the oil gas pipe network by data transmission network and stop up location-server.When flowing states such as pipeline generation obstruction were unusual, system can send warning automatically according to signal processing results, and calculates an obstruction point position.

In practical operation, the acoustic signals influence that is interfered of the pump machine start and stop at oil and gas pipes two ends when work interference acoustic signals that produce power is higher, the obstruction reflection echo signal that sonic sensor collects has greatly increased the rate of false alarm of system.

Summary of the invention

At the problems referred to above, the invention provides a kind of adaptive frequency domain filter that utilizes and eliminate the method that the oil and gas pipes low frequency stops up interference acoustic signals in the echo signal.This method can increase the reliability of system, reduces rate of false alarm.

For achieving the above object, the present invention takes following technological scheme: a kind of frequency domain adaptive filtering is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, may further comprise the steps:

1) master reference is set in pipeline,, gathers acoustic signals simultaneously reference sensor being set near pump machine place;

2) to monitoring system input master reference and reference sensor acoustic signals;

3) its frequency domain spectra of low-frequency sound wave signal extraction to importing;

4) the signal frequency-domain spectrum is estimated setting threshold;

5) when frequency spectrum is higher than threshold value, starts sef-adapting filter and eliminate the strong jamming frequency spectrum;

6) utilize Fourier inversion, the time domain low frequency behind the high reject signal that is eliminated stops up echo signal.

In described step 3), the low frequency echo signal of frequency domain spectra extracting method stop up to(for) the oil and gas pipes that contains high reject signal is:

1. it is as follows to define oil and gas pipes obstruction echo signal model:

y(n)＝s(n)+c(n) (1)

Wherein, y (n) is the acoustic signals that master reference collects, and s (n) is that low frequency stops up echo signal, and c (n) is the high reject signal that pipeline start and stop pump power traction rises;

2. input signal y (n) being divided into length is the time window that contains M sampling point, to the sampling point of the M in each time window, extracts frequency domain spectra with Fourier transformation, if M is not 2 integral number power, to N, N is 2 integral number power, that is: with this M sampling point zero padding

$Y\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}y\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(2\right)$

K=1 wherein, 2 ..., N-1, y (n) expression master reference time-domain signal sequence, Y (k) is exactly the frequency domain spectra of current input signal, is also referred to as Fourier transform spectrum;

3. wushu (1) transforms to frequency domain spectra:

Y(k)＝S(k)+C(k) (3)

Wherein, Y (k) is a master reference signal frequency-domain spectrum, and S (k) is a frequency domain spectra of stopping up echo signal, and C (k) is the frequency domain spectra of high reject signal.

In step 5), utilize Adaptive Interference Cancelling Filter elimination strong jamming spectral method to be:

1. calculate the reference undesired signal frequency domain spectra that reference sensor is gathered:

$C_1\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{c}_1\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(4\right)$

2. as reference sensor frequency domain spectra C ₁When (k) being higher than threshold epsilon, according to pipeline field condition, C ₁(k) through the adjustable Interference Cancellation wave filter w (k) of parameter, the estimation of output undesired signal frequency domain spectra:

$\hat{C}\left(k\right)=C_1\left(k\right)w\left(k\right)---\left(5\right)$

Wherein w (k) is the Interference Cancellation wave filter;

3. from master reference signal frequency domain spectrum Y (k), deduct the interfering noise signal frequency domain spectra of estimating

Be exactly system output signal frequency domain spectra Z (k):

$Z\left(k\right)=Y\left(k\right)-\hat{C}\left(k\right)=Y\left(k\right)-C_1\left(k\right)w\left(k\right)---\left(6\right)$

Z (k) approaches the frequency domain spectra S (k) of target signal.

Wherein, the step of adjusting Interference Cancellation filter parameter is as follows:

1. initialization, selected Interference Cancellation wave filter initial weight: w (k);

2. calculate t constantly, the output of Interference Cancellation wave filter:

3. Interference Cancellation: $Z\left(k\right)=Y\left(k\right)-\hat{C}\left(k\right)=S\left(k\right)+C\left(k\right)-C_1\left(k\right)w\left(k\right);$

4. the Interference Cancellation filter parameter upgrades: w (k+1)=w (k)+2 μ Z (k) Y (k), and adaptive step parameter μ adjusts according to actual conditions, and the μ value is less than 1 usually;

5. enter next constantly: t=t+1, jump to step 2., repeat 2.～4. iteration;

6. the output Z of system (k) promptly is a frequency domain spectra of having eliminated the low frequency obstruction echo signal behind the high reject signal.

Method that time domain low frequency behind the high reject signal stops up echo signal is to utilize Fourier inversion to be eliminated:

$\hat{z}\left(n\right)=\underset{k=0}{\overset{N-1}{\mathrm{\Σ}}}\hat{Z}\left(k\right)\·e^{j\frac{2\mathrm{\π}}{N}k\·n}---\left(7\right)$

Promptly be to have eliminated the time domain low frequency behind the high reject signal to stop up echo signal.

The present invention is owing to take above technological scheme, and it has the following advantages: 1, system adopts master reference, reference sensor to gather signal.Reference sensor is mainly gathered the undesired signal that start and stop pump machine produces near the pump machine.Master reference is mainly gathered the line clogging reflection echo signal, and effect of signals also can be interfered.So when master reference signal conversion was frequency domain spectra, its frequency spectrum also comprised obstruction reflection echo signal and undesired signal.The present invention can eliminate the undesired signal that contains in the master reference discriminatively.2, system adopts the Interference Cancellation wave filter, and frequency domain spectra is adopted adaptive algorithm, and progressively iteration is upgraded, and the required data quantity stored of system is less, has greatly improved the reaction time of system.3, system construction is convenient, good reliability, and detection speed is fast, and to not influence of pipeline ordinary production operation, stopping state that can the on-line monitoring oil and gas pipes.

Description of drawings

Fig. 1 is a basic flow sheet of the present invention;

Fig. 2 adopts sef-adapting filter to eliminate the schematic representation of pipeline undesired signal.

Embodiment

Below in conjunction with drawings and Examples the present invention is described in detail.

As shown in Figure 1, the basic step of the inventive method is:

1) master reference is set in pipeline,, gathers acoustic signals simultaneously reference sensor being set near pump machine place;

2) acoustic signals of input master reference and reference sensor in the monitoring system;

3) system extracts its frequency domain spectra to the acoustic signals of input;

4) the signal frequency-domain spectrum is estimated setting threshold;

5) when frequency spectrum is higher than threshold value, starts sef-adapting filter and eliminate the interference sound wave spectrum;

6) utilize Fourier inversion, the time domain low frequency behind the high reject signal that is eliminated stops up echo signal.

In step 3), stop up echo signal and strong jamming acoustic signals owing to contain low frequency in the low-frequency sound wave signal of master reference input, so its frequency domain spectra extracting method is:

1. it is as follows to define oil and gas pipes obstruction echo signal model:

y(n)＝s(n)+c(n) (1)

Wherein, y (n) is the signal that master reference collects, and usually, the signal that collects comprises that low frequency stops up echo signal and disturbs acoustic signals; S (n) is a target signal, and promptly low frequency stops up echo signal; C (n) is the high reject signal that the normal start and stop pump of pipeline power traction rises.

2. master reference input signal y (n) being divided into length is the time window that contains M sampling point, to the sampling point of the M in each time window, extracts frequency domain spectra with Fourier transformation, if M is not 2 integral number power, to N, N is 2 integral number power, that is: with this M sampling point zero padding

$Y\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}y\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(2\right)$

K=1 wherein, 2 ..., N-1, y (n) expression master reference time-domain signal sequence, Y (k) is the frequency domain spectra that the master reference signal obtains by Fourier transformation.Frequency domain spectra Y (k) is analyzed, both can improve and screen low frequency obstruction echo signal, can reduce computational processing again.

3. wushu (1) transforms to frequency domain spectra:

Y(k)＝S(k)+C(k) (3)

Wherein, Y (k) is the frequency domain spectra of master reference acoustic signals; S (k) is the frequency domain spectra that master reference stops up echo signal; C (k) is the frequency domain spectra of master reference high reject signal.

In the step 5), because reference sensor is very near the pump machine, so the signal that reference sensor collects mainly is the high reject signal that start and stop pump machine produces.Calculate the reference undesired signal frequency domain spectra that reference sensor is gathered:

$C_1\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{c}_1\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(4\right)$

As reference sensor frequency domain spectra C ₁When (k) being higher than threshold epsilon, system utilizes frequency domain adaptive filtering that the high reject signal of start and stop pump machine is effectively suppressed.Utilize processing method that sef-adapting filter suppresses undesired signal referring to Fig. 2:

According to the pipeline field condition, reference sensor undesired signal frequency domain spectra C ₁(k) behind the adjustable Interference Cancellation wave filter w (k) of parameter, obtain the estimation of master reference undesired signal frequency domain spectra C (k)

$\hat{C}\left(k\right)=C_1\left(k\right)w\left(k\right)---\left(5\right)$

Wherein w (k) is the Interference Cancellation wave filter.Utilize adaptive algorithm to regulate the parameter of Interference Cancellation wave filter w (k), make the output signal frequency domain spectra

Approach master reference interfering noise signal frequency domain spectra C (k).

Then, from master reference signal frequency domain spectrum Y (k), deduct the interfering noise signal frequency domain spectra of estimating System output signal frequency domain spectra Z (k):

Because Interference Cancellation wave filter output frequency domain spectra

Approach the interfering noise signal frequency domain spectra C (k) of master reference signal superposition, i.e. C (k)-C ₁(k) w (k) levels off to 0, so the frequency domain spectra Z (k) of system's output will approach target signal frequency domain spectra S (k).

The parameter estimation algorithm of Interference Cancellation wave filter w (k) adopts Minimum Mean Square Error error criterion self adaption to estimate to obtain.The adaptive algorithm step is as follows:

1. initialization, selected Interference Cancellation wave filter initial weight: w (k);

2. calculate t constantly, the output of Interference Cancellation wave filter:

3. Interference Cancellation: $Z\left(k\right)=Y\left(k\right)-\hat{C}\left(k\right)=S\left(k\right)+C\left(k\right)-C_1\left(k\right)w\left(k\right);$

4. the Interference Cancellation filter parameter upgrades: w (k+1)=w (k)+2 μ Z (k) Y (k), and adaptive step parameter μ adjusts according to actual conditions, and the μ value is less than 1 usually.

5. enter next constantly: t=t+1, jump to step 2., repeat 2.～4. iteration;

6. the output Z of system (k) promptly is a frequency domain spectra of having eliminated the low frequency obstruction echo signal behind the high reject signal.

The time domain low frequency that utilizes the Fourier inversion algorithm to be eliminated behind the high reject signal stops up echo signal:

$\hat{z}\left(n\right)=\underset{k=0}{\overset{N-1}{\mathrm{\Σ}}}\hat{Z}\left(k\right)\·e^{j\frac{2\mathrm{\π}}{N}k\·n}---\left(7\right)$

Promptly be to have eliminated the time domain low frequency behind the high reject signal to stop up echo signal.

Claims (6)

1. a frequency domain adaptive filtering is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, may further comprise the steps:

1) master reference is set in pipeline,, gathers acoustic signals simultaneously reference sensor being set near pump machine place;

2) to monitoring system input master reference and reference sensor acoustic signals;

3) its frequency domain spectra of low-frequency sound wave signal extraction to importing;

4) the signal frequency-domain spectrum is estimated setting threshold;

5) when frequency spectrum is higher than threshold value, starts sef-adapting filter and eliminate the strong jamming frequency spectrum;

6) utilize Fourier inversion, the time domain low frequency behind the high reject signal that is eliminated stops up echo signal.

2. a kind of frequency domain adaptive filtering as claimed in claim 1 is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, in described step 3), the low frequency echo signal of frequency domain spectra extracting method stop up to(for) the oil and gas pipes that contains high reject signal is:

1. it is as follows to define oil and gas pipes obstruction echo signal model:

y(n)＝s(n)+c(n) (1)

Wherein, y (n) is the acoustic signals that master reference collects, and s (n) is that low frequency stops up echo signal, and c (n) is the high reject signal that pipeline start and stop pump power traction rises;

2. input signal y (n) being divided into length is the time window that contains M sampling point, to the sampling point of the M in each time window, extracts frequency domain spectra with Fourier transformation, if M is not 2 integral number power, to N, N is 2 integral number power, that is: with this M sampling point zero padding

$Y\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}y\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(2\right)$

K=1 wherein, 2 ..., N-1, y (n) expression master reference time-domain signal sequence, Y (k) is exactly the frequency domain spectra of current input signal, is also referred to as Fourier transform spectrum;

3. wushu (1) transforms to frequency domain spectra:

Y(k)＝S(k)+C(k) (3)

Wherein, Y (k) is a master reference signal frequency-domain spectrum, and S (k) is a frequency domain spectra of stopping up echo signal, and C (k) is the frequency domain spectra of high reject signal.

3. a kind of frequency domain adaptive filtering as claimed in claim 1 or 2 is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, in described step 5), Adaptive Interference Cancelling Filter is eliminated the strong jamming spectral method and is:

1. calculate the reference undesired signal frequency domain spectra that reference sensor is gathered:

$C_1\left(k\right)=\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}{c}_1\left(n\right)\·e^{-j\frac{2\mathrm{\π}}{N}\mathrm{kn}}---\left(4\right)$

2. as reference sensor frequency domain spectra C1 (k) when being higher than threshold epsilon, according to pipeline field condition, C ₁(k) through the adjustable Interference Cancellation wave filter w (k) of parameter, the estimation of output undesired signal frequency domain spectra:

$\hat{C}\left(k\right)=C_1\left(k\right)w\left(k\right)---\left(5\right)$

Wherein w (k) is the Interference Cancellation wave filter;

3. from master reference signal frequency domain spectrum Y (k), deduct the interfering noise signal frequency domain spectra of estimating

Be exactly system output signal frequency domain spectra Z (k):

$Z\left(k\right)=Y\left(k\right)-\hat{C}\left(k\right)=Y\left(k\right)-C_1\left(k\right)w\left(k\right)---\left(6\right)$

Z (k) approaches the frequency domain spectra S (k) of target signal.

4. a kind of frequency domain adaptive filtering as claimed in claim 3 is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, the step of regulating the Interference Cancellation filter parameter is as follows:

1. initialization, selected Interference Cancellation wave filter initial weight: w (k);

2. calculate t constantly, the output of Interference Cancellation wave filter:

3. Interference Cancellation: $Z\left(k\right)=Y\left(k\right)-\hat{C}\left(k\right)=S\left(k\right)+C\left(k\right)-C_1\left(k\right)w\left(k\right);$

4. the Interference Cancellation filter parameter upgrades: w (k+1)=w (k)+2 μ Z (k) Y (k), and adaptive step parameter μ adjusts according to actual conditions, and the μ value is less than 1 usually.

5. enter next constantly: t=t+1, jump to step 2., repeat 2.～4. iteration;

6. the output Z of system (k) promptly is a frequency domain spectra of having eliminated the low frequency obstruction echo signal behind the high reject signal.

5. eliminate the strongly disturbing method of line clogging acoustic signals as claim 1 or 2 or 4 described a kind of frequency domain adaptive filterings, it is characterized in that, method that the time domain low frequency behind the high reject signal stops up echo signal is to utilize Fourier inversion to be eliminated:

$\hat{z}\left(n\right)=\underset{k=0}{\overset{N-1}{\mathrm{\Σ}}}\hat{Z}\left(k\right)\·e^{j\frac{2\mathrm{\π}}{N}k\·n}---\left(7\right)$

Promptly be to have eliminated the time domain low frequency behind the high reject signal to stop up echo signal.

6. a kind of frequency domain adaptive filtering as claimed in claim 3 is eliminated the strongly disturbing method of line clogging acoustic signal, it is characterized in that, method that the time domain low frequency behind the high reject signal stops up echo signal is to utilize Fourier inversion to be eliminated:

$\hat{z}\left(n\right)=\underset{k=0}{\overset{N-1}{\mathrm{\Σ}}}\hat{Z}\left(k\right)\·e^{j\frac{2\mathrm{\π}}{N}k\·n}---\left(7\right)$

Promptly be to have eliminated the time domain low frequency behind the high reject signal to stop up echo signal.

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