CN103363880A - Pipeline girth weld joint identification and positioning method - Google Patents

Abstract

The invention discloses a method for identifying and positioning a pipeline girth weld, which is characterized in that an upper computer calculates a position sequence { s } of each weld_bAnd acquiring a weld position normalization sequence_c}; acquiring a magnetic field wavelet sequence, an acceleration wavelet sequence and a sound wavelet sequence; down-sampling the acceleration wavelet sequence and the sound wavelet sequence, and calculating a total wavelet sequence; calculating the average sampling point number E between two welding lines and the cut-off frequency of a low-pass filter; passing the total wavelet series with a cut-off frequency of f_bsFiltering by a beta-order low-pass filter to obtain a smooth wavelet sequence, and taking the moment when the peak value appears as the moment when the welding seam appears; and arranging all the weld moments in sequence to obtain a weld positioning moment sequence, and performing normalization processing to obtain a normalized weld positioning moment sequence. The method improves the identification rate and the positioning precision of the pipeline circumferential weld, reduces the power consumption and the positioning cost, and enlarges the range in practical application.

Description

A kind of pipeline girth weld recognition positioning method

Technical field

The present invention relates to the pipe signal process field, particularly a kind of pipeline girth weld recognition positioning method.

Background technology

In-pipeline detector can detect defect of pipeline and defective is positioned under the state of conduit running, have vital role to guaranteeing the pipe safety operation.Because the same pipeline of defect of pipeline (internal detector) position that in-pipeline detector is measured is corresponding one by one, must accurately know each constantly position of in-pipeline detector.In-pipeline detector localization method commonly used such as mileage wheel method and inertial navigation method etc., all needs the land mark device to carry out auxiliary positioning to eliminate cumulative errors at present, uses inconvenience.

Because the surface configuration at pipeline girth weld place and the singularity of inner crystal phase structure, there is a great difference in all the other positions of acoustic impedance and electromagnetic resistivity and pipeline, can adopt in theory eddy current, the active non-destructive detecting device such as ultrasonic to identify and tack weld.But these two kinds of active methods all need exciting bank, and power dissipation ratio is larger, usually need to the tube wall special compounding, structure is more complicated also, it is very inconvenient to use.In addition, for gas or product oil conveying pipe, also can consider to use optical sensor to detect weld seam, but price comparison is expensive, and the transparency of oil product is had very high requirement, very impracticable.

The simple pipeline internal magnetic field that relies on removes to identify weld seam, and discrimination is limited, needs to adopt new method reduction wrong identification and omit the probability of identification.

Summary of the invention

The invention provides a kind of pipeline girth weld recognition positioning method, the present invention does not need exciting bank, has reduced power consumption and location cost, has enlarged range of application, sees for details hereinafter and describes:

A kind of pipeline girth weld recognition positioning method said method comprising the steps of:

Three-component Magnetic Sensor, three-component accelerometer, sound transducer are fixed on the optional position in the in-pipeline detector, obtain ducted internal magnetic field signal, acceleration signal and voice signal, and 3 kinds of signals are transferred to host computer;

Described host computer calculates the position sequence { s that each weld seam occurs _b, and obtain position while welding normalization sequence { s _c;

Obtain magnetic field wavelet sequence { DB _j, acceleration wavelet sequence { DA _jAnd sound wavelet sequence { DV _j;

To described acceleration wavelet sequence { DA _jAnd described sound wavelet sequence { DV _jCarry out down-sampledly, and calculate total wavelet sequence { D _k;

Calculate the count cutoff frequency of E and low-pass filter of average sample between two weld seams;

With total wavelet sequence { D _kBe f by cutoff frequency _BsThe low-pass filter filtering of β rank, obtain level and smooth wavelet sequence, the moment that the moment that peak value is occurred occurs as weld seam;

The moment that all weld seams are occurred arranges sequentially and obtains constantly sequence of weld seam location, and obtains constantly sequence of normalization weld seam location as normalized.

Described host computer calculates the position sequence { s that each weld seam occurs _b, and obtain position while welding normalization sequence { s _cStep be specially:

1) in construction information, reads welding seam No and every pipe joint road length, get every pipe joint road length sequences;

2) calculate the position { s that each weld seam occurs _a, replenish s ₀=0 to { s _aMust position while welding sequence { s _b| b=0,1,2 ..., A}, A are the pipeline number;

3) with position while welding sequence { s _bIn each element position s appears divided by last weld seam _A, get position while welding normalization sequence { s _c| c=0,1,2 ..., A}.

The described magnetic field wavelet sequence { DB that obtains _jStep be specially:

Calculate every bit magnetic field total amount sequence

B wherein _Jx, B _Jy, B _JzThe magnetic field three-component of the every bit of measuring for Magnetic Sensor;

To magnetic field total amount sequence { B _jCarry out M layer continuous wavelet transform, get every layer of magnetic field coefficient of wavelet decomposition { CB _Ij;

Wherein

Be the small echo of the magnetic field B of j position of i layer, Be used female small echo, τ is the independent variable of small echo;

Magnetic field coefficient of wavelet decomposition { CB to different layers _IjDo following computing, get magnetic field wavelet sequence { DB _j}:

${\mathrm{DB}}_j=\sqrt{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}}{C}_{\mathrm{Bij}.}^2$

Described to described acceleration wavelet sequence { DA _jAnd described sound wavelet sequence { DV _jCarry out down-sampledly, and calculate total wavelet sequence { D _jStep be specially:

NB represents the field pulses element number; NV represents the sound sequence element number; NA represents the element number of acceleration total amount sequence; The down-sampled coefficient of sonic transducer and acceleration transducer is respectively:

N _S=NV/NB，Na=NA/NB

Voice signal after down-sampled and the wavelet sequence of acceleration signal are respectively:

DV _k=DV _j|j=k*Ns,k=1,2,3,...,NV/Ns

DA _k=DA _j|j=k*Na,k=1,2,3,...,NA/Na

DB _k=DB _j|j=k,k=1,2,3,...,NB；

Total wavelet sequence is:

$D_k=\sqrt{{{\mathrm{DB}}_k}^2+{{\mathrm{DA}}_k}^2+{{\mathrm{DV}}_k}^2}$

The count step of cutoff frequency of E and low-pass filter of average sample between two weld seams of described calculating is specially:

$E=\frac{f\·l}{v}$

$l=\frac{1}{A}\underset{i=1}{\overset{A}{\mathrm{\Σ}}}{l}_i$

Wherein, l is the average length of pipeline; V is the average pace of internal detector; The cutoff frequency of low-pass filter is: f _Bs=pf/E, f are the sample frequency of Magnetic Sensor, and p is setting value.

The beneficial effect of technical scheme provided by the invention is: process by pipeline internal magnetic field signal, acceleration signal and voice signal being carried out data, select suitable small echo to carry out continuous wavelet transform, girth joint place magnetic field breakpoint, sound breakpoint, acceleration breakpoint are strengthened and adopt the method butt welded seam place jump signal of low-pass filtering to identify and locate, thereby improve discrimination and bearing accuracy to pipeline girth weld, reduce power consumption and location cost, enlarged the scope in the practical application.

Description of drawings

Fig. 1 is a kind of process flow diagram of pipeline girth weld recognition positioning method;

Fig. 2 is magnetic signal actual measured value and wavelet sequence;

Fig. 3 is the acceleration signal wavelet sequence after down-sampled;

Fig. 4 is the voice signal wavelet sequence after down-sampled;

Fig. 5 is total wavelet sequence.

Embodiment

For making the purpose, technical solutions and advantages of the present invention clearer, embodiment of the present invention is described further in detail below in conjunction with accompanying drawing.

In order to reduce power consumption and location cost, enlarge range of application, the embodiment of the invention provides a kind of pipeline girth weld recognition positioning method, referring to Fig. 1, sees for details hereinafter and describes:

101: sensor is fixed on optional position in the in-pipeline detector, obtains ducted signal, and signal is transferred to host computer;

Being operating as in detail of this step: three-component Magnetic Sensor, three-component accelerometer, sound transducer are fixed on the optional position in the in-pipeline detector, internal detector is thrown pipe patrols and examines, measuring channel internal magnetic field signal, acceleration signal and voice signal, patrol and examine complete, the above-mentioned signal of internal detector record is downloaded to host computer, carry out data and process.

Wherein, the embodiment of the invention does not limit sensor (being three-component Magnetic Sensor, three-component accelerometer, sound transducer) and the model of in-pipeline detector, as long as the device that can finish above-mentioned functions all can, such as: in-pipeline detector can be cylindricality internal detector or spherical internal detector etc.

102: host computer calculates the position sequence { s that each weld seam occurs _b, and obtain position while welding normalization sequence { s _c;

Being operating as in detail of this step:

1) in construction information, reads welding seam No and every pipe joint road length, get every pipe joint road length sequences { l _i| i=1,2 ..., A}, A are the pipeline number;

2) calculate the position that each weld seam occurs

Replenish s ₀=0 to { s _aMust position while welding sequence { s _b| b=0,1,2 ..., A}, A are the pipeline number;

3) with position while welding sequence { s _bIn each element position s appears divided by last weld seam _A, get position while welding normalization sequence { s _c| c=0,1,2 ..., A}.

103: calculate every bit magnetic field total amount sequence { B _jAnd carry out M layer continuous wavelet transform, every layer of magnetic field coefficient of wavelet decomposition { CB obtained _Ij, to every layer of magnetic field coefficient of wavelet decomposition squared do and, get magnetic field wavelet sequence { DB _j;

Being operating as in detail of this step:

Calculate every bit magnetic field total amount sequence

B wherein _Jx, B _Jy, B _JzThe magnetic field three-component of the every bit of measuring for Magnetic Sensor.

To magnetic field total amount sequence { B _jCarry out M layer continuous wavelet transform, and be about to the Wavelet-Weighted sum that field signal is decomposed into different zoom coefficient and different translation coefficients, get every layer of magnetic field coefficient of wavelet decomposition { CB _Ij, the small echo of the corresponding different layers of the small echo of different zoom coefficient and different translation coefficients and diverse location.

Wherein

Be the small echo of the magnetic field B of j position of i layer,

Be used female small echo, τ is the independent variable of small echo.

Magnetic field coefficient of wavelet decomposition { CB to different layers _IjDo following computing, get magnetic field wavelet sequence { DB _j}:

${\mathrm{DB}}_j=\sqrt{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}}{\mathrm{CB}}_{\mathrm{ij}}^2$

104: in like manner adopt the method in the step 103 to obtain acceleration wavelet sequence { DA _jAnd sound wavelet sequence { DV _j;

That is, calculate every bit acceleration total amount sequence

A wherein _Jx, A _Jy, A _JzAcceleration three-component for every bit.To acceleration total amount sequence { A _jCarry out continuous wavelet transform:

Wherein Small echo for j position acceleration A of acceleration total flow control i layer; Acceleration coefficient of wavelet decomposition { CA to different layers _IjDo following computing, get acceleration wavelet sequence { DA _j}:

${\mathrm{DA}}_j=\sqrt{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}}{\mathrm{CA}}_{\mathrm{ij}}^2$

With the voice signal that gets access in the step 101 as sound total amount sequence { V _j, to sound total amount sequence { V _jCarry out continuous wavelet transform:

Wherein

Small echo for sound total flow control i layer j position sound V; Sound coefficient of wavelet decomposition { CV to different layers _IjDo following computing, get sound wavelet sequence { DV _j}:

${\mathrm{DV}}_j=\sqrt{\underset{i=1}{\overset{M}{\mathrm{\Σ}}}}{\mathrm{CV}}_{\mathrm{iy}}^2$

Wherein, when finding the solution the magnetic field wavelet sequence,

Be the used female small echo in magnetic field, τ is the independent variable of magnetic field small echo; Accordingly when finding the solution the acceleration wavelet sequence,

Be the used female small echo of acceleration, τ is the independent variable of acceleration small echo; Or, when finding the solution the sound wavelet sequence,

Be the used female small echo of sound, τ is the independent variable of sound small echo.

105: to acceleration wavelet sequence { DA _jAnd sound wavelet sequence { DV _jCarry out down-sampledly, and calculate total wavelet sequence { D _j;

NB represents the field pulses element number, i.e. { the maximal value of j in the Bj} sequence; NV represents the sound sequence element number, i.e. { the maximal value of j in the Vj} sequence; NA represents the element number of acceleration total amount sequence, i.e. { the maximal value of j in the Aj} sequence.Then the down-sampled coefficient of sonic transducer and acceleration transducer is respectively:

N _S=NV/NB，Na=NA/NB

Voice signal after then down-sampled and the wavelet sequence of acceleration signal are respectively:

DV _k=DV _j|j=k*Ns,k=1,2,3,...,NV/Ns

DA _k=DA _j|j=k*Na,k=1,2,3,...,NA/Na

And calculate and expression for convenient, with DB _jSequence is carried out such as down conversion:

DB _k=DB _j|j=k,k=1,2,3,...,NB。

Can learn that by above-mentioned calculating the value of k in three sequences all is NB,

Then total wavelet sequence is:

$D_k=\sqrt{{{\mathrm{DB}}_k}^2+{{\mathrm{DA}}_k}^2+{{\mathrm{DV}}_k}^2}$

106: calculate the count cutoff frequency of E and Butterworth Butterworth LPF of average sample between two weld seams;

$E=\frac{f\·l}{v}$

$l=\frac{1}{A}\underset{i=1}{\overset{A}{\mathrm{\Σ}}}{l}_i$

Wherein, l is the average length of pipeline, i.e. mean distance l between every adjacent two weld seams; V is the average pace of internal detector.

The cutoff frequency of getting the Butterworth low-pass filter is: f _Bs=pf/E, wherein f is the sample frequency of Magnetic Sensor, p is desirable 0.5, can be according to the actual conditions adjustment.

107: with total wavelet sequence { D _jBe f by cutoff frequency _BsThe Butterworth low-pass filter filtering of β rank, obtain relatively level and smooth wavelet sequence, it is carried out peak value detects, the moment that peak value is occurred has namely been identified weld seam as the moment that weld seam occurs;

Wherein, the value of β can get 4, can also adjust according to the situation in the practical application, but in order to get access to preferably filter effect, the value of β is preferably 4 to 8, surpasses 8 filter effects not obvious.

108: the moment that all weld seams are occurred arranges sequentially and obtains constantly sequence of weld seam location, and obtains constantly sequence of normalization weld seam location as normalized.

The below verifies the feasibility of a kind of pipeline girth weld recognition positioning method that the embodiment of the invention provides with concrete test, see for details hereinafter to describe:

Adopt method of the prior art can obtain the result of Fig. 2, as can be seen from the figure magnetic signal can be told the weld seam of some, but has undetected situation.If calculate in conjunction with the voice signal wavelet sequence after down-sampled among the acceleration signal wavelet sequence after down-sampled among Fig. 3 and Fig. 4, can obtain wavelet sequence total among Fig. 5.Can tell all weld seams by Fig. 5.Than only relying on magnetic signal to detect, the method has reduced undetected situation, has improved the weld seam recognition rate.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the invention described above embodiment sequence number does not represent the quality of embodiment just to description.

The above only is preferred embodiment of the present invention, and is in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of doing, is equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (5)

1. a pipeline girth weld recognition positioning method is characterized in that, said method comprising the steps of:

Three-component Magnetic Sensor, three-component accelerometer, sound transducer are fixed on the optional position in the in-pipeline detector, obtain ducted internal magnetic field signal, acceleration signal and voice signal, and 3 kinds of signals are transferred to host computer;

Described host computer calculates the position sequence { s that each weld seam occurs _b, and obtain position while welding normalization sequence { s _c;

Obtain magnetic field wavelet sequence { DB _j, acceleration wavelet sequence { DA _jAnd sound wavelet sequence { DV _j;

To described acceleration wavelet sequence { DA _jAnd described sound wavelet sequence { DV _jCarry out down-sampledly, and calculate total wavelet sequence { D _k;

Calculate the count cutoff frequency of E and low-pass filter of average sample between two weld seams;

With total wavelet sequence { D _kBe f by cutoff frequency _BsThe low-pass filter filtering of β rank, obtain level and smooth wavelet sequence, the moment that the moment that peak value is occurred occurs as weld seam;

The moment that all weld seams are occurred arranges sequentially and obtains constantly sequence of weld seam location, and obtains constantly sequence of normalization weld seam location as normalized.

2. a kind of pipeline girth weld recognition positioning method according to claim 1 is characterized in that, described host computer calculates the position sequence { s that each weld seam occurs _b, and obtain position while welding normalization sequence { s _cStep be specially:

1) in construction information, reads welding seam No and every pipe joint road length, get every pipe joint road length sequences;

2) calculate the position { s that each weld seam occurs _a, replenish s ₀=0 to { s _aMust position while welding sequence { s _b| b=0,1,2 ..., A}, A are the pipeline number;

3) with position while welding sequence { s _bIn each element position s appears divided by last weld seam _A, get position while welding normalization sequence { s _c| c=0,1,2 ..., A}.

3. a kind of pipeline girth weld recognition positioning method according to claim 1 is characterized in that, the described magnetic field wavelet sequence { DB that obtains _jStep be specially:

Calculate every bit magnetic field total amount sequence

B wherein _Jx, B _Jy, B _JzThe magnetic field three-component of the every bit of measuring for Magnetic Sensor;

To magnetic field total amount sequence { B _jCarry out M layer continuous wavelet transform, get every layer of magnetic field coefficient of wavelet decomposition { CB _Ij;

Wherein Be the small echo of the magnetic field B of j position of i layer,

Be used female small echo, τ is the independent variable of small echo;

Magnetic field coefficient of wavelet decomposition { CB to different layers _IjDo following computing, get magnetic field wavelet sequence { DB _j}:

4. a kind of pipeline girth weld recognition positioning method according to claim 1 is characterized in that, and is described to described acceleration wavelet sequence { DA _jAnd described sound wavelet sequence { DV _jCarry out down-sampledly, and calculate total wavelet sequence { D _kStep be specially:

NB represents the field pulses element number; NV represents the sound sequence element number; NA represents the element number of acceleration total amount sequence; The down-sampled coefficient of sonic transducer and acceleration transducer is respectively:

N _S=NV/NB，Na=NA/NB

Voice signal after down-sampled and the wavelet sequence of acceleration signal are respectively:

DV _k=DV _j|j=k*Ns,k=1,2,3,...,NV/Ns

DA _k=DA _j|j=k*Na,k=1,2,3,...,NA/Na

DB _k=DB _j|j=k,k=1,2,3,...,NB；

Total wavelet sequence is:

。

5. a kind of pipeline girth weld recognition positioning method according to claim 1 is characterized in that, the count step of cutoff frequency of E and low-pass filter of the average sample between two weld seams of described calculating is specially:

Wherein, l is the average length of pipeline; V is the average pace of internal detector; The cutoff frequency of low-pass filter is: f _Bs=pf/E, f are the sample frequency of Magnetic Sensor, and p is setting value.

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