CN109991518A - Transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm - Google Patents
Transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm Download PDFInfo
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- CN109991518A CN109991518A CN201910284879.XA CN201910284879A CN109991518A CN 109991518 A CN109991518 A CN 109991518A CN 201910284879 A CN201910284879 A CN 201910284879A CN 109991518 A CN109991518 A CN 109991518A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/10—Locating faults in cables, transmission lines, or networks by increasing destruction at fault, e.g. burning-in by using a pulse generator operating a special programme
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
- G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
Abstract
The transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm that the present invention relates to a kind of, comprising the following steps: step S1, analogue simulation transmission line malfunction transient state travelling wave signal；Step S2, selection determine corresponding window function；Step S3 designs predictive operator and lifting operator；Step S4, wavelet packet travelling wave signal decompose；Step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis；Step S6, liftering window WAVELET PACKET DECOMPOSITION；Step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location.Compared with prior art, the present invention has many advantages, such as to improve the speed of ranging while improving range accuracy.
Description
Technical field
The present invention relates to a kind of transmission line malfunction travelling wave analysis methods, are based on liftering window small echo more particularly, to one kind
The transmission line malfunction travelling wave analysis method of packet algorithm.
Background technique
Transmission line malfunction problem be it is generally existing inevitably, be difficult since its is distributed more widely, when breaking down and
When find specific location, and caused by it loss be huge.And at this stage, also not for the research of line fault ranging
Maturation still remains problem in ranging accuracy and reliability, and normal production and living order can be threatened when serious.Institute
With the research of measuring distance of transmission line fault is essential in power grid and the national economic development.
Currently, impedance analysis and travelling wave analysis are the main methods of fault location.Impedance Analysis is with standard electric tolerance
Basis by the voltage and current information counter circuit impedance parameter of measurement point, and then determines fault distance, is a kind of comparative maturity
Distance measuring method.However, being influenced very greatly, to require study for the solution of this problem by line parameter circuit value in its ranging process.Row
Wave method is mainly calculated by using with the time of the traveling wave generated at failure or time difference, is that current application is the widest
A kind of general route distance measuring method.Traveling wave method includes single-ended method and both-end method, and single-ended method development is more early, but deposits with principle sheet
In deficiency and the problem of be affected by line parameter circuit values such as transition resistances；And both-end method has principle simple, range accuracy is theoretical
Property it is high, traveling wave identification is easy and is influenced small feature by line parameter circuit value.
The key technology that both-end traveling wave method is realized is the identification and calibration of wavefront.Therefore, it solves to simplify ranging process
The problem of with precision is improved, effective method are to improve the recognition speed and accuracy of wavefront.Based on wavelet transformation
The characteristics of time frequency analysis, suitable for capturing the initial wavefront for reaching collection point, domestic and foreign scholars have carried out much this
Research.Such as route travelling wave ranging is carried out using wavelet transformation, it is improved range accuracy, but wavelet transformation cannot be to letter
Number high frequency section decomposed；Such as the correlative study of travelling wave ranging has been carried out to wavelet packet and envelope, it realizes to letter
Number high-frequency decomposition, Range finding reliability is further enhanced, the disadvantage is that wavelet package transforms are relative to wavelet transformation decomposable process
It is more complicated；Such as joined Lifting Wavelet algorithm in fault localization, ranging time is reduced well, but in phase accuracy
Error is very big.
On the basis of numerous pairs of fault traveling waves analysis at home and abroad, liftering window Wavelet Packet Algorithm is decomposed in transient state travelling wave
And signal analysis aspect has good effect, while providing safeguard on transmission line of electricity ranging accuracy and speed.Current one
In a little rangings using small echo related algorithm, some use a kind of three end location algorithms based on Phase information, in single-ended and both-end
Three-terminal p-n-p-n switch is carried out on the basis of principle and comes fault point position, but is largely influenced by velocity of wave problem, for
The identification of traveling wave head is complicated and performance declines；Even if the correction of traveling wave speed degree and optimization row improve the accurate of travelling wave ranging
Degree, but have the shortcomings that amendment and optimization process are complicated, increase the difficulty of travelling wave ranging.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be based on liftering window
The transmission line malfunction travelling wave analysis method of Wavelet Packet Algorithm.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm, comprising the following steps:
Step S1, analogue simulation transmission line malfunction transient state travelling wave signal；
Step S2, selection determine corresponding window function；
Step S3 designs predictive operator and lifting operator；
Step S4, wavelet packet travelling wave signal decompose；
Step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis；
Step S6, liftering window WAVELET PACKET DECOMPOSITION；
Step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location.
Preferably, the step S2, selection determine corresponding window function, and wherein window function uses Kaiser (401,10)
Window, if wNIt (t) is Kaiser window, time-domain expression are as follows:
Wherein k is integer
In formula, I0(β) is that the Ith class deforms zero Bessel function；β is window function form parameter, if value change is got over
Come bigger, the waveform of the two sides of that Kaiser window frequency spectrum can become more and more smooth；D is window function length；T is adding window segment
Signal time；X, k is the variable of power series expansion, and representative function has k order derivative.Preferably, the step S3, design are pre-
Measuring and calculating and lifting operator specifically:
1) it divides: referring to that windowing signal splits into even order fe(k) and odd numbered sequences fo(k)；
2) prediction and update: each sub-band using prediction, update operator, after calculating l layers of liftering window wavelet packet decomposition；
3) reconstruct of liftering window wavelet packet is realized.
Preferably, the step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis specifically:
Sliding-model control is carried out to sampled data signal f (t), obtaining frequency spectrum is F (f) discrete function f (n Δ t)；Then,
To f, (n Δ t) does windowing process and obtains: fN(t)=f (t) wN(t), wherein N indicates discretization, wNIt (t) is Kaiser window.
Preferably, the step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location specifically: according to step
Adding window WAVELET PACKET DECOMPOSITION detail view obtains the position of wavefront identification to calculate the time in S6, completes both-end travelling wave ranging.
Preferably, this method is using the Two-terminal Fault Location method based on transient state travelling wave as main object, by designing window function,
Specific do not wait is carried out to the clock signal of truncation to weight, and is kept the both ends low frequency component for being truncated waveform smoothened, is come with this
The secondary lobe of window is forced down, to improve ranging accuracy and speed；
On this basis, the superperformance all segmented using wavelet packet to low-and high-frequency inserts adding window wavelet package transforms, into one
Step improves range accuracy；
Finally, one kind has been write in design in order to improve adding window wavelet packet calculation amount than the defect that adding window small echo greatly increases
Liftering window wavelet package transforms, significantly improve accuracy and speed on the basis of above-mentioned.
Compared with prior art, the present invention can use the traveling wave time for the lookup of failure point of power transmission line come real
Now to this feature of the calculating of fault distance, using to travelling wave signal windowing process, Via Lifting Scheme processing, adding window wavelet packet point
The analysis of the series of algorithms such as solution, liftering window WAVELET PACKET DECOMPOSITION, quick and precisely realizes fault travelling wave ranging, has following beneficial to effect
Fruit:
1. small echo can be comprehensively considered, the advantage that WAVELET PACKET DECOMPOSITION handles travelling wave signal.
2. analysis while the low-and high-frequency to signal may be implemented in adding window WAVELET PACKET DECOMPOSITION, the essence of signal identification is improved
Degree.
3. liftering window WAVELET PACKET DECOMPOSITION combines above-mentioned all advantages, improved while improving range accuracy
The speed of ranging.
Detailed description of the invention
Fig. 1 is both-end distance measuring schematic diagram；
Fig. 2 is liftering window and transformation general diagram；
Fig. 3 is simulation model figure；
Fig. 4 is flow chart of the present invention；
Fig. 5 is the line fault travelling wave signal curve graph that test obtains；
Fig. 6 is using the line fault travelling wave signal curve graph after adding window；
Fig. 7 is the detail curve figure after adding window WAVELET PACKET DECOMPOSITION signal；
Fig. 8 is the detail curve figure after liftering window WAVELET PACKET DECOMPOSITION signal.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is a part of the embodiments of the present invention, rather than whole embodiments.Based on this hair
Embodiment in bright, those of ordinary skill in the art's every other reality obtained without making creative work
Example is applied, all should belong to the scope of protection of the invention.
As shown in Figure 1 to 4, the transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm, including
Following steps:
Step S1, analogue simulation transmission line malfunction transient state travelling wave signal；
Step S2, selection confirmation window function；
Step S3 designs predictive operator and lifting operator；
Step S4, wavelet packet travelling wave signal decompose；
Step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis；
Step S6, liftering window WAVELET PACKET DECOMPOSITION；
Step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location.
Transmission line malfunction travelling wave ranging, which is one, can be changed into fault point lookup the calculating of travelling wave signal propagation time
The problem of, crucial and key problem is quick and precisely to identify and demarcate initial wavefront signal.WAVELET PACKET DECOMPOSITION and adding window are small
The comparative analysis that wave packet decomposes, it can be seen that be improved in the signal identification precision after adding window but elongated on operation time
?.And the precision of wavefront identification had not only can be improved in liftering window Wavelet Packet Algorithm, but also the speed of operation can be improved, and was one
The effective ways of kind analysis travelling wave signal.
As shown in Figure 1, fault distance expression formula can be obtained according to its principle are as follows:
Liftering window wavelet package transforms main process in the present invention: windowing process first is carried out to sampling travelling wave signal, is prevented
Frequency spectrum will not serious distortion in conversion process；Then Via Lifting Scheme is added in wavelet package transforms, while obtaining local message
Improve speed；Finally calculate the time difference that same wavefront is propagated.As shown in Fig. 2.
Step S1 is by taking the single-phase fault of three-phase system as an example.As shown in Fig. 3, mainly double using the building of PSCAD4.2 version
Ranging model is held, system nominal voltage is 750kV, and ground resistance is 100 Ω, and signal acquisition point is located at the bus of both ends.Sampling
Obtain fault data, handled, emulated by Matlab software, since calculate wave head reach time difference.
1, adding window WAVELET PACKET DECOMPOSITION
Discretization (N indicates discretization) processing is carried out to sampled data signal f (t), available frequency spectrum is that F (f) is discrete
Function f (n Δ t).Then, to f (n Δ t) does windowing process and obtains:
fN(t)=f (t) wN(t) (4)
It can be obtained according to multiple Convolution Formula:
It is above it is various in, w (t)-window function；wN(t)-discretization window function；fN(t) discrete after-data-signal adding window
Change function；FN(f)-signal discrete frequency spectrum；WN(f)-discretization window function frequency spectrum.
From formula as can be seen that the waveform after travelling wave current signal windowing process in its time domain and frequency domain can become
Change, and this and window function wN(t) frequency spectrum WN(f) there is close connection.Therefore, it can be handled according to travelling wave signal here
It is required that selection window function appropriate, obtains the detail signal of its signal decomposition.
2, liftering window WAVELET PACKET DECOMPOSITION
On the basis of adding window shown in the principle general diagram attached drawing 2 of design prediction, lifting operator and Via Lifting Scheme.
(1) it divides: referring to that windowing signal splits into even order fe(k) and odd numbered sequences fo(k)；
fe(k)={ fN(2k),k∈Z} (6)
fo(k)={ fN(2k+1),k∈Z} (7)
In formula, k-subsequence fe(k) and fo(k) the sample serial number in.
(2) prediction and update: each sub- frequency using prediction, update operator, after calculating l layers of liftering window wavelet packet decomposition
Band；
fl1=f(l-1)lo-S(f(l-1)le) (8)
fl2=f(l-1)le+G(fl1) (9)
…
In formula: S-Lifting Wavelet packet predictive operator；G-Lifting Wavelet packet update operator.
(3) following formula is utilized, realizes the reconstruct of liftering window wavelet packet；
f(l-1)le=fl2-G(fl1) (16)
f(l-1)lo=fl1+S(f(l-1)1e) (17)
f(l-1)l(2k)=f(l-1)1e(k), (18) k ∈ Z
f(l-1)l(2k+1)=f(l-1)1o(k), (19) k ∈ Z
By formula (12) it is found that- detail signal, detail signal are the effective informations for carrying out identification function, contain portion
The mutagenic components for dividing low-frequency component and high frequency, is based on this point, and the algorithm in the present invention can just portray the office in detail view
Portion's maximum point demarcates the time point that initial traveling wave reaches therefrom.
Simulation analysis, as shown in Fig. 3, line length take 120km, and abort situation is set in away from the bus 60km of left end,
System model line parameter circuit value is as follows:
R1=0.020 Ω/km, X1=0.17 Ω/km, C1=0.0120 μ F/km
R1=0.123 Ω/km, X1=0.67 Ω/km, C1=0.0051 μ F/km
Fig. 5 is the line fault travelling wave signal that test obtains.
After handling using Kaiser (401,10) window, it is as shown in Figure 6 that current form figure can be obtained.
In order to illustrate effectiveness of the invention, from adding window WAVELET PACKET DECOMPOSITION and the comparative analysis of liftering window wavelet packet, such as Fig. 7
With shown in Fig. 8, the respectively signal detail figure of adding window WAVELET PACKET DECOMPOSITION and liftering window WAVELET PACKET DECOMPOSITION.
1 analysis of simulation result of table
It is available such as to draw a conclusion from the point of view of the interpretation of result data of the resulting signal detail figure of above-mentioned decomposition and table 1:
(1) adding window wavelet packet needs 3 layers for the level of decomposition required for travelling wave signal, and liftering window wavelet packet is by thin
Section figure is it can be seen that be 2 layers；
(2) compare decomposition details, it can be clearly seen that Lifting Wavelet packet adds the advantage of window function；
(3) end the m time of failure T that adding window wavelet packet obtainsmFor 200.2672 μ s, the end n that same method obtains
Time of failure TnFor 201.0024 μ s, wave velocity v=2.9975 × 105Km/s, then formula meter used in 1 with reference to the accompanying drawings
The fault distance D of calculationmFFor 60.1102km, error 110.2m, and the fault distance D of adding window wavelet packetmFFor 60.1125km,
Error is 112.5m；
(4) range accuracy based on liftering window Wavelet Packet Algorithm wants high compared with adding window wavelet packet, but due to decomposition layer
Several reductions reduces 15.4% than adding window Wavelet Packet Algorithm in runing time, and the speed of service is significantly improved.
In order to test the range accuracy of liftering window Wavelet Packet Algorithm, the present invention event to single-phase earthing and different distance again
Barrier point has carried out simulation analysis, as shown in table 2；In view of the influence of transition resistance, the actual range of fault point is set as fixed
Value, further simulates and analyzes the distance measurement result under different transition resistances, as shown in table 3.
The simulation result (single-phase earthing) of 2 different faults point of table
| Actual range/km | Measure distance/km | Error/m |
| 15 | 14.8890 | -111.0 |
| 45 | 45.1131 | 113.1 |
| 85 | 85.1124 | 112.4 |
| 125 | 124.8902 | -109.8 |
The different simulation result (single-phase earthing) of 3 transition resistance value of table
| Transition resistance/Ω | Fault distance/km | Measure distance/km | Error/m |
| 0 | 55 | 55.1141 | 114.1 |
| 50 | 55 | 55.1132 | 113.2 |
| 100 | 55 | 55.1170 | 117.0 |
| 160 | 55 | 55.1115 | 111.5 |
Liftering window wavelet packet decomposition algorithm proposed by the present invention can be effectively applied to transmission line malfunction travelling wave ranging and ask
In topic.The comparison of adding window WAVELET PACKET DECOMPOSITION and liftering window WAVELET PACKET DECOMPOSITION, it can be seen that in the signal identification precision after adding window
It is improved but the WAVELET PACKET DECOMPOSITION time is upper elongated.And wavefront identification had both can be improved in liftering window Wavelet Packet Algorithm
Precision, and the speed of operation can be improved, it is a kind of effective ways for analyzing travelling wave signal.This hair is demonstrated by simulation analysis
It is bright that there is practical application value.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection scope subject to.
Claims (6)
1. a kind of transmission line malfunction travelling wave analysis method based on liftering window Wavelet Packet Algorithm, which is characterized in that including with
Lower step:
Step S1, analogue simulation transmission line malfunction transient state travelling wave signal；
Step S2, selection determine corresponding window function；
Step S3 designs predictive operator and lifting operator；
Step S4, wavelet packet travelling wave signal decompose；
Step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis；
Step S6, liftering window WAVELET PACKET DECOMPOSITION；
Step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location.
2. a kind of transmission line malfunction travelling wave analysis side based on liftering window Wavelet Packet Algorithm according to claim 1
Method, which is characterized in that the step S2, selection determine corresponding window function, and wherein window function uses Kaiser (401,10)
Window, if wNIt (t) is Kaiser window, time-domain expression are as follows:
Wherein k is integer
In formula, I0(β) is that the Ith class deforms zero Bessel function；β is window function form parameter, if value becomes increasingly
Greatly, what the waveform of the two sides of that Kaiser window frequency spectrum can become is more and more smooth；D is window function length；T is the signal of adding window segment
Time；X, k is the variable of power series expansion, and representative function has k order derivative.
3. a kind of transmission line malfunction travelling wave analysis side based on liftering window Wavelet Packet Algorithm according to claim 1
Method, which is characterized in that the step S3 designs predictive operator and lifting operator specifically:
1) it divides: referring to that windowing signal splits into even order fe(k) and odd numbered sequences fo(k)；
2) prediction and update: each sub-band using prediction, update operator, after calculating l layers of liftering window wavelet packet decomposition；
3) reconstruct of liftering window wavelet packet is realized.
4. a kind of transmission line malfunction travelling wave analysis side based on liftering window Wavelet Packet Algorithm according to claim 1
Method, which is characterized in that the step S5, adding window WAVELET PACKET DECOMPOSITION comparative analysis specifically:
Sliding-model control is carried out to sampled data signal f (t), obtaining frequency spectrum is F (f) discrete function f (n Δ t)；Then, to f (n
Δ t) does windowing process and obtains: fN(t)=f (t) wN(t), wherein N indicates discretization, wNIt (t) is Kaiser window.
5. a kind of transmission line malfunction travelling wave analysis side based on liftering window Wavelet Packet Algorithm according to claim 1
Method, which is characterized in that the step S7 calculates the traveling wave propagation time, carries out Two-terminal Fault Location specifically: according to step S6
Middle adding window WAVELET PACKET DECOMPOSITION detail view obtains the position of wavefront identification to calculate the time, completes both-end travelling wave ranging.
6. a kind of transmission line malfunction travelling wave analysis side based on liftering window Wavelet Packet Algorithm according to claim 1
Method, which is characterized in that this method is using the Two-terminal Fault Location method based on transient state travelling wave as main object, by designing window function,
Specific do not wait is carried out to the clock signal of truncation to weight, and is kept the both ends low frequency component for being truncated waveform smoothened, is come with this
The secondary lobe of window is forced down, to improve ranging accuracy and speed；
On this basis, the superperformance all segmented using wavelet packet to low-and high-frequency is inserted adding window wavelet package transforms, further mentioned
High range accuracy；
Finally, a kind of adding window has been write in design in order to improve adding window wavelet packet calculation amount than the defect that adding window small echo greatly increases
Lifting wavelet package transform significantly improves accuracy and speed on the basis of above-mentioned.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111751654A (en) * | 2020-05-18 | 2020-10-09 | 深圳供电局有限公司 | Power system fault processing method and device, computer equipment and medium |
| CN114137356A (en) * | 2021-11-05 | 2022-03-04 | 昆明理工大学 | Direct current transmission line distance measuring method and system |
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Application publication date: 20190709 |