CN104237713B - Deformation of transformer winding diagnostic method based on wavelet transform - Google Patents
Deformation of transformer winding diagnostic method based on wavelet transform Download PDFInfo
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Abstract
The present invention provides a kind of deformation of transformer winding diagnostic method based on wavelet transform, and discrete small wave converting method is applied in the diagnosis of deformation of transformer winding frequency response analysis by it.The measured waveform that the present invention utilizes wavelet transform to obtain frequency response analysis carries out resolution process with reference waveform in many levels, then the smoothed data after utilization processes carries out mathematical statistics analysis, and according to the deformation degree of corresponding criterion diagnosis Transformer Winding.This kind of diagnostic mode can effectively reduce and be caused the error of conventional diagnostic pattern by white noise interference during frequency response measurement and the strongest noise spot of some local, can be with Accurate Diagnosis deformation of transformer winding degree, for the determination methods that the estimation offer of transformer fault type and fault progression trend is new.
Description
Technical field
The present invention relates to deformation of transformer winding diagnostic field, specifically a kind of based on discrete wavelet
The deformation of transformer winding diagnostic method of conversion.
Background technology
According to the incomplete statistics of State Grid Corporation of China, national grid system was at 2002 to 2006
Year this five-year period, electric pressure 110kV and above transformator have an accident total
162 times, this has become power system and has realized the Tough questions that safe and stable operation is faced.
When especially main transformer and electromotor are joined directly together, the impaired of it will force electromotor to stop sending out
Electricity, has an accident when large-scale power transformer runs in systems, may cause large-area power-cuts,
Maintenance after coil is impaired is highly difficult, and its turn(a)round typically wants half a year more than, spends very big,
Affect face very wide, severely impact the safe and reliable operation of power system.
At present, the method for existing detection deformation of transformer winding includes: short circuit impedance method, shake
Dynamic KLR signal approach, frequency response analysis.Short circuit impedance method is the tradition judging winding failure
Method, has the advantages such as the shortest, but sensitivity is the highest;Analysis of vibration signal method is according to oil
Vibration signal on case judges the state of transformator, it is impossible to reflection short circuit in winding fault comprehensively,
By external influence many factors;Frequency response analysis is a kind of measurement on wider frequency band
Analyze winding frequency response characteristic, it is judged that the method for winding state, have highly sensitive, connect
The advantages such as line is simple, bandwidth, have been widely used in deformation of transformer winding detection.
But, further investigations have shown that, frequency response analysis yet suffers from following defect
Or not enough: exist easily disturbed by background noise, low frequency resolution is relatively low, driving source energy
The problems such as limitation.In the deformation of transformer winding of frequency response analysis diagnoses, rely primarily on
Relatively practical frequency response curve and the difference degree of reference waveform, thus the process of signal and spy
Levy the extraction of parameter it is critical that.The interference of measured signal mainly comprises two classes: a class is
White noise, signal amplitude is relatively low, but runs through whole measurement always;Two classes are some local
The strongest noise spot.More precisely to reflect winding deformation, it is desirable to have effect rejects interference
The impact of signal.Therefore, need badly in correlative technology field find more sophisticated transformator around
Group deformation diagnostic method, in order to solve the defect of prior art.
Summary of the invention
The present invention provides a kind of deformation of transformer winding diagnostic method based on wavelet transform,
Can effectively reduce and be disturbed with some local the most relatively by white noise during frequency response measurement
Strong noise spot and cause the error of conventional diagnostic pattern, can be with Accurate Diagnosis Transformer Winding shape
Range degree, for the judgement side that the estimation offer of transformer fault type and fault progression trend is new
Method.
A kind of deformation of transformer winding diagnostic method based on wavelet transform, it is characterised in that
Comprise the steps:
Step one: the sine wave exciting signal to the low pressure winding terminal applying different frequency of transformator
Encourage, gather the frequency response signal of transformator, by frequency response signal divided by excitation letter
Number obtain transformer frequencies response measured waveform, the frequency range of measured waveform and reference waveform is
1Hz-1MHz;
Step 2: respectively measured waveform and reference waveform are carried out multilamellar wavelet transform, real
Existing denoising and the smoothing of waveform;
Step 3: measured waveform and reference waveform after the most successively relative analysis smoothing processing
Data difference: from 1Hz start to high-frequency range detect the most high layer smoothing processing reality
Survey waveform and the data difference of reference waveform inspection, when described data difference exceedes a certain threshold value,
Record to should the frequency of discrepancy as abnormal frequency point, simultaneously using this abnormal frequency point as
The frequency starting point that the measured waveform of next layer of smoothing processing and reference waveform compare, if last layer
The no abnormal Frequency point of smoothing processing, then next layer of smoothing processing compares from the beginning of 1Hz,
Until ground floor smoothing processing Difference test completes;
Step 4: by the measured waveform after two-layer smoothing processing neighbouring in step 3 and reference waveform
The frequency range that two abnormal frequency point that contrast obtains comprise is as abnormal frequency band, to abnormal frequency
Wave data in band carries out ratio MM based on min-max value and the number of correlation coefficient CC
Learn Indexes Comparison, contrast in order to measured waveform after quantitative analysis smoothing processing and reference waveform and obtain
The data difference of abnormal frequency band, carry out the supplemental diagnostics of fault, the ratio of min-max value
The expression formula of MM and correlation coefficient CC is
Wherein, y1, y2 are respectively the measured waveform after smoothing processing and reference waveform, and n is number
The number at strong point;
Step 5: according to supplemental diagnostics criterion based on mathematical criterion, when min-max value it
When all meeting certain condition than MM and correlation coefficient CC, determine fault type and the order of severity.
Further, described step 4 is particularly as follows: when MM < 0.9 and CC < when 0.96, recognize
For there is obvious winding deformation;When 0.9 < MM < 0.96 and 0.96 < CC < when 0.98, Ke Nengcun
At slight deformation;As MM > 0.96 and CC > 0.98 time, without winding deformation.
The present invention compared with prior art, mainly possesses following technological merit:
1, by the change of multilamellar discrete wavelet, the experiment curv of frequency response analysis is put down
Sliding process, it is possible to filter white noise and the strong jamming of local simultaneously, retain the feature of primary signal,
Improve the precision with reference signal contrast diagnosis, reliability;
2, by the measured waveform of multilamellar wavelet transform and reference waveform are carried out score
Analysis, it can be deduced that the scope of abnormal frequency band occur, more traditional fixed frequency band division has higher
Diagnostic accuracy;
3, by carrying out supplemental diagnostics based on mathematical criterion to comprising abnormal frequency band,
On the basis of detection frequency response curve difference, determine whether that frequency response relative analysis is abnormal
With the relatedness of actual winding deformation, improve the reliability of judgement.
Accompanying drawing explanation
Fig. 1 is the deformation of transformer winding diagnostic system block diagram constructed by the present invention;
Fig. 2 is present invention deformation of transformer winding based on wavelet transform diagnostic method
Schematic flow sheet.
In figure: 1 broadband excitation signal source, 2 signal input build-out resistors, 3 signal inputs
Cable, 4 transformators, 5 signal output cables, 6 signal output matching resistance, 7 is high
Precision oscillograph, 8 host computers.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with
Drawings and Examples, are further elaborated to the present invention.Should be appreciated that this place is retouched
The specific embodiment stated only in order to explain the present invention, is not intended to limit the present invention.Additionally,
As long as technical characteristic involved in each embodiment of invention described below is each other
Between do not constitute conflict just can be mutually combined.
Fig. 1 is according to the deformation of transformer winding diagnostic system block diagram constructed by the present invention.Such as figure
Shown in 1, this deformation of transformer winding diagnostic system mainly include broadband excitation signal source 1,
Signal input build-out resistor 2, signal input cable 3, transformator 4, signal output cable 5,
Signal output matching resistance 6, in high precision oscillograph 7 and host computer 8.In the present embodiment, wide
Frequently exciting signal source uses FRAX-101, and its output signal amplitude is 5V, and frequency range is
1Hz-10MHz.With low by broadband excitation signal source 1 and transformator 4 of signal input cable 3
Pressure winding terminal X is connected, and the sine wave exciting signal that this end imposes different frequency swashs
Encourage, utilize signal output cable 5 pumping signal to be sent into high accuracy oscillograph 7, by coaxially
Shielding line is by the responder x of transformator 4 and output signal build-out resistor 6, in high precision oscillograph
7 are connected, and the response signal of high pressure winding is sent into high accuracy oscillograph 7.In the present embodiment,
Shown transformator 4 is A phase winding test wiring, the in high precision oscillograph of DYn type transformator
7 use Tektronix TDS3052C, and it carries a width of 500MHz, and sample frequency is 5GS/s.
Diagnosing system software part in host computer 8 of the present invention uses Matlab platform development,
There are data extract, analyze and manage function, it is possible to automatically the abnormal frequency band of display, process progress,
Process the function such as images outputting, result output.This system meets deformation of transformer winding diagnosis
The requirements such as accurate measurement, state estimation.
See Fig. 1, Fig. 2, utilize network service, the excitation that high accuracy oscillograph 7 is gathered
Signal uploads to host computer 8 with the data file of frequency response signal.The data literary composition of reference waveform
Part is saved in host computer 8 the most in advance.First pass through frequency response signal to obtain divided by pumping signal
Taking transformer frequencies response measured waveform, the frequency range of measured waveform and reference waveform is
1Hz-1MHz.Measured waveform and reference waveform are carried out multilamellar wavelet transform, this enforcement
In case, the highest wavelet transform carrying out 7 layers.First compare the reality of the 7th layer of smoothing processing
Surveying waveform and reference waveform L7, any one represents a winding deformation extremely.Open from 1Hz
Begin to detect difference to high-frequency range, when measured waveform and the ginseng of the 7th layer of smoothing processing detected
When examining the data difference of waveform inspection more than 1.5dB, record to should the frequency of discrepancy as different
Often Frequency point, simultaneously as the frequency starting point of the 6th layer of smoothing processing waveform comparison.If indifference
Different, then the 6th layer of smoothing processing compares from the beginning of 1Hz, until the 1st layer of smoothing processing difference
Detection completes.
Two that measured waveform after neighbouring two-layer smoothing processing and reference waveform contrast are obtained
The frequency range that individual abnormal frequency point comprises is as abnormal frequency band.Utilize the ratio of min-max value
Wave data in abnormal frequency band is carried out based on mathematical criterion by MM and correlation coefficient CC
Supplemental diagnostics, the expression formula of the ratio MM and correlation coefficient CC of min-max value is
Wherein, y1, y2Being respectively the trial curve after smoothing processing and reference waveform, n is number
The number at strong point.In the implementation case, when MM < 0.9 and CC are < when 0.96, it is believed that exist
Substantially winding deformation;When 0.9 < MM < 0.96 and 0.96 < CC < when 0.98, it is understood that there may be slight
Deformation;As MM > 0.96 and CC > 0.98 time, without winding deformation.
The above, the only detailed description of the invention of the present invention, but protection scope of the present invention is also
Being not limited to this, any those skilled in the art of belonging to are at the technology model that the invention discloses
In enclosing, the change that can readily occur in or replacement, all should contain within protection scope of the present invention.
Claims (1)
1. a deformation of transformer winding diagnostic method based on wavelet transform, its feature
It is to comprise the steps:
Step one: the sine wave exciting signal to the low pressure winding terminal applying different frequency of transformator
Encourage, gather the frequency response signal of transformator, by frequency response signal divided by excitation letter
Number obtain transformer frequencies response measured waveform, the frequency range of measured waveform and reference waveform is
1Hz-1MHz;
Step 2: respectively measured waveform and reference waveform are carried out multilamellar wavelet transform, real
Existing denoising and the smoothing of waveform;
Step 3: measured waveform and reference waveform after the most successively relative analysis smoothing processing
Data difference: from 1Hz start to high-frequency range detect the most high layer smoothing processing reality
Survey waveform and the data difference of reference waveform inspection, when described data difference exceedes a certain threshold value,
Record to should the frequency of discrepancy as abnormal frequency point, simultaneously using this abnormal frequency point as
The frequency starting point that the measured waveform of next layer of smoothing processing and reference waveform compare, if last layer
The no abnormal Frequency point of smoothing processing, then next layer of smoothing processing compares from the beginning of 1Hz,
Until ground floor smoothing processing Difference test completes;
Step 4: by the measured waveform after two-layer smoothing processing neighbouring in step 3 and reference waveform
The frequency range that two abnormal frequency point that contrast obtains comprise is as abnormal frequency band, to abnormal frequency
Wave data in band carries out ratio MM based on min-max value and the number of correlation coefficient CC
Learn Indexes Comparison, contrast in order to measured waveform after quantitative analysis smoothing processing and reference waveform and obtain
The data difference of abnormal frequency band, carry out the supplemental diagnostics of fault, the ratio of min-max value
The expression formula of MM and correlation coefficient CC is
Wherein, y1, y2 are respectively the measured waveform after smoothing processing and reference waveform, and n is number
The number at strong point;
Step 5: according to supplemental diagnostics criterion based on mathematical criterion, when min-max value it
When all meeting certain condition than MM and correlation coefficient CC, determine deformation of transformer winding degree,
Particularly as follows: when MM < 0.9 and CC are < when 0.96, it is believed that there is obvious winding deformation;When
0.9 < MM < 0.96 and 0.96 < CC < when 0.98, it is understood that there may be slight deformation;Work as MM > 0.96
And during CC > 0.98, without winding deformation.
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CN105468858A (en) * | 2015-12-01 | 2016-04-06 | 国家电网公司 | Structural transformer fault diagnosis method based on finite element simulation and field test |
CN107315991B (en) * | 2017-05-05 | 2020-12-22 | 华南理工大学 | IFRA frequency response curve denoising method based on wavelet threshold denoising |
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CN109581055A (en) * | 2018-12-28 | 2019-04-05 | 广东电网有限责任公司 | A kind of transformer winding fault type detection method based on Multiresolution Decomposition method |
CN109669101A (en) * | 2019-02-13 | 2019-04-23 | 云南电网有限责任公司电力科学研究院 | A kind of method and device that transformer winding self-oscillation wave characteristic is extracted |
CN109669100A (en) * | 2019-02-13 | 2019-04-23 | 云南电网有限责任公司电力科学研究院 | A kind of transformer self-oscillation wave extracting method and system |
CN111624404B (en) * | 2020-05-08 | 2022-04-05 | 西安交通大学 | Online transformer impedance spectrum measurement system and measurement method |
CN112763848A (en) * | 2020-12-28 | 2021-05-07 | 国网北京市电力公司 | Method and device for determining power system fault |
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