CN109975397A - Heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal - Google Patents
Heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal Download PDFInfo
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Abstract
The invention belongs to eddy detection technology field, specially a kind of heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal.Acquisition multifrequency Eddy signal data matrix, which determines, to be offseted channel and offsets channel, pairs of reality, imaginary signals of the above-mentioned channel in detection zone are extracted later, it offsets to obtain four corresponding phasors parallel, the similar processing of two dimension is carried out to two of them, similar processing result sR and sI, which educates figure with Li Sa, to be indicated.Based on+frequency mixing method as two-dimensional phase is offseted parallel, the defect information of extraction is better than conventional mixer method on the fidelity of amplitude and phase, improves the accuracy of depth of defect and height detecting；Detection range can be expanded with the method detecting defects signal, simplify signal scaling step, reduce artificial manual operations, be conducive to realize automatic signal detection.
Description
Technical field
The invention belongs to eddy detection technology fields, and in particular to a kind of heat-transfer pipe damage letter based on multifrequency Eddy signal
Cease extracting method.
Background technique
The heat-transfer pipe of evaporator of nuclear power station is usually made of the identical pipe of dozens or even hundreds of material specification, in pipe
Portion's liquid medium flow and external vibration generate abrasion and corrosion to support plate and heat transfer pipe outer wall contact site.Traditional is single
The forceful electric power magnetic signal that the induction of frequency EDDY CURRENT support plate generates has flooded response signal caused by the position defect.
Supporting clapboard interference signal can be eliminated using multifrequency eddy current testing method at present.But since this method changes
The real imaginary part ratio of defect or abrasion, two dimension eddy current signal derived from institute lead to the depth of defect or abrasion there are severely deformed
There is very big error in degree and width measurement, need constantly to be demarcated by calibrating tube measurement data, work computationally intensive, automatically
Process performance is poor, and error is big.
Summary of the invention
The object of the present invention is to provide a kind of heat-transfer pipe damage information high-fidelity extraction side based on multifrequency Eddy complex signal
Method, can Accurate Determining heat-transfer pipe damage information, error is small, high reliablity.
Technical scheme is as follows:
A kind of heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal, this method include following step
It is rapid:
1) multifrequency Eddy signal data matrix X is obtained
Multifrequency differential path signal and absolute channel signal are assigned to X with a matrix type, and the detection frequency of signal is by height
To low, four are classified as one group, and every group of frequency is identical, and there are two channels, i.e. differential path and absolute channel, and each channel is divided into reality
Portion and imaginary part two arrange, and for the X matrix by row from top to bottom according to time sampling, every row time point is identical；
2) it determines and is offseted channel and offset channel；
When defect is located at detection pipes road surface, high frequency differential path is selected to be offseted channel, low frequency differential path is pair
Disappear channel；
Defect is located among pipeline, then intermediate frequency differential path may be selected as channel is offseted, high and low frequency difference is logical
Road is used as reference to offset channel；
Defect is located at pipeline inner layer, selects low frequency differential path as channel, high frequency differential path is offseted and is used as to right
Disappear reference channel；
3) pairs of reality, imaginary signals of the above-mentioned channel in detection zone are extracted from matrix X；
4) channel and two reference channel complex signals are detected and implement to offset to obtain parallel four corresponding phasor F1 (:, 1), F1
(:,2),F2(:,1),F2(:,2)；
5) F1 (:, 1:2) and F2 (:, 1:2) are subjected to the similar processing of two dimension respectively, are as a result denoted as sR and sI；
6) similar processing result sR and sI is educated figure with Li Sa indicates.
The step 4) is by the real part CC of detected differential path signal CC (:, 1) and imaginary part CC (:, 2) respectively with two
The real and imaginary parts of a K1 for offseting differential path and K2 carry out offseting processing, obtain corresponding four vector F1 (:, 1), F1
(:,2)、F2(:,1)、F2(:,2)。
The method that offsets is specially
If being offseted signal and offseting signal is respectively C and F；
3.1) adaptive neural network net is constructed；
3.1.1 initial network structure net=network (1,2, [1) is defined；1],[1；0],[00；10], [01]),
Network function is defined as MatlabR2009b library file；
3.1.2) using formula d (i, j)=| w (i, 1)-p (1, j) | define equal length column vector w and row vector p it
Between distance matrix d=distm (w, p), calculate d=distm (F', F), wherein F ' be F transposition；
3.1.3) utilize formulaDetermine network transmission function
3.1.4 the weight w 2 and partially of neural network hidden layer weight w 1 and deviation b1 and output layer) is determined using following formula
Poor b2；
Hidden layer weight w 1=F'；
Hidden layer deviationN is detection zone length；
Intermediate variable X=C/ [A；11×n]；
Output layer weight w 2=X (:, 1:n)；
Output layer deviation b2=X (:, n+1)；
3.1.5 above-mentioned weight and deviation) are assigned to neural network；
3.2) it to network net and F the input function sim after assignment, obtains width output signal Out, sim function and is defined as
MatlabR2009b library file；
3.3) C and Out is subtracted each other, obtains in eddy current signal C and offsets signal Flaw.
The step 5) carried out in terms of real vector sum void vector two respectively two Li Sha educate figure between distance thresholding
Differentiate, realizes that two two dimension Lee Sa Yu scheme similar processing.
The high frequency refers to that 170kHz, low frequency refer to that 50kHz and 25kHz, intermediate frequency refer to 100kHz.
Remarkable result of the invention is as follows: in the method for multifrequency Eddy complex signal mixing, based on offseting+two-dimensional phase parallel
As frequency mixing method, the defect information of extraction on the fidelity of amplitude and phase be better than conventional mixer method, improve defect depth
The accuracy of degree and height detecting；Detection range can be expanded with the method detecting defects signal, simplify signal scaling step,
Artificial manual operations is reduced, is conducive to realize automatic signal detection.
Wherein, step 4) is that detected channel and the implementation of two reference channel complex signals offset parallel.Eddy current signal is to include
The complex signal of phase (associated with depth of defect), therefore, the offseting to offset including real part of this signal are offseted with imaginary part, are wrapped
It includes the zero-mean of early period and noise suppression preprocessing and processing is offseted based on nerual network technique.Zero-mean processing does not change Lee's Sa
Educate the phase angle of flaw indication in figure；Denoising uses wden wavelet compression function, and (bearing length is symmetrically small for 8 Daubechies
Wave, three layers of decomposition, fixed hard -threshold)；Neural network, which is offseted, realizes output using newrbe function and sim function, then uses
Echo signal subtracts output realization and offsets.
Step 5) is differentiated by one-dimensional signal component distance thresholdization, realizes that two two dimension Lee Sa Yu scheme similar processing.In
Li Sa, which educates the point in figure, to be determined by real vector sum void vector, can carry out two respectively in terms of real vector sum void vector two
The thresholding of distance differentiates between Li Shayu figure, realizes that two two dimension Lee Sa Yu scheme similar processing.Here it is the real imaginary parts of step 5)
Distance threshold method realizes the reason of Li Sha educates figure two dimension similar processing.
The method is applied to eddy current testing signal analysis field, effectively to extract heat-transfer pipe actual change, promoting automatic place
Rationality can provide reference.
Detailed description of the invention
Fig. 1 is that this method implements main flow chart；
Fig. 2 is the flow chart that function realization is individually offseted in this method；
Fig. 3 is that each channel data Matrix Pattern that certain nuclear power plant's Eddy current detector obtains is shown；
Fig. 4 is the real and imaginary parts for 4 differential paths that frequency is 170kHz, 100kHz, 50kHz and 25kHz 4500
Signal between to 7500；
Fig. 5 is the flaw indication as standard；
Fig. 6 is defect detection effect of the frequency mixing method that proposes of conventional mixer method and this patent when there is an architecture signals
Fruit；
Fig. 7 is defect detection effect of the frequency mixing method that proposes of conventional mixer method and this patent when there are two architecture signals
Fruit；
Fig. 8 is defect detection effect of the frequency mixing method that proposes of conventional mixer method and this patent in no architecture signals.
Specific embodiment
Below by the drawings and the specific embodiments, the invention will be further described.
As shown in Figure 1, this method is as follows the step of implementation:
Step 1) downloads multifrequency Eddy signal data file to be processed, is indicated with matrix X.
Include multifrequency differential path signal and absolute channel signal in data file, it is assigned to X with a matrix type.
Matrix X stores the multifrequency differential path signal and absolute channel signal measured by Eddy current detector in column form,
(absolute channel signal can not be considered when emulation), from high to low, four are classified as one group to the detection frequency of use, and every group of frequency is identical,
And there are two channel, i.e. differential path and absolute channel, each channel is divided into the column of real and imaginary parts two, and defect information passes through by difference
The Li Shayu figure amplitude and phase that subchannel real and imaginary parts determine determine.Matrix by rows is from top to bottom according to time sampling, every row
Time point is identical.
Some loads the multifrequency difference that Eddy current detector measures and absolute channel signal data file is
DCR007C025I136.txt can be downloaded data file with load (' DCR007C025I136.txt '), then with tax
Data are assigned to X by value sentence X=DCR007C025I136 with a matrix type, thus can be under Matlab software environment
Carry out data processing.
Step 2) is according to defects detection task, and determination is offseted differential path (Checkchannel) and two offset difference
Channel (k1 and k2) and detected region Checkregion.
When defect is located at detection pipes road surface, usual hf channel just contains the information, at this moment selects high frequency difference logical
Road is to be offseted channel, and low frequency differential path is to offset channel；Defect is located among pipeline, then intermediate frequency differential path may be selected and make
To be offseted channel, high and low frequency differential path is used as reference to offset channel；Defect is located at pipeline inner layer, selects low frequency difference
As being offseted channel, high frequency differential path is used as to offseting reference channel in channel.
Step 3) extracts pairs of reality, imaginary signals of the above-mentioned channel in detection zone from matrix X.
Illustrate according to data file, according to the parameter that Detection task determines, can therefrom extract each channel signal data.
For example, data file DCR007C025I136.txt illustrates table 1:
Certain the Eddy current detector detection data information format of table 1
If extract the 2nd differential path real part information, table look-up it is found that the data be located at matrix the 5th column, R=X can be enabled
(:,5)。
In Matlab software, differential path signal CC can be offseted with the realization of following sentence and two offset differential path
Signal K1, K2:
CC=X (Checkregion, 2*Checkchannel-1:2*Checkchannel)；
K1=X (Checkregion, 2*k1-1:2*k1)；
K2=X (Checkregion, 2*k2-1:2*k2)；
Above-mentioned matrix first is classified as signal real part, and second is classified as imaginary part.
Step 4) signal parallel offsets.
It is logical that the real part CC of detected differential path signal CC (:, 1) and imaginary part CC (:, 2) are offseted into difference with two respectively
The real and imaginary parts of the K1 and K2 in road carry out offseting processing, obtain corresponding four vector F1 (:, 1), F1 (:, 2), F2 (:, 1),
F2(:,2)。
It is detected channel and the implementation of two reference channel complex signals offsets parallel.This offset offsets and imaginary part pair including real part
Disappear.The method of offseting is specially
If being offseted signal and offseting signal is respectively C and F；
First, in accordance with step a)~e) construction adaptive neural network net；
A) initial network structure net=network (1,2, [1 is defined；1],[1；0],[00；10], [01]), network
Function is defined as MatlabR2009b library file；
B) using formula d (i, j)=| w (i, 1)-p (1, j) | define equal length column vector w and row vector p between
Distance matrix d=distm (w, p) is calculated d=distm (F', F), wherein F ' is the transposition of F；
C) formula is utilizedDetermine network transmission function
D) weight w 2 and deviation of neural network hidden layer weight w 1 and deviation b1 and output layer are determined using following formula
b2；
Hidden layer weight w 1=F'；
Hidden layer deviationN is detection zone length；
Intermediate variable X=C/ [A；11×n]；
Output layer weight w 2=X (:, 1:n)；
Output layer deviation b2=X (:, n+1)；
E) above-mentioned weight and deviation are assigned to neural network；
Then it to network net and F the input function sim after assignment, obtains width output signal Out, sim function and is defined as
MatlabR2009b library file；
Finally C and Out are subtracted each other, obtains in eddy current signal C and offsets signal Flaw.
F1 (:, 1:2) and F2 (:, 1:2) are carried out the similar processing of two dimension respectively by step 5).
Define d1=max (F1 (:, 1))-min (F1 (:, 1)), d2=max (F1 (:, 2))-min (F1 (:, 2)), α is set1
And α2Respectively real and imaginary parts threshold coefficient, if | F2 (i, 1)-F1 (i, 1) |≤α1d1, and | F2 (i, 2)-F1 (i, 2) |≤α2d2Otherwise sR (i)=sI (i)=0 then sR (i)=F1 (i, 1), sI (i)=F1 (i, 2).Processing result remembers it with sR and sI.
Four vector F1 (:, 1), F1 (:, 2), F2 (:, 1), F2 (:, 2) can draw two Lee Sa Yu figure F1 (:, 1:2)
With F2 (:, 1:2).Defect information position position in data sequence is almost the same in two Lee's Sa Yu figures, and the amplitude of corresponding points
It is not much different.It two Li Sha is carried out in terms of real vector sum void vector two respectively educates the thresholding of distance between figure differentiating, realize two
A two dimension Lee Sa Yu schemes similar processing.
Similar processing result sR and sI is educated figure with Li Sa by step 6) to be indicated.
The following account this document (DCR007C025I136.txt) of embodiment measures from certain nuclear power station Eddy current detector
The data arrived, data format are shown in Table 1, and under Matlab software environment, Fig. 3 can be obtained with downloading picture sentence.Channel this
There is the signal of those suspected defects near 5700 in the signal of 16 column displays in this figure, discovery.Here, show that frequency is
Signal of the real and imaginary parts of 4 differential paths of 170kHz, 100kHz, 50kHz and 25kHz between 4500 to 7500, is shown in
Fig. 4.As can be seen that the differential path 3 that differential path and frequency that frequency is 170kHz are 100kHz occurs near 5700
Sign mutation, frequency be 50kHz differential path and frequency be 25kHz differential path become very weak, intuitive judgment is here
There may be a defects.
The data of 5500-5800 are intercepted in the differential path that frequency is 170kHz, draw its Lee Sa Yu Fig. 5.Directly calculate,
The angle of transformation of available those suspected defects.
After the calibration of calibrating tube measurement data, obtaining defect phase angle is 8.0908 °.Corresponding defect internal injury depth is about
It is 20%.
In the present embodiment, provides conventional mixer method and originally offset the result of method processing.Here conventional mixer method
Realization principle is referring to document [Xu Kebei, Zhou Junhua EDDY CURRENT (the 1st edition) Beijing [M]: China Machine Press, 2006]
(p86-87).This method is exactly that will offset after signal is adjusted to consistent with signal energy is offseted in fact, the signal being mixed
In real part be by offseted signal real part with offset signal imaginary part and, imaginary part is to be offseted signal imaginary part and to offset signal real part
Difference.
Four between 4500-5800 are intercepted in the differential path that frequency is 170kHz and 25kHz with conventional mixer method
Group data, Frequency mixing processing is as a result, referring to Fig. 6 (left side).As can be seen that remaining architecture signals have seriously affected the spy to defect
It surveys.Parameter alpha with this patent method, in algorithm1And α2It is taken as 0.02 respectively.Mixing results are referring to Fig. 6 (right side).As can be seen that
This method can inhibit architecture signals well, leave flaw indication, be surveyed by educating defect angle of transformation in figure to its Li Sha
After measuring and passing through the calibration of calibrating tube measurement data, obtained defect phase angle is 7.86 °, consistent with defect phase standard value.It will
Parameter alpha1And α2It is taken as 0.19 respectively, between 4000-7000, conventional method fails data cutout length substantially, this patent method
Obtained defect phase angle is 8.655 °, and effect is preferable, referring to Fig. 7.
Above two method intercepts four groups of numbers between 5500-5800 in the differential path that frequency is 170kHz and 25kHz
According to Frequency mixing processing is as a result, referring to Fig. 8.As can be seen that conventional method causes to extend on mixed frequency signal real axis, seriously change scarce
Signal shape is fallen into, flaw indication phase angle has been changed simultaneously, has needed to calibrate again, seen Fig. 8 (left side)；And use this patent method
Obtained mixing results are referring to Fig. 8 (right side), the parameter alpha in algorithm here1And α2It is adjusted to 0.35, flaw indication form has centainly
The variation of degree, but defect phase angle variations are little, without calibrating again.
Claims (5)
1. a kind of heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal, which is characterized in that this method
Include the following steps:
1) multifrequency Eddy signal data matrix X is obtained
Multifrequency differential path signal and absolute channel signal are assigned to X with a matrix type, the detection frequency of signal from high to low,
Four are classified as one group, and every group of frequency is identical, and there are two channel, i.e. differential path and absolute channel, each channel be divided into real part and
Imaginary part two arranges, and for the X matrix by row from top to bottom according to time sampling, every row time point is identical；
2) it determines and is offseted channel and offset channel；
When defect is located at detection pipes road surface, high frequency differential path is selected to be offseted channel, low frequency differential path is logical to offset
Road；
Defect is located among pipeline, then intermediate frequency differential path may be selected as channel, high and low frequency differential path is offseted and make
Channel is offseted for reference；
Defect is located at pipeline inner layer, selects low frequency differential path as being offseted channel, and high frequency differential path is used as to offseting ginseng
Examine channel；
3) pairs of reality, imaginary signals of the above-mentioned channel in detection zone are extracted from matrix X；
4) be detected channel and two reference channel complex signals implement to offset to obtain parallel four corresponding phasor F1 (:, 1), F1 (:,
2),F2(:,1),F2(:,2)；
5) F1 (:, 1:2) and F2 (:, 1:2) are subjected to the similar processing of two dimension respectively, are as a result denoted as sR and sI；
6) similar processing result sR and sI is educated figure with Li Sa indicates.
2. the heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal as described in claim 1, special
Sign is: the step 4) by the real part CC of detected differential path signal CC (:, 1) and imaginary part CC (:, 2) respectively with two
The real and imaginary parts for offseting the K1 and K2 of differential path carry out offseting processing, obtain corresponding four vector F1 (:, 1), F1 (:,
2)、F2(:,1)、F2(:,2)。
3. the heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal as claimed in claim 2, special
Sign is: the method that offsets is specially
If being offseted signal and offseting signal is respectively C and F；
4.1) adaptive neural network net is constructed；
4.1.1 initial network structure net=network (1,2, [1) is defined；1],[1；0],[00；10], [01]), network
Function is defined as MatlabR2009b library file；
4.1.2) using formula d (i, j)=| w (i, 1)-p (1, j) | define equal length column vector w and row vector p between
Distance matrix d=distm (w, p) is calculated d=distm (F', F), wherein F ' is the transposition of F；
4.1.3) utilize formulaDetermine network transmission function
4.1.4 the weight w 2 and deviation of neural network hidden layer weight w 1 and deviation b1 and output layer) are determined using following formula
b2；
Hidden layer weight w 1=F'；
Hidden layer deviationN is detection zone length；
Intermediate variable X=C/ [A；11×n]；
Output layer weight w 2=X (:, 1:n)；
Output layer deviation b2=X (:, n+1)；
4.1.5 above-mentioned weight and deviation) are assigned to neural network；
4.2) it to network net and F the input function sim after assignment, obtains width output signal Out, sim function and is defined as
MatlabR2009b library file；
4.3) C and Out is subtracted each other, obtains in eddy current signal C and offsets signal Flaw.
4. the heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal as described in claim 1, special
Sign is: the step 5) carries out two Li Sha in terms of real vector sum void vector two respectively educates the thresholding of distance between figure and sentences
Not, realize that two two dimension Lee Sa Yu scheme similar processing.
5. the heat-transfer pipe damage information high-fidelity extracting method based on multifrequency Eddy complex signal as described in claim 1, special
Sign is: the high frequency refers to that 170kHz, low frequency refer to that 50kHz and 25kHz, intermediate frequency refer to 100kHz.
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