CN109635781A - The coarse Data Detection modification method of digital signal and system based on wavelet transformation - Google Patents
The coarse Data Detection modification method of digital signal and system based on wavelet transformation Download PDFInfo
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Abstract
The invention discloses a kind of coarse Data Detection modification method of digital signal based on wavelet transformation and systems, comprising: the intelligent substation the digitized measurement system sine digital signal sequences to be measured of acquisition are carried out wavelet decomposition and obtain high frequency detail coefficient and low-frequency approximation coefficient；Sinusoidal digital signal sequences are reconstructed according to high frequency detail coefficient, obtain reconstructed number signal sequence；Absolute value is subtracted average value and regards as coarse data item greater than the item of preset threshold, extends the coarse data item after being expanded by the standard deviation and average value for seeking the reconstructed number signal sequence each single item absolute value obtained；Original sinusoidal digital signal sequences are rejected according to the coarse data item after extension, interpolation correcting process is then carried out and obtains the sinusoidal digital signal sequences without coarse data.Present invention fitting number is relatively fewer, and calculation amount is relatively small, and can screen two even more than continuous coarse data.
Description
Technical field
The invention belongs to the detection fields of coarse data in intelligent substation the digitized measurement system digital signal sequences, special
It is not related to a kind of coarse Data Detection modification method of the digital signal based on wavelet transformation and system.
Background technique
Digital display circuit is when sampling analog signal, if there is interference, such as from coupling on power supply or ground wire
Unify an interference voltage, then ADC is possible to sample a maximum value or minimum value, referred to as coarse data.
In the digitized measurement system of intelligent substation, digitalized electrical energy meter virtual instrument directly obtains from combining unit
The waveform sampling data of electronic mutual inductor are taken, this data is digital quantity.In this process, electronic mutual inductor was sampling
Some coarse data may be coupled in journey, this data is high-frequency signal；If these coarse data are without processing, eventually right
The electric energy calculating of digital electricity meter has an impact.Therefore it has to look for suitable algorithm to detect coarse data and reject, and applies
Algorithm is modified, this has a very important significance to electric energy calculating error is reduced.
About the detection of coarse data, conventional method is one group of number (normal length for taking digital signal sequences regular length
7), to reject a maximum value and a minimum value, it is believed that the two values be coarse data, then using least square fitting into
Row amendment.Current method the problem is that: fitting number is more, and calculation amount is larger, and can not screen more than two continuous
Coarse data.
Summary of the invention
The purpose of the present invention is to provide a kind of coarse Data Detection modification method of digital signal based on wavelet transformation and
System, to solve above-mentioned technical problem.Detection method fitting number of the invention is relatively fewer, and calculation amount is relatively
It is small, and two can be screened even more than continuous coarse data.
In order to achieve the above objectives, the invention adopts the following technical scheme:
A kind of coarse Data Detection modification method of digital signal based on wavelet transformation, comprising the following steps:
Step 1, the intelligent substation the digitized measurement system sine digital signal sequences to be measured of acquisition are subjected to small wavelength-division
Solution, obtains high frequency detail coefficient and low-frequency approximation coefficient by decomposition；
Step 2, sinusoidal digital signal sequences are reconstructed according to the high frequency detail coefficient that step 1 obtains, are reconstructed
Digital signal sequences；
Step 3, the standard deviation and average value of the reconstructed number signal sequence each single item absolute value of step 2 acquisition are sought, it will
Absolute value subtracts average value and regards as coarse data item greater than the item of preset threshold；
Step 4, the coarse data item that step 3 obtains is extended, the coarse data item after being expanded；
Step 5, the coarse data item after the extension obtained according to step 4 is to sinusoidal digital signal sequence original in step 1
Column are rejected, and are then carried out interpolation correcting process and are obtained the sinusoidal digital signal sequences without coarse data.
Further, in step 1, select the db2 wavelet basis function in Daubechies wavelet systems to the intelligence to be measured of acquisition
Energy substation the digitized measurement system sine digital signal sequences are decomposed to obtain high frequency detail coefficient and low-frequency approximation coefficient.
Further, step 3 specifically: seek the standard deviation of reconstructed number signal sequence each single item absolute value and be averaged
Value, absolute value subtract average value and regard as coarse data item greater than the item of twice of standard deviation.
Further, in step 4 extension specifically, the previous item for each coarse data item that step 3 is obtained and
Latter regards as coarse data item.
Further, the interpolation correcting process in step 5 includes: to the sinusoidal digital signal sequence for weeding out coarse data
Column, are fitted using least square method, Lagrange's interpolation or cubic spline interpolation method, are obtained without coarse data
Sinusoidal digital signal sequences.
Further, it is programmed and is realized by MATLAB.
Further, in step 1, three layers are carried out by wavelet decomposition function [C, L]=wavedec (X, N, ' wname')
It decomposes,
In formula, Matrix C is used to store each layer coefficients after the completion of decomposing, each series of strata after the completion of matrix L is decomposed for storage
Several length；X is the signal for needing wavelet decomposition；N is the number of plies decomposed；' wname' be alternative wavelet filter.
Further, in step 2, by wavelet reconstruction function X'=wrcoef (' type', C, L, ' wname', N) to letter
It number is reconstructed；
Wherein, X' is reconstruction signal, and C, L are respectively coefficient matrix and coefficient length matrix；
N is to choose the level of coefficient in restructuring procedure；' wname' is to need the wavelet filter chosen；' type' be choosing
Select reconstructed high frequency details or low-frequency approximation.
Further, in step 2, low-frequency approximation is reconstructed using third layer approximation coefficient；Using first layer detail coefficients weight
Structure high frequency detail.
A kind of coarse Data Detection update the system of digital signal based on wavelet transformation, comprising:
Wavelet decomposition module, the intelligent substation the digitized measurement system sine digital signal sequences to be measured for that will acquire
Wavelet decomposition is carried out, obtains high frequency detail coefficient and low-frequency approximation coefficient by decomposition；
Sequence reconstructed module is obtained for sinusoidal digital signal sequences to be reconstructed according to the high frequency detail coefficient of acquisition
Obtain reconstructed number signal sequence；
Coarse data item assert module, the standard deviation of the reconstructed number signal sequence each single item absolute value for seeking obtaining
And average value, absolute value is subtracted into average value and regards as coarse data item greater than the item of preset threshold；
Coarse data item expansion module, for being extended to obtained coarse data item, the coarse number after being expanded
According to item；
Correction module is rejected, the coarse data item after the extension obtained for basis is to original sinusoidal digital signal sequences
It is rejected, then carries out interpolation correcting process and obtain the sinusoidal digital signal sequences without coarse data.
Compared with prior art, the invention has the following advantages:
The coarse Data Detection modification method of digital signal of the invention, using the local detail analytical characteristics of wavelet analysis,
The coarse Data Position of precise positioning simultaneously carries out deletion fitting, has fitting number few compared to conventional method, the small feature of calculation amount；
In addition, being extended after determining coarse data item for the first time to it, avoid the coarse data continuously occurred to wavelet analysis high frequency
The influence of detail coefficients, comparison conventional method assert that maximin is coarse data, the present invention in regular length signal sequence
Two can be screened even more than continuous coarse data.
Detailed description of the invention
Fig. 1 is the u in a kind of example of the coarse data detection method of digital signal based on wavelet transformation of the invention
[k], z [k], u'[k] alignment's schematic diagram；Fig. 1 (a) is the number without coarse data obtained by sinusoidal analog signal sampling
Word signal sequence u [k] schematic diagram；Fig. 1 (b) is coarse data sequence z [k] schematic diagram of construction；Fig. 1 (c) is containing coarse data
Sinusoidal digital signal sequences u'[k] schematic diagram；
Fig. 2 is low-frequency approximation reconstruction signal sequence Xa3With high frequency detail reconstruction signal sequence Xd1Contrast schematic diagram；Fig. 2 (a)
For low-frequency approximation reconstruction signal sequence Xa3Schematic diagram；Fig. 2 (b) is high frequency detail reconstruction signal sequence Xd1Schematic diagram；
Fig. 3 is the signal sequence u'[k containing coarse data] and signal sequence y [k] after rejecting coarse data and being fitted it is right
Compare schematic diagram；Fig. 3 (a) is the signal sequence u'[k containing coarse data] schematic diagram；Fig. 3 (b) is after rejecting coarse data and being fitted
Signal sequence y [k] schematic diagram.
Specific embodiment
Invention is further described in detail in the following with reference to the drawings and specific embodiments.
A kind of coarse data detection method of digital signal based on wavelet transformation of the invention, comprising the following steps:
Step 1: according to intelligent substation the digitized measurement system sine digital signal sequences transmission feature, selection
Db2 wavelet basis function in Daubechies wavelet systems carries out three layers of decomposition to the sinusoidal digital signal sequences containing coarse data；
Step 2: applying step 1 decomposes obtained first layer high frequency detail coefficient and carries out weight to sinusoidal digital signal sequences
Structure；
Step 3: seeking the standard deviation and average value of reconstructed number signal sequence each single item absolute value, absolute value subtracts average
The item that value is greater than twice of standard deviation is considered coarse data item；
Step 4: be missed even more than continuous coarse data item in order to avoid two, the coarse number that step 3 is obtained
It is extended according to item, that is, assert the previous item for each coarse data item that step 3 obtains and latter is coarse data item；
Step 5: initial sinusoids digital signal sequences being rejected according to the coarse data item that step 4 obtains, after rejecting
It is fitted to obtain the sinusoidal digital signal sequences without coarse data using least square method.
Embodiment
A kind of number using wavelet transformation that the present invention is realized using MATLAB (can also be other machines language) programming
The coarse Data Detection Algorithm of signal, comprising:
1, the sinusoidal voltage waveform that construction amplitude is frequency f=55Hz, u=sin (2 π ft).With sample frequency fs=4kHz
Sampling formation sequence u [k] is carried out to it, takes preceding 399 sampled points to be studied, i.e. 1≤k≤399.
2, coarse data are simulated, as shown in table 1 in tectonic sequence z [k], 1≤k≤399；The item in table is not appeared in wherein
Value is 0.
Non-zero item in table 1.z [k] sequence
| k | 50 | 51 | 52 | 100 | 101 | 102 | 130 | 131 | 137 | 138 | 164 |
| z[k] | 0.3 | -0.2 | 0.4 | -0.4 | -0.3 | 0.2 | -0.2 | 0.3 | 0.4 | 0.5 | 0.3 |
| k | 165 | 166 | 208 | 209 | 210 | 244 | 245 | 246 | 277 | 278 | 327 |
| z[k] | -0.2 | 0.4 | 0.2 | 0.3 | 0.2 | -0.3 | -0.1 | -0.4 | 0.4 | 0.3 | 0.2 |
3, u'[k is enabled]=u [k]+z [k], 1≤k≤399, i.e. u'[k] it is the sinusoidal sequence containing coarse data.By above-mentioned u
[k], z [k], u'[k] sequence drawn with MATLAB compare respectively, and comparing result is as shown in Figure 1.
4, wavelet decomposition function [C, the L]=wavedec (X, N, ' wname') provided using MATLAB is to u'[k] carry out 3
Layer decomposes, i.e. [C, L]=wavedec (u'[k], 3, ' db2')；Wherein, Matrix C is used to store each series of strata after the completion of decomposing
Number, matrix L are used to store the length of each layer coefficients after the completion of decomposition.X is the signal for needing wavelet decomposition；N is the number of plies decomposed,
In the present invention using 3 grades of decomposition；' wname' be alternative wavelet filter, in the present invention choose ' db2'.
5, the wavelet reconstruction function X'=wrcoef (' type', C, L, ' wname', N) provided with MATLAB to signal into
Row reconstruct.
Wherein, X' is reconstruction signal, and C, L are coefficient matrix obtained in the previous step and coefficient length matrix.
N chooses the level of coefficient in restructuring procedure；' wname' is to need the wavelet filter chosen, it selects in the present invention
Take ' db2'；' type' is selection reconstruct low-frequency approximation or high frequency detail.
The present invention reconstructs low-frequency approximation, i.e. X using third layer approximation coefficienta3=wrcoef (' a', C, L, ' db2', 3)；Benefit
With first layer detail coefficients reconstructed high frequency details, i.e. Xd1=wrcoef (' d', C, L, ' db2', 1)；By low-frequency approximation reconstruction signal
Sequence and high frequency detail reproducing sequence are drawn with MATLAB, as shown in Figure 2.
6, from Xd1The coarse data item of Detection and Extraction in sequence.
Seek Xd1The standard deviation s of sequence, wherein Xd1Be considered coarse data item of the absolute value greater than 2s, utilizes in sequence
The index that the find function that MATLAB is provided extracts coarse data item is stored in one-dimension array b, as shown in table 2.
Table 2. is from high frequency detail reproducing sequence Xd1The coarse data entry index extracted
| 50 | 51 | 52 | 99 | 101 | 102 | 130 | 131 | 132 | 137 | 139 | 164 |
| 165 | 166 | 207 | 209 | 243 | 244 | 245 | 246 | 277 | 279 | 327 |
Comparison Tables 1 and 2 can obtain, and individual continuous coarse big datas are missed or judge by accident.In order to solve this problem, to one
Dimension group b carries out table 3 such as and extends, it is believed that the previous item of coarse data and latter are coarse data in table 2, are denoted as b'.
Coarse data entry index after the extension of table 3.
| 49 | 50 | 51 | 52 | 53 | 98 | 99 | 100 | 101 | 102 | 103 | 129 |
| 130 | 131 | 132 | 133 | 136 | 137 | 138 | 139 | 163 | 164 | 165 | 166 |
| 167 | 206 | 207 | 208 | 209 | 210 | 242 | 243 | 244 | 245 | 246 | 247 |
| 276 | 277 | 278 | 279 | 280 | 326 | 327 | 328 |
Contrast table 1 and table 3 can obtain, and the coarse data entry index after extension contains all coarse data item of the introducing of table 1.
7, from u'[k] array b'(table 3 is rejected in (1≤k≤399)) in coarse data item, using least square fitting
New data are supplemented, new sequences y [k] (1≤k≤399) are formed.As shown in figure 3, being containing coarse data sequence respectively in Fig. 3
U'[k] and the new sequences y [k] that generates after rejecting coarse data using wavelet transformation and being fitted again.
To sum up, the present invention provides a kind of coarse Data Detection calculation of the digital signal using wavelet transformation partial analysis characteristic
Method.The detection amendment of coarse data is realized using the good partial analysis characteristic of wavelet transformation, this is to digitlization metering system
Accurate Measurements of Electric Energy it is significant.
Present invention can apply to intelligent substation the digitized measurement system combining unit front end and digital electricity meter front end into
The detection of row voltage and current digital signal sequences is corrected, and solves electronic mutual inductor in intelligent substation the digitized measurement system
In the high-frequency signal of sampling process coupling, i.e., the adverse effect that coarse data generate electrical energy measurement, this is to realization digitlization meter
The accurate metering of amount system, the construction for pushing digital intelligent substation and popularization, ensure the good economic benefit of electric system,
Constructing trusting between electric power enterprise and user all has very positive meaning.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, although referring to above-described embodiment pair
The present invention is described in detail, those of ordinary skill in the art still can to a specific embodiment of the invention into
Row modification perhaps equivalent replacement these without departing from any modification of spirit and scope of the invention or equivalent replacement, applying
Within pending claims of the invention.
Claims (10)
1. a kind of coarse Data Detection modification method of digital signal based on wavelet transformation, which comprises the following steps:
Step 1, the intelligent substation the digitized measurement system sine digital signal sequences to be measured of acquisition are subjected to wavelet decomposition, warp
Excessive solution obtains high frequency detail coefficient and low-frequency approximation coefficient；
Step 2, sinusoidal digital signal sequences are reconstructed according to the high frequency detail coefficient that step 1 obtains, obtain reconstructed number
Signal sequence；
Step 3, the standard deviation and average value for seeking the reconstructed number signal sequence each single item absolute value of step 2 acquisition, will be absolute
Value subtracts average value and regards as coarse data item greater than the item of preset threshold；
Step 4, the coarse data item that step 3 obtains is extended, the coarse data item after being expanded；
Step 5, coarse data item after the extension obtained according to step 4 to sinusoidal digital signal sequences original in step 1 into
Row is rejected, and is then carried out interpolation correcting process and is obtained the sinusoidal digital signal sequences without coarse data.
2. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 1, special
Sign is, in step 1, selects the db2 wavelet basis function in Daubechies wavelet systems to the intelligent substation number to be measured of acquisition
Word metering system sine digital signal sequences are decomposed to obtain high frequency detail coefficient and low-frequency approximation coefficient.
3. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 1, special
Sign is, step 3 specifically: seek the standard deviation and average value of reconstructed number signal sequence each single item absolute value, absolute value subtracts
The item for going average value to be greater than twice of standard deviation regards as coarse data item.
4. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 1, special
Sign is that the extension in step 4 is specifically, the previous item and latter of each coarse data item that step 3 is obtained are recognized
It is set to coarse data item.
5. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 1, special
Sign is that the interpolation correcting process in step 5 includes: to the sinusoidal digital signal sequences for weeding out coarse data, using minimum
Square law, Lagrange's interpolation or cubic spline interpolation method are fitted, and obtain the sine number letter without coarse data
Number sequence.
6. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 1, special
Sign is, is programmed and is realized by MATLAB.
7. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 6, special
Sign is, in step 1, carries out three layers of decomposition by wavelet decomposition function [C, L]=wavedec (X, N, ' wname'),
In formula, Matrix C is used to store each layer coefficients after the completion of decomposing, and matrix L is used to store each layer coefficients after the completion of decomposition
Length；X is the signal for needing wavelet decomposition；N is the number of plies decomposed；' wname' be alternative wavelet filter.
8. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 7, special
Sign is, in step 2, carries out weight to signal by wavelet reconstruction function X'=wrcoef (' type', C, L, ' wname', N)
Structure；
Wherein, X' is reconstruction signal, and C, L are respectively coefficient matrix and coefficient length matrix；
N is to choose the level of coefficient in restructuring procedure；' wname' is to need the wavelet filter chosen；' type' be selection weight
Structure high frequency detail or low-frequency approximation.
9. the coarse Data Detection modification method of a kind of digital signal based on wavelet transformation according to claim 7, special
Sign is, in step 2, reconstructs low-frequency approximation using third layer approximation coefficient；Using first layer detail coefficients reconstructed high frequency details.
10. a kind of coarse Data Detection update the system of digital signal based on wavelet transformation characterized by comprising
Wavelet decomposition module, the intelligent substation the digitized measurement system sine digital signal sequences to be measured for that will acquire carry out
Wavelet decomposition obtains high frequency detail coefficient and low-frequency approximation coefficient by decomposition；
Sequence reconstructed module is weighed for sinusoidal digital signal sequences to be reconstructed according to the high frequency detail coefficient of acquisition
Structure digital signal sequences；
Coarse data item assert module, the standard deviation peace of the reconstructed number signal sequence each single item absolute value for seeking obtaining
Absolute value is subtracted average value and regards as coarse data item greater than the item of preset threshold by mean value；
Coarse data item expansion module, for being extended to obtained coarse data item, the coarse data item after being expanded；
Correction module is rejected, for carrying out according to the coarse data item after obtained extension to original sinusoidal digital signal sequences
It rejects, then carries out interpolation correcting process and obtain the sinusoidal digital signal sequences without coarse data.
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