CN109307798A - A kind of power signal filtering method for switch events detection - Google Patents
A kind of power signal filtering method for switch events detection Download PDFInfo
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Abstract
The present invention provides a kind of power signal filtering method for switch events detection, filters in the prior art for solving the problems, such as, is difficult to accurately carry out switch events detection to having apparent non-stationary and non-Gaussian feature ambient noise that function signal can not be effectively performed.The described method includes: carrying out the summation of all scales to filtered power signal is sought, filtered power matrix is obtained.The present invention is by carrying out multiple dimensioned summation after filtering to power signal, effectively filter out non-stationary and non-Gaussian feature noise, it is effective to carry out power signal filtering, carry out accurate switch events detection, filtering method is simple, calculating speed is very fast, to complete the accurate decomposition of household electricity load.
Description
Technical field
The invention belongs to power domains, and in particular to a kind of power signal filtering method for switch events detection.
Background technique
With the development of smart grid, the analysis of household electricity load is become more and more important.Pass through point of power load
Analysis, domestic consumer can obtain the power information of each electric appliance and the fining inventory of the electricity charge in time；Power department can obtain
More detailed user power utilization information is obtained, and the accuracy of electro-load forecast can be improved, provides overall planning for power department
Foundation.Current power load decomposition is broadly divided into two methods of intrusive load decomposition and non-intrusion type load decomposition.It is non-to invade
Enter formula load decomposition method not needing that monitoring device is installed in the power inside equipment of load, it is only necessary to total according to power load
Information can be obtained the information on load of each electrical equipment, less investment, convenient to use, the decomposition suitable for family's load electricity consumption.
In non-intrusion type load decomposition algorithm, the switch events detection of electrical equipment is most important one link.Any one electricity consumption
The operating status of equipment changes, and consumed performance number also necessarily changes, and the change also will be all
It is embodied in general power consumed by electric appliance, common switch events detection is using the changing value Δ P of active-power P as event
The judgment basis of detection.Fig. 1 show the Energy Decomposition simulation schematic diagram of household electricity load in the prior art.
This method needs to be arranged the reasonable threshold value of power change values, exists simultaneously following problems: when certain appliance startings
The instantaneous power value at quarter will appear biggish spike, i.e. impulsive noise (for example, motor start-up current is much larger than rated current), meeting
Cause electric appliance steady state power changing value inaccurate, to influence the judgement to switch events；The transient process of different household electrical appliance
Long or short (duration of impulsive noise and occurrence frequency difference are larger), therefore the determination of power change values becomes more to be stranded
It is difficult；It the case where will appear mutation due to variation (such as voltage die) active power of power quality, is likely to miss in this way
Sentence.Fig. 2 is that the power signal surveyed by switch events detection device in the prior art and common detection algorithm (can also claim
For power data sequence), it can be seen that the distribution situation of noise (including impulsive noise) in signal, in the power sequence shown in
The intensity of (pulse) noise is very big, although really switch events only one, detect 3 switch events.Therefore, it switchs
In event detection procedure, being filtered to power signal is a critically important step.
Noise eliminating equipment commonly used in the prior art is low-pass filter and median filter.Low-pass filter is to steady
Property and the noise that meets Gauss law have a good eradicating efficacy, but non-stationary and non-Gaussian feature noise is eliminated and is imitated
Fruit is poor.In daily life non-linear electric appliance using more and more, such as use the fruit juice mixer, coffee machine and soy bean milk making machine of motor
Deng occurring more and more impulsive noises in ambient noise.This noise like instantaneous power is big, shows more apparent non-flat
The filtering of function signal can not be effectively performed using noise eliminating equipment commonly used in the prior art in stability and non-Gaussian feature, difficult
Accurately to carry out switch events detection.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of power signal filtering method for switch events detection, needles
To in the prior art non-stationary and non-Gaussian system power signal, signal filtering can also be effectively carried out, is carried out accurate
Switch events detection, filtering method is simple, and calculating speed is very fast, thus the accurate decomposition of household electricity load.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of power signal filtering for switch events detection
Method, which comprises filtered power signal matrix is sought in the summation to all scales.
Wherein, the method also includes following steps:
Before seeking filtered power signal matrix:
Step S1 inputs the power signal of actual measurement；
The power signal of the actual measurement is segmented by step S2, and is power letter by the data permutation after segmentation
Number matrix；
Step S3 seeks the Discrete Fourier Transform function of basic function；
Step S4 seeks the discrete value of basic function according to the Fourier transform function of basic function；
Step S5 seeks the discrete value of generating function according to the discrete value of basic function；
Step S6 asks projection of the power signal under generating function according to the discrete value of generating function, obtains transformed power
Signal matrix；
Step S7 filters transformed power signal matrix；
After obtaining filtered power signal matrix, further includes:
Filtered power signal matrix conversion is data sequence, rearranges data, filtered out and made an uproar by step S9
The power signal of sound.
Wherein, the step S2 further comprises:
Step S21 sets the power signal length of the input actual measurement as N, all data is divided into NRSection；
Step S22 is segmented according to data precedence, and every section contains NCA data,
Wherein, symbolIt is rounded in expression；
Step S23, if N < NR×NC, then by insufficient part zero padding；
Data permutation after segmentation is the form of matrix by step S24.
Wherein, basic function is sought in the step S3Fourier transform functionSpecifically:
Wherein:
Z indicates all integers
Wherein, the discrete value of basic function is sought in the step S4Are as follows:
Wherein, the discrete value ψ of generating function is sought in the step S5lmijAre as follows:
L=1,2, L, 10
M=1,2, L, 10
I=1,2, L, NR
J=1,2, L, NC
Wherein,
Wherein, projection of the power signal under generating function is sought in the step S6 further comprises:
Step S61, by the discrete value ψ of generating functionlmijBe converted to generating function matrix:
Wherein, ψlmijFor matrix ΓlmThe i-th row jth column element；
Power signal matrix and generating function matrix are done point multiplication operation and obtain transformed power letter by step S62
Number matrix:
Wherein, l=1,2, L, 10；M=1,2, L, 10.
Wherein, transformed power signal matrix is filtered in the step S7, further comprises:
Step S71 is calculate by the following formula threshold value λlm:
Wherein, median [ψlmij] indicate that variable l and m are fixed, the ψ in the case where i j takes all valueslmijIntermediate value；
Step S72, according to threshold value λlmDetermine the value of each element of new matrix.
Wherein,
In the step S71, pass through
Calculate threshold value λlm；
Wherein, median [ψlmij] indicate that variable l and m are fixed, the ψ in the case where i j takes all valueslmijIntermediate value；
The step S72 is further are as follows:
IfAny one of element be less than threshold value λ, then enable this element be 0；It is new by being obtained after so handling
MatrixI-th row jth column element of this matrix is expressed as
Wherein, described pair of all scale summation, seeking filtered power signal matrix is step S8, specifically, described
Filtered power signal matrix are as follows:
P1=[Pij] (6)
Wherein,I, j represent scale, sum to all i, j, to sum to all scales.
Above-mentioned technical proposal of the present invention has the beneficial effect that:
It is special effectively to filter out non-stationary and non-gaussian by carrying out multiple dimensioned summation after filtering to power signal by the present invention
Property noise, it is effective to carry out power signal filtering.The signal after noise is filtered out, signal-to-noise ratio improves 5dB or so, after being
Continuous switch events detection is laid a good foundation.Filtering method is simple, and calculating speed is very fast.
Detailed description of the invention
For the elaboration the embodiment of the present invention being more clear and existing technical solution, below by technical side of the invention
Case illustrates that attached drawing does simple introduction, it is clear that, without creative efforts, ordinary skill people
Member can obtain other attached drawings by this attached drawing.
Fig. 1 is that the Energy Decomposition of household electricity load in the prior art simulates schematic diagram；
Fig. 2 is the power signal surveyed by switch events detection device in the prior art and common detection algorithm
Figure；
Fig. 3 is the filtering method flow diagram that the embodiment of the present invention is used for switch events detection；
Fig. 4 is data sectional and matrix arrangement schematic diagram.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The present invention can not be effective filtered out for noise eliminating equipment commonly used in the prior art with non-stationary and non-
The noise of Gaussian characteristics is difficult to the problem of accurately carrying out switch events detection, proposes that one kind is novel, is directed in power signal
The filtering method of noise characteristic carries out multi-scale filtering to power signal, and filtering algorithm is simple, and calculating speed is fast, effectively filters
Except the noise (containing impulsive noise) of the ambient noise in power signal, especially non-stationary non-gaussian type, accurately opened
Close event detection.
Below by specific embodiment, in conjunction with attached drawing, the present invention is described in further detail.
Embodiment
A kind of power signal filtering method for switch events detection is present embodiments provided, Fig. 3 show this implementation
The example power signal filtering method.As shown in figure 3, the power signal filtering method for switch events detection includes such as
Lower step:
Step S1, inputs the power signal of actual measurement, and setting signal length is N.
Specifically, the power signal sequence P (1), P (2), L, P (N) of input actual measurement, N is the length of power signal sequence.
The power signal of the actual measurement is carried out segmentation and is power signal by the data permutation after segmentation by step S2
Matrix P.
Specifically, including:
All data are divided into N by step S21RSection.
Preferably, the NR=256 or 512 or 1024.
Step S22 is segmented according to data precedence, and every section contains NCA data.
Wherein,SymbolIt is rounded in expression.Such asThe purpose done so
It is that all data are involved in operation, does not give up data.
Step S23, if N < NR×NC, then by insufficient part zero padding.
Data permutation after segmentation is the form of matrix by step S24.
Fig. 4 is data sectional and matrix arrangement schematic diagram.As shown in figure 4, one piece of data is a line, therefore, the function
Rate signal matrix P shares NRRow, NCColumn.
Step S3, seeks basic functionDiscrete Fourier Transform function
Specifically, function after transformation are as follows:
Wherein:
Z indicates all integers
Step S4 seeks the discrete value of basic function according to the Fourier transform of basic function
Wherein, i=1,2, L, NR；J=1,2, L, NC
Step S5, according to the discrete value of basic functionSeek the discrete value ψ of generating functionlmij:
Wherein, l=1,2, L, 10；M=1,2, L, 10；I=1,2, L, NR；J=1,2, L, NC；
Step S6, according to the discrete value ψ of generating functionlmijProjection of the power signal under generating function is asked, is obtained transformed
Power signal matrix.
Further, this step specifically includes:
Step S61, by the discrete value ψ of generating functionlmijBe converted to generating function matrix:
ψ in formula (3)lmijRepresenting matrix ΓlmThe i-th row jth column element, this matrix shares NRRow, NCColumn.
Power signal matrix and generating function matrix are done point multiplication operation and obtain transformed power letter by step S62
Number matrix:
Wherein, l=1,2, L, 10；M=1,2, L, 10.
Step S7 filters transformed power signal matrix.
Specifically, the filtering includes the following steps:
Step S71 is calculate by the following formula threshold value λlm:
Wherein, median [ψlmij] indicate that variable l and m are fixed, the ψ in the case where i j takes all valueslmijIntermediate value；
Step S72 determines the value of each element of new matrix according to threshold value.
Specifically, ifAny one of element be less than threshold value λlm, then enabling this element is 0；By so handling it
New matrix is obtained afterwardsI-th row jth column element of this matrix is expressed as
Step S8 sums to all scales, seeks filtered power signal matrix:
P1=[Pij] (6)
Wherein,
I in this step, j represent scale, sum to all i, j, as sum to all scales.
Filtered power signal matrix conversion is data sequence, rearranges data, filtered out and made an uproar by step S9
The power signal of sound.
Specifically, this step includes: by matrix P1The first row data as first segment, the 2nd row data as second segment,
And so on, last line data connect these sections as final stage in sequence, and intercept N number of number of front
According to a data sequence is formed, this data sequence is exactly the power signal filtered out after ambient noise (especially flash noise).
As can be seen from the above technical solutions, the present embodiment is used for the power signal filtering method of switch events detection, leads to
Multi-scale filtering is crossed, non-stationary and non-Gaussian feature noise is effectively filtered out, it is effective to carry out power signal filtering, it carries out
Accurate switch events detection, filtering method is simple, and calculating speed is very fast, to complete the accurate decomposition of household electricity load.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of power signal filtering method for switch events detection, which is characterized in that the described method includes: to all rulers
Filtered power signal matrix is sought in the summation of degree.
2. power signal filtering method according to claim 1, which is characterized in that the method also includes following steps:
Before seeking filtered power signal matrix:
Step S1 inputs the power signal of actual measurement；
The power signal of the actual measurement is segmented by step S2, and is power signal square by the data permutation after segmentation
Battle array；
Step S3 seeks the Discrete Fourier Transform function of basic function；
Step S4 seeks the discrete value of basic function according to the Fourier transform function of basic function；
Step S5 seeks the discrete value of generating function according to the discrete value of basic function；
Step S6 asks projection of the power signal under generating function according to the discrete value of generating function, obtains transformed power signal
Matrix；
Step S7 filters transformed power signal matrix；
After obtaining filtered power signal matrix, further includes:
Filtered power signal matrix conversion is data sequence, rearranges data, filtered out noise by step S9
Power signal.
3. power signal filtering method according to claim 1, which is characterized in that the step S2 further comprises:
Step S21 sets the power signal length of the input actual measurement as N, all data is divided into NRSection；
Step S22 is segmented according to data precedence, and every section contains NCA data,
Wherein, symbolIt is rounded in expression；
Step S23, if N < NR×NC, then by insufficient part zero padding；
Data permutation after segmentation is the form of matrix by step S24.
4. power signal filtering method according to claim 1, which is characterized in that seek basic function in the step S3
Fourier transform functionSpecifically:
Wherein:
Z indicates all integers
5. power signal filtering method according to claim 1, which is characterized in that asked in the step S4 basic function from
Dissipate valueAre as follows:
6. power signal filtering method according to claim 1, which is characterized in that asked in the step S5 generating function from
Dissipate value ψlmijAre as follows:
L=1,2, L, 10
M=1,2, L, 10
I=1,2, L, NR
J=1,2, L, NC
Wherein,
7. power signal filtering method according to claim 1, which is characterized in that seek power signal in the step S6
Projection under generating function further comprises:
Step S61, by the discrete value ψ of generating functionlmijBe converted to generating function matrix:
Wherein, ψlmijFor matrix ΓlmThe i-th row jth column element；
Power signal matrix and generating function matrix are done point multiplication operation and obtain transformed power signal matrix by step S62:
Wherein, l=1,2, L, 10；M=1,2, L, 10.
8. power signal filtering method according to claim 1, which is characterized in that transformed function in the step S7
The filtering of rate signal matrix further comprises:
Step S71 is calculate by the following formula threshold value λlm:
Wherein, median [ψlmij] indicate that variable l and m are fixed, the ψ in the case where i j takes all valueslmijIntermediate value；
Step S72, according to threshold value λlmDetermine the value of each element of new matrix.
9. power signal filtering method according to claim 8, which is characterized in that
In the step S71, pass through
Calculate threshold value λlm；
Wherein, median [ψlmij] indicate that variable l and m are fixed, the ψ in the case where i j takes all valueslmijIntermediate value；
The step S72 is further are as follows:
IfAny one of element be less than threshold value λ, then enable this element be 0；By obtaining new square after so handling
Battle arrayI-th row jth column element of this matrix is expressed as
10. power signal filtering method according to claim 1, which is characterized in that described pair of all scale summation is asked
Filtered power signal matrix is step S8, specifically, the filtered power signal matrix are as follows:
P1=[Pij] (6)
Wherein,I, j represent scale, sum to all i, j, to sum to all scales.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109902961A (en) * | 2019-03-04 | 2019-06-18 | 广东石油化工学院 | The multi-scale filtering method and system filtered for power signal in Energy Decomposition |
| CN110196354A (en) * | 2019-04-23 | 2019-09-03 | 广东石油化工学院 | A kind of detection method and device of the switch events of load |
| CN110221121A (en) * | 2019-06-28 | 2019-09-10 | 广东石油化工学院 | A kind of on-load switch event detecting method and system based on Signal separator |
| CN110531149A (en) * | 2019-08-31 | 2019-12-03 | 广东石油化工学院 | A kind of power signal filtering method and system based on waveform regularization |
| CN110542855A (en) * | 2019-09-08 | 2019-12-06 | 广东石油化工学院 | Load switch event detection method and system based on discrete cosine transform |
| CN110726870A (en) * | 2019-10-20 | 2020-01-24 | 广东石油化工学院 | Load switch event detection method and system based on data purity |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1610144A2 (en) * | 2004-06-23 | 2005-12-28 | Whirlpool Corporation | Method for calibrating offset from DC bus |
| JP4765180B2 (en) * | 2001-03-07 | 2011-09-07 | パナソニック株式会社 | Method for measuring output power of inductive load of electric powered vehicle |
| CN102288285A (en) * | 2011-05-24 | 2011-12-21 | 南京航空航天大学 | Blind source separation method for single-channel vibration signals |
| CN102841341A (en) * | 2012-09-03 | 2012-12-26 | 深圳先进技术研究院 | Pulse radar moving-target detection method |
| CN106908657A (en) * | 2017-03-06 | 2017-06-30 | 中国海洋大学 | A kind of load switch detection means and method based on power |
-
2018
- 2018-08-29 CN CN201810995998.1A patent/CN109307798B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4765180B2 (en) * | 2001-03-07 | 2011-09-07 | パナソニック株式会社 | Method for measuring output power of inductive load of electric powered vehicle |
| EP1610144A2 (en) * | 2004-06-23 | 2005-12-28 | Whirlpool Corporation | Method for calibrating offset from DC bus |
| CN102288285A (en) * | 2011-05-24 | 2011-12-21 | 南京航空航天大学 | Blind source separation method for single-channel vibration signals |
| CN102841341A (en) * | 2012-09-03 | 2012-12-26 | 深圳先进技术研究院 | Pulse radar moving-target detection method |
| CN106908657A (en) * | 2017-03-06 | 2017-06-30 | 中国海洋大学 | A kind of load switch detection means and method based on power |
Non-Patent Citations (3)
| Title |
|---|
| MENGCONG TANG 等: "Research of Transmission Parameters of Four-Conductor Cables for Power Line Communication", 《2008 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING》 * |
| 彭志威 等: "矩阵稀疏化中的最优子波滤波器组设计", 《西安电子科技大学学报》 * |
| 陈志光 等: "基于稀疏矩阵变换的电网故障电流快速算法", 《广东电力》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109902961A (en) * | 2019-03-04 | 2019-06-18 | 广东石油化工学院 | The multi-scale filtering method and system filtered for power signal in Energy Decomposition |
| CN110196354A (en) * | 2019-04-23 | 2019-09-03 | 广东石油化工学院 | A kind of detection method and device of the switch events of load |
| CN110196354B (en) * | 2019-04-23 | 2021-09-17 | 广东石油化工学院 | Method and device for detecting switching event of load |
| CN110221121A (en) * | 2019-06-28 | 2019-09-10 | 广东石油化工学院 | A kind of on-load switch event detecting method and system based on Signal separator |
| CN110531149A (en) * | 2019-08-31 | 2019-12-03 | 广东石油化工学院 | A kind of power signal filtering method and system based on waveform regularization |
| CN110531149B (en) * | 2019-08-31 | 2021-06-18 | 广东石油化工学院 | Power signal filtering method and system based on waveform regularization |
| CN110542855A (en) * | 2019-09-08 | 2019-12-06 | 广东石油化工学院 | Load switch event detection method and system based on discrete cosine transform |
| CN110542855B (en) * | 2019-09-08 | 2021-09-21 | 广东石油化工学院 | Load switch event detection method and system based on discrete cosine transform |
| CN110726870A (en) * | 2019-10-20 | 2020-01-24 | 广东石油化工学院 | Load switch event detection method and system based on data purity |
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