CN107144769A - The three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range - Google Patents
The three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range Download PDFInfo
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- CN107144769A CN107144769A CN201710250576.7A CN201710250576A CN107144769A CN 107144769 A CN107144769 A CN 107144769A CN 201710250576 A CN201710250576 A CN 201710250576A CN 107144769 A CN107144769 A CN 107144769A
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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
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering 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
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
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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
- G06F2218/16—Classification; Matching by matching signal segments
- G06F2218/18—Classification; Matching by matching signal segments by plotting the signal segments against each other, e.g. analysing scattergrams
Abstract
The invention discloses a kind of three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range, belong to power equipment Partial Discharge Detecting Technology field, in this method, propose a kind of new hyperfrequency single wave analyzing device based on statistical thinking, FFT is carried out to multiple single waveforms of electric discharge type of the same race, count maximum of the multiple single waveforms of same electric discharge type in each Frequency point, discharge frequency peak maximum distribution spectrogram Hmax (f) is obtained, " discharge frequency amplitude and " F of multiple frequency bands is calculatedmaxAnd its account for the proportion K of whole frequency band " amplitude and "max, and calculate the K of different any three frequency bands of electric discharge typemaxCorresponding Euclidean space distance, three maximum optimal frequency bands of selection theorem in Euclid space distance average, draws KmaxThree-dimensional cluster spectrogram, realize the regional branch office's portion's electric discharge type of simple, intuitive.
Description
Technical field
The invention belongs to power equipment Partial Discharge Detecting Technology field, and in particular to one kind is based on different frequency range electric discharge width
It is worth the three-dimensional clustering recognition method of shelf depreciation of sum, the identification for power equipment shelf depreciation type.
Background technology
The insulating materials of power equipment is to ensure the significant components that power equipment is normally run, but is due to that insulating materials exists
Aging or insulating materials manufacturing deficiency under forceful electric power field action, occur local put in power equipment operation inside insulating materials
Electricity, the development of shelf depreciation can accelerate the aging of insulating materials, so as to cause the power equipment lost of life, so must send out as early as possible
Now with the type of identification shelf depreciation, slow down the aging of power equipment using measure.
Pulse current of PD signal is ns grades of pulse signals, and pulse current is broadband signal, its superelevation excited
Frequency electromagnetic waves signal is similarly broadband signal, and bandwidth is from tens MHz to upper GHz, and based on the part of electromagnetic wave coupling principle
The Measurement bandwidth of electric discharge ultra-high-frequency detection can reach tens MHz to upper GHz frequency, so being examined using local discharge superhigh frequency
Survey the shelf depreciation frequency information that can be measured that more horn of plenty.
Because the pulse current waveform of different electric discharge types is not quite similar, the frequency letter that its electromagnetic wave signal excited is included
Breath is also not all the same, so can very effectively distinguish shelf depreciation class by extracting these shelf depreciation frequency information features
Type, mainly uses the information of different frequency sections to carry out shelf depreciation type identification, also utilizes wavelet decomposition in numerous researchs
Mode extract characteristic parameter, characteristic parameter has energy feature parameter, and fractal characteristic parameter also achieves relatively good result.
The content of the invention
The invention aims to solve more efficient extraction to recognize the shelf depreciation electromagnetism of shelf depreciation type
The problem of wave energy measure feature there is provided a kind of three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range,
And demonstrate the validity in shelf depreciation type identification.
To reach above-mentioned purpose, the present invention adopts the following technical scheme that to realize：
The three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range, is comprised the following steps：
1) multiple local discharge superhigh frequency single waveforms of a variety of electric discharge types are gathered, to each local discharge superhigh frequency list
Secondary waveform carries out FFT to frequency domain, obtains FFT sequences (x, f), wherein x=[x1,x2,….xi,…xm], x length is m,
xiIt is the amplitude of each FFT point, f is frequency array, f=[f1,f2,….fi,…fm], fiFor Frequency point, f length is
m；
2) the same multiple single waveforms of electric discharge type are counted in the maximum of each Frequency point, discharge frequency peak are obtained most
The distribution spectrogram H being worth greatlymax(f) H, is calculatedmax(f) the discharge frequency amplitude and F in the range of 0~2500MHzmax；
3) local discharge signal basic frequency section 0~2500MHz scopes are divided into multiple frequency ranges again, calculate each frequency range
Fmaxi；
4) F of each frequency range is calculatedmaxiRelative to whole frequency band FmaxRate of specific gravity Kmaxi；
5) three suitable frequency range k, j and l K are selectedmax-k、Kmax-jAnd Kmax-lRespectively as X-coordinate, Y-coordinate and Z coordinate,
Build the three-dimensional frequency range identification figure of local discharge signal, the type identification for different shelf depreciations.
Of the invention further improve be, step 2) in discharge frequency amplitude and FmaxCalculation formula it is as follows：
Wherein i is Frequency point, and N counts for the sum frequency of FFT, xiFor the amplitude of each FFT point.
Of the invention further improve be, step 3) 0~2500MHz points of local discharge signal basic frequency section is six frequencies
Rate section, is represented, wherein i=1,2,3,4,5,6, i.e. 0≤fb1 with fbi<100MHz, 100≤fb2 ＜ 200MHz, 200≤fb3 ＜
300MHz, 300≤fb4 ＜ 500MHz, 500≤fb5 ＜ 1000MHz and 1000≤f6≤2500MHz.
The present invention, which is further improved, to be, step 4) the middle F for calculating each frequency rangemaxiRelative to the rate of specific gravity of whole frequency domain
KmaxiSpecific formula it is as follows：
N in formulafFor the number of frequency range.
Of the invention further improve be, step 5) optimal the frequency range k, j and l of selection three Kmax-k, Kmax-jWith
Kmax-lMethod respectively as X-coordinate, Y-coordinate and Z coordinate is as follows：
501) to step 2) in six frequency bands KmaxAny three combinations (k, j, l), constitute one group of (Kmax-k, Kmax-j,
Kmax-l) coordinate；
502) three-dimensional between the electric discharge type not of the same race under different frequency range combination is quantitatively calculated using theorem in Euclid space Furthest Neighbor
Poly- data point (Kmaxk, Kmaxj, Kmax-l) the distance between d, formula is as follows：
Wherein a and b represent two kinds of electric discharge types, Kmax-k、Kmax-jAnd Kmax-lRepresent two kinds of electric discharge types in k, j and l frequency
The upper F of sectionmaxiRelative to the rate of specific gravity K of whole frequency domainmaxi；
401) and 402) 503) repeat the above steps and obtain theorem in Euclid space distance between one group of different electric discharge type, take it
The maximum one group of frequency range combination of middle Euclidean distance d average value, as suitable frequency range combination；
504) with the K of three frequency ranges chosenmaxDraw (the K of different electric discharge typesmaxk, Kmaxj, Kmax-l) coordinate points,
Obtain the three-dimensional frequency range clustering recognition figure of local discharge signal.
Compared with prior art, the present invention has following innovative point：
1. by counting a large amount of shelf depreciation electromagnetic wave signal frequecy characteristics, it is determined that high-frequency local discharging signal characteristic
Frequency band, and calculate " frequency amplitude and " F of different frequency sectionsmax, and the proportion K in whole frequency bandmax；
2. the method for finding optimal three frequency bands combination is determined, and utilize the corresponding K of these three frequency bandsmaxPaint
Three-dimensional dendrogram has been made, different electric discharge types more can be significantly distinguished.
Compared with prior art, the present invention has following remarkable advantage：
1st, a kind of new hyperfrequency single wave analyzing device based on statistical thinking is proposed, to many of electric discharge type of the same race
Individual single waveform carries out FFT, counts the same multiple single waveforms of electric discharge type in the maximum of each Frequency point, obtains
Discharge frequency peak maximum distribution spectrogram Hmax(f)；
2nd, propose and three optimal frequency bands are determined using Euclidean distance, utilize " the electric discharge frequency of these three frequency bands
Rate amplitude and " FmaxProportion Kmax, drawing three-dimensional cluster spectrogram, can show to simple, intuitive the classification knot of shelf depreciation
Really.
In summary, the present invention proposes a kind of effective from multiple multiple frequency bands of local discharge superhigh frequency single waveform
Extract " discharge frequency amplitude and " FmaxAnd the proportion K in whole frequency bandmax, and determine three most preferably using Euclidean distance
The K of frequency bandmaxThe method of reflection shelf depreciation classifying quality directly perceived.
Brief description of the drawings
Fig. 1 is the flow chart of shelf depreciation three-dimensional clustering recognition method of the present invention based on different frequency range electric discharge amplitude sum.
Fig. 2 is the inventive method discharge frequency peak maximum distribution spectrogram Hmax(f) schematic diagram, abscissa is frequency, model
Enclose from 0~2.5GHz, ordinate is maximum amplitude of multiple hyperfrequency single waveforms in a certain Frequency point of electric discharge type of the same race,
Unit is mV.
Fig. 3 is the signal of the theorem in Euclid space distance between the different electric discharge types of the different three-dimensional frequency range combinations of the present invention
Figure.
Fig. 4 is that the inventive method is based on frequency band 300≤fb4 ＜ 500MHz, 500≤fb5 ＜ 1000MHz and 1000≤f6
≤ 2500MHz " discharge frequency amplitude and " FmaxKmaxThree-dimensional dendrogram identification schematic diagram.
Embodiment
The present invention is made further instructions below in conjunction with accompanying drawing.
As shown in figure 1, the basic thought of the present invention is to calculate different frequency sections " discharge frequency amplitude and " FmaxAccount for whole
The proportion K of frequency bandmax, three K of selection optimum frequency sectionmaxDrawing three-dimensional cluster schematic diagram carries out shelf depreciation type knowledge
Not, idiographic flow is as follows：
1) gather in local discharge superhigh frequency signal, the present invention and have selected four kinds of shelf depreciation types, be to suspend to put respectively
Electricity, corona discharge, bubble-discharge and oil wedge discharge, the oscillograph used its with a width of 100MHz~3GHz, its sample rate is
5GS/s, the sensor used is microstrip antenna sensor, and it is with a width of 100MHz~6000MHz；
2) FFT is carried out to frequency domain to multiple hyperfrequency single waveforms of different shelf depreciation types, counted same
The multiple single waveforms of electric discharge type obtain discharge frequency peak maximum distribution spectrogram H in the maximum of each Frequency pointmax(f),
As shown in Fig. 2 calculating Hmax(f) " discharge frequency amplitude and " F in the range of 0~2500MHzmax；
3) local discharge signal main frequency section (0~2500MHz) scope is divided into multiple frequency ranges, the present invention with six
Exemplified by frequency band, be respectively 0~100MHz, 100~200MHz, 200~300MHz, 300~500MHz, 500~1000MHz and
1000~2500MHz, calculates the F of each frequency rangemaxi, and calculate the F of each frequency rangemaxiRelative to whole frequency domain (0~2500MHz)
Rate of specific gravity Kmaxi, formula is as follows：
Wherein i is Frequency point, and N counts for the sum frequency of FFT, xiFor frequency amplitude, Nf is the number of frequency range；
4) three suitable frequency range k, j and l K are selectedmax-k, Kmax-jAnd Kmax-lRespectively as X-coordinate, Y-coordinate and Z coordinate
Method it is as follows：
A) by the K of six frequency bandsmaxAny three combinations (k, j, l), constitute one group of (Kmax-k, Kmax-j, Kmax-l) coordinate；
B) three-dimensional is poly- between the electric discharge type not of the same race under different frequency range combination is quantitatively calculated using theorem in Euclid space Furthest Neighbor
Data point (Kmaxk, Kmaxj, Kmax-l) the distance between d, formula is as follows, as shown in Figure 3：
Wherein a and b represent three kinds of electric discharge types, Kmax-k、Kmax-jAnd Kmax-lRepresent two kinds of electric discharge types in k, j and l frequency
The upper F of sectionmaxiRelative to the rate of specific gravity K of whole frequency domainmaxi；
C) repeat the above steps and a) and b) obtain theorem in Euclid space distance between one group of different electric discharge type, take wherein European
The maximum one group of frequency range combination of space length d average value, as suitable frequency range combination；
5) with the K of three frequency ranges chosenmaxDraw (the K of different electric discharge typesmaxk, Kmaxj, Kmax-l) coordinate points, obtain
To the three-dimensional frequency range clustering recognition figure of local discharge signal, as shown in Figure 4.
Claims (5)
1. the three-dimensional clustering recognition method of shelf depreciation for amplitude sum of being discharged based on different frequency range, it is characterised in that including following step
Suddenly：
1) multiple local discharge superhigh frequency single waveforms of a variety of electric discharge types are gathered, to each local discharge superhigh frequency single ripple
Shape carries out FFT to frequency domain, obtains FFT sequences (x, f), wherein x=[x1,x2,….xi,…xm], x length is m, xiIt is
The amplitude of each FFT point, f is frequency array, f=[f1,f2,….fi,…fm], fiFor Frequency point, f length is m；
2) the same multiple single waveforms of electric discharge type are counted in the maximum of each Frequency point, discharge frequency peak maximum is obtained
Distribution spectrogram Hmax(f) H, is calculatedmax(f) the discharge frequency amplitude and F in the range of 0~2500MHzmax；
3) local discharge signal basic frequency section 0~2500MHz scopes are divided into multiple frequency ranges again, calculate the F of each frequency rangemaxi；
4) F of each frequency range is calculatedmaxiRelative to whole frequency band FmaxRate of specific gravity Kmaxi；
5) three suitable frequency range k, j and l K are selectedmax-k、Kmax-jAnd Kmax-lRespectively as X-coordinate, Y-coordinate and Z coordinate, build
The three-dimensional frequency range identification figure of local discharge signal, the type identification for different shelf depreciations.
2. the three-dimensional clustering recognition method of shelf depreciation of amplitude sum according to claim 1 of being discharged based on different frequency range, its
Be characterised by, step 2) in discharge frequency amplitude and FmaxCalculation formula it is as follows：
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3. the three-dimensional clustering recognition method of shelf depreciation of amplitude sum according to claim 1 of being discharged based on different frequency range, its
It is characterised by, step 3) 0~2500MHz points of local discharge signal basic frequency section is six frequency bands, represented with fbi, wherein i=
1,2,3,4,5,6, i.e. 0≤fb1<100MHz, 100≤fb2 ＜ 200MHz, 200≤fb3 ＜ 300MHz, 300≤fb4 ＜
500MHz, 500≤fb5 ＜ 1000MHz and 1000≤f6≤2500MHz.
4. the three-dimensional clustering recognition method of shelf depreciation of amplitude sum according to claim 3 of being discharged based on different frequency range, its
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5. the three-dimensional clustering recognition method of shelf depreciation of amplitude sum according to claim 4 of being discharged based on different frequency range, its
Be characterised by, step 5) optimal the frequency range k, j and l of selection three Kmax-k, Kmax-jAnd Kmax-lSat respectively as X-coordinate, Y
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501) to step 2) in six frequency bands KmaxAny three combinations (k, j, l), constitute one group of (Kmax-k, Kmax-j,
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502) three-dimensional poly- number between the electric discharge type not of the same race under different frequency range combination is quantitatively calculated using theorem in Euclid space Furthest Neighbor
Strong point (Kmaxk, Kmaxj, Kmax-l) the distance between d, formula is as follows：
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On FmaxiRelative to the rate of specific gravity K of whole frequency domainmaxi；
401) and 402) 503) repeat the above steps and obtain theorem in Euclid space distance between one group of different electric discharge type, take its Central European
Formula is apart from the maximum one group of frequency range combination of d average value, as suitable frequency range combination；
504) with the K of three frequency ranges chosenmaxDraw (the K of different electric discharge typesmaxk, Kmaxj, Kmax-l) coordinate points, obtain office
The three-dimensional frequency range clustering recognition figure of portion's discharge signal.
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| CN109581150A (en) * | 2018-12-18 | 2019-04-05 | 国网天津市电力公司电力科学研究院 | Cable fault independent positioning method based on spectral decay characteristic |
| CN109581150B (en) * | 2018-12-18 | 2020-11-03 | 国网天津市电力公司电力科学研究院 | Cable fault point positioning method based on frequency spectrum attenuation characteristics |
| CN110190924A (en) * | 2019-05-17 | 2019-08-30 | 中科融通物联科技无锡有限公司 | A kind of frequency hopping unmanned plane defence method and device |
| CN111007369A (en) * | 2019-12-27 | 2020-04-14 | 广东电网有限责任公司电力科学研究院 | Ultrahigh frequency electromagnetic wave signal arrival time difference calculation method and device |
| CN111474451A (en) * | 2020-04-26 | 2020-07-31 | 威胜集团有限公司 | Detection method and device for improving fault arc accuracy and readable storage medium |
| CN112198399A (en) * | 2020-09-07 | 2021-01-08 | 红相股份有限公司 | Identification method and terminal for multi-source electromagnetic wave signals |
| CN112198399B (en) * | 2020-09-07 | 2023-12-19 | 红相股份有限公司 | Multi-source electromagnetic wave signal identification method and terminal |
| CN113625133A (en) * | 2021-08-06 | 2021-11-09 | 郴州市东塘电气设备有限公司 | Online monitoring feedback system and method for partial discharge of power distribution equipment |
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