CN107561416A - A kind of local discharge signal acquisition system and method based on compressed sensing - Google Patents
A kind of local discharge signal acquisition system and method based on compressed sensing Download PDFInfo
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- CN107561416A CN107561416A CN201710530563.5A CN201710530563A CN107561416A CN 107561416 A CN107561416 A CN 107561416A CN 201710530563 A CN201710530563 A CN 201710530563A CN 107561416 A CN107561416 A CN 107561416A
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Abstract
The invention discloses a kind of local discharge signal acquisition system based on compressed sensing, it includes：Extra-high video sensor, it gathers original local discharge signal；Signal gathering unit, it is connected with extra-high video sensor, to receive original local discharge signal, and carries out step：(1) original local discharge signal is measured with the frequency less than nyquist sampling rate, so as to complete the compression collection to original local discharge signal；Processing unit, it is connected with signal gathering unit, and carries out step：(2) local discharge signal based on compression collection reconstructs the rarefaction representation of original local discharge signal；(3) inverse transformation is carried out to the rarefaction representation of original local discharge signal, obtains reconstructing local discharge signal.Correspondingly, the invention also discloses a kind of acquisition method.The present invention can obtain the relatively complete information of local discharge signal under conditions of being acquired with the frequency less than nyquist sampling rate to local discharge signal.
Description
Technical field
The present invention relates to electric apparatus monitoring field, more particularly to a kind of local discharge signal acquisition system and method.
Background technology
In power industry, on-line monitoring is carried out to power equipment in transformer station can find power failure in time, improve
Trouble hunting efficiency, it is effectively prevented from the generation of major accident.In transformer station, insulation degradation is cause equipment fault important
One of reason, the main reason for causing insulation degradation are the burr, impurity and loose contact on power equipment surface etc., it is this kind of therefore
Barrier is mainly shown as generation shelf depreciation, and shelf depreciation can aggravate the degree of insulation degradation in turn, forms vicious circle, most
Insulation breakdown is caused eventually, triggers serious accident.Therefore, shelf depreciation can be quickly found by carrying out detection to local discharge signal
Source, overhaul efficiency is improved, it is effectively guaranteed that power system security, stable operation.When shelf depreciation occurs, ultrasound can be produced
Ripple, heat and superfrequency (UHF) electromagnetic wave etc..Wherein, UHF electromagnetic waves are non-due to its outstanding anti-interference and spread speed
Often it is adapted to the detection of local discharge signal in transformer station.
For the e measurement technology of UHF shelf depreciations, because the hardware condition of the links such as analog-to-digital conversion is limited, often exist
It can be difficult to when running into high sample frequency requirement, or to buy the high-frequency element of costliness.Nyquist (Nyquist) samples
Theorem points out that the sample frequency of signal needs more than 2 times that the reach signal highest frequency complete letters that can collect signal
Breath, and in practical engineering application, 2 times of sample frequency is often inadequate, it is necessary to which the sample frequency of more high magnification numbe could be complete
Into effective sampling.Therefore, while in order to obtain the complete information relatively of local discharge signal reduce hsrdware requirements, it is necessary to
Seek the new Sampling techniques of breakthrough nyquist sampling theorem.
The content of the invention
An object of the present invention is to provide a kind of local discharge signal acquisition system based on compressed sensing, the system energy
Local discharge signal is obtained under conditions of being acquired with the frequency less than nyquist sampling rate to local discharge signal
Relatively complete information.
Based on above-mentioned purpose, the invention provides a kind of local discharge signal acquisition system based on compressed sensing, and it is wrapped
Include：
Extra-high video sensor, it gathers original local discharge signal；
Signal gathering unit, it is connected with extra-high video sensor, is put with receiving the original part of extra-high video sensor collection
Electric signal, and step is at least handled as follows：
(1) the original local discharge signal is measured with the frequency less than nyquist sampling rate, so as to complete
Compression collection to the original local discharge signal；
Processing unit, it is connected with the signal gathering unit, and step is at least handled as follows：
(2) local discharge signal based on compression collection reconstructs the rarefaction representation of the original local discharge signal；
(3) inverse transformation is carried out to the rarefaction representation of the original local discharge signal, obtains the corresponding original part and put
The reconstruct local discharge signal of electric signal.
Local discharge signal acquisition system of the present invention based on compressed sensing, it is based on compressed sensing
(Compressed Sensing, CS) Technology design.Compressed sensing technology refer to if signal meet it is sparse under certain condition
Property, then can is acquired with the frequency far below nyquist sampling rate to signal, then by reconstructing calculation accordingly
Method obtains complete signal.Compressed sensing technology has broken nyquist sampling theorem, is applied and is surveyed in local discharge signal
In amount technology, local discharge signal data acquisition can be carried out with relatively low sample rate, be then based on local discharge signal one
Openness reconstruct local discharge signal under fixed condition, so as to obtain the relatively complete information of local discharge signal.The present invention
System due to can ensure obtain local discharge signal relatively complete information on the premise of sample frequency be greatly reduced, because
This can effectively reduce hardware cost.
It is usually that analog signal connects between the extra-high video sensor and signal gathering unit, the signal gathering unit
It is usually data signal connection between processing unit.
Concrete principle of the present invention is as follows：
1. local discharge signal compression sampling.
If the signal of measurement is sparse in certain space, then signal is carried out spatial alternation by can, is then utilized
Calculation matrix is compressed sampling to signal, obtains the sampled value much smaller than original signal strength, then by restructing algorithm just
Primary signal can be solved.So signal is premise using compressed sensing technology in the openness of certain space.
If tested local discharge signal is RNThe X in space, the sparse base vector ψ tieed up by one group of N × 1i, i=1,2 ... N's
X rarefaction representation S is obtained after conversion, expression formula is：
In formula (1), K nonzero element is only existed in the vectorial S that N × 1 is tieed up, remaining element is zero or is similar to
Zero, and require K<<N.What sparse base Ψ was commonly used has FFT base, dct transform base and wavelet transformation base etc..
Original signal X data volume is N, and the core procedure of compressed sensing is exactly with less m data table by this N number of data
Show, it is therefore desirable to m × N calculation matrix Φ=[φ1,φ2,。。。,φm]TX is measured, m here is also referred to as surveyed
Measure number.Finally give measurement result vector Y=(y1,y2,。。。,ym).The expression formula of this process is：
Y=Φ X=Φ Ψ S=Θ S (2)
Θ=Φ Ψ are m × N sensing matrix in formula (2).Due to m<<N, this completes data compression.Finally lead to
Restructing algorithm is crossed, S is reconstructed by Y, the inverse transformation by (1) formula can be obtained by original signal X.
2. the structure of calculation matrix.
Perceiving matrix Θ needs to meet that constraint isometry (Restricted Isometry Property, RIP) can
Guarantee accurately reconstructs original signal.RIP requires that S and Θ meets the inequality relation of (3) formula：
In formula, ε ∈ (0,1), ε are the random number between 0 to 1.
The judgement that RIP conditions are carried out using (3) formula is more complicated.But if matrix Φ and Ψ is uncorrelated, then
Θ meets that RIP conditional probability is very high.Because the correlation of random matrix and given matrix is smaller, so calculation matrix Φ mono-
As use random matrix, commonly use gaussian random matrix.
3. signal reconstruction.
After measurement result vector Y is obtained, (2) formula is a underdetermined equation, can not direct solution.But signal X is becoming
Change into and be provided with after S openness, therefore can is converted into the problem of solving minimum l0 norms the problem of reconstruct S, solves this
Optimization problem can reconstructs the signal S of N-dimensional, then can be obtained by original signal X by corresponding inverse transformation.
Minimum l0 norm optimizations model is：
min||S||0S.t.Y=Φ X=Φ Ψ S (4)
Solving model (4) algorithm mainly has convex optimized algorithm and greedy algorithm.The precision of convex optimized algorithm is of a relatively high, but
It is that computing is more complicated, arithmetic speed is slow.The precision of greedy algorithm is slightly less than convex optimized algorithm, but algorithm complex is smaller, fortune
Calculate speed.In high voltage digital measurement, due to needing faster measuring speed, generally optimized from greedy algorithm
The solution of model.
Further, in the local discharge signal acquisition system of the present invention based on compressed sensing, the step (1)
In the measurement carried out by calculation matrix.
Further, in the above-mentioned local discharge signal acquisition system based on compressed sensing, the calculation matrix be with
Machine matrix.
Further, in the above-mentioned local discharge signal acquisition system based on compressed sensing, the random matrix is height
This random matrix.
Further, in the local discharge signal acquisition system of the present invention based on compressed sensing, the step (2)
Described in the transformation relation based on sparse base, the sparse Ji Bao between rarefaction representation and the original local discharge signal be present
Include at least one of FFT base, dct transform base and wavelet transformation base.
Further, in the local discharge signal acquisition system of the present invention based on compressed sensing, the step (2)
Middle use is solved on original described in the minimum l0 norm optimizations model reconstruction of the rarefaction representation of the original local discharge signal
The rarefaction representation of local discharge signal.
Further, in the above-mentioned local discharge signal acquisition system based on compressed sensing, the minimum l0 norms are excellent
Changing the derivation algorithm of model includes at least one of convex optimized algorithm and greedy algorithm.
Further, in the above-mentioned local discharge signal acquisition system based on compressed sensing, the minimum l0 norms are excellent
Change the preferred greedy algorithm of derivation algorithm of model.
Further, in the local discharge signal acquisition system of the present invention based on compressed sensing, the step (2)
The middle rarefaction representation that the original local discharge signal is reconstructed using orthogonal matching pursuit algorithm.
It is a further object of the present invention to provide a kind of local discharge signal acquisition method based on compressed sensing, this method energy
Local discharge signal is obtained under conditions of being acquired with the frequency less than nyquist sampling rate to local discharge signal
Relatively complete information.
Based on above-mentioned purpose, the invention provides a kind of local discharge signal acquisition method based on compressed sensing, and it is wrapped
Include the signal transacting step of any of the above-described system.
Local discharge signal acquisition method of the present invention based on compressed sensing, it is due to including any of the above-described system
Signal transacting step, therefore with the frequency less than nyquist sampling rate local discharge signal can be equally acquired
Under the conditions of obtain local discharge signal relatively complete information.Describe, will not be repeated here before concrete principle.
Local discharge signal acquisition system of the present invention based on compressed sensing, it has advantages below and beneficial to effect
Fruit：
1) can under conditions of being acquired with the frequency less than nyquist sampling rate to local discharge signal acquisition office
The relatively complete information of portion's discharge signal.
2) requirement for hardware is small, it is easy to accomplish, and there is higher signal reconstruction precision.
3) collecting efficiency of transformer station partial discharge signals can be improved, there is preferable application prospect.
4) electrical equipment malfunction can be monitored effectively, so as to improve overhaul efficiency and power system well
Security.
Local discharge signal acquisition method of the present invention based on compressed sensing, it equally has above advantage and had
Beneficial effect.
Brief description of the drawings
Fig. 1 is the local discharge signal acquisition system of the present invention based on compressed sensing under a kind of embodiment
Workflow schematic diagram.
Fig. 2 is the original local discharge signal oscillogram gathered in the checking example of the present invention.
Fig. 3 is the local discharge signal oscillogram reconstructed when sampled point number is 200 in checking example of the invention.
Fig. 4 is the local discharge signal oscillogram reconstructed when sampled point number is 100 in checking example of the invention.
Fig. 5 is the local discharge signal oscillogram reconstructed when sampled point number is 50 in checking example of the invention.
Fig. 6 is the local discharge signal oscillogram reconstructed when sampled point number is 20 in checking example of the invention.
Fig. 7 is the corresponding relation figure of sampled point number and error rate in checking example of the invention.
Embodiment
Technical solutions according to the invention are further illustrated with reference to Figure of description and embodiment.
Fig. 1 illustrates the local discharge signal acquisition system of the present invention based on compressed sensing in a kind of embodiment
Under workflow.
As shown in figure 1, the local discharge signal acquisition system based on compressed sensing of present embodiment includes extra-high keep pouring in
Sensor, signal gathering unit and processing unit, wherein analog signal connects between extra-high video sensor and signal gathering unit,
Data signal connects between signal gathering unit and processing unit, and workflow includes step：
Step 110：Extra-high video sensor gathers original local discharge signal.
In present embodiment, extra-high video sensor gathers original local discharge signal, and is transmitted to signal acquisition list
Member.
Step 120：Signal gathering unit receives the original local discharge signal of extra-high video sensor collection, and to original office
Portion's discharge signal is measured with the frequency less than nyquist sampling rate, so as to complete the compression to original local discharge signal
Collection.
In present embodiment, the step specific method is as follows：
If original local discharge signal is RNThe X in space, it has openness under certain condition, you can to pass through one group
The sparse base vector ψ that N × 1 is tieed upi, i=1 obtains X rarefaction representation S after 2 ... N conversion, expression formula is：
In formula (1), K nonzero element is only existed in the vectorial S that N × 1 is tieed up, remaining element is zero or is similar to
Zero, and require K<<N.Sparse base Ψ can use one kind in FFT base, dct transform base and wavelet transformation base.
If original local discharge signal X data volume is N.Pass through m × N calculation matrix Φ=[φ1,φ2,。。。,
φm]TX is measured, wherein, calculation matrix is gaussian random matrix, and m is also referred to as pendulous frequency, the frequency of its corresponding measurement,
And m<<N.Finally give measurement result vector Y=(y1,y2,。。。,ym).The expression formula of this process is：
Y=Φ X=Φ Ψ S=Θ S (2)
Θ=Φ Ψ are m × N sensing matrix in formula (2).Due to m<<N, this completes compression to gather.
Step 130：The local discharge signal of processing unit reception signal collecting unit compression collection, and based on compression collection
Local discharge signal reconstruct the rarefaction representation of original local discharge signal.
In present embodiment, by restructing algorithm, S is reconstructed by Y.Specific method is as follows：
Solve it is following on S minimum l0 norm optimizations model (4) to reconstruct the signal S of N-dimensional：
min||S||0S.t.Y=Φ X=Φ Ψ S (4).
Wherein, solving model (4) algorithm uses greedy algorithm.
Under some embodiments, using orthogonal matching pursuit algorithm reconstruction signal S.The realization of the algorithm is by model
What the solution of number Optimized model was realized.
Step 140：Processing unit carries out inverse transformation to the rarefaction representation of original local discharge signal, obtains corresponding original office
The reconstruct local discharge signal of portion's discharge signal.
In present embodiment, the signal S based on reconstruct, the local discharge signal that the inverse transformation by (1) formula is reconstructed
X。
The method of the invention is embodied in said system, thus not still further individually explanation.
The present invention is verified below by instantiation, the example is based on said system and corresponding steps are implemented.
High-Voltage Experimentation hall is selected to carry out experimental verification, its space environment and electromagnetic environment are all complex, therefore can be with
The environment of imitating substation to a certain extent.
In an experiment, shelf depreciation is carried out using the local discharge signal source of standard, made at 8 meters of Partial Discharge Sources
Measured with extra-high video sensor portion's discharge signal of playing a game.The original local discharge signal waveform measured is as shown in Figure 2.If
The total strong point number of local discharge signal is 1000, i.e. N=1000.
Then, a portion data are randomly selected by random measurement matrix in original local discharge signal data,
The data for being then based on choosing carry out the reconstruct of local discharge signal, and restructing algorithm chooses orthogonal matching pursuit (OMP) algorithm.Weight
Structure effect is characterized with error rate, and the calculating of error rate is as shown in (5) formula.
Wherein, i represents data point sequence number, xi' represent to reconstruct i-th of data dot values of local discharge signal, xiRepresent original
I-th of data dot values of local discharge signal.
For preferably verification algorithm performance, change the sampling number of local discharge signal data, to calculate different samplings
The size of reconstructed error rate under rate.
In the case that Fig. 3-Fig. 6 illustrates different sampling numbers, the situation of local discharge signal reconstruct.
From figure 3, it can be seen that when sampled point number be 200 when, i.e., using 20% local discharge signal data, reconstruct
Local discharge signal and original local discharge signal almost there is no difference, quality reconstruction is very good.From fig. 4, it can be seen that work as
When sampled point number is reduced to 100, the signal noise of reconstruct becomes big, but still can recover most primary signal.From Fig. 5
As can be seen that when sampled point number is reduced to 50, the signal noise of reconstruct is very big, indistinctly there is the profile of some primary signals.From
Fig. 6 can be seen that when sampled point number is reduced to 20, and the signal noise of reconstruct is very big, and does not almost see primary signal
Profile, almost all is noise.
Fig. 7 is illustrated as sampled point number changes, the variation tendency of error rate.It can be seen from figure 7 that work as sampled point
For number when within 50, error rate is local discharge signal serious distortion that is very high, now reconstructing, can not be used.
With the increase of sampled point number, error rate rapid decrease, and decrease speed is slower and slower.When sampled point number is 100,
Error rate drops to 10.8%, now by the reconstruct of compressed sensing, can recover the information of most local discharge signal,
The local discharge signal reconstructed is also available with.When sampled point number is more than 300, error rate is locally put close to zero
Electric signal can be reconstructed exactly.Therefore, local discharge signal is reconstructed using 10% local discharge signal data can,
10.8% error rate is also acceptable, the influence very little to Partial Discharge Detection.
It was verified that the present invention can be acquired with the frequency less than nyquist sampling rate to local discharge signal
Under the conditions of obtain local discharge signal relatively complete information, electrical equipment malfunction can be monitored effectively, very
The good security for improving overhaul efficiency, improving power system.
Above-described embodiment is the preferable embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, other any Spirit Essences without departing from the present invention with made under principle change, modification, replacement, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (10)
- A kind of 1. local discharge signal acquisition system based on compressed sensing, it is characterised in that including：Extra-high video sensor, it gathers original local discharge signal；Signal gathering unit, it is connected with extra-high video sensor, is believed with receiving the original shelf depreciation of extra-high video sensor collection Number, and step is at least handled as follows：(1) the original local discharge signal is measured with the frequency less than nyquist sampling rate, so as to complete to institute State the compression collection of original local discharge signal；Processing unit, it is connected with the signal gathering unit, and step is at least handled as follows：(2) local discharge signal based on compression collection reconstructs the rarefaction representation of the original local discharge signal；(3) inverse transformation is carried out to the rarefaction representation of the original local discharge signal, obtains the corresponding original shelf depreciation letter Number reconstruct local discharge signal.
- 2. the local discharge signal acquisition system based on compressed sensing as claimed in claim 1, it is characterised in that the step (1) measurement is carried out by calculation matrix in.
- 3. the local discharge signal acquisition system based on compressed sensing as claimed in claim 2, it is characterised in that the measurement Matrix is random matrix.
- 4. the local discharge signal acquisition system based on compressed sensing as claimed in claim 3, it is characterised in that described random Matrix is gaussian random matrix.
- 5. the local discharge signal acquisition system based on compressed sensing as claimed in claim 1, it is characterised in that the step (2) transformation relation based on sparse base between rarefaction representation described in and the original local discharge signal be present, it is described sparse Base includes at least one of FFT base, dct transform base and wavelet transformation base.
- 6. the local discharge signal acquisition system based on compressed sensing as described in claim 1-5, it is characterised in that the step Suddenly use and solved on described in the minimum l0 norm optimizations model reconstruction of the rarefaction representation of the original local discharge signal in (2) The rarefaction representation of original local discharge signal.
- 7. the local discharge signal acquisition system based on compressed sensing as claimed in claim 6, it is characterised in that the minimum The derivation algorithm of l0 norm optimization models includes at least one of convex optimized algorithm and greedy algorithm.
- 8. the local discharge signal acquisition system based on compressed sensing as claimed in claim 6, it is characterised in that the minimum The preferred greedy algorithm of derivation algorithm of l0 norm optimization models.
- 9. the local discharge signal acquisition system based on compressed sensing as described in claim 1-5, it is characterised in that the step Suddenly the rarefaction representation of the original local discharge signal is reconstructed in (2) using orthogonal matching pursuit algorithm.
- 10. a kind of local discharge signal acquisition method based on compressed sensing, it is characterised in that including appointing in claim 1-9 The signal transacting step of system described in a claim of anticipating.
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| CN108318761A (en) * | 2018-02-06 | 2018-07-24 | 内蒙古工业大学 | Wind power generating set power quality detection method based on compressed sensing |
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| CN112629651A (en) * | 2020-10-16 | 2021-04-09 | 国网江苏省电力有限公司盐城供电分公司 | Power transmission line galloping information reconstruction method based on compressed sensing |
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| GB2597444A (en) * | 2020-07-21 | 2022-02-02 | Eaton Intelligent Power Ltd | Arc fault detection device |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108318761A (en) * | 2018-02-06 | 2018-07-24 | 内蒙古工业大学 | Wind power generating set power quality detection method based on compressed sensing |
| CN108663606A (en) * | 2018-05-17 | 2018-10-16 | 国网辽宁省电力有限公司电力科学研究院 | A kind of method and system that local discharge signal is acquired with low sample frequency |
| CN109557434A (en) * | 2018-12-04 | 2019-04-02 | 红相股份有限公司 | Local discharge signal recognition methods under strong background noise based on the classification of compound dictionary rarefaction representation |
| CN109557434B (en) * | 2018-12-04 | 2021-01-05 | 红相股份有限公司 | Partial discharge signal identification method under strong background noise based on composite dictionary sparse representation classification |
| GB2597444A (en) * | 2020-07-21 | 2022-02-02 | Eaton Intelligent Power Ltd | Arc fault detection device |
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| GB2597444B (en) * | 2020-07-21 | 2024-06-26 | Eaton Intelligent Power Ltd | Arc fault detection device |
| CN112629651A (en) * | 2020-10-16 | 2021-04-09 | 国网江苏省电力有限公司盐城供电分公司 | Power transmission line galloping information reconstruction method based on compressed sensing |
| CN113346908A (en) * | 2021-05-11 | 2021-09-03 | 中国电力科学研究院有限公司 | Method and system for pre-compressing network data measured by high-voltage cable |
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