CN108594035A - A kind of load testing method and system - Google Patents
A kind of load testing method and system Download PDFInfo
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- CN108594035A CN108594035A CN201810246406.6A CN201810246406A CN108594035A CN 108594035 A CN108594035 A CN 108594035A CN 201810246406 A CN201810246406 A CN 201810246406A CN 108594035 A CN108594035 A CN 108594035A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/25—Arrangements for measuring currents or voltages or for indicating presence or sign thereof using digital measurement techniques
- G01R19/2513—Arrangements for monitoring electric power systems, e.g. power lines or loads; Logging
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Abstract
The invention discloses a kind of load testing method, the method includes：According to preset period of time in the bus at the main entrance of the load of acquisition voltage signal and current signal carry out windowing process, and determine the corresponding power signal of each window；The candidate load collection of each window is determined according to the duration features of the corresponding power signal of each window；The characteristic information of the corresponding each candidate load of each window is determined according to the power signal of the power signal of each window and corresponding each candidate load；The load of each window is determined according to characteristic information feature weight group corresponding with each candidate's load.Present invention gathered data by the way of offline keeps data more accurate, can obtain more complete waveform；Switch events detection and load identification are put together, the load of window is determined using the feature weight and characteristic information of different loads, improves the accuracy of the accuracy of loading history monitoring and the identification classification of load.
Description
Technical field
The present invention relates to load monitoring technical fields, and more particularly, to a kind of load testing method and system.
Background technology
It is capable of normal operation with house and commercial building to ensure that the energy requirements of electric power can attain full and complete satisfaction
On basis, we should take effective measures and reasonably save electric power, improve the utilization ratio of electric power, then the prison of load
Control and measurement just become particularly important.
While being monitored and measuring to load, in order to reduce investment and temporal a large amount of consumption, we are from firmly
Residence and the bus of commercial building obtain the information of electric current and voltage, analyze it and handle, obtain the letter of voltage, electric current
Number.Then, corresponding feature is extracted from signal, using corresponding algorithm, different load decompositions is come out, and is obtained each negative
The power information of lotus.Since the function of each load is various, principle is complicated, the information of sometimes simple voltage, electric current is difficult to pair
The load that multimode persistently changes effectively is classified.
The method of load monitoring is mainly to carry out analyzing processing using electric current, the information of voltage in bus at present, merely
In terms of electric signal, it is monitored in real time.Its Method type is broadly divided into two classes, and one is points based on load steady state characteristic
Analysis method, one is the analysis methods based on load transient characteristic.Analysis method based on load steady state characteristic is mainly to negative
The exemplary currents of lotus, voltage are sampled, are superimposed, and realize the emulation of load stable state waveform.Analysis method based on load transient state
Mainly the electric current of transient state, voltage are sampled, then extraction characteristic value, such as form factor, peak-to-peak value etc. are divided
Class.It is by decision node, branch that sorting technique, which mainly has C4.5 decision Tree algorithms, spectral clustering etc., C4.5 decision Tree algorithms,
It is formed with leaf node, decision node indicates that sample, the different values of some decision node of branching representation, leaf node indicate possible
Classification results.Its process is trained to it using training set, and model is obtained, then the decision since root node, along point
Branch reaches leaf node, obtains possible tag along sort.Spectral clustering first has to prepare data, generates the adjacency matrix of figure, so
This matrix of pula is normalized afterwards, is generated characteristic value and feature vector, is clustered, finally classified according to criteria for classifying.Though
These right methods can realize that load identifies to a certain extent, but there is also some defects, are mainly manifested in following several
Point：Method for distinguishing is known in general monitoring, detection, and switch events and load identify that two parts are to separate to differentiate, there is switch
Event flase drop does not detect and the situation of signal interference, to be impacted to subsequent identification；Merely from electric current, voltage
Variation go to be detected and identify, many loads are easy to obscure；And load is monitored in real time, obtained information content
Limited, detection and load identification to switch events all cause certain obstruction.
Invention content
The present invention provides a kind of load testing method and systems, to solve the problems, such as how to be detected to load.
To solve the above-mentioned problems, according to an aspect of the invention, there is provided a kind of load testing method, the method
Including：
According to preset period of time in the bus at the main entrance of the load of acquisition voltage signal and current signal into
Row windowing process, and determine the corresponding power signal of each window；
The candidate load collection of each window is determined according to the duration features of the corresponding power signal of each window,
Each candidate's load collection includes at least one candidate load；
It is determined according to the power signal of the power signal of each window and corresponding each candidate load each
The characteristic information of the corresponding each candidate load of window；
The load of each window is determined according to characteristic information feature weight group corresponding with each candidate's load.
Preferably, wherein the method further includes：
To in the bus at the main entrance of the load of acquisition voltage signal and current signal be filtered, and will be through
It crosses the voltage signal being filtered and current signal is converted to voltage digital signal and current digital signal.
Preferably, wherein using model AD1256 24 analog-digital converters to the main entrance of the load of acquisition at
Voltage signal and current signal in bus are filtered.
Preferably, wherein the method further includes：
Before the candidate load collection of each window of determination, the power features according to the corresponding power signal of each window are true
Determine the corresponding candidate load range of each window.
Preferably, wherein the characteristic information includes：Edge feature information, trend feature information, temporal characteristics information, frequency
Rate characteristic information and sequence signature information.
Preferably, wherein described believe according to the power signal of each window and the power of corresponding each candidate load
Number determine the characteristic information of the corresponding each candidate load of each window, including：
The edge type quantity of edge type quantity and corresponding each candidate load in each window is divided by, is determined
Each edge feature information of the corresponding each candidate load of window；
The trend number of types of trend number of types and corresponding each candidate load in each window is divided by, is determined
Each trend feature information of the corresponding each candidate load of window；
The opening time section of the time interval of each window and corresponding each candidate load is compared, is determined every
The temporal characteristics information of the corresponding each candidate load of a window；Wherein, if the time interval of window is in corresponding each candidate
In the opening time section of load, then temporal characteristics information is 1, conversely, temporal characteristics information is 0；
The quantity that the edge type of each window repeats is divided by with the trend number of types of corresponding each candidate load,
Determine the frequecy characteristic information of the corresponding each candidate load of each window；
The ratio that the sequence variables in the backward variable quantity and window of candidate load are subtracted using 1, determines each window pair
Each of answer the sequence signature information of candidate load.
Preferably, wherein described determine each according to characteristic information feature weight group corresponding with each candidate's load
The load of window, including：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information point
The corresponding characteristic information number array of the candidate load of each of each window is not formed, is calculated the characteristic information array and is waited with each
Difference after selecting the corresponding feature weight group of load to be multiplied with preset critical is chosen the corresponding candidate load of maximum difference and is made
For the load of each window.
According to another aspect of the present invention, a kind of cutting load testing system is provided, the system comprises：
Windowing processing module is used for according to preset period of time to the voltage in the bus at the main entrance of the load of acquisition
Signal and current signal carry out windowing process, and determine the corresponding power signal of each window；
Candidate load collection determining module, it is true for the duration features according to the corresponding power signal of each window
The candidate load collection of fixed each window, each candidate's load collection include at least one candidate load；
Characteristic information determining module, for according to the power signal of each window and corresponding each candidate load
Power signal determines the characteristic information of the corresponding each candidate load of each window；
Window load determining module, for true according to characteristic information feature weight group corresponding with each candidate's load
The load of fixed each window.
Preferably, wherein the system also includes：
Be filtered module, for in the bus at the main entrance of the load of acquisition voltage signal and current signal into
Row is filtered, and the voltage signal of filtered processing and current signal are converted to voltage digital signal and current digital letter
Number.
Preferably, wherein using model AD1256 24 analog-digital converters to the main entrance of the load of acquisition at
Voltage signal and current signal in bus are filtered.
Preferably, wherein the system also includes：
Candidate load range determining module is used for before the candidate load collection of each window of determination, according to each window
The power features of corresponding power signal determine the corresponding candidate load range of each window.
Preferably, wherein the characteristic information includes：Edge feature information, trend feature information, temporal characteristics information, frequency
Rate characteristic information and sequence signature information.
Preferably, wherein the characteristic information determining module, according to the power signal of each window and corresponding every
The power signal of a candidate's load determines the characteristic information of the corresponding each candidate load of each window, including：
Edge feature information determination unit, for by edge type quantity in each window and corresponding each candidate negative
The edge type quantity of lotus is divided by, and determines the edge feature information of the corresponding each candidate load of each window；
Trend feature information determination unit, for by trend number of types in each window and corresponding each candidate negative
The trend number of types of lotus is divided by, and determines the trend feature information of the corresponding each candidate load of each window；
Temporal characteristics information determination unit, for opening the time interval of each window and corresponding each candidate load
It opens time interval to be compared, determines the temporal characteristics information of the corresponding each candidate load of each window；Wherein, if window
Time interval is in the opening time section of corresponding each candidate load, then temporal characteristics information is 1, conversely, temporal characteristics
Information is 0；
Frequecy characteristic information determination unit, the quantity for repeating the edge type of each window and corresponding each time
It selects the trend number of types of load to be divided by, determines the frequecy characteristic information of the corresponding each candidate load of each window；
Sequence signature information determination unit, the sequence in backward variable quantity and window for subtracting candidate load using 1
The ratio of variable determines the sequence signature information of the corresponding each candidate load of each window.
Preferably, wherein the window load determining module, corresponding with each candidate load according to the characteristic information
Feature weight group determines the load of each window, is specifically used for：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information point
The corresponding characteristic information number array of the candidate load of each of each window is not formed, is calculated the characteristic information array and is waited with each
Difference after selecting the corresponding feature weight group of load to be multiplied with preset critical is chosen the corresponding candidate load of maximum difference and is made
For the load of each window.
The present invention provides a kind of load testing method and system, the gathered data by the way of offline makes data more
Accurately, more complete waveform can be obtained, the identification of load will not be impacted, more information content can be obtained；It adopts
With power features to constant load range really roughly, improves accuracy rate and also want that part workload can be reduced；According to each window
The power signal of the power signal of mouth and corresponding each candidate load determines the corresponding each candidate load of each window
Characteristic information, by switch events detection and load identification put together, reduce flase drop or do not detect the case where, improve
The accuracy rate of identification；Finally, the load that window is determined using the feature weight and characteristic information of different loads, is more represented
Property, improve the accuracy of the accuracy of loading history monitoring and the identification classification of load.
Description of the drawings
By reference to the following drawings, exemplary embodiments of the present invention can be more fully understood by：
Fig. 1 is the flow chart according to the load testing method 100 of embodiment of the present invention；
Fig. 2 is the schematic device according to the signal-data processing of embodiment of the present invention；And
Fig. 3 is the structural schematic diagram according to the load detection device 300 of embodiment of the present invention.
Specific implementation mode
Exemplary embodiments of the present invention are introduced referring now to the drawings, however, the present invention can use many different shapes
Formula is implemented, and is not limited to the embodiment described herein, and to provide these embodiments be to disclose at large and fully
The present invention, and fully convey the scope of the present invention to person of ordinary skill in the field.Show for what is be illustrated in the accompanying drawings
Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements use identical attached
Icon is remembered.
Unless otherwise indicated, term (including scientific and technical terminology) used herein has person of ordinary skill in the field
It is common to understand meaning.Further it will be understood that with the term that usually used dictionary limits, should be understood as and its
The context of related field has consistent meaning, and is not construed as Utopian or too formal meaning.
Fig. 1 is the flow chart according to the load testing method 100 of embodiment of the present invention.As shown in Figure 1, the present invention is implemented
The load testing method 100 of mode, in the bus at the main entrance of the load of acquisition voltage signal and current signal carry out
Windowing process determines the candidate load collection of each window according to the duration features of the corresponding power signal of each window；Root
Determine that each window is corresponding each according to the power signal of each window and the power signal of corresponding each candidate load
The characteristic information of candidate load determines the load of each window according to characteristic information.The gathered data by the way of offline, makes number
According to more accurately, more complete waveform can be obtained, the identification of load will not be impacted, more information can be obtained
Amount；Using power features to constant load range really roughly, improves accuracy rate and also want that part workload can be reduced；According to every
The power signal of the power signal of a window and corresponding each candidate load determines the corresponding each candidate of each window
The characteristic information of load carries the case where putting together by switch events detection and load identification, reduce flase drop or do not detect
The high accuracy rate of identification；Finally, the load of window, more generation are determined using the feature weight and characteristic information of different loads
Table improves the accuracy of the accuracy of loading history monitoring and the identification classification of load.
The load testing method 100 of embodiment of the present invention is since step 101 place, in step 101 according to preset time
Period in the bus at the main entrance of the load of acquisition voltage signal and current signal carry out windowing process, and determine each
The corresponding power signal of window.
Preferably, wherein the method further includes：
To in the bus at the main entrance of the load of acquisition voltage signal and current signal be filtered, and will be through
It crosses the voltage signal being filtered and current signal is converted to voltage digital signal and current digital signal.
Preferably, wherein using model AD1256 24 analog-digital converters to the main entrance of the load of acquisition at
Voltage signal and current signal in bus are filtered.
In embodiments of the present invention, by switch events and load identification together with differentiate, reduce error.Then,
We handle the data and waveform of one day or one week, can be obtained more information content, make it by the way of offline
As a result more precisely.For similar load, we are special from edge feature, trend feature, temporal characteristics, sequence signature, frequency
Sign, power features are compared, we are first divided with power features, be classified as high-power (1000W or more) and
Two kinds of small-power (1000W or less), this measure can improve the accuracy rate of identification, can also reduce workload when identification.Then
It is effectively identified using edge feature, trend feature, temporal characteristics, sequence signature, frequecy characteristic.
Fig. 2 is the schematic device according to the signal-data processing of embodiment of the present invention.As shown in Fig. 2, voltage sensor
Device and current sensor are respectively used to obtain the voltage signal and current signal in the bus at the main entrance of load, and will be described
Voltage signal and current signal sending value A/D modules, by the current signal and voltage signal be converted to current digital signal and
Then the current digital signal and voltage digital signal are sent to ARM nucleus modules and are carried out to data by voltage digital signal
The processing such as filtering, are then identified detection by data transmission module sending value server to load.Described device further includes
Memory module, for being stored to the data in processing procedure.24 moulds of model AD1256 are used on hardware
Number converter, primarily to reduce signal interference, so as to get signal it is more accurate, waveform is more ideal.
Preferably, it is determined according to the duration features of the corresponding power signal of each window in step 102 each
The candidate load collection of window, each candidate's load collection include at least one candidate load.
In embodiments of the present invention, according to the collocation different with failing edge of rising edge in each window, load is recorded
Duration, establish the table of Classification and Identification, lasting situation will not met and deleted, remaining forms each window and corresponds to
Candidate load collection.For example, a rising edge and failing edge midfeather 2min, this duration is for kettle, refrigerator
Time is too short, so the corresponding kettle of this candidate window and refrigerator should just be deleted.
Preferably, wherein the method further includes：
Before the candidate load collection of each window of determination, the power features according to the corresponding power signal of each window are true
Determine the corresponding candidate load range of each window.In embodiments of the present invention, in the detection window of power waveform, rise
Value, Δ α along transition is power features.After being extracted by the power features to the corresponding power signal of each window
It is compared with 1000W, judges that the possible load of window for high-power load or small-power load, roughly divides load
Range can efficiently reduce workload.
Preferably, in step 103 according to the power of the power signal and corresponding each candidate load of each window
Signal determines the characteristic information of the corresponding each candidate load of each window.
Preferably, wherein the characteristic information includes：Edge feature information, trend feature information, temporal characteristics information, frequency
Rate characteristic information and sequence signature information.
Preferably, wherein described believe according to the power signal of each window and the power of corresponding each candidate load
Number determine the characteristic information of the corresponding each candidate load of each window, including：
The edge type quantity of edge type quantity and corresponding each candidate load in each window is divided by, is determined
Each edge feature information of the corresponding each candidate load of window；
The trend number of types of trend number of types and corresponding each candidate load in each window is divided by, is determined
Each trend feature information of the corresponding each candidate load of window；
The opening time section of the time interval of each window and corresponding each candidate load is compared, is determined every
The temporal characteristics information of the corresponding each candidate load of a window；Wherein, if the time interval of window is in corresponding each candidate
In the opening time section of load, then temporal characteristics information is 1, conversely, temporal characteristics information is 0；
The quantity that the edge type of each window repeats is divided by with the trend number of types of corresponding each candidate load,
Determine the frequecy characteristic information of the corresponding each candidate load of each window；
The ratio that the sequence variables in the backward variable quantity and window of candidate load are subtracted using 1, determines each window pair
Each of answer the sequence signature information of candidate load.
Preferably, true according to characteristic information characteristic information weight group corresponding with each candidate's load in step 104
The load of fixed each window.
Preferably, wherein described determine according to characteristic information characteristic information weight group corresponding with each candidate's load
The load of each window, including：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information point
The corresponding characteristic information number array of the candidate load of each of each window is not formed, is calculated the characteristic information array and is waited with each
It is corresponding candidate negative to choose maximum difference for difference after selecting the corresponding characteristic information weight group of load to be multiplied with preset critical
Load of the lotus as each window.
In embodiments of the present invention, according to the power of the power signal of each window and corresponding each candidate load
Signal determines the characteristic information of the corresponding each candidate load of each window, including：Edge feature information, trend feature letter
Breath, temporal characteristics information, frequecy characteristic information and sequence signature information, then by these characteristic information composition characteristic information arrays
X.Wherein, the power signal of each candidate load is stored in the database being pre-designed.
Edge feature information XedgeBy edge type quantity N' in detection windowedgeWith the edge type quantity of candidate load
NedgeIt is divided by obtain.
Trend feature information, including increase wave crest, decline wave crest, pulse, fluctuation, quickly change, being gradually reduced and smoothly,
Pass through its slope of windows detecting.Trend feature information XtrendBy trend number of types N' in detection windowtrendBecome with candidate load
Gesture number of types NtrendIt is divided by obtain.
Temporal characteristics information refers to by the opening time area of the time interval of each window and corresponding each candidate load
Between be compared, determine the temporal characteristics information of the corresponding each candidate load of each window；Wherein, if the time interval of window
In the opening time section of corresponding each candidate load, then temporal characteristics information is 1, conversely, temporal characteristics information is 0.
A period for having unlatching per sample load according to candidate window, for example, electric cooker can be 6:00-9:00、11:00-14:
00、16：00-20:00 these three periods used frequent.If candidate window is within the period of corresponding load, XtimeFor
1, it is otherwise 0.
Frequecy characteristic information XrateThe quantity N' repeated by edge type in detection windowrateWith candidate load trend type
Quantity NrateIt is divided by obtain.
The ratio for the backward variable quantity and the sequence variables in window that sequence signature use of information 1 subtracts candidate load comes true
It is fixed.There is the electric appliance of fixed sequence program for washing machine, dish-washing machine etc., the method that we use a kind of calibration of sequence herein.For example, washing
Clothing machine has water filling, immersion, laundry, drying Four processes, corresponds to 1,2,3,4, needs to calculate backward variable quantity M=| 1-4 |+|
2-3 |+| 3-2 |+| 4-1 |=8
, then sequence variation amount N in calculation window, if sequence is 2,1,3,4 in window, variable quantity N=| 1-2 |
+ | 2-1 |+| 3-3 |+| 4-4 |=2.Last XorderThe ratio for subtracting M and N for 1.
In embodiments of the present invention, according to characteristic information characteristic information weight corresponding with each candidate's load
Group determines the load of each window.By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information, sequence
Row characteristic information is put into characteristic information array X, and characteristic information array X weights omegas corresponding with each candidate's load are multiplied to obtain
ω TX, corresponding this group of weight of each candidate's load, for different loads, the proportion of weight is different.For example, sequence is special
Reference breath accounted in the fixed type load such as washing machine proportion is larger, frequecy characteristic information repeats to account in type load in hot-water bottle etc.
It is slightly higher to obtain proportion, temporal characteristics information provides suggestion for most of life type load.Characteristic information array X and each candidate load
Corresponding characteristic information weight group calculates the difference with preset critical λ after being multiplied, it is corresponding candidate negative to choose maximum difference
Load of the lotus as each window.
Fig. 3 is the structural schematic diagram according to the load detection device 300 of embodiment of the present invention.As shown in figure 3, of the invention
The cutting load testing system 300 of embodiment includes：Windowing processing module 301, candidate load collection determining module 302, characteristic information
Determining module 303 and window load determine mould 304.Preferably, in the windowing processing module 301, according to preset period of time
To in the bus at the main entrance of the load of acquisition voltage signal and current signal carry out windowing process, and determine each window
Corresponding power signal.
Preferably, wherein the system also includes：
Be filtered module, for in the bus at the main entrance of the load of acquisition voltage signal and current signal into
Row is filtered, and the voltage signal of filtered processing and current signal are converted to voltage digital signal and current digital letter
Number.
Preferably, wherein using model AD1256 24 analog-digital converters to the main entrance of the load of acquisition at
Voltage signal and current signal in bus are filtered.
Preferably, in the candidate load collection determining module 302, according to holding for each corresponding power signal of window
Continuous temporal characteristics determine the candidate load collection of each window, and each candidate's load collection includes at least one candidate load.
Preferably, wherein the system also includes：
Candidate load range determining module is used for before the candidate load collection of each window of determination, according to each window
The power features of corresponding power signal determine the corresponding candidate load range of each window.
Preferably, in the characteristic information determining module 303, according to the power signal of each window and corresponding every
The power signal of a candidate's load determines the characteristic information of the corresponding each candidate load of each window.Preferably, wherein
The characteristic information includes：Edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence are special
Reference ceases.
Preferably, wherein the characteristic information determining module, according to the power signal of each window and corresponding every
The power signal of a candidate's load determines the characteristic information of the corresponding each candidate load of each window, including：
Edge feature information determination unit, for by edge type quantity in each window and corresponding each candidate negative
The edge type quantity of lotus is divided by, and determines the edge feature information of the corresponding each candidate load of each window；
Trend feature information determination unit, for by trend number of types in each window and corresponding each candidate negative
The trend number of types of lotus is divided by, and determines the trend feature information of the corresponding each candidate load of each window；
Temporal characteristics information determination unit, for opening the time interval of each window and corresponding each candidate load
It opens time interval to be compared, determines the temporal characteristics information of the corresponding each candidate load of each window；Wherein, if window
Time interval is in the opening time section of corresponding each candidate load, then temporal characteristics information is 1, conversely, temporal characteristics
Information is 0；
Frequecy characteristic information determination unit, the quantity for repeating the edge type of each window and corresponding each time
It selects the trend number of types of load to be divided by, determines the frequecy characteristic information of the corresponding each candidate load of each window；
Sequence signature information determination unit, the sequence in backward variable quantity and window for subtracting candidate load using 1
The ratio of variable determines the sequence signature information of the corresponding each candidate load of each window.
Preferably, corresponding with each candidate load according to the characteristic information in the window load determining module 304
Feature weight group determines the load of each window.
Preferably, wherein the window load determining module, corresponding with each candidate load according to the characteristic information
Feature weight group determines the load of each window, is specifically used for：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information point
The corresponding characteristic information number array of the candidate load of each of each window is not formed, is calculated the characteristic information array and is waited with each
Difference after selecting the corresponding feature weight group of load to be multiplied with preset critical is chosen the corresponding candidate load of maximum difference and is made
For the load of each window.
The load detection device 300 of the embodiment of the present invention is used for cutting load testing side with an alternative embodiment of the invention
Method 100 is corresponding, and details are not described herein.
The present invention is described by reference to a small amount of embodiment.However, it is known in those skilled in the art, as
Defined by subsidiary Patent right requirement, in addition to the present invention other embodiments disclosed above are equally fallen the present invention's
In range.
Normally, all terms used in the claims are all solved according to them in the common meaning of technical field
It releases, unless in addition clearly being defined wherein.All references " one/described/be somebody's turn to do [device, component etc.] " are all opened ground
It is construed at least one of described device, component etc. example, unless otherwise expressly specified.Any method disclosed herein
Step need not all be run with disclosed accurate sequence, unless explicitly stated otherwise.
Claims (14)
1. a kind of load testing method, which is characterized in that the method includes：
According to preset period of time in the bus at the main entrance of the load of acquisition voltage signal and current signal add
Window processing, and determine the corresponding power signal of each window；
The candidate load collection of each window is determined according to the duration features of the corresponding power signal of each window, each
Candidate load collection includes at least one candidate load；
Each window is determined according to the power signal of the power signal of each window and corresponding each candidate load
The characteristic information of corresponding each candidate load；
The load of each window is determined according to characteristic information feature weight group corresponding with each candidate's load.
2. according to the method described in claim 1, it is characterized in that, the method further includes：
To in the bus at the main entrance of the load of acquisition voltage signal and current signal be filtered, and will through filtering
The voltage signal and current signal of wave processing are converted to voltage digital signal and current digital signal.
3. according to the method described in claim 2, it is characterized in that, using model AD1256 24 analog-digital converters pair
Voltage signal in bus and current signal at the main entrance of the load of acquisition are filtered.
4. according to the method described in claim 1, it is characterized in that, the method further includes：
Before the candidate load collection of each window of determination, determined according to the power features of the corresponding power signal of each window every
The corresponding candidate load range of a window.
5. according to the method described in claim 1, it is characterized in that, the characteristic information includes：Edge feature information, trend are special
Reference breath, temporal characteristics information, frequecy characteristic information and sequence signature information.
6. according to the method described in claim 5, it is characterized in that, the power signal and correspondence according to each window
Each of the power signal of candidate load determine the characteristic information of the corresponding each candidate load of each window, including：
The edge type quantity of edge type quantity and corresponding each candidate load in each window is divided by, is determined each
The edge feature information of the corresponding each candidate load of window；
The trend number of types of trend number of types and corresponding each candidate load in each window is divided by, is determined each
The trend feature information of the corresponding each candidate load of window；
The opening time section of the time interval of each window and corresponding each candidate load is compared, determines each window
The temporal characteristics information of the corresponding each candidate load of mouth；Wherein, if the time interval of window is in corresponding each candidate load
Opening time section in, then temporal characteristics information be 1, conversely, temporal characteristics information be 0；
The quantity that the edge type of each window repeats is divided by with the trend number of types of corresponding each candidate load, is determined
Each frequecy characteristic information of the corresponding each candidate load of window；
The ratio that the sequence variables in the backward variable quantity and window of candidate load are subtracted using 1 determines that each window is corresponding
The sequence signature information of each candidate's load.
7. according to the method described in claim 5, it is characterized in that, described according to the characteristic information and each candidate's load pair
The feature weight group answered determines the load of each window, including：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information group respectively
At the corresponding characteristic information number array of the candidate load of each of each window, calculates the characteristic information array and each candidate is negative
Difference after the corresponding feature weight group multiplication of lotus with preset critical chooses the corresponding candidate load of maximum difference as every
The load of a window.
8. a kind of cutting load testing system, which is characterized in that the system comprises：
Windowing processing module is used for according to preset period of time to the voltage signal in the bus at the main entrance of the load of acquisition
Windowing process is carried out with current signal, and determines the corresponding power signal of each window；
Candidate load collection determining module, it is every for being determined according to the duration features of the corresponding power signal of each window
The candidate load collection of a window, each candidate's load collection include at least one candidate load；
Characteristic information determining module is used for the power of the power signal and corresponding each candidate load according to each window
Signal determines the characteristic information of the corresponding each candidate load of each window；
Window load determining module, it is every for being determined according to characteristic information feature weight group corresponding with each candidate's load
The load of a window.
9. system according to claim 8, which is characterized in that the system also includes：
It is filtered module, the voltage signal and current signal in the bus at the main entrance to the load of acquisition are filtered
Wave processing, and the voltage signal of filtered processing and current signal are converted into voltage digital signal and current digital signal.
10. system according to claim 9, which is characterized in that
The voltage in the bus at the main entrance of the load of acquisition is believed using 24 analog-digital converters of model AD1256
Number and current signal be filtered.
11. system according to claim 8, which is characterized in that the system also includes：
Candidate load range determining module, for before the candidate load collection of each window of determination, being corresponded to according to each window
The power features of power signal determine the corresponding candidate load range of each window.
12. system according to claim 8, which is characterized in that the characteristic information includes：Edge feature information, trend
Characteristic information, temporal characteristics information, frequecy characteristic information and sequence signature information.
13. system according to claim 12, which is characterized in that the characteristic information determining module, according to described each
The power signal of the power signal of window and corresponding each candidate load determines the corresponding each candidate load of each window
Characteristic information, including：
Edge feature information determination unit, for by each window edge type quantity and corresponding each candidate load
Edge type quantity is divided by, and determines the edge feature information of the corresponding each candidate load of each window；
Trend feature information determination unit, for by each window trend number of types and corresponding each candidate load
Trend number of types is divided by, and determines the trend feature information of the corresponding each candidate load of each window；
Temporal characteristics information determination unit, when being used for the unlatching by the time interval of each window and corresponding each candidate load
Between section be compared, determine the temporal characteristics information of the corresponding each candidate load of each window；Wherein, if the time of window
Section is in the opening time section of corresponding each candidate load, then temporal characteristics information is 1, conversely, temporal characteristics information
It is 0；
Frequecy characteristic information determination unit, the quantity and corresponding each candidate for repeating the edge type of each window are negative
The trend number of types of lotus is divided by, and determines the frequecy characteristic information of the corresponding each candidate load of each window；
Sequence signature information determination unit, the sequence variables in backward variable quantity and window for subtracting candidate load using 1
Ratio, determine the sequence signature information of the corresponding each candidate load of each window.
14. system according to claim 12, which is characterized in that the window load determining module, according to the feature
Information feature weight group corresponding with each candidate's load determines the load of each window, is specifically used for：
By edge feature information, trend feature information, temporal characteristics information, frequecy characteristic information and sequence signature information group respectively
At the corresponding characteristic information number array of the candidate load of each of each window, calculates the characteristic information array and each candidate is negative
Difference after the corresponding feature weight group multiplication of lotus with preset critical chooses the corresponding candidate load of maximum difference as every
The load of a window.
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| CN112883545A (en) * | 2021-01-13 | 2021-06-01 | 吉林大学 | Simulation method of power load waveform |
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