CN105486938B - A kind of substation's mixed noise separation method - Google Patents
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Abstract
The present invention relates to a kind of substation's mixed noise separation methods, this method first obtains the noise characteristic frequency spectrum and vocal print figure of Main Noise Sources in substation, after going out 100Hz and its a series of harmonics constituents extractions in frequency spectrum, the time-domain signal of this bulk noise is obtained using Fourier inversion.By the otherness on spectrum signature, the separation of this bulk noise is realized.Secondly the characteristic of corona noise in the time domain, the i.e. short-time characteristic of pulse are utilized.Using the generation of short-time pulse in wavelet analysis method identification noise signal, isolated corona noise.It finally obtains as fan noise.The method is checked and accepted for the noise under substation's actual operating state, noise abatement provides theoretical foundation and evaluation method.
Description
Technical field:
The present invention relates to a kind of noise separation methods, are more particularly to a kind of substation's mixed noise separation method.
Background technique:
In the field of environmental technology in the places such as substation, substation's factory outside noise meets wanting for national relevant environment standard
One primary condition of Seeking Truth project of transmitting and converting electricity design, from the point of view of the completed project of transmitting and converting electricity noise abatement situation in China,
The project planning phase predicts noise, for rationally determining substation and route design parameter, guarantees substation and route peace
It full reliability service and reduces engineering construction operating cost, meet environmental protection requirement etc. and all have highly important meaning, according to
The environmentally friendly Completion Inspecting and Monitoring and analogy monitoring result of the substation largely run at present, the power frequency electric that project of transmitting and converting electricity generates
Field, magnetic induction intensity, radio interference field strength and factory's circle audible noise are able to satisfy the standard limited value requirement of recommendation.But with
The rapid development of national economy and power grid construction, and on the attention that project of transmitting and converting electricity environment influences, how to further decrease change
Influence of the power station noise to surrounding enviroment, Creating Green environmental protection substation are a problems of current substation's construction.
Power transformation station equipment is more, and noise circumstance is complicated, and various noises mix so that noise prediction, control, administering and changing
It makes and all there is certain difficulty.Therefore, carry out the technical research of power transmission and transformation noise separation, by noise of equipment, ambient noise, corona noise
Etc. a variety of noise separations, clear scene Main Noise Sources all have the environmental impact assessment of power transmission and transformation line noise, noise abatement, noise prediction
There is important role.In the noise source existing for substation, other than transformer, reactor body noise, there are also coolings to set
Standby noise and inside and outside corona noise of standing.Due to the spectral characteristic in its broadband, decaying is very fast for fan noise and corona noise, therefore
The main source of noise pollution is transformer, reactor arrangement at boundary.Existing prediction technique as only considers its ontology
The result of noise.It is other but under certain specific environments, such as in the lesser substation of scale or substation at sensitive spot
The influence of two kinds of noises cannot be ignored.Therefore noise level is predicted in order to be more accurate, three kinds need to be obtained from integrated noise makes an uproar
The size of acoustic energy grade, is predicted respectively, with the result more refined.
According to above-mentioned reason, the present invention proposes a kind of transformer mixed noise separation method, efficiently separates out in substation and becomes
Three kinds of depressor, fan, corona pink noises, the input value when result after separation can be used as site noise prediction are controlled with noise
Reference value when reason.Effective means is provided simultaneously for substation's noise measuring and improvement.
Summary of the invention:
The object of the present invention is to provide a kind of substation's mixed noise separation method, this method is substation's actual motion shape
Noise under condition is checked and accepted, noise abatement provides theoretical foundation and evaluation method.
To achieve the above object, the invention adopts the following technical scheme: a kind of substation's mixed noise separation method, described
Method is the method for the individual transformer body noise of separation, fan noise and corona noise；It the described method comprises the following steps:
(1) noise characteristic of transformer substation body noise, fan noise and corona noise is determined；
(2) transformer body noise is separated；
(3) corona noise is separated；
(4) fan noise is separated.
A kind of substation's mixed noise separation method provided by the invention, the transformer body noise in the step (1)
100Hz is concentrated on for its frequency and using 100Hz as the harmonics ingredient of fundamental frequency；The fan noise of cooling equipment is white noise,
Its frequency be less than 1500Hz in be uniformly distributed；The AC corona noise is widely distributed in the main frequency range of audible noise；It is main
Wanting frequency range is 20Hz-20kHz.
A kind of substation's mixed noise separation method provided by the invention, the separation process of the step (2) are as follows:
It will include time domain ambient noise s (n) the progress small echo of the transformer body noise, corona noise and fan noise
Transformation；
Coefficient c after the wavelet transformation1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
The coefficient c1(n) the transformer body noise is obtained by passband comb filter and wavelet inverse transformation
Another preferred a kind of substation's mixed noise separation method provided by the invention, the wavelet transformation use
Daubechies filter group；The coefficient c1(n) corresponding frequency range is 0-f/64, and f is basic sample frequency；It is described logical
Band connection frequency with comb filter is the frequency of its ontology vibration frequency fundamental frequency 50Hz and 50Hz integral multiple.
Another preferred a kind of substation's mixed noise separation method provided by the invention, the separation in the step (3)
Process are as follows:
It will include time domain ambient noise s (n) the progress small echo of the transformer body noise, corona noise and fan noise
Transformation；
Coefficient c after the wavelet transformation1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
By the coefficient c5(n) and c6(n) inverse wavelet transform is time domain waveform r (n)；
Judge whether time domain waveform r (n) occurs corona noise.
Another preferred a kind of substation's mixed noise separation method provided by the invention, when the time domain waveform r (n) not
When corona noise occurs, corona noise 0；When corona noise occurs for the time domain waveform r (n):
By the coefficient c1(n) by after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and
c6(n) inverse wavelet transform is carried out jointly form time domain waveform y (n)；
The time domain waveform y (n) is formed by Fast Fourier Transform (FFT) comprising corona noise frequency spectrum and fan noise frequency
The Y of spectrumq(k)；
Frequency spectrum Y is determined by spectrum-subtractionq(k) the corona noise frequency spectrum in.
Another preferred a kind of substation's mixed noise separation method provided by the invention, the time domain waveform y (n) and r
(n) sub-frame processing, frame length N, it is P that frame, which moves, and q frame data have:
yq=[y (qP-N+1), y (qP-N+2) ... y (qP)]T
rq=[r (qP-N+1), r (qP-N+2) ... r (qP)]T
The frequency spectrum Yq(k) are as follows:
Wherein, w (m) is window function.
Another preferred a kind of substation's mixed noise separation method provided by the invention, when the time domain waveform r (n) not
When corona noise occurs, pass through the frequency spectrum Yq(k) its noise spectrum is determined:
WhereinAnd NqIt (k) is respectively minimum spectrum, maximum spectrum and noise spectrum；α, β and κ are smooth
Parameter, value are α=0.01, β=0.5, κ=0.1；
When corona noise occurs for the time domain waveform r (n), then noise spectrum remains unchanged Nq(k)=Nq-1(k)；
Corona noise frequency spectrum Dq(k) are as follows:
The corona noise frequency spectrum Dq(k) time domain d is obtained by inverse fast Fourier transformq(m):
Wherein, m=0,1 ... N-1.
Another preferred a kind of substation's mixed noise separation method provided by the invention, if frame moves P=N, quick Fu
In leaf transformation there is no adding window, then
Wherein, m=0,1 ... P-1；
Judge whether the time domain waveform r (n) occurs corona noise by following formula:
Wherein, T is corona noise detection limit；, ξTFor threshold value；E{r2(n) } it can be determined with following formula:
Wherein, γ=0.99 is smoothing factor,For E { r2(n) } estimated value.
Another preferred a kind of substation's mixed noise separation method provided by the invention, the separation in the step (4)
Process are as follows:
It will include time domain ambient noise s (n) the progress small echo of the transformer body noise, corona noise and fan noise
Transformation；
Coefficient c after the wavelet transformation1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
By the coefficient c1(n) by after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and
c6(n) inverse wavelet transform is carried out jointly form time domain waveform y (n)；
The fan noise is by will remove corona noise d in the time domain waveform y (n)q(m) it determines.
Another preferred a kind of substation's mixed noise separation method provided by the invention, fan noise described in q frameThen:
Wherein, gqIt (m) is the frequency spectrum Yq(k) fan noise power spectrum G is determinedq(k) FFT inverse transformation:
The Gq(k) are as follows:
The stop-band frequency of the stopband comb filter is its ontology vibration frequency fundamental frequency 50Hz and 50Hz integral multiple
Frequency.
Compared with the nearest prior art, the technical scheme provide by that invention has the following excellent effect
1, the present invention checks and accepts for the noise under substation's actual operating state, noise abatement provides theoretical foundation and evaluation
Method；
2, the present invention is complicated for substation field noise, it is difficult to the solution party that the case where determining all kinds of noise contributions proposes
Method；
3, the present invention guarantees substation and line security reliability service for rationally determining substation and route design parameter
Highly important meaning is all had with reducing engineering construction operating cost, meeting environmental protection requirement etc.；
4, the present invention predicts noise level more accurately, the result more refined；
5, the present invention efficiently separates out three kinds of transformer in substation, fan, corona pink noises, and the result after separation can
Reference value when input value and noise abatement when being predicted as site noise；
6, the present invention provides effective means for substation's noise measuring and improvement.
Detailed description of the invention
Fig. 1 is the time domain waveform of corona noise of the invention；
Fig. 2 is the vocal print figure of corona noise of the invention；
Fig. 3 is the time domain waveform of transformer body noise of the invention；
Fig. 4 is the vocal print figure of transformer body noise of the invention；
Fig. 5 is the time domain waveform of fan noise of the invention；
Fig. 6 is the vocal print figure of fan noise of the invention；
Fig. 7 is substation's integrated noise separation algorithm block diagram of the invention；
The spectrogram of low-frequency range when Fig. 8 is this bulk noise after separation of the invention；
Fig. 9 is the corona noise time-frequency spectrum after separation of the invention；
Figure 10 is the fan noise time-frequency spectrum after separation of the invention；
Figure 11 is flow chart of the method for the present invention.
Specific embodiment
Below with reference to embodiment, the invention will be described in further detail.
Embodiment 1:
As shown in figs 1-9, the method for the invention of this example is to separate individual transformer body noise, fan noise and corona
The method of noise, method includes the following steps:
One, the noise characteristic of transformer substation body noise, fan noise, corona noise is determined.
Shown in Fig. 1-Fig. 6, to pass through the time domain waveform and time-frequency spectrum (i.e. vocal print figure) of testing obtained each noise like.Become
This bulk noise of depressor is the apparent periodic noise of line spectrum feature, and energy concentrates on 100Hz and its a series of harmonics ingredients
(upper limit of Energy distribution is about 1000Hz)；Cooling equipment fan noise is typical white noise, and energy is in wider frequency band model
It is uniformly distributed in enclosing；And AC corona noise is a series of set of pings in short-term.
Two, transformer body noise is separated first
Assuming that the ambient noise s (n) of microphone measurement, ignores measurement noise, including this bulk noise b (n), corona noise d
(n) and fan noise g (n), have:
S (n)=b (n)+d (n)+g (n)
Have on frequency domain:
S (f)=B (f)+D (f)+G (f)
Wherein, S (f), B (f), D (f), G (f) are s (n), b (n), d (n), g (n) Fourier variation respectively.Known fan
Noise power concentrates on f < 1.5Kz low-frequency range；Transformer body noise power spectrum shows as alternating current fundamental frequency and integral multiple is high
The line spectrum of frequency can be ignored in f > 1Kz range line spectrum energy；Corona noise is similar to impulsive sound, and power spectrum is in f < fs/2
Range is uniformly distributed, and in the time domain, corona noise shows as the feature of cutting in and out, and when corona discharge occurs, corona noise goes out
It is existing, when corona discharge does not occur, corona noise zero；Fan noise, corona noise, this bulk noise think irrelevant.Root
Upper analysis accordingly, it is known that it to realize noise separation, need from the aspect of time domain, frequency domain two, separation algorithm block diagram such as Fig. 7.
Wherein wavelet transformation uses Daubechies filter group, and the wavelet conversion coefficient of five layers of decomposition is c1(n),c2
(n),c3(n),c4(n),c5(n),c6(n)；Corresponding frequency range is 0-f/64, f/64-f/32, f/32-f/16, f/16-f/
8, f/8-f/4, f/4-f/2, f are basic sample frequency.Passband, stopband comb filter band connection frequency, stop-band frequency are ontology
Vibration frequency fundamental frequency 50Hz and each integer multiple frequency.
Low frequency wavelet transformation coefficient c1(n) pass through passband comb filter, filter output result is doing wavelet inverse transformation
Obtain the estimation of this bulk noise
It is as shown in Figure 8 that this bulk noise time-frequency obtained is separated from example integrated noise data.By can obviously be seen in figure
Low-frequency range is using 100Hz as a series of harmonics spectral lines of fundamental frequency out.
Three, corona noise separates
It first will include time domain ambient noise s (n) progress of the transformer body noise, corona noise and fan noise
Wavelet transformation；Coefficient c after the wavelet transformation1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；Utilize high frequency wavelet
Transformation coefficient c5(n),c6(n) inverse wavelet transform is r (n), and whether the corona noise in detection r (n) occurs, wherein H1It indicates
Corona noise is assumed；H0Indicate that corona noise is not assumed.Select c5(n),c6(n), it makes an uproar primarily to reducing fan
The adverse effect that sound detects corona noise, because fan noise is in high band f/8~f/2, energy very little, f is basic sampling
Frequency.By the coefficient c1(n) by after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and c6
(n) inverse wavelet transform is carried out jointly form time domain waveform y (n)；The inverse wavelet transform is time domain waveform y (n) and r (n) framing
Processing, frame length N, it is P that frame, which moves, and q frame data have:
yq=[y (qP-N+1), y (qP-N+2) ... y (qP)]T
rq=[r (qP-N+1), r (qP-N+2) ... r (qP)]T
Judge whether the time domain waveform r (n) occurs corona noise by following formula:
Wherein, T is corona noise detection limit, ξTFor threshold value, ξ is taken in testT=10, E { r2(n) } it can be carried out with following formula
It determines:
Wherein, γ=0.99 is smoothing factor,For E { r2(n) } estimated value.
Secondly, q frame data y (n) fast Fourier (FFT) converts Yq(k) have:
Wherein w (m) is window function.
The corona noiseCalculating process it is as follows:
If q frame data frame is judged as H0, then using Yq(k) its noise spectrum is determined:
Wherein NqIt (k) is minimum, maximum and the noise spectrum of estimation, α, β, κ is smoothing parameter, is taken
Value is α=0.01, β=0.5, κ=0.1, q frame corona noiseValue
It is zero.
If q frame data are judged as H1, determining noise spectrum remains unchanged N at this timeq(k)=Nq-1(k)。Yq(k) include in
Corona noise frequency spectrum and fan noise frequency spectrum utilize spectrum-subtraction, corona noise frequency spectrum Dq(k) have:
Dq(k) FFT is inversely transformed into dq(m):
If frame moves P=N, FFT transform does not have adding window, then having
P=64, N=128 are taken in test, takes Perfect Reconstruction cosine function window, calculate q frame electricity using overlap-add method
Dizzy noise data has:
It is as shown in Figure 9 that the corona noise time-frequency figure obtained is separated from example integrated noise data.By can be clear in figure
Find out that, in a series of pulses that time domain occurs at equal intervals, which can be accurately located out the arteries and veins in short-term occurred in time domain in ground
Punching.
Four, fan noise separates
It will include time domain ambient noise s (n) the progress small echo of the transformer body noise, corona noise and fan noise
Transformation；Coefficient c after the wavelet transformation1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；By the coefficient c1(n) lead to
Cross after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and c6(n) inverse wavelet transform shape is carried out jointly
At time domain waveform y (n)；The fan noise is by will remove corona noise d in the time domain waveform y (n)q(m) it determines.
Q frame fan noiseHave:
Wherein, gqIt (m) is the frequency spectrum Yq(k) fan noise power spectrum G is determinedq(k) FFT inverse transformation:
Wherein:
It is as shown in Figure 10 that the fan noise time-frequency obtained is separated from example integrated noise data, after the separation known in figure
Fan noise be still energy more equally distributed white noise over the entire frequency band.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, institute
The those of ordinary skill in category field is although should be understood with reference to the above embodiments: still can be to a specific embodiment of the invention
It is modified or replaced equivalently, these are without departing from any modification of spirit and scope of the invention or equivalent replacement, in Shen
Within claims of the invention that please be pending.
Claims (7)
1. a kind of substation's mixed noise separation method, it is characterised in that: the method is to separate individual transformer body to make an uproar
The method of sound, fan noise and corona noise；It the described method comprises the following steps:
(1) noise characteristic of transformer body noise, fan noise and corona noise is determined；
(2) transformer body noise is separated；
(3) corona noise is separated；
(4) fan noise is separated；
The separation process of the step (2) are as follows:
It will include time domain ambient noise s (n) the progress small echo change of the transformer body noise, corona noise and fan noise
It changes；
Coefficient after the wavelet transformation is c1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
The coefficient c1(n) the transformer body noise is obtained by passband comb filter and wavelet inverse transformation
Separation process in the step (3) are as follows:
It will include time domain ambient noise s (n) the progress small echo change of the transformer body noise, corona noise and fan noise
It changes；
Coefficient after the wavelet transformation is c1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
By the coefficient c5(n) and c6(n) wavelet inverse transformation is time domain waveform r (n)；
Judge whether time domain waveform r (n) occurs corona noise；
Separation process in the step (4) are as follows:
It will include time domain ambient noise s (n) the progress small echo change of the transformer body noise, corona noise and fan noise
It changes；
Coefficient after the wavelet transformation is c1(n)、c2(n)、c3(n)、c4(n)、c5(n) and c6(n)；
By the coefficient c1(n) by after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and c6(n)
The common wavelet inverse transformation that carries out forms time domain waveform y (n)；
The fan noise is by will remove corona noise d in the time domain waveform y (n)q(m) it determines；
When corona noise does not occur for the time domain waveform r (n), corona noise 0；When corona occurs for the time domain waveform r (n)
When noise:
By the coefficient c1(n) by after stopband comb filter with the coefficient c2(n)、c3(n)、c4(n)、c5(n) and c6(n)
The common wavelet inverse transformation that carries out forms time domain waveform y (n)；
The time domain waveform y (n) is formed into the Y comprising corona noise frequency spectrum and fan noise frequency spectrum by Fast Fourier Transform (FFT)q
(k)；
Frequency spectrum Y is determined by spectrum-subtractionq(k) the corona noise frequency spectrum in.
2. a kind of substation's mixed noise separation method as described in claim 1, it is characterised in that: in the step (1)
Transformer body noise is that its frequency concentrates on 100Hz and using 100Hz as the harmonics ingredient of fundamental frequency；The fan of cooling equipment
Noise is white noise, and frequency is uniformly distributed being less than in 1500Hz；The corona noise is wide in the main frequency range of audible noise
General distribution, main frequency range are 20Hz-20kHz.
3. a kind of substation's mixed noise separation method as described in claim 1, it is characterised in that: the wavelet transformation uses
Daubechies filter group；The coefficient c1(n) corresponding frequency range is 0-f/64, and f is basic sample frequency；It is described logical
Band connection frequency with comb filter is the frequency of its ontology vibration frequency fundamental frequency 50Hz and 50Hz integral multiple.
4. a kind of substation's mixed noise separation method as described in claim 1, it is characterised in that: the time domain waveform y (n)
With r (n) sub-frame processing, frame length N, it is P that frame, which moves, and q frame data have:
yq=[y (qP-N+1), y (qP-N+2) ... y (qP)]T
rq=[r (qP-N+1), r (qP-N+2) ... r (qP)]T
The frequency spectrum Yq(k) are as follows:
Wherein, w (m) is window function.
5. a kind of substation's mixed noise separation method as claimed in claim 4, it is characterised in that: as the time domain waveform r
(n) when corona noise not occurring, pass through the frequency spectrum Yq(k) its noise spectrum is determined:
WhereinAnd NqIt (k) is respectively minimum spectrum, maximum spectrum and noise spectrum；α, β and κ are smoothing parameter,
Value is α=0.01, β=0.5, κ=0.1；γ=0.99 is smoothing factor；
When corona noise occurs for the time domain waveform r (n), then noise spectrum remains unchanged Nq(k)=Nq-1(k)；
Corona noise frequency spectrum Dq(k) are as follows:
The corona noise frequency spectrum Dq(k) corona noise d is obtained by inverse fast Fourier transformq(m):
Wherein, m=0,1 ... N-1.
6. a kind of substation's mixed noise separation method as claimed in claim 5, it is characterised in that: if frame moves P=N, fastly
Fast Fourier transformation does not have adding window, then
Wherein, m=0,1 ... P-1；
Judge whether the time domain waveform r (n) occurs corona noise by following formula:
Wherein, T is corona noise detection limit；ξTFor threshold value；E{r2(n) } it can be determined with following formula:
Wherein, γ=0.99 is smoothing factor,For E { r2(n) } estimated value.
7. a kind of substation's mixed noise separation method as described in claim 1, it is characterised in that: fan described in q frame is made an uproar
SoundThen:
Wherein, gqIt (m) is the frequency spectrum Yq(k) fan noise power spectrum G is determinedq(k) FFT inverse transformation:
The Gq(k) are as follows:
The stop-band frequency of the stopband comb filter is the frequency of its ontology vibration frequency fundamental frequency 50Hz and 50Hz integral multiple
Rate.
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| CN107167232B (en) * | 2017-05-25 | 2021-06-22 | 中国电力科学研究院 | Method and system for carrying out noise reduction processing on high-voltage transmission line noise-containing corona audible noise signal |
| CN108051659B (en) * | 2017-12-01 | 2020-05-12 | 中国直升机设计研究所 | Method for separating and extracting rotor noise |
| CN109444519A (en) * | 2018-10-30 | 2019-03-08 | 国网上海市电力公司 | Substation's noise source separation method towards complicated acoustic environment |
| CN109991520A (en) * | 2019-03-19 | 2019-07-09 | 中国电力科学研究院有限公司 | A kind of cable oscillation wave partial discharge detecting system velocity of wave New calculating method |
| CN110567576B (en) * | 2019-09-11 | 2022-10-28 | 中国电力科学研究院有限公司 | Method and device for determining reason for standard exceeding of factory boundary noise of transformer substation |
| CN111854920A (en) * | 2020-07-24 | 2020-10-30 | 贵州电网有限责任公司 | Preprocessing method and system based on DVS vibration monitoring signal |
| CN112484844A (en) * | 2020-11-30 | 2021-03-12 | 国网湖南省电力有限公司 | Method and system for detecting noise and environmental interference resistance of transformer |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102194027A (en) * | 2011-04-29 | 2011-09-21 | 重庆电力科学试验研究院 | Optimized analytical method and system for noise control in transformer station |
| CN103217211A (en) * | 2013-04-09 | 2013-07-24 | 国家电网公司 | Substation noise source distribution measuring method based on synthetic aperture principle |
| CN103604494A (en) * | 2013-11-27 | 2014-02-26 | 国家电网公司 | Method for improving accuracy of transformer substation boundary noise measurement |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012107917A (en) * | 2010-11-16 | 2012-06-07 | Tokyo Electric Power Co Inc:The | Noise analysis method of electric power substation |
-
2014
- 2014-09-19 CN CN201410484583.XA patent/CN105486938B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102194027A (en) * | 2011-04-29 | 2011-09-21 | 重庆电力科学试验研究院 | Optimized analytical method and system for noise control in transformer station |
| CN103217211A (en) * | 2013-04-09 | 2013-07-24 | 国家电网公司 | Substation noise source distribution measuring method based on synthetic aperture principle |
| CN103604494A (en) * | 2013-11-27 | 2014-02-26 | 国家电网公司 | Method for improving accuracy of transformer substation boundary noise measurement |
Non-Patent Citations (3)
| Title |
|---|
| 两座城区变电站噪声超标的现场治理;孙胜涛等;《变压器》;20100731;第47卷(第7期);第64-68页 |
| 变电站复杂声场中多点噪声源的鉴别;罗超等;《环境科学与管理》;20121031;第37卷(第10期);第94-96页 |
| 基于声成像技术的变电站主变噪声识别及其特性研究;罗超等;《变压器》;20131130;第50卷(第11期);第51-53页 |
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