CN105182172B - Winding state diagnostic method under transformer sudden short circuit based on vibration signal morphology spectrum - Google Patents
Winding state diagnostic method under transformer sudden short circuit based on vibration signal morphology spectrum Download PDFInfo
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Abstract
The invention discloses winding state diagnostic method under a kind of transformer sudden short circuit based on vibration signal morphology spectrum, including：(1) short circuit monitoring in real time is carried out to transformer, and, the steady-state vibration signal aspect that vibration signal is gathered when one section of continuous vibration signal of transformer box wall is gathered whenever detecting that sudden short circuit occurs for transformer, and calculating transformer generation sudden short circuit each time by the method for following steps (2) to step (6) composes entropy；(7) according to steady-state vibration signal xs(t) morphology spectrum entropy differentiates to winding state：When the changes delta H of morphology spectrum entropy meets
Description
Technical field
The present invention relates to a kind of signal monitoring method, more particularly to a kind of transformer to occur winding state during sudden short circuit
Diagnostic method.
Background technology
Transformer is one of most important equipment in power system, and its operation stability influences pole to power system security
Greatly.With the increasingly increase of China's net capacity, capacity of short circuit also constantly increase therewith, because external short circuit and caused by transformer
Winding deformation failure is remained high always, is relatively conventional failure during transformer station high-voltage side bus, and the safety of power system is transported
Row causes very big threat.
Transformer is by after sudden short circuit, and loosening or slight deformation may occur first for its winding, and Transformer Winding becomes
Shape has cumulative effect, if can not find and repair in time Transformer Winding loosen or metaboly, when transformer loosen or
Deformation accumulation can make the anti-short circuit capability of transformer decline to a great extent afterwards to a certain extent, now, even if being rushed by less short circuit
Electric current is hit to be also possible to that big accident can be triggered to occur.
On the one hand winding deformation can cause Transformer Winding mechanical strength to decline, on the other hand can also cause coil inside office
Portion's insulation distance changes, and minor insulation weak spot occurs, when running into overvoltage effect, it is possible to occurs between cake or turn-to-turn
Short circuit causes transformer insulated breakdown accident, or causes shelf depreciation because local field strength increases, the meeting of insulation harm position
Gradually expand, ultimately result in transformer and dielectric breakdown accident occurs and triggers the further state of affairs to expand.
Therefore, conventional inspection after transformer experienced external short circuit accident or after operation a period of time in the process of running
In repairing, Transformer Winding how is effectively detected with the presence or absence of loosening and deformation, and then take effective O＆M measure just to show
Must be particularly significant, this is the important means for ensureing transformer safety operation.
At present, winding deformation detection is one of routine test project of current transformer, the detection method in practical application
Mainly there are short circuit impedance method and Frequency Response Analysis method.Wherein, short circuit impedance method by the short-circuit reactance of transformer is detected come
Judge whether subject Transformer Winding is qualified.Generally, after operating transformer receives the impact of short circuit current, or
In regular routine inspection by the short-circuit impedance value measured and original record be compared to judge winding whether there occurs
Deformation, if short-circuit impedance value changes are larger, such as it is set as that change more than 3%, then can confirm that winding has notable change in national standard
Shape.Up to the present, short circuit impedance method has established standard in long-term production practices, and criterion is more clear and definite, in international electricity
The criterion of winding deformation degree is clearly given in work standard IEC 60076-5 and GB1095-85.It is but this in many cases
The sensitivity of method is very low, only can just access clearer and more definite reflection when coil overall deformation situation is more serious.
Frequency Response Analysis method judges it by analyzing the situation of change of the network transfer function curve of Transformer Winding to analyze
Whether internal network electrical parameter changes, so as to infer whether corresponding mechanical structure is deformed.I.e. by a stabilization
Sine sweep voltage signal ViOne end of subject Transformer Winding is applied to, then records port V simultaneouslyiWith other outputs
Voltage V on porto, so as to obtain the one of the subject winding group of Frequency Response curve, its expression formula is
H (j ω)=Vo/Vi
The measurement sensitivity of Frequency Response Analysis method is high compared with short circuit impedance method, but due to the complexity of its frequency response waveform, to winding
The differentiation of situation needs more experience, it is more difficult to forms clear and definite quantitative criteria, therefore does not form discrimination standard so far.
The starting point of short circuit impedance method and Frequency Response Analysis method both approaches is sent out according to the electrical parameter of Transformer Winding
Changing measures differentiation to it, and it is more suitable that this Transformer Winding occurs obvious deformation, but to winding
Generation slight deformation, especially relative loosening and torsional deformation state existing for Transformer Winding can not be provided more clear and definite
Judge.Loosened in view of Transformer Winding or torsional deformation has a great impact to its anti-short circuit capability, it is therefore desirable to sought more
For sensitive winding condition diagnosing method.
The general principle of vibration analysis method developed in recent years is that Transformer Winding is regarded as a mechanical structure body,
Then when any change occurs for winding construction or stress, it can be reflected from its mechanical vibration performance change.Winding
Vibration transformer-cabinet is delivered to by inside transformer structural connection, so shaking of obtaining of transformer-cabinet Surface testing
The basket vibration characteristic of dynamic signal and transformer has close relationship.Believe in view of transformer-cabinet surface vibration under sudden short circuit
Number predominantly basket vibration, therefore, can using the analysis of vibration signal on transformer-cabinet surface as transformer winding fault diagnosis
An approach.Compared with foregoing electrical measurements, the great advantage of vibration analysis method is can be by adsorbing in transformer tank
Vibrating sensor on wall obtains the vibration signal of transformer, judges winding state by analyzing the change of its vibration characteristics
Situation of change, can shaking from it as long as the mechanical property (such as malformation, pretightning force loosen) of winding changes
Reflected in dynamic characteristic change, so as to substantially increase the sensitivity of detection.In addition, vibrating sensor is placed on tank wall
Vibration detection is not connected directly with whole strong power system, can develop into a kind of more accurate, convenient, safe on-line monitoring
Method.
When transformer is by sudden short circuit, huge electrodynamic action is had in Transformer Winding so that transformer shakes
Stage, vibration amplitude metastable stage and the short circuit of vibration amplitude increase is presented in dynamic aggravation, its vibrational waveform in time domain
The vibration amplitude decling phase after current vanishes.Therefore, can from sudden short circuit when vibrational waveform time domain form on seek transformation
The change indicator of device winding state, and use it for the efficient diagnosis of transformer winding state.
The content of the invention
The technical problems to be solved by the invention are：A kind of transformer sudden short circuit based on vibration signal morphology spectrum is provided
Lower winding state diagnostic method, transformer box wall vibration signal is to winding work when can be by monitoring transformer sudden short circuit on-line
Differentiated as state.
Solves above-mentioned technical problem, the technical solution adopted in the present invention is as follows：
Winding state diagnostic method under a kind of transformer sudden short circuit based on vibration signal morphology spectrum, including following step
Suddenly：
(1) short circuit monitoring in real time is carried out to transformer, also, collection becomes whenever detecting that sudden short circuit occurs for transformer
One section of continuous vibration signal of depressor tank wall, and transformation each time is calculated by the method for following steps (2) to step (6)
Device occurs to gather the steady-state vibration signal aspect spectrum entropy of vibration signal during sudden short circuit；Wherein, sudden short circuit occurs for transformer
When to transformer box wall gather vibration signal at the beginning of between should try one's best close to transformer occur sudden short circuit initial time,
The end time of transformer box wall collection vibration signal can be judged by existing vibration detection device, with as far as possible complete
Collect transformer box wall because sudden short circuit and caused vibration signal occur for transformer；
The vibration signal that above-mentioned transformer each time occurs to be collected from transformer box wall during sudden short circuit is expressed as x0
(t)；
(2) as steps described below according to vibration signal x0(t) white noise of the narrowband signal g (t) is constructed：
2a. is to vibration signal x0(t) Fourier transformation is carried out, obtains vibration signal x0(t) spectrum distribution；In this step
Fourier transformation is mathematical method conventional in the art, therefore inventor is no longer described in detail herein；
2b. is according to vibration signal x0(t) spectrum distribution generation white noise signal s0(t), wherein white noise signal s0(t)
Amplitude A expression formula be
In formula, K is coefficient, and COEFFICIENT K value is vibration signal x0(t) the 1/10 of amplitude average value；NfFor vibration signal x0
(t) highest frequency component f in spectrum componentHWith 50Hz ratio；fi(i=1,2 ..., Nf) it is vibration signal x0(t) each
Frequency component；ai(i=1,2 ..., Nf) it is vibration signal x0(t) amplitude corresponding to each frequency component；
2c. is using Butterworth bandpass filter to white noise signal s0(t) it is filtered, obtains white noise of the narrowband signal
g(t)；The transmission function expression formula of the Butterworth bandpass filter is
In formula, ωcl=KL2πfLFor low-frequency cut-off frequency, fLFor vibration signal x0(t) low-limit frequency in spectrum component point
Amount, KLFor low frequency bandwidth factor, 1.5 are generally taken；ωch=KH2πfHFor high-frequency cut-off frequency, fHFor vibration signal x0(t) frequency spectrum
Highest frequency component in component, KHFor high frequency bandwidth coefficient, 0.8 is generally taken；M is filter order；The π f ' of ω=2 are angular frequency
Rate, f '=50Hz；
(3) by vibration signal x0(t) it is added with white noise of the narrowband signal g (t), obtains superposed signal x (t), according to
Superposed signal x (t) is decomposed into several intrinsic mode function component (Intrinsic Mode Function, letters by following step
Referred to as IMF components)：
3a. obtains time series y (t) to superposed signal x (t) derivations；
3b. calculates adjacent 2 points of time series y (t) product
pyi(t)=yi(t)×yi-1(t)
In formula, i=2,3 ..., N-1, wherein, N counts for signal；
3c. is according to product pyi(t) it is positive and negative with time series y (t), superposed signal x (t) all parts are looked for successively
Maximum point eb (t) and all local minizing point es (t)：
Work as pyi(t) during ＜ 0, if pyi(t) ＜ 0 and yi-1(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ＜
0 and yi-1(t) ＞ 0, then xi-1(t) it is Local modulus maxima；
Work as pyi(t) during ＞ 0, xi-1(t) it is non-extreme point；
Work as pyi(t) when=0, if yi-1(t) two point y=0, are calculatediAnd y (t)i-2(t) product, makes pyi(t) '=yi(t)
×yi-2(t), if pyi(t) ' ＜ 0 and yi-2(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ' ＜ 0 and yi-2(t) ＞
0, then xi-1(t) it is Local modulus maxima；If yi-2(t)=0, then xi-1(t) it is non-extreme point；
All Local modulus maxima eb (t) and all local minizing point es (t) are used cubic spline functions s by 3d.
(t) connect and obtain coenvelope line e respectivelymaxAnd lower envelope line e (t)min(t), described cubic spline functions s (t)
It is each minizone [t in superposed signal x (t)i,ti+1] it is no more than multinomial three times on (i=1,2 ..., N-1), its
Expression formula is
In formula, miAnd mi+1It is cubic spline functions s (t) in section [ti,ti+1] second derivative values at two-end-point；
The algorithm of envelope is mathematical method conventional in the art in this step, therefore inventor no longer carries out detailed retouch herein
State；
3e. is according to the coenvelope line e tried to achievemaxAnd lower envelope line e (t)min(t) the average m (t) of upper and lower envelope is calculated
=(emax(t)+emin(t) superposed signal x (t))/2, is subtracted into m (t), obtains a new time series y1(t)；
3f. judges time series y1(t) whether following two conditions are met simultaneously：
A. in whole signal length, the number of extreme point and zero crossing must be equal or at most only differs one；
B. at any time, the coenvelope line defined by maximum point and the lower envelope line that is defined by minimum point are averaged
Value is zero；
If meet above-mentioned two condition, y simultaneously1(t) it is intrinsic mode function component；If above-mentioned two can not be met simultaneously
Individual condition, then by y1(t) original component is used as, abovementioned steps 3a~3e is repeated, until time series y1(t) meet simultaneously
Above-mentioned two condition, the y of above-mentioned two condition will be met simultaneously1(t) it is designated as ci(t), then ci(t) it is the one of superposed signal x (t)
Individual intrinsic mode function component, and i=1,2 ..., Nh, NhFor superposed signal x (t) intrinsic mode function component total quantity；
3g. is by ci(t) separated from superposed signal x (t), obtain difference signal ri(t) it is
ri(t)=x (t)-ci(t)
3h. is by difference signal ri(t) as pending signal substituting superposed signal x (t) come the 3a~3g that repeats the above steps,
Until meeting Stopping criteria, whole N are obtainedhIndividual intrinsic mode function component, the Stopping criteria are：Obtain new
Time series yi(t) it is narrow band signal, the narrow band signal refers to that the bandwidth deltaf f of signal is much smaller than centre frequency fCSignal, its is general
Read as well known to one of ordinary skilled in the art；
By above-mentioned steps, vibration signal x0(t) several intrinsic mode function components have been broken down into difference to believe
Number sum, its expression formula are
x0(t)=∑ ci(t)+ri(t)；
(4) vibration signal x is calculated0(t) phase between each obtained intrinsic mode function component is decomposed with step (3)
Relation number, and the intrinsic mode function component chosen corresponding to the maximum coefficient correlation of numerical value is characterized vibration natural mode of vibration point
Amount, is designated as IMFm；
Wherein, the vibration signal x0(t) phase of k-th of the intrinsic mode function component obtained with the middle decomposition of step (3)
Relation number corkCalculation formula be
In formula, x0i(t) it is vibration signal x0(t) in t+i/f0The amplitude at moment；For vibration signal x0(t) amplitude
Average value；cki(t) for k-th of intrinsic mode function component in t+i/f0The amplitude at moment；For k-th of natural mode
Formula function component ck(t) average value of amplitude；f0For vibration signal x0(t) sample frequency；
(5) as steps described below according to natural mode of vibration component IMFmPeak change determine vibration signal x0(t) steady-state vibration
The initial time t of processbWith finish time te, and remember vibration signal x0(t) from initial time tbTo finish time tePeriod
Interior part is steady-state vibration signal xs(t)：
5a. calculates eigen vibration natural mode of vibration component IMFmSpectrum distribution, choose amplitude maximum in spectrum component and shake
Dynamic frequency is characterized frequency, is designated as fm；
5b. is from vibration signal x0(t) initial time starts to calculate vibration signal x successively in chronological order0(t) each
The grid number Ng (t) at moment, wherein, grid number Ng (t) refers to vibration signal x0(t) in period [t, t+0.5Tm] interior variable quantity
The average value of absolute value sum, its calculation formula are
Tm=1/fm
In formula, N0For vibration signal x0(t) in period [t, t+0.5Tm] in data length；x0iAnd x (t)0(i+1)(t)
Respectively vibration signal is in t+i/f0Moment and t+ (i+1)/f0The amplitude at moment；TmIt is characterized frequency fmInverse；
5c. is in chronological order successively to vibration signal x0(t) the grid number Ng (t) at each moment is screened, screening
Principle be：If grid number Ng (t) sometime is more than default threshold value, retain the grid number at the moment；If some when
The Ng (t) at quarter is less than default threshold value, then the grid number at the moment is arranged into 0；Remember vibration signal x0(t) after being screened
Grid number is grid number Ng'(t after screening)；Wherein, the preferred value of default threshold value for grid number Ng (t) maximums 20% simultaneously
Round value；
5d. is since grid number Ng'(t after screening) in first non-zero grid number at the time of correspond to opened successively
Top-hat computings, first peak value detected is vibration signal x0(t) the initial time t of steady-state vibration processb；From screening
Grid number Ng'(t afterwards) in last non-zero grid number start reversely to carry out out Top-hat computings successively at the time of correspond to, examine
First peak value measured is vibration signal x0(t) the finish time t of steady-state vibration processe；Described opens Top-hat computings
Expression formula be
In formula, f is grid number Ng'(t)；G is structural element；To carry out out fortune to signal f using structural element g
Calculate；F Θ g are to carry out erosion operation to signal f using structural element g；To use structural element g to signal f Θ g
Carry out dilation operation；The basic operation of mathematical morphology, is conventional in the art when described dilation operation and erosion operation
Mathematical method, therefore inventor is no longer described in detail herein；
(6) steady-state vibration signal x is calculateds(t) morphology spectrum and morphology spectrum entropy, its calculation formula are
Q (λ)=PSf(λ,g)/S(f·λming)
In formula, H (f/g) is morphology spectrum entropy；PSf(λ, g) is morphology spectrum；F is grid number Ng'(t)；G is structural element；λ
For yardstick；λmaxFor yardstick maximum；λminFor yardstick minimum value.f·λminG represents to use structural element λminG is carried out to signal f
Closed operation；Represent to carry out opening operation to signal f using structural element λ g；
Represent to carry out opening operation to signal f using structural element (λ+1) g；
F (- λ) g represents to carry out closed operation to signal f using structural element (- λ) g；
F (- λ+1) g represents to carry out closed operation to signal f using structural element (- λ+1) g；
(7) according to steady-state vibration signal xs(t) morphology spectrum entropy differentiates to winding state：When the change of morphology spectrum entropy
Δ H meetsWhen, judge that in transformer the short circuit of Y secondary bursts occurs for the winding of transformer
Shi Fasheng loosens or deformation, now needs to carry out overhaul plan in time, avoids the formation of significant trouble；Wherein, H1For transformer the 1st
The secondary steady-state vibration signal aspect spectrum entropy for occurring to gather vibration signal during sudden short circuit, HYHappened suddenly for the Y times for transformer
The steady-state vibration signal aspect spectrum entropy of vibration signal is gathered when short-circuit.
Compared with prior art, the invention has the advantages that：
First, the transformer box wall vibration signal when present invention is by monitoring transformer sudden short circuit on-line, and from transformation
Device occurs sudden short circuit state at second and started, and the steady-state vibration for gathering vibration signal when this sudden short circuit state is lower is believed
Sentence compared with the steady-state vibration signal aspect spectrum entropy of number morphology spectrum entropy when first time sudden short circuit state is occurring for transformer
Not, the working condition of Transformer Winding is judged, in order to be able to pinpoint the problems in time, transformer is overhauled in time, have
There is accurately and efficiently advantage.
Second, the present invention constructs white noise of the narrowband signal in step 2 according to the spectral characteristic of transformer vibration signal,
Vibration signal is effectively inhibited to improve using the modal overlap phenomenon that empirical mode decomposition is in intrinsic mode function decomposable process
Discomposing effect, improve the accuracy composed entropy according to steady-state vibration signal aspect and judged winding state under sudden short circuit.
Brief description of the drawings
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings：
Fig. 1 is the vibrational waveform when transformer winding state monitored in the present embodiment is good；
Fig. 2 is the vibrational waveform when transformer winding state monitored in the present embodiment deteriorates；
Fig. 3 shows morphology spectrum when transformer winding state is well with loosening in the present embodiment.
Embodiment
Short-circuit impact experiment is carried out by subjects of certain Utilities Electric Co. 35kV transformers.Mesolow short circuit in winding is tested,
High pressure B phase windings are powered, and carry out 3 short-circuit impacts, record the vibration signal in each short-circuit impact experiment, and Fig. 1 shows change
Vibrational waveform when depressor winding state is good, Fig. 2 show vibrational waveform when Transformer Winding working condition deteriorates.
Winding working condition when the present invention judges transformer short-circuit according to the following steps：
(1) short circuit monitoring in real time is carried out to transformer, also, collection becomes whenever detecting that sudden short circuit occurs for transformer
One section of continuous vibration signal of depressor tank wall, and transformation each time is calculated by the method for following steps (2) to step (6)
Device occurs to gather the steady-state vibration signal aspect spectrum entropy of vibration signal during sudden short circuit；Wherein, sudden short circuit occurs for transformer
When to transformer box wall gather vibration signal at the beginning of between should try one's best close to transformer occur sudden short circuit initial time,
The end time of transformer box wall collection vibration signal can be judged by existing vibration detection device, with as far as possible complete
Collect transformer box wall because sudden short circuit and caused vibration signal occur for transformer；In this example, transformer is gathered
Vibration signal from the generation sudden short circuit moment in 0.45s, completely to collect transformer box wall because transformer occurs to dash forward
Send out short circuit and caused vibration signal；
The vibration signal that above-mentioned transformer each time occurs to be collected from transformer box wall during sudden short circuit is expressed as x0
(t)。
(2) as steps described below according to vibration signal x0(t) white noise of the narrowband signal g (t) is constructed：
2a. is to vibration signal x0(t) Fourier transformation is carried out, obtains vibration signal x0(t) spectrum distribution；In this step
Fourier transformation is mathematical method conventional in the art, therefore inventor is no longer described in detail herein；
2b. according to vibration signal x0(t) spectrum distribution generation white noise signal s0(t), wherein white noise signal s0(t)
Amplitude A expression formula be
In formula, K is coefficient, and COEFFICIENT K value is vibration signal x0(t) the 1/10 of amplitude average value, takes 0.4；NfBelieve for vibration
Number x0(t) highest frequency component f in spectrum componentHWith 50Hz ratio；fi(i=1,2 ..., Nf) it is vibration signal x0(t) each
Individual frequency component；ai(i=1,2 ..., Nf) it is vibration signal x0(t) amplitude corresponding to each frequency component；
2c. is using Butterworth bandpass filter to white noise signal g0(t) it is filtered, obtains white noise of the narrowband signal
s(t)；The transmission function expression formula of the Butterworth bandpass filter is
In formula, ωcl=KL2πfLFor low-frequency cut-off frequency, fLFor vibration signal x0(t) low-limit frequency in spectrum component point
Amount, KLFor low frequency bandwidth factor；ωch=KH2πfHFor high-frequency cut-off frequency, KHFor high frequency bandwidth coefficient；M is filter order,
Take 4；Wherein, KL=1.5, KH=0.8；The π f ' of ω=2 are angular frequency, f '=50Hz；
(3) by vibration signal x0(t) it is added with white noise of the narrowband signal g (t), obtains superposed signal x (t), according to
Superposed signal x (t) is decomposed into several IMF components by following step：
3a. obtains time series y (t) to superposed signal x (t) derivations；
3b. calculates adjacent 2 points of time series y (t) product
pyi(t)=yi(t)×yi-1(t)
In formula, i=2,3 ..., N-1, wherein, N counts for signal；
3c. is according to product pyi(t) it is positive and negative with time series y (t), superposed signal x (t) all parts are looked for successively
Maximum point eb (t) and all local minizing point es (t)：
Work as pyi(t) during ＜ 0, if pyi(t) ＜ 0 and yi-1(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ＜
0 and yi-1(t) ＞ 0, then xi-1(t) it is Local modulus maxima；
Work as pyi(t) during ＞ 0, xi-1(t) it is non-extreme point；
Work as pyi(t) when=0, if yi-1(t) two point y=0, are calculatediAnd y (t)i-2(t) product, makes pyi(t) '=yi(t)
×yi-2(t), if pyi(t) ' ＜ 0 and yi-2(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ' ＜ 0 and yi-2(t) ＞
0, then xi-1(t) it is Local modulus maxima；If yi-2(t)=0, then xi-1(t) it is non-extreme point；
All Local modulus maxima eb (t) and all local minizing point es (t) are used cubic spline functions s by 3d.
(t) connect and obtain coenvelope line e respectivelymaxAnd lower envelope line e (t)min(t), the cubic spline functions s (t) be
Superposed signal x (t) each minizone [ti,ti+1] it is no more than multinomial three times on (i=1,2 ..., N-1), it is expressed
Formula is
In formula, miAnd mi+1It is cubic spline functions s (t) in section [ti,ti+1] second derivative values at two-end-point；
3e. is according to the coenvelope line e tried to achievemaxAnd lower envelope line e (t)min(t) the average m (t) of upper and lower envelope is calculated
=(emax(t)+emin(t) superposed signal x (t))/2, is subtracted into m (t), obtains a new time series y1(t)；
3f. judges time series y1(t) whether following two conditions are met simultaneously：
A. in whole signal length, the number of extreme point and zero crossing must be equal or at most only differs one；
B. at any time, the coenvelope line defined by maximum point and the lower envelope line that is defined by minimum point are averaged
Value is zero；
If meet above-mentioned two condition, y simultaneously1(t) it is intrinsic mode function component；If above-mentioned two can not be met simultaneously
Individual condition, then by y1(t) original component is used as, abovementioned steps 3a~3e is repeated, until time series y1(t) meet simultaneously
Above-mentioned two condition, the y of above-mentioned two condition will be met simultaneously1(t) it is designated as ci(t), then ci(t) it is the one of superposed signal x (t)
Individual intrinsic mode function component, and i=1,2 ..., Nh, NhFor superposed signal x (t) intrinsic mode function component total quantity；
3g. is by ci(t) separated from superposed signal x (t), obtain difference signal ri(t) it is
ri(t)=x (t)-ci(t)
3h. is by difference signal ri(t) as pending signal substituting superposed signal x (t) come the 3a~3g that repeats the above steps,
Until meeting Stopping criteria, whole N are obtainedhIndividual intrinsic mode function component, Stopping criteria are：Obtain the new time
Sequences yi(t) it is narrow band signal；
By above-mentioned steps, initial vibration signal x0(t) 6 IMF components have been broken down into.
(4) vibration signal x is calculated0(t) phase between each obtained intrinsic mode function component is decomposed with step (3)
Relation number, and the intrinsic mode function component chosen corresponding to the maximum coefficient correlation of numerical value is characterized vibration natural mode of vibration point
Amount, is designated as IMFm；
Wherein, the vibration signal x0(t) phase of k-th of the intrinsic mode function component obtained with the middle decomposition of step (3)
Relation number corkCalculation formula be
In formula, x0i(t) it is vibration signal x0(t) in t+i/f0The amplitude at moment；For vibration signal x0(t) amplitude
Average value；cki(t) for k-th of intrinsic mode function component in t+i/f0The amplitude at moment；For k-th of natural mode
Formula function component ck(t) average value of amplitude；f0For vibration signal x0(t) sample frequency；
(5) as steps described below according to natural mode of vibration component IMFmPeak change determine vibration signal x0(t) steady-state vibration
The initial time t of processbWith finish time te, and remember vibration signal x0(t) from initial time tbTo finish time tePeriod
Interior part is steady-state vibration signal xs(t)：
5a. calculates eigen vibration natural mode of vibration component IMFmSpectrum distribution, choose amplitude maximum in spectrum component and shake
Dynamic frequency is characterized frequency, is designated as fm, it is herein 100Hz；
5b. is from vibration signal x0(t) initial time starts to calculate vibration signal x successively in chronological order0(t) each
The grid number Ng (t) at moment, wherein, grid number Ng (t) refers to vibration signal x0(t) in period [t, t+0.5Tm] interior variable quantity
The average value of absolute value sum, its calculation formula are
Tm=1/fm
In formula, N0For vibration signal x0(t) in period [t, t+0.5Tm] in data length；x0iAnd x (t)0(i+1)(t)
Respectively vibration signal is in t+i/f0Moment and t+ (i+1)/f0The amplitude at moment；f0For vibration signal x0(t) sampling frequency
Rate, it is herein 10240；TmIt is characterized frequency fmInverse, be herein 0.01；
5c. is in chronological order successively to vibration signal x0(t) the grid number Ng (t) at each moment is screened, screening
Principle be：If grid number Ng (t) sometime is more than default threshold value, retain the grid number at the moment；If some when
The Ng (t) at quarter is less than default threshold value, then the grid number at the moment is arranged into 0；Remember vibration signal x0(t) after being screened
Grid number is grid number Ng'(t after screening)；Wherein, default threshold value value is the 20% of grid number Ng (t) maximums and rounded
Value；
5d. is since grid number Ng'(t after screening) in first non-zero grid number at the time of correspond to opened successively
Top-hat computings, first peak value detected is vibration signal x0(t) the initial time t of steady-state vibration processb；From screening
Grid number Ng'(t afterwards) in last non-zero grid number start reversely to carry out out Top-hat computings successively at the time of correspond to, examine
First peak value measured is vibration signal x0(t) the finish time t of steady-state vibration processe；Described opens Top-hat computings
Expression formula be
In formula, f is grid number Ng'(t)；G is structural element；To carry out out fortune to signal f using structural element g
Calculate；F Θ g are to carry out erosion operation to signal f using structural element g；To use structural element g to signal f Θ g
Carry out dilation operation；The basic operation of mathematical morphology, is conventional in the art when described dilation operation and erosion operation
Mathematical method, therefore inventor is no longer described in detail herein；
(6) steady-state vibration signal x is calculateds(t) morphology spectrum and morphology spectrum entropy, its calculation formula are
Q (λ)=PSf(λ,g)/S(f·λming)
In formula, H (f/g) is morphology spectrum entropy；PSf(λ, g) is morphology spectrum；F is grid number Ng'(t)；G is structural element；λ
For yardstick；λmaxIt is herein 51 for yardstick maximum；λminIt is herein 1 for yardstick minimum value.f·λminG represents to use structural elements
Plain λminG carries out closed operation to signal f；Represent to carry out opening operation to signal f using structural element λ g；
Represent to carry out opening operation to signal f using structural element (λ+1) g；
F (- λ) g represents to carry out closed operation to signal f using structural element (- λ) g；
F (- λ+1) g represents to carry out closed operation to signal f using structural element (- λ+1) g.
Fig. 3 is morphology spectrum when transformer winding state is well with loosening in the present embodiment.
(7) according to steady-state vibration signal xs(t) morphology spectrum entropy differentiates to winding state：When the change of morphology spectrum entropy
Δ H meetsWhen, judge that in transformer the short circuit of Y secondary bursts occurs for the winding of transformer
Shi Fasheng loosens or deformation, now needs to carry out overhaul plan in time, avoids the formation of significant trouble；Wherein, H1For transformer the 1st
The secondary steady-state vibration signal aspect spectrum entropy for occurring to gather vibration signal during sudden short circuit, HYHappened suddenly for the Y times for transformer
The steady-state vibration signal aspect spectrum entropy of vibration signal is gathered when short-circuit.
As it can be seen from table 1 in the present embodiment, preceding 2 short-circuit impacts, the absolute value rate of the change of its morphology spectrum entropy is
2.97%, illustrate that transformer winding state is normal.When 3rd Secondary Shocks are tested, the absolute value of the change of morphology spectrum entropy is
28.31%, show transformer winding state exception, it is necessary to be overhauled in time to it, avoid the formation of significant trouble.
Table 1
| Short-circuit impact number | Morphology spectrum entropy | Morphology spectrum progressive increase rate/% |
| 1 | 0.70493 | - |
| 2 | 0.68402 | 2.97 |
| 3 | 0.90449 | 28.31 |
The present invention do not limit to above-mentioned embodiment, according to the above, according to the ordinary technical knowledge of this area
And customary means, under the premise of the above-mentioned basic fundamental thought of the present invention is not departed from, the present invention can also make other diversified forms
Equivalent modifications, replacement or change, all fall among protection scope of the present invention.
Claims (6)
1. winding state diagnostic method under a kind of transformer sudden short circuit based on vibration signal morphology spectrum, comprises the following steps：
(1) short circuit monitoring in real time is carried out to transformer, also, transformer is gathered whenever detecting that sudden short circuit occurs for transformer
One section of continuous vibration signal of tank wall, and transformer hair each time is calculated by the method for following steps (2) to step (6)
The steady-state vibration signal aspect spectrum entropy of vibration signal is gathered during raw sudden short circuit；
Wherein, the vibration signal that above-mentioned transformer each time occurs to be collected from transformer box wall during sudden short circuit is expressed as x0
(t)；
(2) vibration signal x is used0(t) white noise of the narrowband signal g (t) is constructed；
(3) by vibration signal x0(t) it is added with white noise of the narrowband signal g (t), obtains superposed signal x (t), and superposition is believed
Number x (t) is decomposed into several intrinsic mode function components；
(4) vibration signal x is calculated0(t) and step (3) decomposes the phase relation between each obtained intrinsic mode function component
Number, and the intrinsic mode function component chosen corresponding to the maximum coefficient correlation of numerical value is characterized vibration natural mode of vibration component, note
For IMFm；
Wherein, the vibration signal x0(t) coefficient correlation of k-th of the intrinsic mode function component obtained with the middle decomposition of step (3)
corkCalculation formula be
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In formula, x0i(t) it is vibration signal x0(t) in t+i/f0The amplitude at moment；For vibration signal x0(t) amplitude is flat
Average；cki(t) for k-th of intrinsic mode function component in t+i/f0The amplitude at moment；For k-th of natural mode letter
Number component ck(t) average value of amplitude；f0For vibration signal x0(t) sample frequency；
(5) according to natural mode of vibration component IMFmPeak change determine vibration signal x0(t) the initial time t of steady-state vibration processb
With finish time te, and remember vibration signal x0(t) from initial time tbTo finish time tePeriod in part shaken for stable state
Dynamic signal xs(t)；
(6) steady-state vibration signal x is calculateds(t) morphology spectrum and morphology spectrum entropy, its calculation formula are
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Q (λ)=PSf(λ,g)/S(f·λming)
In formula, H (f/g) is morphology spectrum entropy；PSf(λ, g) is morphology spectrum；F is grid number Ng'(t)；G is structural element；λ is chi
Degree；λmaxFor yardstick maximum；λminFor yardstick minimum value；f·λminG represents to use structural element λminG carries out closing fortune to signal f
Calculate；Represent to carry out opening operation to signal f using structural element λ g；Expression uses structural element (λ+1)
G carries out opening operation to signal f；F (- λ) g represents to carry out closed operation to signal f using structural element (- λ) g；f·(-λ+1)g
Represent to carry out closed operation to signal f using structural element (- λ+1) g；
(7) according to steady-state vibration signal xs(t) morphology spectrum entropy differentiates to winding state：When the changes delta H of morphology spectrum entropy expires
FootWhen, judge that the winding of transformer occurs when Y secondary burst short circuits occur for transformer
Loosen or deform；Wherein, H1Steady-state vibration signal aspect by gathering vibration signal during the 1st generation sudden short circuit of transformer
Compose entropy, HYEntropy is composed by the steady-state vibration signal aspect that vibration signal is gathered during the Y times generation sudden short circuit of transformer.
2. according to the method for claim 1, it is characterised in that：In the step (1a), the transformer box wall is gathered
The initial time of sudden short circuit occurs between at the beginning of vibration signal close to the transformer.
3. according to the method for claim 1, it is characterised in that：In described step (2), with vibration signal x0(t) construct
White noise of the narrowband signal g (t) method comprises the following steps：
2a. is to vibration signal x0(t) Fourier transformation is carried out, obtains vibration signal x0(t) spectrum distribution；
2b. is according to vibration signal x0(t) spectrum distribution generation white noise signal s0(t), wherein white noise signal s0(t) width
Value A expression formula is
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In formula, K is coefficient, and COEFFICIENT K value is vibration signal x0(t) the 1/10 of amplitude average value；NfFor vibration signal x0(t) frequency
Highest frequency component f in spectral componentHWith 50Hz ratio；fi(i=1,2 ..., Nf) it is vibration signal x0(t) each frequency point
Amount；ai(i=1,2 ..., Nf) it is vibration signal x0(t) amplitude corresponding to each frequency component；
2c. is using Butterworth bandpass filter to white noise signal s0(t) it is filtered, obtains white noise of the narrowband signal g (t)；
The transmission function expression formula of the Butterworth bandpass filter is
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In formula, ωcl=KL2πfLFor low-frequency cut-off frequency, fLFor vibration signal x0(t) lowest frequency components in spectrum component, KL
For low frequency bandwidth factor；ωch=KH2πfHFor high-frequency cut-off frequency, fHFor vibration signal x0(t) highest frequency in spectrum component
Component, KHFor high frequency bandwidth coefficient；M is filter order；The π f ' of ω=2 are angular frequency, f '=50Hz.
4. according to the method for claim 1, it is characterised in that：In described step (3), superposed signal x (t) is decomposed into
The method of several intrinsic mode function components comprises the following steps：
3a. obtains time series y (t) to superposed signal x (t) derivations；
3b. calculates adjacent 2 points of time series y (t) product
pyi(t)=yi(t)×yi-1(t)
In formula, i=2,3 ..., N-1, wherein, N counts for signal；
3c. is according to product pyi(t) it is positive and negative with time series y (t), superposed signal x (t) all local maximums are looked for successively
Point eb (t) and all local minizing point es (t)：
Work as pyi(t) during ＜ 0, if pyi(t) ＜ 0 and yi-1(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ＜ 0 and
yi-1(t) ＞ 0, then xi-1(t) it is Local modulus maxima；
Work as pyi(t) during ＞ 0, xi-1(t) it is non-extreme point；
Work as pyi(t) when=0, if yi-1(t) two point y=0, are calculatediAnd y (t)i-2(t) product, makes pyi(t) '=yi(t)×yi-2
(t), if pyi(t) ' ＜ 0 and yi-2(t) ＜ 0, then xi-1(t) it is local minizing point；If pyi(t) ' ＜ 0 and yi-2(t) ＞ 0, then
xi-1(t) it is Local modulus maxima；If yi-2(t)=0, then xi-1(t) it is non-extreme point；
3d. connects all Local modulus maxima eb (t) and all local minizing point es (t) with cubic spline functions s (t)
Pick up to obtain coenvelope line e respectivelymaxAnd lower envelope line e (t)min(t), described cubic spline functions s (t) is folded
Plus signal x (t) each minizone [ti,ti+1] it is no more than multinomial three times, its expression formula on (i=1,2 ..., N-1)
For
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In formula, miAnd mi+1It is cubic spline functions s (t) in section [ti,ti+1] second derivative values at two-end-point；
3e. is according to the coenvelope line e tried to achievemaxAnd lower envelope line e (t)min(t) calculate the average m (t) of upper and lower envelope=
(emax(t)+emin(t) superposed signal x (t))/2, is subtracted into m (t), obtains a new time series y1(t)；
3f. judges time series y1(t) whether following two conditions are met simultaneously：
A. in whole signal length, the number of extreme point and zero crossing must be equal or at most only differs one；
B. at any time, the average value of the coenvelope line defined by maximum point and the lower envelope line defined by minimum point is
Zero；
If meet above-mentioned two condition, y simultaneously1(t) it is intrinsic mode function component；If above-mentioned two bar can not be met simultaneously
Part, then by y1(t) original component is used as, abovementioned steps 3a~3e is repeated, until time series y1(t) while meet above-mentioned
Two conditions, the y of above-mentioned two condition will be met simultaneously1(t) it is designated as ci(t), then ci(t) one for superposed signal x (t) is solid
There are mode function component, and i=1,2 ..., Nh, NhFor superposed signal x (t) intrinsic mode function component total quantity；
3g. is by ci(t) separated from superposed signal x (t), obtain difference signal ri(t) it is ri(t)=x (t)-ci(t)
3h. is by difference signal ri(t) as pending signal substituting superposed signal x (t) come the 3a~3g that repeats the above steps, until
Meet Stopping criteria, obtain whole NhIndividual intrinsic mode function component, the Stopping criteria are：Obtain the new time
Sequences yi(t) it is narrow band signal；
By above-mentioned steps, vibration signal x0(t) be broken down into several intrinsic mode function components and difference signal it
With its expression formula is
x0(t)=∑ ci(t)+ri(t)。
5. according to the method for claim 1, it is characterised in that：In described step (5), according to natural mode of vibration component IMFm
Peak change determine vibration signal x0(t) the initial time t of steady-state vibration processb, finish time teWith steady-state vibration signal xs
(t) method comprises the following steps：
5a. calculates eigen vibration natural mode of vibration component IMFmSpectrum distribution, choose spectrum component in amplitude maximum vibration frequency
Frequency is characterized, is designated as fm；
5b. is from vibration signal x0(t) initial time starts to calculate vibration signal x successively in chronological order0(t) at each moment
Grid number Ng (t), wherein, grid number Ng (t) refers to vibration signal x0(t) in period [t, t+0.5Tm] interior variable quantity is absolute
It is worth the average value of sum, its calculation formula is
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<mn>0.5</mn>
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Tm=1/fm
In formula, N0For vibration signal x0(t) in period [t, t+0.5Tm] in data length；x0iAnd x (t)0(i+1)(t) respectively
It is vibration signal in t+i/f0Moment and t+ (i+1)/f0The amplitude at moment；f0For vibration signal x0(t) sample frequency；Tm
It is characterized frequency fmInverse；
5c. is in chronological order successively to vibration signal x0(t) the grid number Ng (t) at each moment is screened, the principle of screening
For：If grid number Ng (t) sometime is more than default threshold value, retain the grid number at the moment；If Ng sometime
(t) it is less than default threshold value, then the grid number at the moment is arranged to 0；Remember vibration signal x0(t) grid number after being screened
For grid number Ng'(t after screening)；
5d. is since grid number Ng'(t after screening) in first non-zero grid number at the time of correspond to carry out out Top-hat successively
Computing, first peak value detected is vibration signal x0(t) the initial time t of steady-state vibration processb；The grid after screening
Number Ng'(t) in last non-zero grid number start reversely to carry out out Top-hat computings successively at the time of correspond to, detect
First peak value is vibration signal x0(t) the finish time t of steady-state vibration processe；The described expression for opening Top-hat computings
Formula is
In formula, f is grid number Ng'(t)；G is structural element；To carry out opening operation to signal f using structural element g；fΘ
G is to carry out erosion operation to signal f using structural element g；To be carried out using structural element g to signal f Θ g
Dilation operation.
6. according to the method for claim 5, it is characterised in that：In described step 5c, the default threshold value value is
Grid number Ng (t) maximums 20% and round value.
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| CN106202616B (en) * | 2016-06-23 | 2020-08-14 | 广东电网有限责任公司电力科学研究院 | Method and system for simulating motion characteristics of transformer under short-circuit fault |
| RU2643940C1 (en) * | 2016-12-30 | 2018-02-06 | Общество с ограниченной ответственностью Научно-производственное объединение "Логотех" | Method of vibratory unavailable diagnosis of transformer |
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| CN107991074A (en) * | 2017-11-21 | 2018-05-04 | 西安交通大学 | Winding machinery method for diagnosing status during transformer sudden short circuit based on noise signal |
| CN108332955A (en) * | 2017-12-22 | 2018-07-27 | 江苏新道格自控科技有限公司 | A kind of mechanical linkages loosening detection and method for early warning based on vibration signal |
| CN110737867A (en) * | 2018-07-19 | 2020-01-31 | 武汉盛捷达电力科技有限责任公司 | Transformer based on deep learning and mechanical vibration charged acquisition processing device |
| CN110266024B (en) * | 2019-06-12 | 2020-12-29 | 国网福建省电力有限公司 | Power grid short-circuit current limiting method based on current distribution entropy |
| CN112665707B (en) * | 2020-12-15 | 2023-03-03 | 国网天津市电力公司电力科学研究院 | Cumulative effect after short circuit impact of transformer and diagnosis method |
| CN114113939B (en) * | 2021-11-24 | 2022-11-18 | 国网宁夏电力有限公司宁东供电公司 | Transient vibration signal-based transformer fault detection method |
| CN115453427A (en) * | 2022-10-18 | 2022-12-09 | 云南电网有限责任公司电力科学研究院 | Method and device for monitoring transient mechanical state of transformer winding |
| CN116295812B (en) * | 2023-05-22 | 2023-08-18 | 南方电网科学研究院有限责任公司 | Monitoring method and device for power transformer and electronic device |
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