CN103398295A - Device and method for compressing pipeline magnet leakage signal data - Google Patents
Device and method for compressing pipeline magnet leakage signal data Download PDFInfo
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- CN103398295A CN103398295A CN2013102800488A CN201310280048A CN103398295A CN 103398295 A CN103398295 A CN 103398295A CN 2013102800488 A CN2013102800488 A CN 2013102800488A CN 201310280048 A CN201310280048 A CN 201310280048A CN 103398295 A CN103398295 A CN 103398295A
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Abstract
The invention discloses a device and method for compressing pipeline magnet leakage signal data and belongs to the technical field of non-destructive testing. The method comprises the steps that step 1, a pipeline magnet leakage signal is collected and converted to an electric signal, and after filtering amplification is conducted, the electric signal is further converted to a digital signal; step 2, feature parameter extraction is conducted on the digital signal output from the step 1 through the wavelet transforming arithmetic based on a self-adaptation threshold value, a one-dimensional magnet leakage signal is converted to a two-dimensional magnet leakage signal, integer wavelet transformation is conducted on the two-dimensional magnet leakage signal so that a wavelet coefficient matrix can be obtained, and therefore important information of the magnet leakage signal is concentrated in the low-frequency portion of the wavelet transformation coefficient; step 3, lossy compression is conducted on the wavelet coefficient matrix through the improved SPIHT arithmetic. Compared with the prior art, the device and method for compressing the pipeline magnet leakage signal data overcome the shortages that the compression rate when the non-destructive compression is conducted on the long-distance oil pipeline magnet leakage signal by a detector with limited size is low and the distortion degree of the lossy compression is high.
Description
Technical field
The invention belongs to technical field of nondestructive testing, particularly a kind of pipeline magnetic flux leakage signal data compression device and method.
Background technique
Along with progressively lengthening, the transport volume of domestic and international oil and gas pipes progressively strengthens, oil and gas pipes is carried efficiently and safely and has been obtained paying attention to widely.Due to reasons such as long burn into wearing and tearing and unexpected mechanical deteriorations, the ferromagnetism pipe-line can form various defects., for preventing the generation of leakage accident, be necessary to utilize pipe detection device to detect pipeline.The Magnetic Flux Leakage Inspecting method requires lowly to measurement environment, does not need Couplant, is one of detecting method that has in very extensive use field and application prospect.Pipeline Magnetic Flux Leakage Inspection generally adopts on-line detecting system, and the length of detected pipeline can reach tens of kms, and the magnetic leakage signal data volume that collects is larger.Yet limited space in pipeline, the equipment volume and the storage space that cause storing data are less, therefore must carry out data reduction to the Pipeline Magnetic Flux Leakage Inspection data.Traditional lossless compression method, although as Huffman coding, arithmetic coding constant entropy coding and can't harm predictive encoding and can realize that data fully nondestructively compress, compression ratio is very low; Diminish predictive encoding and transition coding and have larger compression ratio, but when the magnetic leakage signal data reduction, a large amount of loss of the important information that lossy compression method is brought are unacceptable.Adopt Lossless Compression at existing pipe leakage data compression method, its compression ratio is lower more, is unfavorable for the raising and the lengthening that detects duct length of testing precision.
Summary of the invention
Deficiency for prior art exists, the objective of the invention is to consider that long distance oil pipeline magnetic leakage signal Lossless Compression compression ratio is low, and the high characteristics of the lossy compression method distortion factor propose a kind of pipeline magnetic flux leakage signal data compression device and method.
Technological scheme of the present invention is achieved in that a kind of pipeline magnetic flux leakage signal data compression device, comprising:
Data acquisition unit: be used for gathering magnetic leakage signal, and after being translated into electrical signal, send into conditioning circuit;
Conditioning circuit: after being used for the electrical signal that data acquisition unit sends is carried out filtering, amplification, export to the A/D converting unit;
The A/D converting unit: the analogue signal that is used for conditioning circuit is sent here is converted into digital signal, exports to CPLD multichannel collecting control unit;
CPLD multichannel collecting control unit: the conversion order that is used for each passage of control A/D converting unit;
The DSP data processing unit: be used for first utilizing Wavelet Transform Feature value extractor to extract the eigenvalue of Analysis of Magnetic Flux Leakage Testing Signals, then utilize the lossy compression method device to carry out lossy compression method to Analysis of Magnetic Flux Leakage Testing Signals, it further comprises:
Wavelet Transform Feature value extractor: be used for utilizing the Wavelet Transform Feature value extraction algorithm based on adaptive threshold to carry out the eigenvalue extraction to magnetic leakage signal.
Lossy compression method controller: be used for utilizing the lossy compression method method based on the improved SPIHIT algorithm to diminish pressure to magnetic leakage signal
Data storage cell: for the data after store compressed.
Adopt said apparatus to realize the method for pipeline magnetic flux leakage signal data reduction, comprise the following steps:
Step 1: gather pipeline magnetic flux leakage signal, and be converted into electrical signal, after carrying out filter and amplification, further be converted to digital signal;
Step 2: use based on the Wavelet Transformation Algorithm of the self adaption output value digital signal of step 1 output is carried out the eigenvalue extraction,
Step is as follows:
Step 2-1: select the biorthogonal wavelet base, original magnetic leakage signal is carried out Dyadic Wavelet Transform, determine first layer wavelet coefficient and second layer wavelet coefficient;
Step 2-2: the adaptive threshold that calculates respectively first layer and second layer wavelet coefficient, method is as follows: according to experience, first layer or second layer wavelet coefficient are arranged respectively initial threshold and threshold steps, with the wavelet coefficient zero setting of absolute value less than this threshold value, then original threshold value is added that a threshold steps is as new threshold value, along with threshold value increases gradually, the nonzero value of wavelet coefficient reduces gradually, when arriving certain threshold value, non-zero wavelet coefficient number minimizing speed slows down slowly, and the threshold value of selected this moment is the threshold value of first layer or second layer coefficient of wavelet decomposition;
Step 2-3: determine the modulus maximum moment in first layer wavelet coefficient and second layer wavelet coefficient, method is:
Step 2-3-1: the threshold value comparison of this layer coefficient of wavelet decomposition that not in the same time high frequency coefficient and the step 2-2 in the first layer wavelet coefficient determines, if the absolute value of high frequency coefficient is greater than threshold value, keep the high frequency coefficient value constant, if the absolute value of high frequency coefficient is less than threshold value, with the zero setting of high frequency coefficient value;
The threshold value comparison of this layer coefficient of wavelet decomposition that not in the same time high frequency coefficient and the step 2-2 in second layer wavelet coefficient determines, if the absolute value of high frequency coefficient is greater than threshold value, keep the high frequency coefficient value constant, if the absolute value of high frequency coefficient is less than threshold value, with the zero setting of high frequency coefficient value;
Step 2-3-2: determine that modulus maximum point is constantly: if if through the nonzero value of the first layer wavelet coefficient of step 2-3-1 output, meet simultaneously following three conditions:
(1) absolute value of this nonzero value must be more than or equal to the threshold value T of coefficient of wavelet decomposition:
(2) absolute value of this nonzero value should be simultaneously more than or equal to its first nonzero value of left side and first nonzero value of right side;
(3) absolute value of this nonzero value is greater than first nonzero value in its left side, perhaps greater than first nonzero value on its right side; The corresponding moment of this nonzero value is first layer wavelet coefficient modulus maximum constantly;
, if second layer wavelet coefficient not in the same time high frequency coefficient meets above-mentioned three conditions, determine that the corresponding moment of this high frequency coefficient is second layer wavelet coefficient modulus maximum constantly;
Step 2-4: calculate first layer wavelet coefficient modulus maximum constantly and second layer wavelet coefficient modulus maximum mean value constantly;
Step 2-5: the corresponding original magnetic leakage signal point of mean value of step 2-4 generation, as central point, is searched for 10～20 original magnetic leakage signal points simultaneously left, to the right, and the mean point together with step 2-4 produces, be eigenvalue.
Step 3: the one dimension magnetic leakage signal is converted to the two dimensional magnetic leakage signal;
Step 4: the two dimensional magnetic leakage signal is carried out integer wavelet transformation, obtain the wavelet coefficient matrix, make the important information of magnetic leakage signal concentrate on the low frequency part of wavelet conversion coefficient;
Step 5: utilize the improved SPIHIT algorithm to carry out lossy compression method in the wavelet coefficient matrix, step is as follows:
Step 5-1: the wavelet coefficient low frequency part is carried out direct current translational, concrete grammar is as follows: the mean value of obtaining low frequency coefficient, element and this mean value of getting wavelet coefficient matrix medium and low frequency part are poor, result is replaced the element of original low frequency part, low frequency wavelet coefficient amplitude is distributed near 0;
Described low frequency coefficient mean value, be by asking for wavelet coefficient matrix medium and low frequency part element and divided by after low frequency part wavelet coefficient number, round and obtain downwards again.
Step 5-2: the low frequency wavelet coefficient after direct current translational is encoded:
Step 5-2-1: at first find out the low frequency wavelet coefficient of absolute value maximum after direct current translational, then calculate the required minimum number of bits n of this low frequency wavelet coefficient;
Step 5-2-2: all low frequency wavelet coefficients are first output symbol position all, again property output they separately before, the n+1-min position, wherein,
T
minMinimum threshold for scanning;
Step 5-3: wavelet coefficient matrix medium-high frequency is partly encoded, be specially:
Step 5-3-1: total threshold value of calculating high frequency coefficient: at first find out the high frequency wavelet coefficient of absolute value maximum, then calculate the required minimum number of bits n of this high frequency wavelet coefficient; Total threshold value T of high frequency coefficient is: T=2
n
Step 5-3-2: high frequency coefficient is divided into horizontal block, vertical blocks and diagonal blocks by its place subband;
Step 5-3-3: calculate respectively threshold value corresponding to horizontal block, vertical blocks and diagonal blocks in the high frequency coefficient different sub-band;
Step 5-3-4: to the high frequency coefficient scanning of sorting: adopt the full scan strategy for the front filial generation of N generation, for the subband of N after generation, take a strategy of horizontal scan piece, wherein, N be wavelet coefficient decompose the number of plies 1/3;
Described full scan strategy refers to: the threshold value of all pieces of front subband compares with current total threshold value of high frequency coefficient and N generation, if the block threshold value of subband, less than total threshold value, does not just scan this piece;
If the block threshold value of subband, more than or equal to current total threshold value, scans each element in this piece:
If the element in piece, more than or equal to current total threshold value, thinks that this element is important; Otherwise, think that this element is unessential;
The strategy of described horizontal scan piece refers to: the threshold value of horizontal block of rear subband compares with current total threshold value of high frequency coefficient and N generation, if the horizontal block threshold value of subband, less than current total threshold value, does not just scan this piece;
If the horizontal block threshold value of subband greater than or total threshold value, each element in this piece is scanned:
If the element in piece, more than or equal to total threshold value, thinks that this element is important; Otherwise, think that this element is unessential;
Step 5-3-5: high frequency coefficient is carried out fine scanning: step 5-3-4 other important elements except the detected important element of this scanning process are exported respectively their n significant bits, wherein, n=log
2T；
Step 5-3-6: upgrade current total threshold value, concrete steps are as follows:
Judge that whether current total threshold value T is more than or equal to T
minIf,, current total threshold value T is reduced to original half, then jump to step 5-3-4, scanning and fine scanning sort next time; If not, stop current input Analysis of Magnetic Flux Leakage Testing Signals is encoded.
Described data storage cell, also be used for carrying out communication with upper-position unit.
Also be provided with the method that realizes the pipeline magnetic flux leakage signal data decompression in upper-position unit, comprise the following steps:
Step 1: utilize the data in upper-position unit reading out data storage unit;
Step 2: the information to lossy compression method is decoded;
Step 3: utilize the integer wavelet inverse transformation, the matrix after decompressing is reconstructed;
Step 4: the reconstruct 2D signal is operated again according to the opposite direction that the lossy compression method controller generates two-dimensional matrix, recover original one dimension magnetic leakage signal;
Step 5: utilize the eigenvalue of damaging compression controller output, the reconstruction signal of lossy compression method is revised, reduce the distortion factor of important magnetic leakage signal.
Beneficial effect of the present invention: compared with prior art, the compression ratio of the detector that the present invention has overcome finite volume during to long distance oil pipeline magnetic leakage signal Lossless Compression is lower, and the higher deficiency of the lossy compression method distortion factor, a kind of data compression method based on the improved SPIHIT algorithm has been proposed, the high compression ratio compression of realization to the long distance oil pipeline magnetic leakage signal, both reduced the distortion factor of important information, reduced again the consumption of mass data calculating to internal memory, and be easy to hardware and realize.
Description of drawings
Fig. 1 is embodiment of the present invention pipeline magnetic flux leakage signal data compression device structured flowchart;
Fig. 2 is the circuit theory diagrams of embodiment of the present invention conditioning circuit;
Fig. 3 is embodiment of the present invention CPLD multichannel collecting control unit and A/D converting unit interface circuit schematic diagram;
Fig. 4 is embodiment of the present invention DSP data compression unit and CPLD multichannel collecting control unit interface circuit schematic diagram;
Fig. 5 is embodiment of the present invention DSP data compression unit and SD card interface circuit schematic diagram;
Fig. 6 is embodiment of the present invention pipeline magnetic flux leakage signal data compression method flow chart;
Fig. 7 is that the magnetic leakage signal eigenvalue of embodiment of the present invention adaptive threshold Wavelet Transformation Algorithm is extracted flow chart;
Fig. 8 is embodiment of the present invention high frequency wavelet coefficient module maximum schematic diagram constantly;
Fig. 9 is the Lossy Compression Algorithm flow chart of embodiment of the present invention improved SPIHIT algorithm;
Figure 10 is embodiment of the present invention high frequency wavelet coefficient piecemeal schematic diagram;
Figure 11 is embodiment of the present invention pipeline magnetic flux leakage signal uncompressing data flow chart.
Embodiment
Below in conjunction with accompanying drawing, embodiments of the present invention are described in further detail.
Present embodiment provides pipeline magnetic flux leakage signal data compression device structured flowchart, as shown in Figure 1.Formed by data acquisition unit, conditioning circuit, A/D converting unit, CPLD multichannel collecting control unit, DSP data processing unit and data storage cell.
Fig. 2 is the circuit theory diagrams of conditioning circuit, and conditioning circuit is realized the electrical signal of Hall transducer collection is carried out filtering, amplification.This example selects the SS495A Hall transducer to detect magnetic leakage signal, the output process capacitance resistance filtering of Hall transducer, and then carry out signal through operational amplifier INA326 and amplify, give the AD converting unit signal of output finally.
Fig. 3 is CPLD multichannel collecting control unit and A/D converting unit interface circuit schematic diagram.Wherein the A/D converting unit is selected the ADS7844 cake core, and CPLD multichannel collecting control unit is selected the EPM570T100C5N cake core of altera corp.The A/D converting unit is digital signal with analog signal conversion, and CPLD multichannel collecting control unit is selected signal for the A/D converting unit provides clock, chip selection signal and multichannel, and conversion rate, the ALT-CH alternate channel of A/D converting unit are controlled.The Dout that the I/O51 of CPLD multichannel collecting control unit holds, I/O52 holds, I/O53 holds, the I/O54 end connects the A/D converting unit successively holds, Din holds,
End and Dclk end.
Fig. 4 is DSP data processing unit and CPLD multichannel collecting control unit interface circuit schematic diagram.GP[0] pin is chip selection signal, after CPLD is ready to write data, to the GP[5 of DSP] pin sends and interrupts application, waits for that the DSP response interrupts.After the interruption application of DSP response CPLD, choose the data cell that will read by outer address bus EA, and then by external data bus ED[0:11] reading out data.The DSP that this example is selected is the TMS320C6713 of TI company.
Fig. 5 is DSP data processing unit and SD card interface circuit schematic diagram.DSP utilizes the SPI serial ports of McBSP0 module that the control signals such as reading and writing data clock, chip selection signal are provided for the SD card.When the FSX1 of DSP pin is low level, by the DX1 pin, data serial is write in the SD card, by the DR1 pin, data are read from the SD card.
Pipeline magnetic flux leakage signal data compression device working procedure is as follows:
At first, data acquisition unit is converted into electrical signal with pipeline magnetic flux leakage signal, through conditioning circuit, electrical signal is carried out filtering, amplification, then be converted to digital signal through the A/D converting unit under the control of CPLD multichannel collecting control unit, then the DSP data compression unit is compressed the digital signal that collects, and the magnetic leakage signal after compressing finally stores data storage cell into.
The eigenvalue that is based on DSP that data compression method adopts is extracted the scheme in conjunction with lossy compression method, first use in the DSP data compression unit based on the Wavelet Transformation Algorithm of adaptive threshold magnetic leakage signal is carried out the eigenvalue extraction, then with the improved SPIHIT algorithm, it is carried out lossy compression method, with eigenvalue, the reconstruction signal of lossy compression method is revised finally the important information loss that causes to make up lossy compression method.
Adopt said apparatus to realize the method for pipeline magnetic flux leakage signal data reduction, its flow process as shown in Figure 6, comprises the following steps:
Step 1: gather pipeline magnetic flux leakage signal, and be converted into electrical signal, after carrying out filter and amplification, further be converted to digital signal;
Step 2: use based on the Wavelet Transformation Algorithm of adaptive threshold the digital signal of step 1 output is carried out the eigenvalue extraction, and recording feature value and the moment thereof, as shown in Figure 7, detailed process is as follows for the process that eigenvalue is extracted:
Step 2-1: select biorthogonal wavelet base bior4.4, to magnetic leakage signal sequence X={ x
i, i=1,2 ... carry out 5 layers of Dyadic Wavelet Transform, obtain each layer wavelet coefficient: d1[
n], d
2[n] ..., d
5[n], a
5[n], wherein, gather n=0 constantly, 1,2 ... d
j[n] is the high frequency coefficient of j layer wavelet decomposition, j1, and 2 ... 5, a
5[n] is the low frequency coefficient of the 5th layer of wavelet decomposition; If i〉16384, the burst that remains leakage field is waited for processing next time;
Step 2-2: calculate first layer and second layer coefficient of wavelet decomposition d
1[n], d
2[n] (n=0,1,2 ...) adaptive threshold T
j(j=1,2), method is as follows: according to experience, this layer is arranged initial threshold T
First j(j=1,2) and threshold steps s, if d
1[n]＜T
j, with d
1[n] zero setting; Otherwise, keep d
1[n] is constant, then with original threshold value T
jAdd a threshold steps s as new threshold value, along with threshold value increases gradually, the nonzero value of wavelet coefficient reduces gradually, and when arriving certain threshold value, non-zero wavelet coefficient number minimizing speed slows down slowly, the threshold value T of selected this moment
jThreshold value for this layer coefficient of wavelet decomposition;
Step 2-3: determine the modulus maximum moment in first layer wavelet coefficient and second layer wavelet coefficient, method is:
Step 2-3-1: to first layer and second layer coefficient of wavelet decomposition d
1[n], d
2[n] (n=0,1,2 ...) respectively with step 2-2 in the threshold value T that produces
1And T
2, even | d
j[k] | 〉=T
j, keep d
j[k] is constant; If | d
j[k] |＜T
j, with d
j[k] zero setting, j=1 wherein, 2 and k ∈ n;
Step 2-3-2: determine d
1[n], d
2[n] (n=0,1,2 ...) the modulus maximum point, even n=m is modulus maximum point, d so
j[m], (j=1,2) meet following three conditions simultaneously:
(1)|d
j[m]|≥T
j；
(2) | d
j[m] | 〉=| d
j[m-1] | and | d
j[m] | 〉=| d
j[m+1] |;
(3) | d
j[m] |〉| d
j[m-1] | perhaps | d
j[m] |〉| d
j[m+1] |;
D
j[m] corresponding moment is the modulus maximum moment t of this layer wavelet coefficient
j[p], j=1,2; P=0,1,2,
Suppose d in first layer high frequency wavelet coefficient
1[n], 5 of A, B, c, D, E are all greater than threshold value T as shown in Figure 8
1, t
AFor a modulus maximum moment of first layer wavelet coefficient;
Step 2-4: calculate first layer wavelet coefficient modulus maximum constantly and second layer wavelet coefficient modulus maximum mean value constantly, formula is as follows:
In formula, t[p] be modulus maximum mean value constantly, t
1[p] is the first layer wavelet coefficient modulus maximum moment, t
2[p] is the second layer wavelet coefficient modulus maximum moment;
Step 2-5: with the mean value t[p of step 2-4 generation] corresponding original magnetic leakage signal point is as central point, the while is searched for 10 original magnetic leakage signal points left, to the right, together with t[p], be eigenvalue.The moment of eigenvalue can be recorded the leftmost side, the moment of the rightmost side or central point.
Step 3: the one dimension magnetic leakage signal is converted to the two dimensional magnetic leakage signal, concrete steps are as follows: the two-dimensional matrix of supposing structure 256 * 256,1st row of 256 of fronts data as two-dimensional matrix, ensuing 256 data are as the 2nd row, the rest may be inferred, until form the two-dimensional matrix of 256 * 256.When decoder is decoded,, with the each row of data of the two-dimensional matrix of output the first being connected successively, be easy to just can recover the one dimension Pipeline Magnetic Flux Leakage Inspection signal of original 4 passages.
Step 4: the two dimensional magnetic leakage signal that step 3 is obtained carries out integer wavelet transformation, makes the important information of magnetic leakage signal concentrate on the low frequency part of wavelet conversion coefficient.
Step 5: utilize the improved SPIHIT algorithm to carry out lossy compression method in the wavelet coefficient matrix after conversion, as shown in Figure 9, step is as follows:
Step 5-1: the wavelet coefficient low frequency part is carried out direct current translational, and concrete grammar is as follows: the mean value of obtaining low frequency coefficient
, then use
Replace original low frequency wavelet coefficient, formula is as follows:
In formula, a
i,jFor an element in the 2-d wavelet matrix of the coefficients,
For rounding operation downwards.
Obtain the mean value of low frequency coefficient
And it is rounded operation downwards
Then use
Replace original low frequency wavelet coefficient a
i,jDirect current translational distributes the amplitude of wavelet coefficient near 0, reduce the dynamic change scope of low frequency wavelet coefficient.
Step 5-2: the low frequency wavelet coefficient after direct current translational is encoded:
Step 5-2-1: at first find out the low frequency wavelet coefficient of absolute value maximum after direct current translational, then calculate the required minimum number of bits n of this low frequency wavelet coefficient; Suppose that the low frequency wavelet coefficient of absolute value maximum is 63 after direct current translational, so according to formula
That is to say that the required minimum binary digit of low frequency wavelet coefficient is 5.
Step 5-2-2: all low frequency wavelet coefficients are first output symbol position all, if positive number is exported " 1 ", otherwise, output " 0 ".Their front 6-min positions separately of property output again, wherein,
T
minFor the minimum threshold of scanning, usually get 2-8, get T in this example
min=2, namely front 5 of all low frequency wavelet coefficients of disposable output.
Step 5-3: wavelet coefficient matrix medium-high frequency is partly encoded, be specially:
Step 5-3-1: total threshold value of calculating high frequency coefficient: at first finding out the high frequency wavelet coefficient of absolute value maximum, is 107, then calculates its required minimum number of bits
Total threshold value T of high frequency coefficient is: T=2
6=64.
Step 5-3-2: high frequency coefficient is divided into as shown in figure 10 horizontal block, vertical blocks and diagonal blocks by its place subband.
Step 5-3-3: calculate respectively threshold value corresponding to horizontal block, vertical blocks and diagonal blocks in the high frequency coefficient different sub-band.
Step 5-3_4: to the high frequency coefficient scanning of sorting: for N generation front subband adopt the full scan strategy, take a strategy of horizontal scan piece for the subband of N after generation, wherein, N is 1/3 of the wavelet coefficient decomposition number of plies, choosing N in this example is 2, namely the subband before 2 generations is compared the block threshold value of its horizontal block, vertical blocks and diagonal blocks respectively with current total threshold value, if the threshold value of a certain does not scan the element in this piece less than current total threshold value; Otherwise, scan each element in this piece, if element, more than or equal to total threshold value, thinks that this element is important, output " 1 ", and sign bit, otherwise, output " 0 "; For the horizontal scan piece of the subband after 2 generations, if 1 generation the subband horizontal block block threshold value less than current total threshold value, so the filial generation of 1 generation is not scanned, otherwise, scan each element in this piece, if element is more than or equal to total threshold value, think that this element is important, output " 1 ", otherwise and sign bit, output " 0 "; The scanning rule of 2 generations filial generation with 1 generation subband identical.
Step 5-3-5: high frequency coefficient is carried out fine scanning: step 5-3-4 other important elements except the detected important element of this scanning process are exported respectively their n significant bits, wherein, n=log
2T；
Step 5-3-6: upgrade current total threshold value, concrete steps are as follows:
Judge that whether current total threshold value T is more than or equal to T
minIf,, current total threshold value T is reduced to original half, then jump to step 5-3-4, scanning and fine scanning sort next time; If not, stop current input Analysis of Magnetic Flux Leakage Testing Signals is encoded.
Figure 11 is the pipeline magnetic flux leakage signal decompression method flow chart based on the improved SPIHIT algorithm, and concrete steps are as follows:
Step 1: utilize the data in the upper-position unit read memory;
Step 2: the information to lossy compression method is decoded, and is the inverse process of step 5 in the magnetic leakage signal compression method;
Step 3: utilize the integer wavelet inverse transformation, the matrix after decompressing is reconstructed;
Step 4: the reconstruct 2D signal is operated again according to the opposite direction that encoder generates two-dimensional matrix, recover original one dimension magnetic leakage signal;
Step 5: utilize the eigenvalue of encoder output, the reconstruction signal of lossy compression method is revised, reduce the distortion factor of important magnetic leakage signal.
Although more than described the specific embodiment of the present invention, the those skilled in the art in related domain should be appreciated that these instrument are to illustrate, and can make various changes or modifications to these mode of executions, and not deviate from principle of the present invention and essence.Scope of the present invention is only limited by appended claims.
Claims (4)
1. pipeline magnetic flux leakage signal data compression device is characterized in that: comprising:
Data acquisition unit: be used for gathering magnetic leakage signal, and after being translated into electrical signal, send into conditioning circuit;
Conditioning circuit: after being used for the electrical signal that data acquisition unit sends is carried out filtering, amplification, export to the A/D converting unit;
The A/D converting unit: the analogue signal that is used for conditioning circuit is sent here is converted into digital signal, exports to CPLD multichannel collecting control unit;
CPLD multichannel collecting control unit: the conversion order that is used for each passage of control A/D converting unit;
The DSP data processing unit: be used for first utilizing Wavelet Transform Feature value extractor to extract the eigenvalue of Analysis of Magnetic Flux Leakage Testing Signals, then utilize the lossy compression method device to carry out lossy compression method to Analysis of Magnetic Flux Leakage Testing Signals, it further comprises:
Wavelet Transform Feature value extractor: be used for utilizing the Wavelet Transform Feature value extraction algorithm based on adaptive threshold to carry out the eigenvalue extraction to magnetic leakage signal;
Lossy compression method controller: be used for utilizing, based on the lossy compression method method of improved SPIHIT algorithm, magnetic leakage signal carried out lossy compression method;
Data storage cell: for the data after store compressed.
2. the method that adopts pipeline magnetic flux leakage signal data compression device claimed in claim 1 to compress magnetic leakage signal is characterized in that: comprise the following steps:
Step 1: gather pipeline magnetic flux leakage signal, and be converted into electrical signal, after carrying out filter and amplification, further be converted to digital signal;
Step 2: use based on the Wavelet Transformation Algorithm of adaptive threshold the digital signal of step 1 output is carried out the eigenvalue extraction, step is as follows:
Step 2-1: select the biorthogonal wavelet base, original magnetic leakage signal is carried out Dyadic Wavelet Transform, determine first layer wavelet coefficient and second layer wavelet coefficient;
Step 2-2: the adaptive threshold that calculates respectively first layer and second layer wavelet coefficient, method is as follows: according to experience, first layer or second layer wavelet coefficient are arranged respectively initial threshold and threshold steps, with the wavelet coefficient zero setting of absolute value less than this threshold value, then original threshold value is added that a threshold steps is as new threshold value, along with threshold value increases gradually, the nonzero value of wavelet coefficient reduces gradually, when arriving certain threshold value, non-zero wavelet coefficient number minimizing speed slows down slowly, and the threshold value of selected this moment is the threshold value of first layer or second layer coefficient of wavelet decomposition;
Step 2-3: determine the modulus maximum moment in first layer wavelet coefficient and second layer wavelet coefficient, method is:
Step 2-3-1: the threshold value comparison of this layer coefficient of wavelet decomposition that not in the same time high frequency coefficient and the step 2-2 in the first layer wavelet coefficient determines, if the absolute value of high frequency coefficient is greater than threshold value, keep the high frequency coefficient value constant, if the absolute value of high frequency coefficient is less than threshold value, with the zero setting of high frequency coefficient value;
The threshold value comparison of this layer coefficient of wavelet decomposition that not in the same time high frequency coefficient and the step 2-2 in second layer wavelet coefficient determines, if the absolute value of high frequency coefficient is greater than threshold value, keep the high frequency coefficient value constant, if the absolute value of high frequency coefficient is less than threshold value, with the zero setting of high frequency coefficient value;
Step 2-3-2: determine that modulus maximum point is constantly: if if through the nonzero value of the first layer wavelet coefficient of step 2-3-1 output, meet simultaneously following three conditions:
(1) absolute value of this nonzero value must be more than or equal to the threshold value T of coefficient of wavelet decomposition;
(2) absolute value of this nonzero value should be simultaneously more than or equal to its first nonzero value of left side and first nonzero value of right side;
(3) absolute value of this nonzero value is greater than first nonzero value in its left side, perhaps greater than first nonzero value on its right side; The corresponding moment of this nonzero value is first layer wavelet coefficient modulus maximum constantly;
, if second layer wavelet coefficient not in the same time high frequency coefficient meets above-mentioned three conditions, determine that the corresponding moment of this high frequency coefficient is second layer wavelet coefficient modulus maximum constantly;
Step 2-4: calculate first layer wavelet coefficient modulus maximum constantly and second layer wavelet coefficient modulus maximum mean value constantly;
Step 2-5: the corresponding original magnetic leakage signal point of mean value of step 2-4 generation, as central point, is searched for 10～20 original magnetic leakage signal points simultaneously left, to the right, and the mean point together with step 2-4 produces, be eigenvalue;
Step 3: the one dimension magnetic leakage signal is converted to the two dimensional magnetic leakage signal;
Step 4: the two dimensional magnetic leakage signal is carried out integer wavelet transformation, obtain the wavelet coefficient matrix, make the important information of magnetic leakage signal concentrate on the low frequency part of wavelet conversion coefficient;
Step 5: utilize the improved SPIHIT algorithm to carry out lossy compression method in the wavelet coefficient matrix, step is as follows:
Step 5-1: the wavelet coefficient low frequency part is carried out direct current translational, concrete grammar is as follows: the mean value of obtaining low frequency coefficient, element and this mean value of getting wavelet coefficient matrix medium and low frequency part are poor, result is replaced the element of original low frequency part, low frequency wavelet coefficient amplitude is distributed near 0;
Described low frequency coefficient mean value, be by asking for wavelet coefficient matrix medium and low frequency part element and divided by after low frequency part wavelet coefficient number, round and obtain downwards again;
Step 5-2: the low frequency wavelet coefficient after direct current translational is encoded:
Step 5-2-1: at first find out the low frequency wavelet coefficient of absolute value maximum after direct current translational, then calculate the required minimum number of bits n of this low frequency wavelet coefficient;
Step 5-2-2: all low frequency wavelet coefficients are first output symbol position all, their front n+1-min positions separately of property output again, wherein,
T
minMinimum threshold for scanning;
Step 5-3: wavelet coefficient matrix medium-high frequency is partly encoded, be specially:
Step 5-3-1: total threshold value of calculating high frequency coefficient: at first find out the high frequency wavelet coefficient of absolute value maximum, then calculate the required minimum number of bits n of this high frequency wavelet coefficient, wherein, n=log
2T；
Step 5-3-2: high frequency coefficient is divided into horizontal block, vertical blocks and diagonal blocks by its place subband;
Step 5-3-3: calculate respectively threshold value corresponding to horizontal block, vertical blocks and diagonal blocks in the high frequency coefficient different sub-band;
Step 5-3-4: to the high frequency coefficient scanning of sorting: adopt the full scan strategy for the front filial generation of N generation, for the subband of N after generation, take a strategy of horizontal scan piece, wherein, N be wavelet coefficient decompose the number of plies 1/3;
Described full scan strategy refers to: the threshold value of all pieces of front subband compares with current total threshold value of high frequency coefficient and N generation, if the block threshold value of subband, less than total threshold value, does not just scan this piece;
If the block threshold value of subband, more than or equal to current total threshold value, scans each element in this piece:
If the element in piece, more than or equal to current total threshold value, thinks that this element is important; Otherwise, think that this element is unessential;
The strategy of described horizontal scan piece refers to: the threshold value of horizontal block of rear subband compares with current total threshold value of high frequency coefficient and N generation, if the horizontal block threshold value of subband, less than current total threshold value, does not just scan this piece;
If the horizontal block threshold value of subband greater than or total threshold value, each element in this piece is scanned:
If the element in piece, more than or equal to total threshold value, thinks that this element is important; Otherwise, think that this element is unessential;
Step 5-3-5: high frequency coefficient is carried out fine scanning: step 5-3-4 other important elements except the detected important element of this scanning process are exported respectively their n significant bits, wherein, n=log
2T；
Step 5-3-6: upgrade current total threshold value, concrete steps are as follows:
Judge that whether current total threshold value T is more than or equal to T
minIf,, current total threshold value T is reduced to original half, then jump to step 5-3-4, scanning and fine scanning sort next time; If not, stop current input Analysis of Magnetic Flux Leakage Testing Signals is encoded.
3. pipeline magnetic flux leakage signal data compression device according to claim 1 is characterized in that: described data storage cell also is used for carrying out communication with upper-position unit.
4. pipeline magnetic flux leakage signal data compression device according to claim 3 is characterized in that: also be provided with the method that realizes the pipeline magnetic flux leakage signal data decompression in described upper-position unit, comprise the following steps:
Step 1: utilize the data in upper-position unit reading out data storage unit;
Step 2: the information to lossy compression method is decoded;
Step 3: utilize the integer wavelet inverse transformation, the matrix after decompressing is reconstructed;
Step 4: the reconstruct 2D signal is operated again according to the opposite direction that the lossy compression method controller generates two-dimensional matrix, recover original one dimension magnetic leakage signal;
Step 5: utilize the eigenvalue of damaging compression controller output, the reconstruction signal of lossy compression method is revised, reduce the distortion factor of important magnetic leakage signal.
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