CN109490701A - A kind of power frequency series arc faults detection method - Google Patents

A kind of power frequency series arc faults detection method Download PDF

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CN109490701A
CN109490701A CN201811079728.2A CN201811079728A CN109490701A CN 109490701 A CN109490701 A CN 109490701A CN 201811079728 A CN201811079728 A CN 201811079728A CN 109490701 A CN109490701 A CN 109490701A
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amplitude
power frequency
detection method
calculates
current data
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CN109490701B (en
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江军
文哲
张潮海
韩啸
谭敏刚
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis

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  • Mathematical Physics (AREA)
  • Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)

Abstract

The invention discloses a kind of power frequency series arc faults detection methods, belong to circuit running protection field.The present invention, which passes through the current data in Acquisition Circuit and carries out Fast Fourier Transform (FFT) to it, obtains spectrogram；Then, it counts the amplitude of fundamental wave and each harmonic and calculates the ratio of each harmonic amplitude and fundamental voltage amplitude；Finally, built-in matrix is added in the ratio of each harmonic amplitude and fundamental voltage amplitude, then carries out principal component analysis, that is, PCA and calculate；By obtained principal component matrix export, and with compared to threshold value, determine load class and affiliated operating status；Its zero section length also is calculated to obtained raw current data simultaneously; equally compared with threshold value; when the two conditions meet simultaneously; can think that arc fault has occurred; this method can identify different loads and accuracy with higher; circuit can be effectively protected, it is ensured that user being capable of safety utilization of electric power.

Description

A kind of power frequency series arc faults detection method
Technical field
The present invention relates to a kind of power frequency series arc faults detection methods, belong to circuit running protection field.
Background technique
Electric arc is a kind of self-maintained discharge phenomenon for issuing strong light and heat, when occurring non-human wish in alive circuit Arc fault has occurred when electric arc.Arc fault includes series arc faults, parallel arc fault and composite arc failure, Wherein parallel arc fault and the fault current of composite arc failure are very big, are easy to be switched off device disconnection, but serial arc The electric current very little of failure, is not easy to be found, once occurring, will result in very big life and property loss.
It is counted according to the Fire Department of Ministry of Public Security, only in 2016, the whole nation is informed of a case fire 31.2 ten thousand altogether, dies 1582 people, wound 1065 People, 37.2 hundred million yuan of direct property loss, wherein electrically installing and using regulation etc. in terms of the immediate cause for causing fire because of violation and drawing Electricity gas fire accounts for the 30.4% of total amount, and in large-sized fire, this ratio rises to 50%.And in these electrical fires, It is also the highest fire of incidence that fire caused by fault electric arc, which is most dangerous,.
And the research of China's low-voltage distribution field breakdown arc prevention technology at present still belongs to blank, the country does not set up event Hinder the database of electric arc, the marketization production of AFCI (arc-fault circuit interrupter) is still in infancy, therefore one is suitable for The low voltage series fault electric arc detection technique of China's electric system has great application prospect.
Summary of the invention
The invention proposes a kind of power frequency series arc faults detection method, this method passes through in sensor Acquisition Circuit Then electric current is handled Wave data using Fast Fourier Transform (FFT), obtain its spectrum information, then count each harmonic With the amplitude ratio of fundamental wave and carry out principal component analysis and carry out dimensionality reduction obtaining new characteristic value, while zero area's accounting is added as auxiliary Criterion is helped, to judge loadtype and whether arc fault have occurred.
The present invention is to solve its technical problem to adopt the following technical scheme that
A kind of power frequency series arc faults detection method, including the following steps:
Step S1, the current data in Acquisition Circuit；
Step S2 seeks its each harmonic amplitude and the ratio between harmonic amplitude and fundamental voltage amplitude to collected current data Rn；
Step S3, by obtained harmonic amplitude ratio RnOnboard data collection is added and carries out PCA calculating；
Step S4 exports RnCorresponding principal component characteristic value and and threshold value comparison, judge loadtype and operating status, if For malfunction, then carry out in next step, if normal condition, then return step S1；
Step S5 executes zero area's assistant criteria；
Step S6, if zero area's assistant criteria meets, arc fault is had occurred in judgement, and provides loadtype.
In step S1, the current data in circuit is acquired in real time by sensor, the sample frequency fs of sensor ≥1kHz。
It is specific to execute shown in steps are as follows in step S2:
Step S2.1 carries out FFT calculating to collected current data；
Step S2.2 counts fundamental voltage amplitude Im1With each harmonic amplitude Imn, wherein n=2-10, and n takes positive integer；
Step S2.3 calculates the ratio between each harmonic amplitude and fundamental voltage amplitudeWherein n=2-10, and n take it is just whole Number.
It is specific to execute shown in steps are as follows in step S3:
Obtained Amplitude Ration addition onboard data collection is obtained new data set D by step S3.1；
Step S3.2 carries out PCA to obtained data set D and principal component matrix is calculated；
Step S3.3 calculates the covariance matrix Y=Cov (D) of data set D；
Step S3.4 calculates the feature vector and characteristic value of covariance matrix Y；
Step S3.5 is arranged according to characteristic value size, is retained 2-3 feature vector and is formed new matrix U；
Step S3.6 calculates new principal component Matrix C=YTD。
It is specific to execute shown in steps are as follows in step S4:
Step S4.1 exports RnCorresponding principal component characteristic value Cm；
Step S4.2 compares C1-Cm, it determines loadtype and operating status, if malfunction, then performs the next step, If normal condition, then return step S1；
In S5, it is shown that specific step is as follows:
Step S5.1 seeks absolute value to collected Wave data；
Step S5.2 seeks waveform maximum value I to the waveform after absolute value is acquiredmax；
Step S5.3 calculates waveform threshold value IT=Imax/10；
Step S5.4 counts all in raw current data and is lower than threshold value ITThe sum of sampling number S2；
Step S5.5 calculates K=S2/ S, wherein S is that the sampling of raw current data is always counted.
Detailed process is as follows by step S6, and specific Rule of judgment is whether zero area accounting K is more than or equal to 0.11, if meeting item Part then determines that arc fault has occurred and provides loadtype according to the result of S4；If being unsatisfactory for condition, return step S1.
Beneficial effects of the present invention are as follows:
The present invention carries out principal component analysis to it based on the spectrum information of current signal and new characteristic value is calculated, It can distinguish different loads and different operating statuses, while zero area's accounting assistant criteria is added, from frequency domain and time domain Angle has carried out analytical calculation, and the accuracy by setting up different threshold values to guarantee detection effect to current waveform, it is ensured that Arc fault can be detected fast and efficiently.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart.
Fig. 2 is harmonic wave and ratio calculation flow chart.
Fig. 3 is PCA calculation flow chart.
Zero area's assistant criteria flow chart of Tu4Wei.
Fig. 5 is the current waveform that certain sampling under certain load obtains.
Fig. 6 is current waveform FFT spectrum figure.
Specific embodiment
The present invention is described in detail with reference to the accompanying drawing:
It is obtained as shown in Figure 1, the present invention carries out PCA (principal component analysis) calculating progress dimensionality reduction by the frequency spectrum to current signal To characteristic value, while zero area's accounting of waveform is calculated, proposes a kind of power frequency series arc faults detection method, this method includes Following steps:
Step S1, the current data in Acquisition Circuit；
In step S1, for guarantee step S2 in Fast Fourier Transform (FFT) result accuracy, by nyquist sampling theorem Sample frequency, which can be obtained, should be greater than 2 times equal to highest frequency, the sample frequency f of sensors≥1kHz。
Step S2 seeks its each harmonic amplitude and the ratio between harmonic amplitude and fundamental voltage amplitude to collected current data Rn；
In step S2, specific execution step is as shown in Figure 2:
Step S2.1 carries out FFT (Fast Fourier Transform (FFT)) to collected current data and calculates；
Step S2.2 counts fundamental voltage amplitude Im1With each harmonic amplitude Imn(n=2-10, n take positive integer).
Step S2.3 calculates the ratio between each harmonic amplitude and fundamental voltage amplitude(n=2-10, n take positive integer).
Step S3, by obtained harmonic amplitude ratio RnOnboard data collection is added and carries out PCA calculating；
In step S3, specific execution step is as shown in Figure 3:
Obtained Amplitude Ration addition onboard data collection is obtained new data set D by step S3.1；
Step S3.2 carries out PCA to obtained data set D and principal component matrix is calculated；
Step S3.3 calculates the covariance matrix Y=Cov (D) of data set D；
Step S3.4 calculates the feature vector and characteristic value of covariance matrix Y；
Step S3.5 is arranged according to characteristic value size, is retained suitable M feature vector and is formed new matrix U；
Step S3.6 calculates new principal component Matrix C=YTD, T represent transposition, i.e. YTFor the transposed matrix of Y；
Step S4 exports RnCorresponding principal component characteristic value and and threshold value comparison, judge loadtype and operating status；
In step S4, the specific execution of threshold comparison is shown in steps are as follows:
Step S4.1 exports RnCorresponding principal component characteristic value Cm；
Step S4.2 compares C1-Cm, it determines loadtype and operating status, if malfunction, then performs the next step, If normal condition, then return step S1；
Step S5 executes zero area's assistant criteria；
In step S5, the step of zero area's assistant criteria execution part, is as shown in Figure 4:
Step S5.1 seeks absolute value to collected Wave data；
Step S5.2 seeks waveform maximum value I to the waveform after absolute value is acquiredmax；
Step S5.3 calculates waveform threshold value IT=Imax/10；
Step S5.4 counts all in raw current data and is lower than threshold value ITThe sum of sampling number S2；
Step S5.5 calculates K=S2/ S, wherein S is that the sampling of raw current data is always counted；
Step S6 can determine that and arc fault has occurred, and provide loadtype if zero area's assistant criteria meets；；
In step S6, specific Rule of judgment is whether K is more than or equal to 0.11, if meeting condition, electricity is had occurred in judgement Arc failure simultaneously provides loadtype according to the result of S4；If being unsatisfactory for condition, return step S1.
This method is specifically described below with reference to example, but this should not be interpreted as to the range of the above-mentioned theme of the present invention It is only limitted to embodiment below, it is all to be all belonged to the scope of the present invention based on the technology that the content of present invention is realized.
Current data first in Acquisition Circuit, sample frequency fs=1.25MHz, sampling period number are 5, sampling number S=2500, obtained waveform diagram are as shown in Figure 5.
Next, carrying out Fast Fourier Transform (FFT) to Wave data, spectrogram is obtained as shown in fig. 6, spectrogram is exported It is as shown in table 1 to table.
Spectrum results after 1 sample waveform FFT of table
Frequency (Hz) Amplitude (A) Frequency (Hz) Amplitude (A) Frequency (Hz) Amplitude (A) Frequency (Hz) Amplitude (A) Frequency (Hz) Amplitude (A)
10 0.003168 110 0.004428 210 0.004287 310 0.004077 410 0.002127
20 0.002316 120 0.003433 220 0.002707 320 0.002879 420 0.001675
30 0.00116 130 0.002544 230 0.004547 330 0.003619 430 0.004582
40 0.378712 140 0.024081 240 0.026295 340 0.015104 440 0.015706
50 0.750856 150 0.044535 250 0.04308 350 0.024773 450 0.023847
60 0.372113 160 0.024322 260 0.022147 360 0.012833 460 0.011267
70 0.001746 170 0.002497 270 0.00218 370 0.000928 470 0.001188
80 0.00199 180 0.001823 280 0.001342 380 0.00092 480 0.001798
90 0.004317 190 0.003522 290 0.002418 390 0.002847 490 0.003321
100 0.004859 200 0.004194 300 0.003721 400 0.003915 500 0.003268
Fundamental voltage amplitude and each harmonic amplitude are counted by the table, each harmonic and fundamental voltage amplitude after statistics simultaneously calculate each The amplitude ratio of subharmonic and fundamental wave is as shown in the table:
2 fundamental wave of table and each harmonic amplitude and ratio
For calculate and derived simplicity, by ratio RnThe last line that onboard data collection is added obtains new data set D, Onboard data integrates the sample data of the different operating statuses as different loads, and part of data are as shown in the table, wherein each One sample of behavior, each amplitude ratio for being classified as a kind of harmonic wave and fundamental wave, since the ratio between 2 subharmonic and fundamental voltage amplitude 2/1, Total 9 column:
3 onboard data collection (part) of table
2/1 3/1 4/1 5/1 6/1 7/1 8/1 9/1 10/1
0.004605 0.571571 0.000499 0.340038 0.00207 0.256996 0.001321 0.172801 0.000796
0.003671 0.571057 0.00114 0.339484 0.001544 0.262031 0.000998 0.172926 0.002288
0.003524 0.571288 0.000994 0.340813 0.002402 0.257808 0.000889 0.172095 0.003141
0.003117 0.576952 0.003047 0.340024 0.002761 0.258102 0.000527 0.163757 0.002829
0.002848 0.57335 0.001823 0.343117 0.001604 0.263931 0.002886 0.174907 0.001257
0.004722 0.567805 0.001068 0.345945 0.00287 0.259424 0.003018 0.177468 0.000514
3.15E-03 0.578271 0.001963 0.34479 0.00153 0.268077 0.001707 0.172359 0.003361
0.001736 0.59684 0.000837 0.32651 0.000723 0.266068 0.001978 0.145804 0.001597
The covariance matrix Y of data set D is calculated first, and specific calculation formula is as follows:
Wherein XnFor the column vector of data set D, it is as follows to substitute into the covariance matrix obtained after data calculate by value 1-9 It is shown:
Because sharing 9 column vectors, obtained covariance matrix is 9 × 9 matrixes.
The characteristic value and feature vector and according to big minispread for calculating covariance matrix in next step, as a result such as following table institute Show:
4 characteristic value of table
Characteristic value
0.30134
0.03501
0.01069
0.00899
0.00297
0.00106
0.00005
0.00028
0.00027
5 feature vector of table
1 2 3 4 5 6 7 8 9
-0.277 -0.394 0.330 -0.575 -0.436 0.221 0.095 0.236 0.161
-0.536 0.473 0.640 0.138 0.221 0.088 -0.004 -0.028 -0.063
-0.316 -0.430 0.031 -0.153 0.117 -0.385 -0.208 -0.555 -0.423
-0.421 0.297 -0.345 0.109 -0.545 -0.461 -0.041 0.277 -0.127
-0.311 -0.368 -0.066 0.216 0.395 -0.263 -0.248 0.320 0.573
-0.295 0.267 -0.387 -0.242 -0.019 0.209 0.076 -0.564 0.515
-0.283 -0.296 -0.145 0.356 0.067 0.141 0.803 -0.003 -0.127
-0.209 0.138 -0.394 -0.475 0.500 0.195 -0.015 0.372 -0.361
-0.228 -0.188 -0.179 0.398 -0.200 0.642 -0.484 -0.008 -0.187
In next step for guarantee judgement accuracy, retain 3 feature vectors, i.e. first three columns form new matrix U, then it is main at Sub-matrix C=YTD, the result being calculated are as shown in the table:
6 principal component matrix of table
C1 C2 C3
-0.56407 -0.46019 -0.08109
-0.5651 -0.46124 -0.07848
-0.56471 -0.46019 -0.07989
-0.56623 -0.46087 -0.08697
-0.56914 -0.46383 -0.07683
-0.5671 -0.46041 -0.07367
-0.57342 -0.46721 -0.0787
-0.56822 -0.46797 -0.10797
-0.57419 -0.46612 -0.08546
-0.57028 -0.46293 -0.07535
… … …
-0.07987 -0.0491 0.00679
Finally export RnThe characteristic value C of corresponding composition characteristics value namely last line out1=-0.07987, C2=- 0.0491, C3=0.00679, threshold value table is as follows:
7 threshold comparison table of table
Comparison is as can be seen that the waveform is the failure operation state of resistive load, therefore executes zero area's assistant criteria.
The amplitude of primary current waveform is 0.78A, therefore waveform threshold value IT=Imax/ 10=0.78/10=0.078A, system It counts absolute value in raw current data and is less than waveform threshold value ITThe sum of points S2=422, calculate zero area accounting K=S2/ S= 422/2500=0.169 is greater than given threshold value 0.11, therefore, it is determined that for arc fault has occurred, while loading is resistive load.
The above content is specific embodiment is combined, further detailed description of the invention, and it cannot be said that this hair Bright specific implementation is only limited to these instructions.For general technical staff of the technical field of the invention it should be known that Under the premise of not departing from present inventive concept, several simple deductions or substitution can also be made, all shall be regarded as belonging to of the invention Protection scope.

Claims (7)

1. a kind of power frequency series arc faults detection method, which is characterized in that including the following steps:
Step S1, the current data in Acquisition Circuit；
Step S2 seeks its each harmonic amplitude and the ratio between harmonic amplitude and fundamental voltage amplitude R to collected current datan；
Step S3, by obtained harmonic amplitude ratio RnOnboard data collection is added and carries out PCA calculating；
Step S4 exports RnCorresponding principal component characteristic value and and threshold value comparison, judge loadtype and operating status, if therefore Barrier state then carries out in next step, if normal condition, then return step S1；
Step S5 executes zero area's assistant criteria；
Step S6, if zero area's assistant criteria meets, arc fault is had occurred in judgement, and provides loadtype.
2. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: in step S1, lead to It crosses sensor to acquire the current data in circuit in real time, sample frequency fs >=1kHz of sensor.
3. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: in step S2, tool The execution of body is shown in steps are as follows:
Step S2.1 carries out FFT calculating to collected current data；
Step S2.2 counts fundamental voltage amplitude Im1With each harmonic amplitude Imn, wherein n=2-10, and n takes positive integer；
Step S2.3 calculates the ratio between each harmonic amplitude and fundamental voltage amplitudeWherein n=2-10, and n takes positive integer.
4. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: in step S3, tool The execution of body is shown in steps are as follows:
Obtained Amplitude Ration addition onboard data collection is obtained new data set D by step S3.1；
Step S3.2 carries out PCA to obtained data set D and principal component matrix is calculated；
Step S3.3 calculates the covariance matrix Y=Cov (D) of data set D；
Step S3.4 calculates the feature vector and characteristic value of covariance matrix Y；
Step S3.5 is arranged according to characteristic value size, is retained 2-3 feature vector and is formed new matrix U；
Step S3.6 calculates new principal component Matrix C=YTD。
5. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: in step S4, tool Body executes shown in steps are as follows:
Step S4.1 exports RnCorresponding principal component characteristic value Cm；
Step S4.2 compares C1-Cm, it determines loadtype and operating status, if malfunction, then performs the next step, if Normal condition, then return step S1.
6. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: in step S5, tool Body is shown in steps are as follows:
Step S5.1 seeks absolute value to collected Wave data；
Step S5.2 seeks waveform maximum value I to the waveform after absolute value is acquiredmax；
Step S5.3 calculates waveform threshold value IT=Imax/10；
Step S5.4 counts all in raw current data and is lower than threshold value ITThe sum of sampling number S2；
Step S5.5 calculates K=S2/ S, wherein S is that the sampling of raw current data is always counted.
7. a kind of power frequency series arc faults detection method according to claim 1, it is characterised in that: the specific mistake of step S6 Journey is as follows, and specific Rule of judgment is whether zero area accounting K is more than or equal to 0.11, if meeting condition, electric arc is had occurred in judgement Failure simultaneously provides loadtype according to the result of S4；If being unsatisfactory for condition, return step S1.
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