CN108710861A - A kind of grid disturbance signal detection recognition methods - Google Patents
A kind of grid disturbance signal detection recognition methods Download PDFInfo
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- CN108710861A CN108710861A CN201810503766.XA CN201810503766A CN108710861A CN 108710861 A CN108710861 A CN 108710861A CN 201810503766 A CN201810503766 A CN 201810503766A CN 108710861 A CN108710861 A CN 108710861A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/211—Selection of the most significant subset of features
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
Abstract
The invention discloses a kind of grid disturbance signal detection recognition methods, the detection recognition method includes, acquire power network signal, more resolution decompositions are carried out using wavelet transformation to power network signal, by the energy coefficient for calculating each layer, feature extraction is carried out, characteristic signal is obtained, classification is identified to the signal of power grid in the signal characteristic information obtained according to extraction.The advantage of the invention is that：It can realize comprehensively in the case where a variety of disturbing signals interfere power grid, be prepared Classification and Identification, can clearly detect the interference that power grid is really subject to, so as to realize the improvement for power grid according to the interference signal received.
Description
Technical field
The present invention relates to electric power network technique field, more particularly to a kind of detection recognition method of grid disturbance signal.
Background technology
With the continuous development of national economy, the electricity needs in China also continuous rapid growth.Some power equipments, it is such as solid
State switching device, the load of non-linear and power electronic switching, unbalanced electric system, lighting control system, computer sum number
According to processing equipment and factory's rectifier and inverter, puts into electric system use more and more, power grid is caused
Increasingly severe pollution causes more interference signal to enter power grid, power grid quality is caused to decline.Simultaneously with electronic technology
Rapid development and the introducing of high-precision equipment, requirement of the electricity consumption side to power quality are higher and higher.Electrical equipment is difficult to tolerate
Interference signal in power grid.Therefore, the interference signal being effectively subject in analysis power grid, specifies the type of interference signal, this is to electricity
The improvement of network pollution, improving power quality is all necessary and positive effect.
In power grid influence power quality disturbing signal include voltage swell, voltage dip, voltage interruption, transient state pulse,
The types such as harmonic wave and flickering.In actual electric network, electrical energy power quality disturbance is often staggeredly folded by a variety of single disturbances and partial noise
It is added together, forms compound disturbance, these disturbing signals easily cause apparatus overheat, motor stalling, protection failure and metering
The serious consequences such as inaccurate, cause serious economic loss and social influence.Electrical equipment is often mingled with noise using process, allows and disturbs
The process of dynamic signal identification increases difficulty.Present recognition methods only resides within and part single signal is identified, and very
Noisy situation is considered less, part interference signal is caused not have recognition detection, thus cannot rational clear interference source.
Invention content
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of grid disturbance signal detection recognition methods.
To achieve the goals above, the technical solution adopted by the present invention is：A kind of grid disturbance signal detection recognition methods,
The detection recognition method includes,
Power network signal is acquired, more resolution decompositions are carried out using wavelet transformation to power network signal, by the energy for calculating each layer
Coefficient carries out feature extraction, obtains characteristic signal, and the signal of power grid is identified in the signal characteristic information obtained according to extraction
Classification.
When carrying out signal characteristic abstraction, the Multiresolution Decomposition based on wavelet transformation is carried out, morther wavelet chooses db wavelet systems
Row.
The method includes carrying out Multiresolution Decomposition using wavelet transformation DWT, to the power grid of acquisition
Signal carries out N layers of decomposition, every layer of energy is calculated using Parseval's theorem, formula is：Wherein the right first item represents the approximation of decomposed signal
Energy value, Section 2 represent the decomposed signal energy value of minutia, correspond to respectively：
Ai,jThat represent is the coefficient that signal carries out MSD decomposition, Di,jRepresent the minutia coefficient of decomposed signal, respectively from
1st layer Dao l layers.What i was represented is the number of plies of signal decomposition, and what j was represented is scale coefficient, and N represents the detailed letter of each layer of decomposition
The number of number coefficient, WDiThat represent is i-th layer of Energy Decomposition coefficient, WAlIt is the approximate energy system for carrying out MSD and decomposing l layers
Number；L layers of the feature vector containing disturbing signal can indicate as follows：FV(WDDS)=[WD1 WD2 ... WDl WAl]；Just
The feature vector of string signal can be expressed as：FV(WDPS)=[WD1 WD2 ... WDl WAl], then it represents that the feature of signal to
Amount can be expressed as Δ W=WDDS-WDPS；
Calculate percentage of the characteristic signal Energy-Entropy with respect to sinusoidal signal：
With WAEClassify to all kinds of disturbing signals.
The method further includes
Calculate the absolute percent of signal entropy after MSD is decomposed：
WDSabsRepresent WDDSAbsolute value, WPSabsRepresent WDPSAbsolute value, W obtained by calculationAEabsEffectively distinguish
High frequency components signal and low-frequency excitation signal.
WAEWhen more than zero：
(1) work as WAEIt is 18%-28% for positive number and value range, illustrates the disturbance risen containing voltage, work as WAEIt is equal to
WAEvswellRise for voltage, works as WAEEqual to WAEvswell+hrRise the compound disturbance with harmonic wave for voltage, works as WAEEqual to WAEvswell+n
Rise the compound disturbance with noise for voltage.
(2) work as WAEFor positive number when and value range be 8%-12%, illustrate the disturbance containing voltage flicker, work as WAEIt is equal to
WAEvfIt is voltage flicker, works as WAEEqual to WAEvf+nIt is the compound disturbance of voltage flicker and noise.
(3) work as WAEFor positive number when and value range be 5%-8%, illustrate the disturbance containing harmonic wave, work as WAEEqual to WAEhrIt is
Voltage harmonic works as WAEEqual to WAEabs-hrnIt is the compound disturbance of harmonic wave and noise；
(4) work as WAEFor positive number when and value range be 0%-1%, illustrate containing transient disturbance, WAEWhen less than zero：
Work as WAEFor negative number when and value range be negative 8%-17%, illustrate to decline containing voltage and disturb, work as WAEIt is equal to
WAEvsagIt is that voltage declines, works as WAEEqual to WAEvsag+hrIt is the compound disturbance of voltage decline and harmonic wave.Work as WAEEqual to WAEvsag+nIt is electricity
The compound disturbance of drops and noise.Work as WAEEqual to WAEviIt is voltage interruption, works as WAEEqual to WAEcsIt is capacitor switch disturbance, when
WAEEqual to WAElsIt is on-load switch disturbance；
Work as WAEWhen equal to zero, it is believed that do not interfere with signal in power grid, be high-quality power network signal.
Work as WAEFor positive number when and value range be 0%-1% when, contain transient signal at this time, further calculate WAEabs, when
WAEabsEqual to WAEabs-hftIt is high frequency transient disturbance, works as WAEEqual to WAEabs-lftIt is low frequency transient disturbance.
The advantage of the invention is that：It can realize in the case where a variety of disturbing signals interfere power grid, be prepared comprehensively
Classification and Identification can clearly detect the interference that power grid is really subject to, so as to be realized pair according to the interference signal received
In the improvement of power grid.
Description of the drawings
Below to each width attached drawing of description of the invention expression content and figure in label be briefly described：
Fig. 1 is that the present invention is based on tri- layers of decomposition diagrams of MSD of DWT；
Fig. 2 is grid disturbance signal characteristic extracting methods schematic diagram of the present invention.
Specific implementation mode
The specific implementation mode of the present invention is made further detailed by the description to optimum embodiment below against attached drawing
Thin explanation.
The present invention provides a kind of detection of new grid disturbance signal and its sorting techniques.Include believing single disturbance
Number, compound disturbance and noise-containing situation carry out effective feature extraction and classification, the present invention using wavelet transformation into
The more resolution decompositions of row carry out feature extraction, effectively classify to disturbing signal by calculating the energy coefficient of each layer.It is single
Disturbing signal model is with reference to table 1.
Table 1
To realize that foregoing invention, specific implementation are as follows：
1, power network signal is acquired, as the input signal of system, carries out power quality analysis.
2, the multiresolution analysis based on wavelet transformation is carried out to the signal of acquisition, to extract signal characteristic.
Signal f (t) wavelet transformation formula：Wherein i, j are integer, ψi,jFor Wavelet Expansions function,
ai,jFor the coefficient of signal f (t) wavelet transformations, can be expressed asBy to ψi,jOperation is carried out, it can be with
Obtain mother wavelet function ψi,j, ψi,j=2i/2ψ(2iT-j), j is transformation parameter, and i is scale parameter.Morther wavelet be not it is unique,
It needs to meet a series of conditions, to carry out Multiresolution Decomposition and need to meetWherein φ (t) is
Scaling functionH (k) will meet uniqueness, orthogonality and a degree of regularity.
Carrying out MSD dimensional analysis conducive to small echo can obtain：
WhereinThat indicate is translation scaling function, ψ
The Wavelet Expansions function of expression.Coefficient c wherein in formulajThat indicate is the scale translation coefficient of jth layer, djWhat is indicated is jth layer
Coefficient of wavelet decomposition, can indicate as followsWherein：g
(n) and the relational expression of h (n)：G (n)=(- 1)nh(L-1-n).The spectrum of signal is divided into a lower passband h (n) and one by the first step
A upper passband g (n)；The signal of low pass is divided into other lower lower passband and another upper passband by second step, is once analogized.
Wherein L represents the length of filter, and MSD decomposition is carried out based on wavelet transformation.Signal basic frequency is f, and L represents the length of filter
The frequency of degree, the voltage signal of acquisition is fsp.Three layers of MSD based on DWT are as shown in Figure 1, according to MSD principles, with this according to letter
Number frequency carry out low-and high-frequency division.First layer low frequency signal ranging from 0-f/2, high-frequency signal f/2-f.And so on, into
After row n-layer MSD is decomposed, each layer of low frequency signal is 0-f/ (2n), high-frequency signal [f/(2n)]-f/2n-1.,
It when carrying out signal characteristic abstraction, carries out the MSD based on wavelet transformation and decomposes, the selection of morther wavelet is extremely important, uses
There is db, harr, Daubechies, Symlets small echo etc. in the morther wavelet of signal processing analysis, by comparative analysis, is easiest to
Carry out electric energy feature extraction is db small echo series.It is compared with other small echos, db small echos have filter width shorter, calculate the time
Soon, it is highly suitable for the real-time monitoring system of power grid.Signal characteristic abstraction is carried out, different type letter is exactly chosen
Number key feature, to reach effectively distinguish various types of signal purpose.MSD technologies are carried out using DWT, to the letter of acquisition
Number carry out N floor decomposition, every layer of energy is calculated using Parseval's theorem.Formula is as follows：Wherein the right first item represents the approximation of decomposed signal
Energy value, Section 2 represent the decomposed signal energy value of minutia, correspond to respectively：
Ai,jThat represent is the coefficient that signal carries out MSD decomposition, Di,jRepresent the minutia coefficient of decomposed signal, respectively from
1st layer to l layers.What i was represented is the number of plies of signal decomposition, and what j was represented is scale coefficient, and N represents the detailed of each layer of decomposition
The number of signal coefficient, WDiThat represent is i-th layer of Energy Decomposition coefficient, WAlIt is the approximate energy for carrying out MSD and decomposing l layers
Coefficient；L layers of the feature vector containing disturbing signal can indicate as follows：FV(WDDS)=[WD1 WD2 ... WDl WAl]；
The feature vector of sinusoidal signal can be expressed as：FV(WDPS)=[WD1 WD2 ... WDl WAl], then it represents that the feature of signal
Vector can be expressed as Δ W=WDDS-WDPS；
Further calculate percentage of the characteristic signal Energy-Entropy with respect to sinusoidal signal：
W is calculated by formula (1)AE, first pass through pre-set it is a variety of single and compound disturb containing harmonic wave, voltage flicker etc.
The power network signal of dynamic ingredient, the various state of disturbance of advance simulated grid, to calculate the corresponding W of power gridAEValue (harmonic disturbance
WAEFor WAEhr, the W of voltage flicker disturbanceAEFor WAEvfDeng), collected signal is then calculated into the actual W of power gridAE's
Value and the W precalculated under various disturbancesAEIt is compared, to compare what types of interference signal judgement is.
By the W for calculating all kinds of disturbing signalsAE, it is previously obtained the corresponding power grid W of different disturbancesAEValue, then according to calculating
Obtained actual power grid WAEValue and the W under various disturbancesAE WAEValue comparison, judges which kind of the disturbance in actual electric network belongs to and disturb
It is dynamic；Various disturbances are classified as：Sinusoidal signal WAEps, voltage decline WAEvsag, voltage rising WAEvswell, harmonic wave WAEhr, voltage flicker
WAEvf, voltage interruption WAEvi, capacitor switch WAEcsAnd on-load switch WAElsWhat the disturbance of generation and harmonic wave and voltage declined
Compound disturbance WAEvsag+hr, the compound disturbance W of harmonic wave and voltage risingAEvswell+hr, voltage rises and the compound disturbance of noise
WAEvswell+n, the compound disturbance W of voltage flicker and noiseAEvf+n, the compound disturbance W of noise reducing under voltageAEvsag+n.Due to HFT and
The W of LFTAENumerical value is more close, therefore is difficult to distinguish.The absolute percent of signal entropy after being decomposed by calculating MSD.
WDSabsRepresent WDSAbsolute value, WPSabsRepresent WPSAbsolute value, the W of HFTAEabsFor WAEabs-hft, the W of LFTAEabs
For WAEabs-lft, the W of HFT LFT signalsAEabsThe two has prodigious gap, therefore can be by calculating WAEabsEffectively distinguish
This two classes signal.
3, carry out disturbing signal classification
By calculating the absolute percent of characteristic signal Energy-Entropy and signal energy entropy, single disturbance letter can be effectively extracted
Number, compound disturbing signal, and under noise situations disturbing signal feature vector, so as to quickly by disturbing signal point
Class.Using the method for calculating Energy-Entropy, can classify to 16 class disturbing signals, respectively pure string signal, voltage rises,
The compound disturbance that voltage decline, harmonic wave and voltage rise, voltage rises and the compound disturbance of noise, and voltage decline is answered with noise
Close disturbance, voltage decline and noise compound disturbance, harmonic wave, the compound disturbance of harmonic wave and noise, voltage flicker, voltage flicker and
The compound disturbance of noise, high frequency transient signal disturbance, the disturbance of low frequency transient signal, voltage interruption, capacitor switch are disturbed and are born
Lotus switching disturbances.
1) go out characteristic vector W using MSD decomposition computationsAEValue；
2) work as WAEWhen more than zero, it may be determined that disturbing signal voltage rises, the compound disturbance that harmonic wave and voltage rise, voltage
Rise and the compound disturbance of noise, harmonic wave, the compound disturbance of harmonic wave and noise, voltage flicker, voltage flicker and noise it is compound
Disturbance, high frequency transient signal disturbance, low frequency transient signal disturb 11 classes,
(1) work as WAEIt is 18%-28% for positive number and value range, illustrates the disturbance risen containing voltage, work as WAEIt is equal to
WAEvswellRise for voltage, works as WAEEqual to WAEvswell+hrRise the compound disturbance with harmonic wave for voltage, works as WAEEqual to WAEvswell+n
Rise the compound disturbance with noise for voltage.
(2) work as WAEFor positive number when and value range be 8%-12%, illustrate the disturbance containing voltage flicker, work as WAEIt is equal to
WAEvfIt is voltage flicker, works as WAEEqual to WAEvf+nIt is the compound disturbance of voltage flicker and noise.
(3) work as WAEFor positive number when and value range be 5%-8%, illustrate the disturbance containing harmonic wave, work as WAEEqual to WAEhrIt is
Voltage harmonic works as WAEEqual to WAEabs-hrnIt is the compound disturbance of harmonic wave and noise.
(4) work as WAEFor positive number when and value range be 0%-1%, illustrate containing transient disturbance, but cannot effectively distinguish
High and low frequency disturbing signal.
3) work as WAEWhen less than zero, voltage declines, and voltage declines and the compound disturbance of noise, and voltage declines compound with noise
Disturbance, voltage interruption, capacitor switch disturbance and on-load switch disturb 5 kinds of situations and work as WAEFor negative number when and value range be negative
8%-17%, illustrate containing voltage decline disturb, work as WAEEqual to WAEvsagIt is that voltage declines, works as WAEEqual to WAEvsag+hrIt is electricity
The compound disturbance of drops and harmonic wave.Work as WAEEqual to WAEvsag+nIt is the compound disturbance of voltage decline and noise.Work as WAEEqual to WAEvi
It is voltage interruption, works as WAEEqual to WAEcsIt is capacitor switch disturbance, works as WAEEqual to WAElsIt is on-load switch disturbance.
4) work as WAEWhen equal to zero, it is believed that do not interfere with signal in power grid, be high-quality power network signal.
5) work as WAEFor positive number when and value range be 0%-1% when, illustrate, containing transient signal, to need to further calculate
WAEabs, work as WAEabsEqual to WAEabs-hftIt is high frequency transient disturbance, works as WAEEqual to WAEabs-lftIt is low frequency transient disturbance.
Method for distinguishing is known in the detection that the present invention provides more disturbing signals under a kind of noise.It can realize comprehensively in a variety of disturbances
In the case of signal interference power grid, it is prepared Classification and Identification, can clearly detect the interference that power grid is really subject to.
Obviously present invention specific implementation is not subject to the restrictions described above, as long as using the methodology and skill of the present invention
The improvement for the various unsubstantialities that art scheme carries out, within protection scope of the present invention.
Claims (6)
1. a kind of grid disturbance signal detection recognition methods, it is characterised in that：The detection recognition method includes acquisition power grid letter
Number, more resolution decompositions are carried out using wavelet transformation to power network signal, by the energy coefficient of each layer of calculating, carry out feature extraction,
Characteristic signal is obtained, classification is identified to the signal of power grid in the signal characteristic information obtained according to extraction.
2. a kind of grid disturbance signal detection recognition methods as described in claim 1, it is characterised in that：Signal characteristic is carried out to carry
When taking, the Multiresolution Decomposition based on wavelet transformation is carried out, morther wavelet chooses db small echo series.
3. a kind of grid disturbance signal detection recognition methods as described in claim 1, it is characterised in that：The method includes profits
Multiresolution Decomposition is carried out with wavelet transformation, N layers of decomposition are carried out to the power network signal of acquisition, are calculated using Parseval's theorem every
The energy of layer, formula are：Wherein the right first item represents
The approximate energy value of decomposed signal, Section 2 represent the decomposed signal energy value of minutia, correspond to respectively：
Ai,jThat represent is the coefficient that signal carries out MSD decomposition, Di,jThe minutia coefficient for representing decomposed signal, respectively from the 1st
Layer arrives l layers；What i was represented is the number of plies of signal decomposition, and what j was represented is scale coefficient, and N represents the following characteristics system of each layer of decomposition
Several numbers, WDiThat represent is i-th layer of Energy Decomposition coefficient, WAlIt is the approximate energy coefficient for carrying out MSD and decomposing l layers；Contain
There is l layers of feature vector of disturbing signal that can indicate as follows：FV(WDDS)=[WD1 WD2 ... WDl WAl]；Sine letter
Number feature vector can be expressed as：FV(WDPS)=[WD1 WD2 ... WDl WAl], then it represents that the vector of the feature of signal can
To be expressed as Δ W=WDDS-WDPS；
Calculate percentage of the characteristic signal Energy-Entropy with respect to sinusoidal signal：
With WAEClassify to all kinds of disturbing signals.
4. a kind of grid disturbance signal detection recognition methods as claimed in claim 3, it is characterised in that：The method further includes
Calculate the absolute percent of signal entropy after MSD is decomposed：
WDSabsRepresent WDDSAbsolute value, WDPSabsRepresent WDPSAbsolute value, W obtained by calculationAEabsDistinguish high frequency components
Signal and low-frequency excitation signal.
5. a kind of grid disturbance signal detection recognition methods as described in claim 3 or 4, it is characterised in that：The method packet
It includes,
WAEWhen more than zero：
(1) work as WAEIt is 18%-28% for positive number and value range, judges the disturbance risen containing voltage, work as WAEEqual to WAEvswell
Rise for voltage, works as WAEEqual to WAEvswell+hrRise the compound disturbance with harmonic wave for voltage, works as WAEEqual to WAEvswell+nFor voltage
Rise the compound disturbance with noise；
(2) work as WAEFor positive number when and value range be 8%-12%, illustrate the disturbance containing voltage flicker, work as WAEEqual to WAEvfIt is
Voltage flicker works as WAEEqual to WAEvf+nIt is the compound disturbance of voltage flicker and noise；
(3) work as WAEFor positive number when and value range be 5%-8%, illustrate the disturbance containing harmonic wave, work as WAEEqual to WAEhrIt is voltage
Harmonic wave works as WAEEqual to WAEabs-hrnIt is the compound disturbance of harmonic wave and noise；
(4) work as WAEFor positive number when and value range be 0%-1%, illustrate containing transient disturbance,
WAEWhen less than zero：
Work as WAEFor negative when and value range be negative 8%-17%, illustrate to decline containing voltage and disturb, work as WAEEqual to WAEvsagIt is
Voltage declines, and works as WAEEqual to WAEvsag+hrIt is the compound disturbance of voltage decline and harmonic wave；
Work as WAEEqual to WAEvsag+nIt is the compound disturbance of voltage decline and noise；Work as WAEEqual to WAEviIt is voltage interruption, works as WAEIt is equal to
WAEcsIt is capacitor switch disturbance, works as WAEEqual to WAElsIt is on-load switch disturbance；
Work as WAEWhen equal to zero, it is believed that do not interfere with signal in power grid, be high-quality power network signal.
6. a kind of grid disturbance signal detection recognition methods as claimed in claim 5, it is characterised in that：Work as WAEFor positive number when and
When value range is 0%-1%, contains transient signal at this time, further calculate WAEabs, work as WAEabsEqual to WAEabs-hftIt is high frequency
Transient disturbance works as WAEEqual to WAEabs-lftIt is low frequency transient disturbance.
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