CN108896161B - A kind of assessment method of Wound iron-core transformer winding failure analog platform - Google Patents
A kind of assessment method of Wound iron-core transformer winding failure analog platform Download PDFInfo
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- CN108896161B CN108896161B CN201810284321.7A CN201810284321A CN108896161B CN 108896161 B CN108896161 B CN 108896161B CN 201810284321 A CN201810284321 A CN 201810284321A CN 108896161 B CN108896161 B CN 108896161B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H11/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties
- G01H11/06—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means
Abstract
The invention discloses a kind of assessment methods of Wound iron-core transformer winding failure analog platform, the Wound iron-core transformer winding failure analog platform includes high and low pressure winding, iron core and dielectric, simulates the radial deformation failure of Wound iron-core transformer winding by changing the dielectric constant of dielectric.The assessment method of Wound iron-core transformer winding failure analog platform includes measurement storage, data processing, parameter determination and Test and analysis, transmission function state-space model is acquired to the frequency response test result of winding, is further analyzed by the parameter to transmission function state-space model to judge the fault condition of transformer winding.The present invention can be effectively prevented from the irreversible injury of winding, and the degree of adjustable winding radial deformation, realize multilevel simulation.Assessment method can not only detect whether Wound iron-core transformer winding deforms, and can be classified fault degree, realize various dimensions, comprehensive assessment.
Description
Technical field
The invention belongs to Wound iron-core transformer winding failure fields, and in particular to a kind of Wound iron-core transformer winding failure mould
The assessment method of quasi- platform.
Background technique
Wound iron-core transformer no-load loss, volume, in terms of there is laminated core transformer not have advantage, and
The transformer long-time idle running situation as caused by traction load intermittence, so that Wound iron-core transformer is in traction power supply system
It gathers around and has broad application prospects in system.Transformer is the core equipment of traction substation, and safe and stable operation is to ensure traction
The most important thing of power supply system reliability service.And the accident collision etc. in the electromagnetic force and transportational process that short circuit generates can all make
It deforms at Wound iron-core transformer winding, serious winding deformation can damage tractive power supply system.And due to rolling up iron
The reasons such as heart transformer iron core structure design are difficult to carry out winding replacement once breaking down, therefore understand rewinding material in time and become
The deformation of depressor winding repairs winding deformation and prevents to have great importance.
Building a deformation of transformer winding platform and carrying out frequency response test to winding is research detection winding deformation
The conventional means of fault method.However the existing means for realizing winding deformation failure often destroy the shape and knot of winding
Structure causes expendable destruction；Meanwhile the characteristic parameter of frequency response test result is proposed to judge using correlation coefficient process
The deformation of winding, but this method saves as the more single problem of characterization result dimension, so that assessment result is not accurate enough.
Summary of the invention
It is an object of the present invention to be the rewinding material of single frame open type, upper yoke using common Wound iron-core transformer
The characteristics of capable of removing, facilitating the extraction of dielectric between high and low pressure winding and iron core, provide one kind can without damage, it is more
Dimensionally react the fault simulation platform of Wound iron-core transformer winding deformation situation.The invention also provides a kind of rewinding material transformations
The assessment method of device winding failure analog platform.
Realize that the technical solution of the object of the invention is as follows:
A kind of Wound iron-core transformer winding failure analog platform, including high-voltage winding, low pressure winding, iron core, the first insulation
Medium and the second dielectric；Iron core, low pressure winding, high-voltage winding are followed successively by concentric circles from inside to outside；First dielectric
Between iron core and low pressure winding；Second dielectric is between low pressure winding and high-voltage winding；First insulation is situated between
Matter and the second dielectric can replace with respectively the dielectric of differing dielectric constant, thus change the direct-to-ground capacitance of winding, around
Capacitor between group realizes the function of analogue transformer winding radial deformation failure.
A kind of assessment method of Wound iron-core transformer winding failure analog platform, comprising the following steps:
The first step, measurement storage:
Using Wound iron-core transformer winding failure analog platform, by biggish first dielectric of replacement dielectric constant,
Second dielectric aggravates winding radial deformation fault degree to realize；It is situated between by lesser first insulation of replacement dielectric constant
Matter, the second dielectric come realize decrease or eliminate winding radial deformation fault degree；The winding radial deformation fault degree
Including 4 grades, i.e., winding is slightly deformed without deformation, winding, the deformation of winding moderate and winding severe deform, and is successively named
Are as follows: failure 0, failure 1, failure 2, failure 3；
Under 0 state of failure, tests, draws and the Wound iron-core transformer stored in 5 100kHz-600kHz frequency ranges is each
The frequency response curve of winding, is averaged, as reference frequency response curve Y0(f)；It is each under 3 state of failure 1, failure 2 and failure again
The frequency response curve for testing, drawing and store each winding of Wound iron-core transformer in 3 100kHz-600kHz frequency ranges, is averaged
Value, as the test frequency response curve Y under each malfunctioni(f), it and is stored；I=1,2,3, respectively correspond failure 1, failure
2 and 3 state of failure；
Second step, data processing:
2.1 utilize fast relaxation Vector Matching Arithmetic to Y0(f) and Yi(f) it is fitted, obtains the shape for referring to frequency response curve
State space model f0(s) and under i-th kind of malfunction the state-space model f of frequency response curve is testedi(s),
S is Laplace operator in formula；I is unit matrix, A0For the sytem matrix with reference to frequency response curve, B0For with reference to frequency
Ring the control matrix of curve, C0For the output matrix with reference to frequency response curve, AiTo test frequency response curve under i-th kind of malfunction
Sytem matrix, BiFor the control matrix for testing frequency response curve under i-th kind of malfunction, CiTo test frequency response under i-th kind of malfunction
The output matrix of curve；a0,nFor n-th of denominator coefficients with reference to frequency response curve, ai,nTo test frequency response under i-th kind of malfunction
N-th of denominator coefficients of curve, b0,nFor n-th of numerator coefficients with reference to frequency response curve, bi,nTo be tested under i-th kind of malfunction
N-th of numerator coefficients of frequency response curve, n are the number of numerator coefficients；d0、e0、di、eiIt is real number；
2.2 calculate the standard deviation CV of the transmission function with reference to frequency response curve0With the mark of transmission function under i-th kind of malfunction
Quasi- difference CVi,
In formula, σ0,aFor the standard deviation with reference to frequency response curve denominator coefficients sequence, σ0,bTo refer to frequency response curve numerator coefficients
The standard deviation of sequence；μ0,aFor the mean value with reference to frequency response curve denominator coefficients sequence, μ0,bTo refer to frequency response curve numerator coefficients sequence
The mean value of column；σi,aFor the standard deviation for testing frequency response curve denominator coefficients sequence under i-th kind of malfunction, σi,bFor i-th kind of failure
The standard deviation of frequency response curve numerator coefficients sequence is tested under state；μi,aTo test frequency response curve denominator system under i-th kind of malfunction
The mean value of Number Sequence, μi,bFor the mean value for testing frequency response curve numerator coefficients sequence under i-th kind of malfunction；
2.3 calculate the distance parameter CD of transmission function under each malfunctioni,
Third step, parameter determine:
3.1 determine winding failure limit parameter L:
It enables
3.2 determine winding failure severity parameter P1、P2:
It enables
4th step, Test and analysis:
4.1 pairs of actual Wound iron-core transformers carry out winding deformation failure Test and analysis, and first measurement obtains 100kHz-
The frequency response curve of each winding of Wound iron-core transformer in 600kHz frequency range, acquires frequency response curve according still further to the method for step 2.1
State space transmission function f (s) acquires the standard deviation CV of transmission function f (s) according still further to the method for step 2.2；If CV≤L
Wound iron-core transformer winding is normal, otherwise determines that Wound iron-core transformer winding has deformation failure, into next step；
4.2 acquire the distance parameter CD of transmission function according to the method for step 2.3；If CD≤P1, then determine that winding occurs
Slight deformation failure；If P1<CD≤P2, then determine that moderate deformation occurs in winding；Work as CD > P2, then determine that severe deformation occurs in winding
Failure.
The advantages and positive effects of the present invention are as follows:
1, it can be effectively prevented from the irreversible injury of winding, and the degree of adjustable winding radial deformation, realized more
Grade simulation；
2, method of the invention can not only detect whether Wound iron-core transformer winding deforms, and can be by event
Hinder grading, realizes various dimensions, comprehensive assessment.
Detailed description of the invention
Fig. 1 is Wound iron-core transformer winding deformation fault simulation schematic diagram；
Fig. 2 is the flow chart of Wound iron-core transformer winding failure assessment method.
Wherein, 1- high-voltage winding, 2- low pressure winding, 3- iron core, the dielectric between 4- iron core and low pressure winding, 5-
Dielectric between high and low pressure winding.
Specific embodiment
Details of the invention is described in further detail with reference to the accompanying drawing:
Fig. 1 is Wound iron-core transformer winding deformation fault simulation schematic diagram, including high-voltage winding 1, low pressure winding 2, iron core
3, dielectric 4 and dielectric 5；The iron core 3, low pressure winding 2, high-voltage winding 1 are followed successively by concentric circles from inside to outside；
The dielectric 4 is between the iron core 3 and the low pressure winding 2；The dielectric 5 is located at described
Between low pressure winding 2 and the high-voltage winding 1.
In specific test, by replacing dielectric 4, the dielectric 5 of differing dielectric constant, change iron core 3 with
Dielectric constant between low pressure winding 2, between low pressure winding 2 and high-voltage winding 1, to change the direct-to-ground capacitance of winding, winding
Between capacitor, realize analogue transformer winding radial deformation failure function；When needing to aggravate winding radial deformation fault degree
When, by being realized in the biggish dielectric 4 of replacement dielectric constant, dielectric 5；Winding diameter even is eliminated when needing to weaken
When to deformation fault degree, by replaced between high-low pressure winding the lesser dielectric 4 of dielectric constant, dielectric 5 come
It realizes；Malfunctioning module may be implemented 4 grade fault degrees, i.e., winding slightly deform without deformation, winding, winding moderate deform with
And the deformation of winding severe, successively are as follows: failure 0, failure 1, failure 2, failure 3.
Fig. 2 is at the flow chart of Wound iron-core transformer winding failure analog platform assessment method, including measurement storage, data
Reason and parameter determination and three steps of Test and analysis:
The first step, measurement storage
Under 0 state of failure, tests, draws and the Wound iron-core transformer stored in 5 100kHz-600kHz frequency ranges is each
The frequency response curve of winding, is averaged, as reference frequency response curve Y0(f)；Again under every kind of malfunction, each test is drawn
And the frequency response curve of each winding of Wound iron-core transformer in 3 100kHz-600kHz frequency ranges is stored, it is averaged, as survey
Try frequency response curve Yi(f), it and is stored；
Second step, data processing
Using fast relaxation Vector Matching Arithmetic to Y0(f) and Yi(f) it is fitted, obtains the state for referring to frequency response curve
Spatial model f0(s) and under i-th kind of malfunction the state-space model f of frequency response curve is testedi(s) following (i=1,2,3):
S is Laplace operator in formula；I is unit matrix, A0For the sytem matrix with reference to frequency response curve, B0For with reference to frequency
Ring the control matrix of curve, C0For the output matrix with reference to frequency response curve, AiTo test frequency response curve under i-th kind of malfunction
Sytem matrix, BiFor the control matrix for testing frequency response curve under i-th kind of malfunction, CiTo test frequency response under i-th kind of malfunction
The output matrix of curve；a0,nFor n-th of denominator coefficients with reference to frequency response curve, ai,nTo test frequency response under i-th kind of malfunction
N-th of denominator coefficients of curve, b0,nFor n-th of numerator coefficients with reference to frequency response curve, bi,nTo be tested under i-th kind of malfunction
N-th of numerator coefficients of frequency response curve, n are the number of numerator coefficients；d0、e0、di、eiIt is real number；
2.2 calculate the standard deviation CV of the transmission function with reference to frequency response curve0With the mark of transmission function under i-th kind of malfunction
Quasi- difference CVi:
In formula, σ0,aFor the standard deviation with reference to frequency response curve denominator coefficients sequence, σ0,bTo refer to frequency response curve numerator coefficients
The standard deviation of sequence；μ0,aFor the mean value with reference to frequency response curve denominator coefficients sequence, μ0,bTo refer to frequency response curve numerator coefficients sequence
The mean value of column；σi,aFor the standard deviation for testing frequency response curve denominator coefficients sequence under i-th kind of malfunction, σi,bFor i-th kind of failure
The standard deviation of frequency response curve numerator coefficients sequence is tested under state；μi,aTo test frequency response curve denominator system under i-th kind of malfunction
The mean value of Number Sequence, μi,bFor the mean value for testing frequency response curve numerator coefficients sequence under i-th kind of malfunction；
CV is calculated0=0.38, CV1=0.72；
2.3 calculate the distance parameter CD of transmission function under each malfunctioni:
CD is calculated1=2.86, CD2=5.02；CD3=6.78；
Third step, parameter determination and Test and analysis
3.1 determine winding failure limit parameter L:
It enables
When reality carries out winding deformation failure Test and analysis to transformer, first measurement obtains 100kHz-600kHz frequency range
The frequency response curve of the interior each winding of real transformer acquires the state space transmission function f of frequency response curve further according to step in 2.1
(s), the standard deviation CV that transmission function f (s) is acquired further according to step in 2.2, judges obtained standard deviation CV size, if CV≤
Then think normal when L, otherwise it is assumed that winding has deformation, and judges winding deformation fault degree.In this example, if when CV≤0.55
Then think normal, otherwise it is assumed that winding has deformation, and goes to 3.2；
3.2 determine winding failure severity parameter P1、P2:
It enables
When reality carries out winding deformation failure Test and analysis to transformer, according to the distance of step transmission function in 2.3
Parameter CD judges the parameter distance CD size for testing frequency response curve, as CD≤P1, winding appearance is slight to be deformed, and P is worked as1<CD≤P2,
There is moderate deformation in winding, works as CD > P2, there is severe deformation in winding.In this example, when CD≤3.94, there is slight deformation in winding,
When 3.94<CD≤5.90, there is moderate deformation in winding, works as CD>5.90, and severe deformation occurs in winding.
Claims (1)
1. a kind of assessment method of Wound iron-core transformer winding failure analog platform, which is characterized in that
The fault simulation platform includes high-voltage winding (1), low pressure winding (2), iron core (3), the first dielectric (4) and second
Dielectric (5)；Iron core (3), low pressure winding (2), high-voltage winding (1) are followed successively by concentric circles from inside to outside；First insulation is situated between
Matter (4) is located between iron core (3) and low pressure winding (2)；Second dielectric (5) is located at low pressure winding (2) and high-voltage winding (1)
Between；First dielectric (4) and the second dielectric (5) can replace with the dielectric of differing dielectric constant respectively,
To change the capacitor between the direct-to-ground capacitance of winding, winding, the function of analogue transformer winding radial deformation failure is realized；
The assessment method includes:
The first step, measurement storage:
Using Wound iron-core transformer winding failure analog platform, pass through biggish first dielectric (4) of replacement dielectric constant, the
Two dielectrics (5) aggravate winding radial deformation fault degree to realize；It is situated between by lesser first insulation of replacement dielectric constant
Matter (4), the second dielectric (5) come realize decrease or eliminate winding radial deformation fault degree；The winding radial deformation event
Barrier degree includes 4 grades, i.e., winding is slightly deformed without deformation, winding, the deformation of winding moderate and winding severe deform, successively
Name are as follows: failure 0, failure 1, failure 2, failure 3；
Under 0 state of failure, tests, draws and store each winding of Wound iron-core transformer in 5 100kHz-600kHz frequency ranges
Frequency response curve, be averaged, as reference frequency response curve Y0(f)；Respectively tested under 3 state of failure 1, failure 2 and failure again,
The frequency response curve for drawing and storing each winding of Wound iron-core transformer in 3 100kHz-600kHz frequency ranges, is averaged, and makees
For the test frequency response curve Y under each malfunctioni(f), it and is stored；I=1,2,3, respectively correspond failure 1, failure 2 and event
Hinder 3 states；
Second step, data processing:
2.1 utilize fast relaxation Vector Matching Arithmetic to Y0(f) and Yi(f) it is fitted, obtains the state sky with reference to frequency response curve
Between model f0(s) and under i-th kind of malfunction the state-space model f of frequency response curve is testedi(s),
S is Laplace operator in formula；I is unit matrix, A0For the sytem matrix with reference to frequency response curve, B0It is bent with reference to frequency response
The control matrix of line, C0For the output matrix with reference to frequency response curve, AiFor the system for testing frequency response curve under i-th kind of malfunction
Matrix, BiFor the control matrix for testing frequency response curve under i-th kind of malfunction, CiTo test frequency response curve under i-th kind of malfunction
Output matrix；a0,nFor n-th of denominator coefficients with reference to frequency response curve, ai,nTo test frequency response curve under i-th kind of malfunction
N-th of denominator coefficients, b0,nFor n-th of numerator coefficients with reference to frequency response curve, bi,nTo test frequency response under i-th kind of malfunction
N-th of numerator coefficients of curve, n are the number of numerator coefficients；d0、e0、di、eiIt is real number；
2.2 calculate the standard deviation CV of the transmission function with reference to frequency response curve0With the standard deviation of transmission function under i-th kind of malfunction
CVi,
In formula, σ0,aFor the standard deviation with reference to frequency response curve denominator coefficients sequence, σ0,bTo refer to frequency response curve numerator coefficients sequence
Standard deviation；μ0,aFor the mean value with reference to frequency response curve denominator coefficients sequence, μ0,bFor with reference to frequency response curve numerator coefficients sequence
Mean value；σi,aFor the standard deviation for testing frequency response curve denominator coefficients sequence under i-th kind of malfunction, σi,bFor i-th kind of malfunction
The standard deviation of lower test frequency response curve numerator coefficients sequence；μi,aTo test frequency response curve denominator coefficients sequence under i-th kind of malfunction
The mean value of column, μi,bFor the mean value for testing frequency response curve numerator coefficients sequence under i-th kind of malfunction；
2.3 calculate the distance parameter CD of transmission function under each malfunctioni,
Third step, parameter determine:
3.1 determine winding failure limit parameter L:
It enables
3.2 determine winding failure severity parameter P1、P2:
It enables
4th step, Test and analysis:
4.1 pairs of actual Wound iron-core transformers carry out winding deformation failure Test and analysis, and first measurement obtains 100kHz-600kHz frequency
The frequency response curve of each winding of Wound iron-core transformer, the state space of frequency response curve is acquired according still further to the method for step 2.1 in section
Transmission function f (s) acquires the standard deviation CV of transmission function f (s) according still further to the method for step 2.2；Rewinding material becomes if CV≤L
Depressor winding is normal, otherwise determines that Wound iron-core transformer winding has deformation failure, into next step；
4.2 acquire the distance parameter CD of transmission function according to the method for step 2.3；If CD≤P1, it is slight to determine that winding occurs
Deform failure；If P1 < CD≤P2, determine that moderate deformation occurs in winding；Work as CD > P2, then determines that severe deformation event occurs in winding
Barrier.
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| CN109298303A (en) * | 2018-09-05 | 2019-02-01 | 国网河北省电力有限公司电力科学研究院 | Transformer winding shelf depreciation propagation characteristic experimental rig and method |
| CN110361611B (en) * | 2019-06-23 | 2020-09-01 | 西南交通大学 | Frequency response test platform under radial deformation of transformer winding and evaluation method thereof |
| CN110376454A (en) * | 2019-06-23 | 2019-10-25 | 西南交通大学 | Winding radial deformation and oscillation wave relevance research platform and its test method |
| CN110361610B (en) * | 2019-06-23 | 2020-09-01 | 西南交通大学 | Transformer winding radial deformation test system and test evaluation method thereof |
| CN114113829B (en) * | 2021-10-28 | 2023-10-24 | 探博士电气技术(杭州)有限公司 | Assembling method of transformer fault simulation device |
| CN116127240B (en) * | 2022-11-22 | 2023-12-05 | 西南交通大学 | Evaluation method for overload capacity of wound core of traction transformer |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101344566A (en) * | 2008-09-03 | 2009-01-14 | 中国电力科学研究院 | Test device and method for detecting winding deformation of power transformer |
| CN102881429A (en) * | 2012-09-24 | 2013-01-16 | 深圳供电局有限公司 | Testing transformer |
| CN103823137A (en) * | 2014-02-25 | 2014-05-28 | 浙江大学 | Method for analyzing response characteristics of electric reactor winding under action of lightning waves |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2860593A1 (en) * | 2003-10-03 | 2005-04-08 | Alstom T & D Sa | Winding fault diagnosing method for three-phase power transformer, involves determining relative variation of resonant frequency greater than specific frequency by comparing two voltage gains |
-
2018
- 2018-04-02 CN CN201810284321.7A patent/CN108896161B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101344566A (en) * | 2008-09-03 | 2009-01-14 | 中国电力科学研究院 | Test device and method for detecting winding deformation of power transformer |
| CN102881429A (en) * | 2012-09-24 | 2013-01-16 | 深圳供电局有限公司 | Testing transformer |
| CN103823137A (en) * | 2014-02-25 | 2014-05-28 | 浙江大学 | Method for analyzing response characteristics of electric reactor winding under action of lightning waves |
Non-Patent Citations (1)
| Title |
|---|
| 基于频率响应法的变压器故障检测仿真;王振宇 等;《绝缘材料》;20170630;第50卷(第6期);第69-72、77页 |
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