CN110458149A - A kind of method and system identifying sinusoidal signal data skew - Google Patents
A kind of method and system identifying sinusoidal signal data skew Download PDFInfo
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- CN110458149A CN110458149A CN201910828544.XA CN201910828544A CN110458149A CN 110458149 A CN110458149 A CN 110458149A CN 201910828544 A CN201910828544 A CN 201910828544A CN 110458149 A CN110458149 A CN 110458149A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
Abstract
The present invention provides a kind of method and system for identifying sinusoidal signal data skew.This method comprises: analog signal is sampled, using full-wave fourier algorithm according to current sampling point and previous cycle institute, and carry out amplitude according to real and imaginary parts and amplitude A be calculated；Amplitude is calculated according to current sampling point and preceding 1/4 cycle sampled point using two o'clock product algorithm, to obtain amplitude B；Calculate the ratio of amplitude A and amplitude B；When ratio is within the scope of default value, determine that current sampling point correlation is consistent, when ratio is not within the scope of default value, determines that current sampling point correlation is inconsistent；The correlation state for counting all sampled points in previous cycle, when determining, nearest 1/4 cycle correlation is all consistent, but in previous cycle the inconsistent sampled point of correlation points be less than points threshold value when, determine data skew.The present invention can quickly identify the continuous analog signal sample data of distortion by the amplitude correlation analysis based on analog quantity fundamental wave between algorithms of different.
Description
Technical field
The present invention relates to the methods of sine wave signal data skew, belong to digital processing field, can use electrical
Equal engineering fields.
Background technique
Sine wave signal utilizes extensively in many systems, such as our alternating currents that use are exactly the sine of a 50Hz
Wave.For this kind of sine wave signal, need to carry out data sampling when carrying out computer disposal.In true physical system
In, waveform may be caused to be distorted due to external disturbance, there are several milliseconds so that output signal is compared with standard sine signal
Data deviate, be no longer the sine wave of a standard；May also data sampling mistake or error of transmission in sampling process,
The sinusoidal signal for there are several data points to deviate standard is caused to form data skew.It must be to such number in computer processing procedure
According to distortion but primal system does not have the case where failure to be identified, if the shape of incorrect identification wrong reaction present physical system
State eventually leads to serious influence so as to cause the error control to the physical system.Based on this, it is necessary to the sinusoidal wave
The distortion of signal is identified.Complete cycle Fourier transform, half cycle Fourier transform, half-cycle integration etc. are the main places of such current signal
Reason method；The amplitude of signal can be sought by these methods, but the abnormal of sinusoidal signal can not be individually identified in such algorithm
Become.
Summary of the invention
The technical problem to be solved by the present invention is to provide the sampling of sinusoidal signal that a kind of recognition efficiency is high and identification precision is high
Data skew recognition methods and system.
In order to solve the above technical problems, sampling of sinusoidal signal data skew recognition methods provided by the invention, the method
Include:
This method can quickly identify distortion based on the amplitude correlation analysis for being tested sinusoidal signal fundamental wave between algorithms of different
Tested sampling of sinusoidal signal data and alert.It is sampled according to fixed intervals, passes through discrete complete cycle Fourier transform meter first
It calculates the real and imaginary parts of fundamental phasors and calculates amplitude A, calculate amplitude B followed by two o'clock product algorithm, it is then right
The fundamental voltage amplitude that two kinds of algorithms of different are calculated is compared, and carries out correlation judgement, if the fundamental wave width that two kinds of algorithms calculate
Correlativity between value is destroyed, and thinks that tested sampling of sinusoidal signal data are distorted.This programme, which can detecte out, to be tested
Sinusoidal signal every cycle sample values distortion, can be in electric system (such as measure and control device, dynamic recording device, network number
According to analyzer etc.) and other sinusoidal signal processing equipments in use.
The method includes the steps of:
Sampling: in equipment, according to the every cycle N point in fixed sample interval (N is not less than 40) to tested sinusoidal signal (signal frequency
Rate is f) to be sampled, and obtains the discrete sampling sequence x of each signalk。
Waveform recognition is carried out to the data of sampling, each sampled point as the step 1 executes primary, the specific steps are as follows:
Using full-wave fourier algorithm according to current sampling point and all sampled points of previous cycle calculate phasors real part and
Imaginary part, and amplitude A is calculated according to real and imaginary parts；The formula specifically used can be such that
Real part:
Imaginary part:
Amplitude:
Using two o'clock product algorithm according to calculating sampled point and 1/4 cycle sampled point (sampled point before namely 4/N) before
Calculate amplitude B；Specific formula for calculation:
Wherein xkFor current sample values, xk-N/4For sampling point value before 4/N.
It is otherwise exited according to the frequency that sampled value calculates channel if frequency between 0.95~1.05f, continues to execute
Correlation criterion；
If the fundamental voltage amplitude B that two o'clock product algorithm calculates is small divided by the ratio for the fundamental voltage amplitude B that full-wave fourier algorithm calculates
In 0.9 or being greater than 1.1, then it is inconsistent to be denoted as the correlation, and it is consistent to be otherwise denoted as correlation.
Statistics is when the phase in previous cycle between each sampled point two o'clock product algorithm and the fundamental phasors of full-wave fourier algorithm
Close implementations.If all the points correlation is all consistent, waveform is completely normal；If nearest 1/4 cycle (namely total N/4 point)
Correlation is all consistent, but the inconsistent points of correlation are greater than 0 in a cycle, but are less than measured signal signal period
20% (namely 0.2N sampled point), then it is assumed that between the fundamental phasors of nearest two o'clock product algorithm and full-wave fourier algorithm
Correlativity be destroyed, be denoted as data skew, provide alarm and record related data；If correlation is inconsistent in a cycle
Point be greater than measured signal signal period 20% (namely 0.2N sampled point), then it is assumed that system may have occurred disturb or
Failure.
Detailed description of the invention
Fig. 1 is the flow chart of the method for the identification sinusoidal signal data skew that first embodiment of the invention provides；
Fig. 2 is the flow chart of the method for the identification sinusoidal signal data skew that second embodiment of the invention provides；
Fig. 3 is the structural schematic diagram of the system for the identification sinusoidal signal data skew that third embodiment of the invention provides；
| The system for identifying sinusoidal signal data skew | 100 | Sampling module | 10 |
| Amplitude computing module | 11 | Condition judgment module | 12 |
| Correlation judgment module | 13 | Distort determination module | 14 |
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Embodiment one
Referring to Fig. 1, be the flow chart of the method for the identification sinusoidal signal data skew that first embodiment of the invention provides,
Comprising steps of
Step S10, according to the default sampling interval, the sampling number of every cycle predetermined number adopts continuous analog signal
Sample, to obtain the discrete sampling sequence of each signal；
Wherein, the predetermined number is not less than 40, specifically, the numerical values recited of the predetermined number can be according to user's need
It asks and is independently configured, which is fixed sample interval；
Step S20, using full-wave fourier algorithm, according to current sampling point and all sampled points of previous cycle calculate phasors
Real and imaginary parts, and amplitude calculating is carried out according to the real part and the imaginary part, to obtain amplitude A；
Step S30 calculates amplitude according to current sampling point and preceding 1/4 cycle sampled point using two o'clock product algorithm, with
To amplitude B；
Step S40, the frequency in channel is calculated according to sampled value, and judges whether the frequency meets correlation and judge item
Part；
Wherein, whether the correlation Rule of judgment is to judge the frequency within base frequency positive and negative 5%；
When step S40, which determines the frequency, does not meet the correlation Rule of judgment, stop the sinusoidal letter of the identification
The method of number distortion；
When step S40, which determines the frequency, meets the correlation Rule of judgment, step S50 is executed；
Step S50 calculates the ratio of the amplitude A Yu the amplitude B；
Step S60 then determines that the current sampling point correlation is consistent when the ratio is within the scope of default value,
When the ratio is not within the scope of the default value, then determine that the current sampling point correlation is inconsistent；
Wherein, the default value range is 0.9 to 1.1；
Step S70 counts the correlation state of all sampled points in the previous cycle, and works as and determine nearest 1/4 week
Wave correlation is all consistent, but the points of the inconsistent sampled point of correlation are not 0 but are less than points threshold value in the previous cycle
When, determine data skew；
In the present embodiment, by the amplitude correlation analysis based on analog quantity fundamental wave between algorithms of different, can quickly it identify
The continuous analog signal sample data of distortion.It is sampled according to fixed intervals, base is calculated by the first preset algorithm first
The real and imaginary parts of wave phasor simultaneously calculate amplitude A, then calculate amplitude B by the second preset algorithm, then not to two kinds
It is compared with the fundamental voltage amplitude that algorithm calculates, carries out correlation judgement, if between the fundamental voltage amplitude that two kinds of algorithms calculate
Correlativity be destroyed, think that continuous analog signal sample data is distorted, so effectively raise data skew knowledge
Other recognition efficiency and identification precision.The embodiment of the present invention can detecte out every cycle sample values distortion, can be in electricity
It is used in Force system dynamic recording device, network data analyzer and protective relaying device.
Embodiment two
Referring to Fig. 2, be the flow chart of the method for the identification sinusoidal signal data skew that second embodiment of the invention provides,
If measured signal base frequency is 50Hz (period 20ms), comprising steps of
Step S11, according to the default sampling interval, the sampling number of every cycle predetermined number adopts continuous analog signal
Sample, to obtain the discrete sampling sequence of each signal；
Step S21, using full-wave fourier algorithm, according to current sampling point and all sampled points of previous cycle calculate phasors
Real and imaginary parts, and amplitude calculating is carried out according to the real part and the imaginary part, to obtain amplitude A；
Step S31 calculates amplitude according to current sampling point and preceding 1/4 cycle sampled point using two o'clock product algorithm, with
To amplitude B；
Step S41, the frequency in channel is calculated according to sampled value, and judges whether the frequency meets correlation and judge item
Part；
When determining the frequency and meeting the correlation Rule of judgment, step S51 is executed；
Step S51 calculates the ratio of the amplitude A Yu the amplitude B；
Step S61 then determines that the current sampling point correlation is consistent when the ratio is within the scope of default value,
When the ratio is not within the scope of the default value, then determine that the current sampling point correlation is inconsistent；
Step S71 counts the correlation state of all sampled points in the previous cycle, and works as and determine nearest 1/4 week
Wave correlation is all consistent, but the points of the inconsistent sampled point of correlation are not 0 but are less than points threshold value in the previous cycle
When, determine data skew；
Step S81 provides alarm and records related data；
Wherein, it can be alerted by the way of the alarm of audio alert, image alarm or wireless signal in the step；
Step S91 determines the sine when the correlation for determining all sampled points in the previous cycle is all consistent
Signal is normal, undistorted；
Wherein, when the correlation for determining all sampled points is all consistent, then determine for the continuous analog signal
Data skew recognition result is normal；
Preferably, in the present embodiment, when the points for determining the sampled point that correlation is inconsistent in the previous cycle are big
In count threshold value when, determine that the Distortion recognition for the continuous analog signal is interfered or failure；
Wherein, the points threshold value is 4ms, i.e. 4*N/20 sampled point, N is in one cycle of the continuous analog signal
The total number of sampled point, it is preferred that in the step, N 40；
Specifically, this method is based on the amplitude correlation for being tested sinusoidal signal fundamental wave between algorithms of different in the present embodiment
Analysis, can quickly identify the tested sampling of sinusoidal signal data of distortion and alert.It is sampled according to fixed intervals, is passed through first
Discrete complete cycle Fourier transform calculates the real and imaginary parts of fundamental phasors and calculates amplitude A, followed by two o'clock product algorithm
Amplitude B is calculated, the fundamental voltage amplitude then calculated two kinds of algorithms of different is compared, correlation judgement is carried out, if two
The correlativity between fundamental voltage amplitude that kind algorithm calculates is destroyed, and thinks that tested sampling of sinusoidal signal data are distorted.This
Scheme can detecte out the every cycle sample values distortion of tested sinusoidal signal, can be (such as measure and control device, dynamic in electric system
State recording device, network data analyzer etc.) and other sinusoidal signal processing equipments in use.
The method includes the steps of:
Sampling: in equipment, according to the every cycle N point in fixed sample interval (N is not less than 40) to tested sinusoidal signal (signal frequency
Rate is f) to be sampled, and obtains the discrete sampling sequence x of each signalk。
Waveform recognition is carried out to the data of sampling, each sampled point as the step 1 executes primary, the specific steps are as follows:
Using full-wave fourier algorithm according to current sampling point and all sampled points of previous cycle calculate phasors real part and
Imaginary part, and amplitude A is calculated according to real and imaginary parts；The formula specifically used can be such that
Real part:
Imaginary part:
Amplitude:
Sampled point and the before width of 1/4 cycle sampled point (sampled point before namely 4/N) are calculated using two o'clock product algorithm
Value B；Specific formula for calculation:
Wherein xkFor current sample values, xk-N/4For sampling point value before 4/N.
It is otherwise exited according to the frequency that sampled value calculates channel if frequency between 0.95~10.5f, continues to execute
Correlation criterion；
If the fundamental voltage amplitude B that two o'clock product algorithm calculates is small divided by the ratio for the fundamental voltage amplitude B that full-wave fourier algorithm calculates
In 0.9 or being greater than 1.1, then it is inconsistent to be denoted as the correlation, and it is consistent to be otherwise denoted as correlation.
Statistics is when the phase in previous cycle between each sampled point two o'clock product algorithm and the fundamental phasors of full-wave fourier algorithm
Close implementations.If all the points correlation is all consistent, waveform is completely normal；If nearest 1/4 cycle (namely total N/4 point)
Correlation is all consistent, but the inconsistent points of correlation are greater than 0 in a cycle, but are no more than 0.2 cycle (namely 4*
N/20 sampled point), then it is assumed that the correlativity between the fundamental phasors of nearest two o'clock product algorithm and full-wave fourier algorithm
It is destroyed, is denoted as data skew, provide alarm and record related data；If the inconsistent point of correlation is greater than 0.2 in a cycle
A cycle (namely 4*N/20 sampled point), then it is assumed that system may have occurred disturbance or failure.
In the present embodiment, by the amplitude correlation analysis based on analog quantity fundamental wave between algorithms of different, can quickly it identify
The continuous analog signal sample data of distortion.It is sampled according to power frequency, fundamental wave phase is calculated by the first preset algorithm first
The real and imaginary parts of amount simultaneously calculate amplitude A, then calculate amplitude B by the second preset algorithm, then to two kinds of different calculations
The fundamental voltage amplitude that method is calculated is compared, and carries out correlation judgement, if the phase between the fundamental voltage amplitude that two kinds of algorithms calculate
Pass relationship is destroyed, and thinks that continuous analog signal sample data is distorted, and then effectively raises data skew identification
Recognition efficiency and identification precision.The embodiment of the present invention can detecte out every cycle sample values distortion, can be in power train
It is used in system dynamic recording device, network data analyzer and protective relaying device.
Embodiment three
Referring to Fig. 3, being the structure of the system 100 for the identification sinusoidal signal data skew that third embodiment of the invention provides
Schematic diagram, comprising: sampling module 10, amplitude computing module 11, condition judgment module 12, correlation judgment module 13 and distortion are sentenced
Cover half block 14, in which:
Sampling module 10, for the sampling number according to every cycle predetermined number of default sampling interval to continuous analog signal
It is sampled, to obtain the discrete sampling sequence of each signal, wherein the predetermined number is greater than 40, specifically, described default
Several numerical values reciteds can be independently configured according to user demand, which is power frequency fixed sample interval.
Amplitude computing module 11, for calculate current sampling point and all sampled point phasors of previous cycle real part and void
Portion, and amplitude calculating is carried out according to the real part and the imaginary part, to obtain amplitude A；Calculate the current sampling point and preceding 1/4
The amplitude of cycle sampled point, to obtain amplitude B, wherein calculate the current sampling point and all sampled point phases of previous cycle
Algorithm used by the real and imaginary parts of amount is full-wave fourier algorithm, calculates the current sampling point and samples with 1/4 cycle before
Algorithm used by the amplitude of point is two o'clock product algorithm.
Condition judgment module 12 for calculating the frequency in channel according to sampled value, and judges whether the frequency meets phase
Closing property Rule of judgment；
Preferably, the condition judgment module 12 is also used to: not meeting the correlation judgement when determining the frequency
When condition, stop the method for the identification sinusoidal signal data skew.
Correlation judgment module 13, for calculating institute when determining the frequency and meeting the correlation Rule of judgment
State the ratio of amplitude A Yu the amplitude B；When the ratio is within the scope of default value, then the current sampling point phase is determined
Closing property is consistent, when the ratio is not within the scope of the default value, then determines that the current sampling point correlation is inconsistent.
Distort determination module 14, for counting the correlation state of all sampled points in the previous cycle, and when judgement
It is all consistent to nearest 1/4 cycle correlation, but the points of the inconsistent sampled point of correlation are not 0 but small in the previous cycle
In count threshold value when, determine data skew.
Further, the distortion determination module 14 is also used to: being provided alarm and is recorded related data.
Further, in the present embodiment, the distortion determination module 14 is also used to: when determining in the previous cycle
When the correlation of all sampled points is all consistent, determine that the sinusoidal signal is normal, it is undistorted；When determining in the previous cycle
When the points of the inconsistent sampled point of correlation are greater than points threshold value, determine that the Distortion recognition for the continuous analog signal is sent out
Interference or failure are given birth to.
In the present embodiment, by the amplitude correlation analysis based on analog quantity fundamental wave between algorithms of different, can quickly it identify
The continuous analog signal sample data of distortion.It is sampled according to power frequency, fundamental wave phase is calculated by the first preset algorithm first
The real and imaginary parts of amount simultaneously calculate amplitude A, then calculate amplitude B by the second preset algorithm, then to two kinds of different calculations
The fundamental voltage amplitude that method is calculated is compared, and carries out correlation judgement, if the phase between the fundamental voltage amplitude that two kinds of algorithms calculate
Pass relationship is destroyed, and thinks that continuous analog signal sample data is distorted, and then effectively raises data skew identification
Recognition efficiency and identification precision.The embodiment of the present invention can detecte out every cycle sample values distortion, can be in power train
It is used in system dynamic recording device, network data analyzer and protective relaying device.
The present embodiment also provides a kind of device for identifying sinusoidal signal data skew, including storage equipment and processor,
The storage equipment is for storing computer program, and the processor runs the computer program so that the sinusoidal letter of the identification
The method that the dress of number distortion executes above-mentioned identification sinusoidal signal data skew.
The present embodiment additionally provides a kind of storage medium, is stored thereon in the dress of above-mentioned identification sinusoidal signal data skew
Used computer program, the program when being executed, include the following steps:
According to the default sampling interval, the sampling number of every cycle predetermined number samples continuous analog signal, to obtain
The discrete sampling sequence of each signal；
Calculate current sampling point and all sampled point phasors of previous cycle real and imaginary parts, and according to the real part and
The imaginary part carries out amplitude calculating, to obtain amplitude A；
The amplitude of the current sampling point Yu preceding 1/4 cycle sampled point is calculated, to obtain amplitude B；
The frequency in channel is calculated according to sampled value, and judges whether the frequency meets correlation Rule of judgment；
When determining the frequency and meeting the correlation Rule of judgment, the ratio of the amplitude A and the amplitude B are calculated
Value；
When the ratio is within the scope of default value, then determine that the current sampling point correlation is consistent, when the ratio
When value is not within the scope of the default value, then determine that the current sampling point correlation is inconsistent；
The correlation state of all sampled points in the previous cycle is counted, and works as and determines nearest 1/4 cycle correlation
All unanimously, when but the points of the inconsistent sampled point of correlation are not 0 but are less than points threshold value in the previous cycle, resulting number
According to distortion.The storage medium, such as: ROM/RAM, magnetic disk, CD.
It is apparent to those skilled in the art that for convenience and simplicity of description, only with above-mentioned each function
The division progress of unit, module can according to need and for example, in practical application by above-mentioned function distribution by different function
Energy unit or module are completed, i.e., the internal structure of storage device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit,
It can be each unit to physically exist alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (10)
1. a kind of method for identifying sinusoidal signal data skew, which is characterized in that the described method includes:
According to the default sampling interval, the sampling number of every cycle predetermined number samples continuous analog signal, to obtain each letter
Number discrete sampling sequence；
Using full-wave fourier algorithm, according to current sampling point and all sampled points of previous cycle calculate the real part and void of phasors
Portion, and amplitude calculating is carried out according to the real part and the imaginary part, to obtain amplitude A；
Using two o'clock product algorithm, amplitude is calculated according to current sampling point and preceding 1/4 cycle sampled point, to obtain amplitude B；
The frequency in channel is calculated according to sampled value, and judges whether the frequency meets correlation Rule of judgment；
When determining the frequency and meeting the correlation Rule of judgment, the ratio of the amplitude A Yu the amplitude B are calculated；
When the ratio is within the scope of default value, then determine that the current sampling point correlation is consistent, when the ratio not
When within the scope of the default value, then determine that the current sampling point correlation is inconsistent；
The correlation state of all sampled points in the previous cycle is counted, and works as and determines nearest 1/4 cycle correlation all one
Cause, but in the previous cycle points of the inconsistent sampled point of correlation be not 0 but be less than points threshold value when, determine data it is abnormal
Become.
2. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that the correlation judgement
Whether condition is to judge the frequency within base frequency positive and negative 5%.
3. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that the method is also wrapped
It includes:
When determining the frequency and not meeting the correlation Rule of judgment, stop the identification sinusoidal signal data skew
Method.
4. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that the judgement data are abnormal
It is described after the step of change further include:
It provides alarm and records related data.
5. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that described further include:
When the correlation for determining all sampled points in the previous cycle is all consistent, determine that the sinusoidal signal is normal, nothing
Distortion.
6. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that calculating is described currently to adopt
Sampling point is two o'clock product algorithm with algorithm used by the amplitude of 1/4 cycle sampled point before.
7. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that calculating is described currently to adopt
Sampling point and all sampled point phasors of previous cycle real and imaginary parts used by algorithm be full-wave fourier algorithm.
8. the method for identification sinusoidal signal data skew according to claim 1, which is characterized in that the predetermined number is not
Less than 40, the default value range is 0.9 to 1.1.
9. a kind of system for identifying sinusoidal signal data skew, which is characterized in that the system comprises:
Sampling module, for being adopted according to the sampling number of every cycle predetermined number of default sampling interval to continuous analog signal
Sample, to obtain the discrete sampling sequence of each signal；
Amplitude computing module, for calculate current sampling point and all sampled point phasors of previous cycle real and imaginary parts, and
Amplitude calculating is carried out according to the real part and the imaginary part, to obtain amplitude A；Calculate the current sampling point and preceding 1/4 cycle
The amplitude of sampled point, to obtain amplitude B；
Condition judgment module for calculating the frequency in channel according to sampled value, and judges whether the frequency meets correlation and sentence
Broken strip part；
Correlation judgment module, for calculating the amplitude A when determining the frequency and meeting the correlation Rule of judgment
With the ratio of the amplitude B；When the ratio is within the scope of default value, then the current sampling point Relativity is determined
It causes, when the ratio is not within the scope of the default value, then determines that the current sampling point correlation is inconsistent；
Distort determination module, for counting the correlation state of all sampled points in the previous cycle, and it is nearest when determining
1/4 cycle correlation is all consistent, but the points of the inconsistent sampled point of correlation are not 0 but are less than points in the previous cycle
When threshold value, data skew is determined.
10. the system of identification sinusoidal signal data skew according to claim 9, which is characterized in that the condition judgement
Module is also used to:
When determining the frequency and not meeting the correlation Rule of judgment, stop the identification sinusoidal signal data skew
Method.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111289797A (en) * | 2020-02-17 | 2020-06-16 | 华北电力大学 | Alternating current signal single interference data identification method and system |
| CN112098719A (en) * | 2020-08-06 | 2020-12-18 | 许昌许继软件技术有限公司 | Frequency-varying sine wave signal Fourier calculation method and relay protection device |
| CN114217119A (en) * | 2021-12-07 | 2022-03-22 | 广西电网有限责任公司电力科学研究院 | Data distortion identification method and system based on sampling values at different moments |
-
2019
- 2019-09-03 CN CN201910828544.XA patent/CN110458149A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111289797A (en) * | 2020-02-17 | 2020-06-16 | 华北电力大学 | Alternating current signal single interference data identification method and system |
| CN112098719A (en) * | 2020-08-06 | 2020-12-18 | 许昌许继软件技术有限公司 | Frequency-varying sine wave signal Fourier calculation method and relay protection device |
| CN114217119A (en) * | 2021-12-07 | 2022-03-22 | 广西电网有限责任公司电力科学研究院 | Data distortion identification method and system based on sampling values at different moments |
| CN114217119B (en) * | 2021-12-07 | 2023-12-19 | 广西电网有限责任公司电力科学研究院 | Data distortion identification method and system based on sampling values at different moments |
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Application publication date: 20191115 |