CN105675956B - A kind of Voltage flicker detection based on windowed interpolation Short Time Fourier Transform - Google Patents
A kind of Voltage flicker detection based on windowed interpolation Short Time Fourier Transform Download PDFInfo
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Abstract
The invention discloses a kind of flickering recognition methods based on windowed interpolation Short Time Fourier Transform, this method mainly comprises the following steps：First, discrete sampling is carried out to voltage signal, obtains N point sampling sequence U (n)；Second, sample sequence U (n) is weighted using Blacknam Harris's triangle convolution window and carries out Short Time Fourier Transform, obtains the amplitude matrix P (i, j) of signal；3rd, using polynomial fitting method, the amplitude expression y of matrix P (i, j) each column is obtainedj(k)；4th, according to expression formula yj(k), voltage signal envelope frequency f is calculatedm(j)；5th, according to envelope range value ymax(j) with envelope frequency fm(j), characteristic quantity V is extracted1、V2、V3、V4、V5、V6；6th, using characteristic quantity V1、V2、V3、V4、V5, calculate signal flash variable coefficient T, and and V6Corresponding threshold comparison, provides testing result.This method extracts characteristic quantity, calculating is simple, extraction characteristic quantity is few and discrimination is high, can meet the requirement that electric system flickering quickly detects based on windowed interpolation Short Time Fourier Transform.
Description
Technical Field
The invention belongs to the technical field of power system fault analysis, and relates to a voltage flicker detection method based on windowed interpolation short-time Fourier transform.
Background
With the continuous development of economy in China, the power demand is continuously increased, and a large-scale power plant and a long-distance and large-scale power transmission network are accelerated to build, so that a power grid system is easily influenced by disturbance; in addition, due to the use of various power electronic equipment and impact and nonlinear loads, a series of problems such as flicker, voltage sag, voltage fluctuation, harmonic waves, voltage gaps, pulse and oscillation transient interference and the like occur, and the power quality and the safety and the stability of the operation of a power grid are directly influenced. Flicker is the visual response of human eyes to unstable light illumination caused by voltage fluctuation, is an important parameter of electric energy quality, and is an important reason for causing failure and invalidation of electrical equipment. With the increase of nonlinear and impact loads of a power system, the voltage fluctuation and flicker of a power grid become more and more serious, and serious influence is caused on industrial production and social life. In 1994, the International Electrotechnical Commission (IEC) listed voltage fluctuation and flicker as important indicators for measuring the quality of electric energy according to the operation condition of modern power supply and utilization systems. China formulated GB12326-2000 allowable fluctuation and flicker of electric energy quality and voltage in 2000. In recent years, voltage fluctuation and flicker detection and identification methods are becoming popular for domestic and foreign research. However, since the IEC only gives a detection principle block diagram for measuring the flicker strength and weakness values and does not explicitly describe the implementation of the block diagram, the block diagram is used by various scholars to implement the short-time flicker value P st Long time flash value P lt The calculation methods of (2) are different. However, the existing flicker detection and identification method has the defects of complex calculation process, large calculation amount, low identification rate and the like, and the voltage flicker detection requirement is difficult to meet.
The method provided by the invention overcomes the defects of complex calculation process, large calculation amount and low recognition rate of the traditional flicker detection method. The time-frequency analysis result of the voltage signal can be quickly obtained by adopting windowed short-time Fourier transform, the envelope amplitude and the envelope frequency are obtained by utilizing an interpolation method according to a signal time-frequency matrix, then the characteristic quantity is extracted, the flicker coefficient is calculated, and the flicker coefficient is compared with a threshold value, so that the detection result can be obtained. The method has the advantages of simple calculation process, less extracted characteristic quantity and high recognition rate, and provides an effective way for the flicker detection of the power system.
Disclosure of Invention
The voltage flicker detection method based on windowed interpolation short-time Fourier transform overcomes the defects of complex calculation process, large calculation amount and low recognition rate of the traditional flicker detection method. The time-frequency analysis result of the voltage signal can be quickly obtained by adopting windowed short-time Fourier transform, the envelope amplitude and the envelope frequency are obtained by utilizing an interpolation method according to a signal time-frequency matrix, then the characteristic quantity is extracted, the flicker coefficient is calculated, and the flicker coefficient is compared with a threshold value, so that the detection result can be obtained. The method has the advantages of simple calculation process, less extracted characteristic quantity and high recognition rate.
In order to solve the technical problems, the solution provided by the invention is as follows: firstly, discrete sampling is carried out on a voltage signal to obtain an N-point sampling sequence U (N); secondly, weighting a sampling sequence U (n) by using a Blackman Harris-triangular convolution window and carrying out short-time Fourier transform to obtain an amplitude matrix P (i, j) of the signal; thirdly, a polynomial fitting method is applied to solve the amplitude expression y of each column of the matrix P (i, j) j (k) (ii) a Fourth, according to the expression y j (k) Calculating the envelope frequency f of the voltage signal m (j) (ii) a Fifthly, according to the envelope amplitude y max (j) With envelope frequency f m (j) Extracting the characteristic quantity V 1 、V 2 、V 3 、V 4 、V 5 、V 6 (ii) a Sixth, the characteristic quantity V is applied 1 、V 2 、V 3 、V 4 、V 5 Calculating the flicker coefficient T of the signal, and comparing with V 6 And comparing corresponding threshold values to give a detection result. The method is based on windowed interpolation short-time Fourier transform, extracts the characteristic quantity, is simple in calculation, less in extracted characteristic quantity and high in recognition rate, and can meet the requirement of rapid flicker detection of the power system.
The technical scheme of the invention is as follows:
a voltage flicker detection method based on windowed interpolation short-time Fourier transform is characterized in that: weighting the sampled voltage signals by adopting a Blackman Harris-triangular convolution window, then carrying out short-time Fourier transform, calculating an amplitude matrix by utilizing a short-time Fourier transform result, and calculating voltage envelope frequency and amplitude by adopting a polynomial fitting method so as to obtain a flicker detection result, wherein the method specifically comprises the following steps of:
step one, sampling frequency f is used for time domain continuous voltage signal u (t) s Sampling to obtain an N-point discrete sampling sequence U (N), wherein N =0,1,2, \ 8230, N-1;
step two, weighting the discrete sampling sequence U (n) of the voltage signal by using a Blackman Harris-triangular convolution window w (n) with the length of L and the movement interval of D, and then carrying out short-time Fourier transform to obtain a short-time Fourier transform result matrix F of the signal STFT (i, j) calculating a signal amplitude matrix P (i, j);
step three, applying a polynomial fitting method, and assuming that the amplitude expression of each column is as follows:where y represents the amplitude, k is the spectral line position,representing the polynomial coefficients, X representing the number of terms of the fitting polynomial, from the amplitude matrix P (i, j) of the signal by least squares
Step four, according to the amplitude expression of each column, an extremum method is applied to obtain the envelope amplitude, namely the maximum value y of each column max (j) And the corresponding spectral line, denoted as k max (j) According to the formula f m (j)＝k max f s L, calculating the envelope frequency f of the signal m (j)；
Step five, according to the envelope amplitude y max (j) And an envelope frequency f m (j) Extracting the average value V of the envelope amplitude of the characteristic quantity 1 Number of envelope large-amplitude sampling points V 2 Number of envelope small-amplitude sampling points V 3 Envelope ofNumber of small amplitude sampling points V 4 And envelope fluctuation characteristic quantity V 5 And calculating a characteristic quantity V of the flicker duration 6 ；
Step six, applying the characteristic quantity V 1 、V 2 、V 3 、V 4 、V 5 Calculating the flicker coefficient T of the signal and corresponding flicker duration characteristic quantity V 6 Reference signal flicker threshold value T of s A comparison is made, wherein the threshold value T s The result is the sine signal calculation result with the frequency of 50Hz when no disturbance exists; if T is more than or equal to T s If the signal is judged to be flickering, if T<T s If so, the signal is judged to be not flickering.
In the second step, the Blackman Harris-triangular convolution window w (n) with the length L is obtained by convolution of a Blackman Harris window and a triangular window with the lengths L/2 respectively, and the formula is as follows: w (n) = w bh (n)*w tri (n) wherein w bh (n)、w tri (n) are time domain expressions of a discrete Blackman Harris window and a discrete triangular window, respectively.
In the method, the characteristic quantity V is set in the fifth step 1 The calculation formula of (c) is:wherein(symbol)Represents rounding down; characteristic quantity V 2 The statistical criteria are: y is max (j)>, 1.1H; characteristic quantity V 3 The statistical criteria are: y is max (j)&0.9H; characteristic quantity V 4 The statistical criteria are: y is max (j)&0.2H; the standard value H is an envelope amplitude average value result calculated by short-time Fourier transform of a sinusoidal signal with the frequency of 50Hz under the condition of no disturbance; characteristic quantity V 5 The calculation formula is as follows:
in the method, the characteristic quantity of the flicker duration in the step fiveWherein I 1 、I 2 The calculation formulas of the high-frequency amplitude total parameter are as follows:whereinl is an integer, and l is not less than 10.
In the sixth step, the calculation formula of the flicker coefficient T is:in the formula, c 1 、c 2 、c 3 、c 4 、c 5 Respectively being characteristic quantities V 1 、V 2 、V 3 、V 4 、V 5 The weight coefficient of (a); c. C 1 、c 2 、c 3 、c 4 、c 5 Given by the training of an overrun learning machine, and trained by a large amount of flicker data to obtain c 1 Value range of [0.4,0.9]，c 2 Value range of [0.3,0.8]，c 3 Value range of [0.2,0.5 ]]，c 4 Value range of [0.4,0.6]，c 5 The value range is [0.6,0.8 ]]。
The voltage flicker detection method based on windowed interpolation short-time Fourier transform provided by the invention overcomes the defects of complex calculation process, large calculation amount and low identification rate of the traditional flicker detection method. The time-frequency analysis result of the voltage signal can be quickly obtained by adopting windowed short-time Fourier transform, the envelope amplitude and the envelope frequency are obtained by utilizing an interpolation method according to a signal time-frequency matrix, then the characteristic quantity is extracted, the flicker coefficient is calculated, and the flicker coefficient is compared with a threshold value, so that the detection result can be obtained. The method has the advantages of simple calculation process, less extracted characteristic quantity and high recognition rate, and provides an effective way for the flicker detection of the power system.
Drawings
FIG. 1 is a schematic block diagram of voltage flicker detection in the present invention.
FIG. 2 is a flowchart of a process for implementing the voltage flicker detection method based on windowed interpolation short-time Fourier transform according to the present invention.
Detailed Description
The invention provides a voltage flicker detection method based on windowed interpolation short-time Fourier transform. The following detailed description is made with reference to the accompanying drawings:
the functional block diagram of flicker detection of the invention is shown in fig. 1, firstly, a time domain voltage signal is processed by short-time Fourier transform to obtain an amplitude matrix of the signal, the voltage envelope frequency and the amplitude are calculated according to the amplitude matrix, and then a characteristic quantity envelope amplitude mean value V is extracted 1 Number of envelope large amplitude sampling points V 2 Envelope small amplitude sampling point number V 3 Number of sampling points V with too small envelope amplitude 4 And envelope fluctuation characteristic quantity V 5 And calculating a characteristic quantity V of the flicker duration 6 Then according to V 1 、V 2 、V 3 、V 4 、V 5 And a weight coefficient c 1 、c 2 、c 3 、c 4 、c 5 Calculating a flicker coefficient T according to V 6 Output threshold value T s Finally by comparing T with T s And giving a flicker detection conclusion.
As shown in fig. 2, a voltage flicker detection method based on windowed interpolation short-time fourier transform has the following process:
first step, with f s Sampling the continuous time domain signals for sampling frequency, wherein the time domain expression of the power grid signals is as follows:
in the formula (I), the compound is shown in the specification,the harmonic order is the highest harmonic order, gamma is the harmonic order, and gamma =1 represents the fundamental wave; a. The γ Is the gamma harmonic amplitude; t is time; f is the frequency of the signal fundamental wave; theta.theta. γ The phase of the gamma-th harmonic. To test the invention, the signal is set to 30s in this example, at 1&And (t is less than or equal to 14s, adding a flicker interference signal of 10Hz, wherein the fundamental wave frequency of other time periods is 50Hz, the fundamental wave amplitude is 220V, the fundamental wave initial phase is 0 degrees, and no harmonic interference exists. According to the Nyquist sampling theorem, the sampling frequency is set to 2000Hz, i.e. the test signal can be expressed as:
discrete sampling is carried out on the signals, and a voltage discrete sequence with the signal length of N =60001 is obtained:
wherein N =0,1,2, \ 8230;, N-1;
secondly, convolving the Blackman Harris window with the length of L/2 and a triangular window to obtain a Blackman Harris-triangular convolution window w (n) with the length of L, wherein the formula is as follows:
w(n)＝w bh (n)*w tri (n) (4)
wherein, the symbol "+" represents convolution operation, wbh (n) and wtri (n) are respectively window functions of a discrete Blackman Harris window and a discrete triangular window;
setting window function movement interval as D, weighting a voltage signal discrete sampling sequence U (n), and applying a short-time Fourier formula to perform short-time Fourier transform, wherein the specific formula is as follows:
wherein tau is an imaginary unit, i =1,2, \ 8230;, L/2, j =1,2, \ 8230;, R, wherein(symbol)Represents rounding down;
the short-time fourier transform matrix FSTFT (i, j) of the voltage signal can be obtained by equation (5), and the magnitude matrix P (i, j) is calculated, which is:
P(i,j)＝|F STFT (i,j)| (6)
in this embodiment, the length L of the blackman harris-triangular convolution window is 256, and the window shift interval D is 48; the resulting short-time fourier transform magnitude matrix P (i, j) has dimensions 128 × 1239, i.e., i =1,2,3, \8230;, 128; j =1,2,3, \ 8230;, 1239;
thirdly, applying a polynomial fitting method, and assuming that in the signal amplitude matrix P (i, j), the amplitude expression of each column is as follows:
wherein y represents the amplitude, k is the spectral line position,representing polynomial coefficients, X representing the number of terms of the fitting polynomial; the polynomial coefficients are then calculated according to a least squares methodThe following formula applies:
in the formula, y tj (k) For the amplitude of j columns i = k rows in P (i, j), the polynomial coefficients can be obtained by solving equation (8)In this embodiment, when X is 7, the precision may meet the requirement, that is, the polynomial coefficient is 7 in this embodiment;
fourthly, solving the envelope amplitude y by applying an extremum method max (j) I.e. the maximum value of the amplitude value of each column, the calculation formula is:
by solving the formula (9), the spectral line corresponding to the amplitude extreme point can be obtained, and the spectral line is substituted into the formula (7) to calculate the envelope amplitude y max (j) Remember y max (j) Corresponding to a spectral line of k max (j) (ii) a Then, according to envelope frequency calculation formula, calculating envelope frequency f of signal m (j) The envelope frequency calculation formula is as follows:
f m (j)＝k max f s /L (10)
fifthly, according to the envelope amplitude y max (j) And an envelope frequency f m (j) Extracting the mean value V of the envelope amplitude of the characteristic quantity 1 Number of envelope large amplitude sampling points V 2 Number of envelope small-amplitude sampling points V 3 Number of sampling points V with too small envelope amplitude 4 And envelope fluctuation characteristic quantity V 5 In which V is 1 The calculation formula of (c) is:
characteristic quantity V 2 The extraction criteria of (a) are:
y max (j)＞1.1H (12)
in the formula, H is a standard value, and H is calculated by a sinusoidal signal with the frequency of 50Hz through the formula (11) under the condition of no disturbance;
characteristic quantity V 3 The extraction criteria of (a) are:
y max (j)＜0.9H (13)
characteristic quantity V 4 The extraction criteria of (a) are:
y max (j)＜0.2H (14)
characteristic quantity V 5 The calculation formula of (2) is as follows:
flicker duration characteristic quantity V 6 The calculation formula of (c) is:
in the formula I 1 、I 2 The lines are respectively corresponding to the maximum value and the second maximum value of the high-frequency amplitude total parameter of the signal, and the calculation formula of the high-frequency amplitude total parameter is as follows:
in the formulal is an integer, and l is not less than 10; in the present embodiment, the characteristic quantity V 1 1506, a characteristic quantity V 2 Is 235, characteristic quantity V 3 Characteristic quantity V of 319 4 To 257, characteristic quantity V 5 2480, characteristic quantity V 5 Is 13.87;
sixth, the characteristic quantity V is applied 1 、V 2 、V 3 、V 4 、V 5 And calculating a signal flicker coefficient T, wherein the formula is as follows:
in the formula, c 1 、c 2 、c 3 、c 4 、c 5 Are respectively a characteristic quantity V 1 、V 2 、V 3 、V 4 、V 5 The weight coefficient of (a); c. C 1 、c 2 、c 3 、c 4 、c 5 Given by the training of an overrun learning machine, and trained by a large amount of flicker data to obtain c 1 Value range of [0.4,0.9]，c 2 Value range of [0.3,0.8 ]]，c 3 Value range of [0.2,0.5 ]]，c 4 Value range of [0.4,0.6]，c 5 The value range is [0.6,0.8 ]](ii) a In this embodiment, the weighting factor c is given by the overrun learning machine 1 、c 2 、c 3 、c 4 、c 5 Respectively as follows: 0.421, 0.359, 0.267, 0.533, 0.685, and 2639.3 obtained by calculating the flicker coefficient;
then according to the flicker duration characteristic quantity V 6 Output threshold value T s Wherein T is s Under the condition of no disturbance, the frequency is 50Hz, and the sampling frequency is f s And with the flicker duration characteristic quantity V 6 Applying the flicker coefficient calculation result of the invention to the sinusoidal signal corresponding to the time length; by contrast, if T is greater than or equal to T s If the signal is judged to be flickering, if T<T s If so, the signal is judged to be not flickering. In the present embodiment, the AND duration feature V 6 Threshold T corresponding to 13.87 s 2400, since T is more than or equal to T s It indicates that the given signal is flickering.
Therefore, the power grid signal flicker detection is completed.
In conclusion, the invention provides a voltage flicker detection method based on windowed interpolation short-time Fourier transform, and overcomes the defects of complex calculation process, large calculation amount and low identification rate of the traditional flicker detection method. The time-frequency analysis result of the voltage signal can be quickly obtained by adopting windowed short-time Fourier transform, the envelope amplitude and the envelope frequency are obtained by utilizing an interpolation method according to a signal time-frequency matrix, then the characteristic quantity is extracted, the flicker coefficient is calculated, and the flicker coefficient is compared with a threshold value, so that the detection result can be obtained. The method is simple in calculation process, less in extracted characteristic quantity and high in recognition rate, and an effective way is provided for flicker detection of the power system.
Claims (5)
1. A voltage flicker detection method based on windowed interpolation short-time Fourier transform is characterized in that: weighting the sampled voltage signals by adopting a Blackman Harris-triangular convolution window, then carrying out short-time Fourier transform, calculating an amplitude matrix by utilizing a short-time Fourier transform result, and calculating voltage envelope frequency and amplitude by adopting a polynomial fitting method so as to obtain a flicker detection result, wherein the method specifically comprises the following steps of:
step one, sampling frequency f is used for time domain continuous voltage signal u (t) s Sampling to obtain an N-point discrete sampling sequence U (N), wherein N =0,1,2, \ 8230, N-1;
step two, weighting a discrete sampling sequence U (n) of the voltage signal by using a Blackman Harris-triangular convolution window w (n) with the length of L and the movement interval of D, and then carrying out short-time Fourier transform to obtain a short-time Fourier transform result matrix F of the signal STFT (i, j) calculating a signal amplitude matrix P (i, j);
step three, applying a polynomial fitting method, and assuming that the amplitude expression of each column is as follows:where y represents the amplitude, k is the spectral line position,representing the coefficients of the polynomial, X representing the number of terms of the fitting polynomial, from the amplitude matrix P (i, j) of the signal, calculated by the least squares method
Step four, according to the amplitude expression of each column, an extremum method is applied to obtain the envelope amplitude, namely the maximum value y of each column max (j) And the corresponding spectral line, denoted as k max (j) According to the formula f m (j)＝k max f s L, calculating the envelope frequency f of the signal m (j)；
Step five, according to the envelope amplitude y max (j) And an envelope frequency f m (j) Extracting the mean value V of the envelope amplitude of the characteristic quantity 1 Number of envelope large amplitude sampling points V 2 Envelope small amplitude sampling point number V 3 Number of sampling points V with too small envelope amplitude 4 And envelope fluctuation characteristic quantity V 5 And calculating a characteristic quantity V of the flicker duration 6 ；
Step six, applying the characteristic quantity V 1 、V 2 、V 3 、V 4 、V 5 Calculating the flicker coefficient T of the signal and corresponding flicker duration characteristic quantity V 6 Reference signal flicker threshold value T of s A comparison is made, wherein the threshold value T s The result is the calculation result of a sine signal with the frequency of 50Hz when no disturbance exists; if T is greater than or equal to T s If the signal is flickering, the signal is judged to be flickering, if T is reached<T s If so, the signal is judged to be not flickering.
2. The method of claim 1, wherein in step two, the Blackman Harris-triangular convolution window w (n) of length L is obtained by convolving Blackman Harris windows of length L/2 with triangular windows, and the formula is: w (n) = w bh (n)*w tri (n) wherein w bh (n)、w tri (n) are window functions of a discrete Blackman Harris window and a discrete triangular window, respectively.
3. The method according to claim 1, characterized in that in step five, the characteristic quantity V 1 The calculation formula of (2) is as follows: wherein the symbol represents a rounding down; characteristic quantity V 2 The statistical criteria are: y is max (j)>, 1.1H; characteristic quantity V 3 The statistical criteria were: y is max (j)<, 0.9H; characteristic quantity V 4 The statistical criteria are: y is max (j)&0.2H; the standard value H is an envelope amplitude mean value result calculated by short-time Fourier transform of a sinusoidal signal with the frequency of 50Hz under the condition of no disturbance; characteristic quantity V 5 The calculation formula is as follows:
4. the method of claim 1, wherein in step five, the characteristic amount of the flicker durationWherein I 1 、I 2 The calculation formulas of the high-frequency amplitude total parameter are as follows:whereinl is an integer, and l is not less than 10.
5. The method according to claim 1, wherein in step six, the flicker coefficient T is calculated by:in the formula, c 1 、c 2 、c 3 、c 4 、c 5 Are respectively a characteristic quantity V 1 、V 2 、V 3 、V 4 、V 5 The weight coefficient of (a); c. C 1 、c 2 、c 3 、c 4 、c 5 Given by the training of an overrun learning machine, and trained by a large amount of flicker data to obtain c 1 Value range of [0.4,0.9]，c 2 Value range of [0.3,0.8 ]]，c 3 Value range of [0.2,0.5 ]]，c 4 Value range of [0.4,0.6 ]]，c 5 The value range is [0.6,0.8 ]]。
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| CN107085134B (en) * | 2017-04-01 | 2019-06-18 | 北京机械设备研究所 | A kind of detection method of voltage flicker |
| CN107271753B (en) * | 2017-07-27 | 2020-06-23 | 华北电力大学 | Voltage flicker detection method and device |
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| CN111044773B (en) * | 2019-10-08 | 2023-06-27 | 国网甘肃省电力公司电力科学研究院 | Accurate detection method for voltage flicker signal based on time-frequency conversion |
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