CN107167234A - Transformer Winding based on vibration signal fractal box loosens state identification method - Google Patents
Transformer Winding based on vibration signal fractal box loosens state identification method Download PDFInfo
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- CN107167234A CN107167234A CN201710432985.9A CN201710432985A CN107167234A CN 107167234 A CN107167234 A CN 107167234A CN 201710432985 A CN201710432985 A CN 201710432985A CN 107167234 A CN107167234 A CN 107167234A
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- 238000004804 winding Methods 0.000 title claims abstract description 53
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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Abstract
State identification method is loosened the present invention relates to a kind of Transformer Winding based on vibration signal fractal box.When being in loosening state based on Transformer Winding, the nonlinear characteristic of its vibration signal strengthens this phenomenon, propose to be used as characteristic quantity using the fractal box of vibration signal time domain waveform, the loosening state of Transformer Winding is identified the nonlinear characteristic of quantitative description basket vibration waveform, the changing rule according to fractal box.Method proposed by the present invention can effectively recognize the loosening state of Transformer Winding, and this method directly carries out state Characteristic Extraction using vibration signal time domain waveform, calculate integrality that is simple and ensure that vibration signal.
Description
Technical field：
State identification method is loosened the present invention relates to a kind of Transformer Winding based on vibration signal fractal box.
Background technology：
The transformer of longtime running may cause transformer due to cross-over block aging, fastener loosening, short-circuit impact etc.
Winding loosens, and winding loosens the anti-short circuit capability that will further decrease transformer, so that cause transformer fault, therefore identification
Transformer winding state is significant to transformer stable operation.Transformer winding state diagnosis skill based on vibration signal
Art is got the attention with it with system without electrical connection, simple operation and other advantages, and its main Research Thinking is：Based on transformation
Device vibration signal, extracts the signal characteristic quantity related to winding state, Transformer Winding is determined according to the changing rule of characteristic quantity
State.It is existing to have researched and proposed including vibration signal fundamental frequency energy accounting, the energy spectrum regularity of distribution and characteristic frequency response
Etc. principal character amount, these characteristic quantities are that the frequency domain of vibration signal is characterized, but based on the theoretical time-frequency conversion of Fourier simultaneously
All information of time-domain signal, and a selected part frequency when extracting characteristic quantity can not be retained, which results in carried based on frequency domain
The characteristic quantity taken does not include the complete information of time-domain signal, may be due to the careless omission of important information, to the accuracy of characteristic quantity
Affected greatly with versatility.The time domain waveform of basket vibration signal for transformer winding vibration directly in response to, based on when
State reflection of the Characteristic Extraction of domain vibration signal to winding will be more accurate.Research shows, after Transformer Winding loosens, its
The nonlinear characteristic enhancing of vibration signal under loosening state, time domain waveform is distorted, based on this phenomenon, is proposed to use and is shaken
The fractal box of dynamic time domain plethysmographic signal, to recognize the loosening state of Transformer Winding, divides shape box as winding state characteristic quantity
Dimension is a geometric parameter, the nonlinear characteristic of energy quantitative descriptive analysis object, and box dimension of fractals numerical value is with analysis object
Non-linear enhancing and increase, therefore according to vibration signal time domain waveform fractal box changing rule to the pine of Transformer Winding
It is feasible that dynamic state, which is identified,.
The content of the invention：
State recognition is loosened it is an object of the invention to provide a kind of Transformer Winding based on vibration signal fractal box
Method.
Above-mentioned purpose is realized by following technical scheme：
(1) collection and pretreatment of transformer winding vibration signal：
Its state is reflected by the vibration signal of transformer.Transformer vibration is mainly that iron core and winding are operationally produced
Vibration, under the conditions of transformer short-circuit, core vibration is ignored, and obtained vibration signal as winding is tested in tank surface
Vibration signal.Test is pasted on oil tank of transformer surface using vibration acceleration sensor, is connected by data cable and Acquisition Instrument
Connect, Acquisition Instrument record vibration data.
There is interference in the basket vibration signal of collection in worksite, interference is concentrated mainly on below 100Hz low-frequency range, and detection
Transformer vibration signal is primarily upon the vibration signal within 1000Hz when assessing winding state, so using bound frequency point
Not Wei 1000Hz and 100Hz band-pass filtering method signal is pre-processed.
(2) fractal box of basket vibration time domain plethysmographic signal is calculated
The non-linear and complexity of fractal box energy quantitative descriptive analysis object.Box counting dimension refers to cover a signal
Minimum box number, the box counting dimension of the yardstick unlike signal of box is different, according to Computing Principle, point shape box of one-dimensional discrete signal
The size of dimension is between 1 and 2, and the complexity of signal is higher, and fractal box is bigger.The definition of box counting dimension such as formula (1)
It is shown：
In formula, X is n dimension theorem in Euclid space RnNon-NULL bounded subset, N (X, ε) represents that maximum gauge is ε and can cover X collection
The minimum number of conjunction, DXFor X fractal box.
(3) Transformer Winding loosens state recognition
Definition according to fractal box knows that box counting dimension size is different with data sample length difference, therefore to winding
Vibration signal under different conditions carries out to ensure that data sample length is consistent during fractal box calculating.It is first depending on a point shape box
The fractal box of basket vibration time domain plethysmographic signal under dimension Computing Principle calculating transformer normal condition, in order to reduce single group
The random error that data band comes, takes different periods multi-group data sample to be calculated, obtains basket vibration signal under normal condition
Fractal box concentrated area, regard the normal box counting dimension distributed areas of state as reference area.When need to judge transformer around
When whether group is in loosening state, basket vibration signal is gathered, multigroup and baseline sample length identical vibration signal data is taken,
Its fractal box is calculated, the new concentrated area of fractal box is obtained, said if new concentrated area is intersected with reference area
Bright transformer winding state is normal, if with reference area from Transformer Winding is in loosening state, need to further be examined
Repair investigation work.
Beneficial effect：
1. the inventive method directly using basket vibration time domain plethysmographic signal carry out winding loosen state recognition, make use of around
The integrality of group vibration signal.
2. the inventive method loosens the characteristic quantity of state using the fractal box of vibration signal time domain waveform as winding,
The loosening state of Transformer Winding can clearly be reflected exactly.
Brief description of the drawings：
Fig. 1 be winding normally with the vibrational waveform under loosening state.
Fig. 2 is that abscissa is sample sequence in the distribution of vibration signal fractal box, figure before and after winding loosens, and ordinate is
Sample fractal box, point represents the corresponding fractal box of sample sequence, and dotted line frame is different sample point shapes under same state
Box counting dimension concentrated area.
Embodiment：
The implementation process to the present invention is described further below in conjunction with the accompanying drawings.
Vibration signal before and after being loosened to a 1000kVA Transformer Winding is acquired, and is distinguished using bound frequency
Band-pass filtering method for 1000Hz and 100Hz is pre-processed to signal, and waveform is as shown in Figure 1.
Normally with loosening state, respectively choosing 10 groups of data samples, every group of data sample length is 1000 data points.Point
Not Ji Suan fractal box result it is as shown in Figure 2.
From Fig. 2 results, fractal box concentrates on 1.185~1.190 regions to winding in normal state, loosens shape
Basket vibration signal fractal box concentrates on 1.220~1.225 regions, winding vibration signal time domain waveform after loosening under state
Fractal box increases, and two state concentrated areas are from the fractal box of vibration signal can accurately reflect Transformer Winding
Loosening state.
Claims (3)
1. the Transformer Winding based on vibration signal fractal box loosens state identification method, it is characterised in that：In transformer
In winding state identification, this method can accurately reflect Transformer Winding by the time domain waveform of transformer winding vibration signal
Loosening state, this method comprises the following steps：
(1) collection and pretreatment of transformer winding vibration signal
Its state is reflected by the vibration signal of transformer, what transformer vibration predominantly iron core and winding were operationally produced shakes
Dynamic, under the conditions of transformer short-circuit, core vibration is ignored, and obtained vibration signal as basket vibration is tested in tank surface
Signal, test is pasted on oil tank of transformer surface using vibration acceleration sensor, is connected, adopted with Acquisition Instrument by data cable
Collect instrument record vibration data；
There is interference in the basket vibration signal of collection in worksite, interference is concentrated mainly on below 100Hz low-frequency range, and detection transformation
Device vibration signal is primarily upon the vibration signal within 1000Hz when assessing winding state, so being respectively using bound frequency
1000Hz and 100Hz band-pass filtering method is pre-processed to signal；
(2) fractal box of basket vibration time domain plethysmographic signal is calculated
The non-linear and complexity of fractal box energy quantitative descriptive analysis object, box counting dimension refers to one signal of covering most
Capsule subnumber, the box counting dimension of the yardstick unlike signal of box is different, according to Computing Principle, the fractal box of one-dimensional discrete signal
Size between 1 and 2, the complexity of signal is higher, and fractal box is bigger, shown in the definition such as formula (1) of box counting dimension：
<mrow>
<msub>
<mi>D</mi>
<mi>X</mi>
</msub>
<mo>=</mo>
<munder>
<mi>lim</mi>
<mrow>
<mi>&epsiv;</mi>
<mo>&RightArrow;</mo>
<mn>0</mn>
</mrow>
</munder>
<mfrac>
<mrow>
<mi>ln</mi>
<mi> </mi>
<mi>N</mi>
<mrow>
<mo>(</mo>
<mi>X</mi>
<mo>,</mo>
<mi>&epsiv;</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>l</mi>
<mi>n</mi>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>/</mo>
<mi>&epsiv;</mi>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula, X is n dimension theorem in Euclid space RnNon-NULL bounded subset, N (X, ε) represent maximum gauge be ε and can cover X set most
Few number, DXFor X fractal box；
(3) Transformer Winding loosens state recognition
Definition according to fractal box knows that box counting dimension size is different therefore different to winding with data sample length difference
Vibration signal under state carries out to ensure that data sample length is consistent during fractal box calculating, is first depending on fractal box
The fractal box of basket vibration time domain plethysmographic signal under Computing Principle calculating transformer normal condition, in order to reduce single group data
The random error brought, takes different periods multi-group data sample to be calculated, and obtains basket vibration signal point shape under normal condition
Box counting dimension concentrated area, using the normal box counting dimension distributed areas of state as reference area, when needing to judge that Transformer Winding is
It is no to gather basket vibration signal when being in loosening state, take multigroup with baseline sample length identical vibration signal data, calculate
Its fractal box, obtains the new concentrated area of fractal box, illustrates to become if new concentrated area is intersected with reference area
Depressor winding state is normal, if with reference area from Transformer Winding is in loosening state, need to carry out further maintenance row
Look into work.
2. state identification method is loosened according to the Transformer Winding based on vibration signal fractal box described in claim 1,
It is characterized in that：State characteristic quantity is loosened using the fractal box of basket vibration time domain plethysmographic signal as Transformer Winding, with
This identification Transformer Winding loosens state.
3. state identification method is loosened according to the Transformer Winding based on vibration signal fractal box described in claim 1,
It is characterized in that：With the intersecting of the multigroup sample fractal box concentrated area of vibration signal under different conditions, from being used as state
Basis of characterization, it is to avoid the random error that single group data band comes.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112329825A (en) * | 2020-10-23 | 2021-02-05 | 贵州电网有限责任公司 | Transformer mechanical fault diagnosis method based on information dimension division and decision tree lifting |
| CN112798474A (en) * | 2020-12-18 | 2021-05-14 | 西安科技大学 | A method and device for monitoring the diffusion range of rock mass grouting |
| CN114511115A (en) * | 2022-02-08 | 2022-05-17 | 珠海格力电器股份有限公司 | Method and device for evaluating performance of air conditioner of machine room |
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| CN102097791A (en) * | 2011-02-25 | 2011-06-15 | 昆明理工大学 | Fractal dimension-based ultrahigh voltage DC transmission line boundary element method |
| CN102565599A (en) * | 2012-02-21 | 2012-07-11 | 昆明理工大学 | Method for judging internal and external faults of alternating current transmission line based on fractal dimension |
| CN205003239U (en) * | 2015-08-26 | 2016-01-27 | 江苏省电力公司南京供电公司 | Power transformer winding becomes flexible defect diagnostic system |
-
2017
- 2017-06-09 CN CN201710432985.9A patent/CN107167234A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102097791A (en) * | 2011-02-25 | 2011-06-15 | 昆明理工大学 | Fractal dimension-based ultrahigh voltage DC transmission line boundary element method |
| CN102565599A (en) * | 2012-02-21 | 2012-07-11 | 昆明理工大学 | Method for judging internal and external faults of alternating current transmission line based on fractal dimension |
| CN205003239U (en) * | 2015-08-26 | 2016-01-27 | 江苏省电力公司南京供电公司 | Power transformer winding becomes flexible defect diagnostic system |
Non-Patent Citations (2)
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| 赵宏飞 等: "基于振动信号的变压器绕组松动实验研究", 《中国电力》 * |
| 郝研: "分形维数特性分析及故障诊断分形方法研究", 《中国博士学位论文全文数据库基础科学辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112329825A (en) * | 2020-10-23 | 2021-02-05 | 贵州电网有限责任公司 | Transformer mechanical fault diagnosis method based on information dimension division and decision tree lifting |
| CN112329825B (en) * | 2020-10-23 | 2022-12-06 | 贵州电网有限责任公司 | Transformer mechanical fault diagnosis method based on information dimension division and decision tree lifting |
| CN112798474A (en) * | 2020-12-18 | 2021-05-14 | 西安科技大学 | A method and device for monitoring the diffusion range of rock mass grouting |
| CN114511115A (en) * | 2022-02-08 | 2022-05-17 | 珠海格力电器股份有限公司 | Method and device for evaluating performance of air conditioner of machine room |
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