CN103116064A - Method and device for detecting voltage fluctuation and flicker based on energy operator and spectrum correction - Google Patents

Abstract

The invention discloses a voltage fluctuation and flicker detection method and device based on energy operator and spectrum correction. By using the Teager-Kaiser energy operator to extract the envelope signal of the voltage flicker signal, the operation speed is accelerated and the flicker envelope is overcome. When the network signal is extracted, it is affected by the change of parameters such as signal frequency, waveform, amplitude and sampling data length, so as to realize fast and real-time detection of flicker signals; the Kaiser window function that can freely select the proportion between the main lobe width and side lobe height Perform improved fast Fourier transform spectrum correction analysis on the voltage flicker signal, and accurately obtain the frequency and amplitude components of the voltage flicker signal when the frequency, waveform and amplitude of the flicker signal change too much; the device based on this method includes The signal conditioning unit, the data processing unit and the data storage and display unit; the signal conditioning unit, the data processing unit and the data storage and display unit are connected in sequence; the detection method is convenient for fast and real-time detection and processing of signals, and the device structure is simple and easy to implement.

Description

A kind of voltage fluctuation and flicker detection method and device based on energy operator and Spectrum Correction

Technical field

The present invention relates to a kind of voltage fluctuation and flicker detection method and device based on energy operator and Spectrum Correction.

Background technology

Electric load, especially impact load sharply increase, and electric system has been consisted of serious pollution, cause line voltage unstable, produce voltage fluctuation and flickering, have increased the labile factor of electrical network, have caused for commercial production and social life and have a strong impact on.Voltage flicker is the important parameter of the quality of power supply, is the major reason that causes confession, consumer fault and inefficacy.To carrying out Measurement accuracy for the voltage flicker in, using electricity system, the impact etc. that can be research flickering root, inhibition and elimination voltage fluctuation and flickering provides scientific basis.

The detection of voltage fluctuation and flicker is adopted short time flicker value P both at home and abroad all according to the IEC standard _stWith long-time flickering value P _ltAs the evaluation index of flickering, but only provided the detection theory diagram of weighing the strong and weak value of flickering due to IEC in standard, block diagram has not been realized offering some clarification on, the various countries scholar uses this block diagram to realize short time flicker value P _st, long-time flickering value P _ltComputing method different.Existing voltage flicker measuring method mainly contain FFT/STFT method, Hilbert transform method, EKF (EKF), least absolute value estimate (LAV) method, small wave converting method, based on Mathematical Morphology Filtering and Hilbert transform method, parallel filter detection method and square detection method.Adopt these methods to carry out detection and can accurately detect the flicker envelope signal, but these method operands are large, the Implementation of Embedded System difficulty is difficult to satisfy the requirement of flickering parameter fast detecting.

Based on the flicker detection algorithm of FFT, be easy to the digital signal processor at DSP() the upper realization is that a kind of flickering parameter that is widely used now employing detects in real time, the flickering value is simplified computing method.In electric system, line voltage, current distortion cause the flicker frequency fluctuation, have the problems such as spectral leakage and fence effect because non-synchronous sampling causes fft algorithm, have restricted the accuracy of flickering fast detecting.And, the impact that the parameter extraction of flicker envelope signal is changed by the parameters such as signal frequency, waveform, amplitude and sampled data length, the extraction error of formation flicker envelope parameter.Spectral leakage and the fence effect that reduces fft algorithm affects, the accuracy of detection of raising flicker envelope parameter is the difficult problem in flickering input and Power quality management.

existing patent document " a kind of flickering real-time computing technique " (201210363581.6), " the Injection Level detection method is polluted in the flickering of disturbance load " (201210179485.6), " a kind of definite voltage flicker primary responsibility party's method and apparatus " (201110367781.4), " a kind of method of measuring electric network voltage flicker " (201110124225.4), " based on the voltage fluctuation flickering measurement method of digital synchronization carrier wave coherent demodulation technology " (200910076715.4), " a kind of flicker demodulation method " (200710144772.2) and " digital voltage flicker tester " (91105178.3) etc., realized voltage flicker value and the party responsible who differentiates interference in accurate quantification ground measurement electric system.Although prior art provides the method for some voltage detections and flicker measurement, but have the features such as diversity, randomness and polymorphism due to the flickering signal, spectral leakage and fence effect that the flicker frequency fluctuation causes still exist, and be more consuming time to extraction and the calculating of envelope signal; Adopt the Cosine Window of regular length to carry out the FFT Fourier transform to the voltage sample sequence in prior art, change when excessive in flickering signal frequency, waveform, amplitude, can't accurately obtain frequency component and the amplitude components of flickering voltage signal, therefore real-time, high-precision flickering input is difficult to realize.

Summary of the invention

The invention provides a kind of voltage fluctuation and flicker detection method and device based on energy operator and Spectrum Correction, its purpose is, overcome the prior art computing velocity slow, flickering signal frequency, waveform, amplitude change when excessive, can't accurately obtain the spectrum component of flickering voltage signal and the problem of fluctuation amplitude.

Voltage fluctuation and flicker detection method based on energy operator and Spectrum Correction comprises the following steps:

Step 1: fixed sampling frequency f is set _sWith sampling number N, wherein, N is natural number, synchronized sampling and analog-to-digital conversion process are carried out in measured signal, obtain voltage flicker discrete signal u (n), utilize the Teager-Kaiser energy operator to extract envelope to u (n), namely u (n) is carried out demodulation process, obtain envelope signal U _r(n);

$U_r\left(n\right)=\mathrm{TK}\left(u\left(n\right)\right)-\frac{1}{N}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}\mathrm{TK}\left(n\right)---\left(1\right)$

Wherein, TK (n) is the Teager-Kaiser energy operator of voltage flicker signal;

The voltage flicker signal is take power-frequency voltage as carrier signal, and by the result of low frequency modulated wave signal modulation, the expression formula of flickering voltage u (t) is as follows:

u(t)=[1+v(t)]cos(2πf ₀t+φ ₀)

In formula, v (t) is the modulated wave voltage signal; f ₀It is the frequency of work frequency carrier signal; f _iIt is the frequency of modulated wave signal; A _iThat the flicker envelope fluctuation is the amplitude of modulated wave; φ ₀It is the initial phase angle of carrier signal;

It is the initial phase angle of modulated wave signal; H represents to comprise the item number of modulated wave signal;

Step 2: build the Kaiser window sequence, its discrete expression is W (n), utilizes the Kaiser window sequence to U _r(n) improve Fast Fourier Transform (FFT) FFT after windowing, then obtain through after discrete processes

The spectral line U of frequency place _W(k Δ f), To U _W(k Δ f) carries out two spectral line difference computings, obtains the spectrum component f of envelope signal _iWith amplitude A _i

$W\left(n\right)=\frac{I_0\left(\mathrm{\β}\sqrt{1-{\left(\frac{n}{N/2}\right)}^2}\right)}{I_0\left(\mathrm{\β}\right)},0\≤\left|n\right|\≤N/2---\left(2\right)$

Wherein, I ₀Be (β) the 1st class distortion zero Bessel function, β is the form parameter of Kaiser window function, is the positive count value; N is the length of Kaiser window sequence, i.e. sampling number; N is the sample variance point;

f _i=k _iΔf=(α+k _i1+0.5)Δf

$A_i=\frac{2(y_1+y_2)}{|W\left(\frac{2\mathrm{\π}(-\mathrm{\α}+0.5)}{N}\right)|+\left|W\left(\frac{2\mathrm{\π}(-\mathrm{\α}-0.5)}{N}\right)\right|}---\left(3\right)$

Wherein, W () is the continuous frequency spectrum function of Kaiser window, and N is the length of Kaiser window function, at peak value frequency f _iCorresponding spectral line k _iThe first amplitude and the second amplitude spectral line that near sampling obtains are respectively k _i1And k _i2, k _i1≤ k _i≤ k _i2(k _i2=k _i1+ 1), the amplitude of these two spectral lines is respectively y ₁=| U _W(k _i1Δ f) | and y ₂=| U _W(k _i2Δ f) |;

Envelope signal is the discrete Fourier transformation expression formula U of modulated wave signal _W(k Δ f) is as follows:

I item flicker envelope signal is the discrete Fourier transformation expression formula U of modulated wave signal _W(k Δ f) is as follows:

Wherein: A _iIt is the amplitude of i item flicker envelope modulated wave;

It is the initial phase angle of i item modulated wave signal; H represents to comprise the item number of modulated wave signal;

Utilize the Kaiser window function to amplitude A _iAdopt polynomial expression to approach approximating method correction:

$A=\frac{(y_1+y_2)}{N}(3.81160858+0.79465173{\mathrm{\α}}^2+0.08673112{\mathrm{\α}}^4+0.00679640{\mathrm{\α}}^6)---\left(5\right)$

Wherein, α=k _i-k _i1-0.5, α span is [0.5,0.5];

Step 3: calculate instantaneous flicker value p:

$p=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left[\frac{{\mathrm{\ΔU}}_f\left(f_i\right)}{{\mathrm{du}}_i}\right]}^2$

Wherein, du _iCorresponding frequencies f during for instantaneous flicker value p=1 _iCorresponding voltage fluctuation standard value d (%); L is maximum flickering occurrence frequency f in this frequency spectrum _iCorresponding numerical value, Δ U _f(f _i) be discrete magnitude of a voltage fluctuation ordered series of numbers, Δ U _f(f _i)=2 * | U _f(f _i) |;

Step 4: the short time flicker value is calculated

Repeating step 1 calculates each instantaneous flicker value p in 10 minutes successively to step 3, finds out the large value of probability corresponding to 99.9%, 99%, 97%, 90% and 50% probability from the p sequence by linear interpolation algorithm, is designated as respectively successively p _0.1, p ₁, p ₃, p ₁₀And p ₅₀, calculate short time flicker value P _st:

$P_{\mathrm{st}}=\sqrt{{0.0314}_{p_{0.1}}+{0.0525}_{p_1}+{0.0657}_{{\mathrm{<figure-callout\; id="3"\; label="p"\; filenames="HDA00002827480000031.png"\; state="\{\{state\}\}">p</figure-callout>}}_3}+{0.28}_{{\mathrm{<figure-callout\; id="10"\; label="p"\; filenames="HDA00002827480000031.png,HDA00002827480000042.png"\; state="\{\{state\}\}">p</figure-callout>}}_{10}}+0.08_{p_{50}}}---\left(6\right)$

Wherein, p _0.1, p ₁, p ₃, p ₁₀, p ₅₀Be respectively the instantaneous flicker value of 10min voltage fluctuation cumulative probability function (CPF) curve ordinate 0.1%, 1%, 3%, 10%, 50% correspondence.

Each instantaneous flicker amount p is the sequence of discrete p on the equal time of the interval due to a period of time (10min), if wherein be not less than some p(such as p _N) time corresponding to all p account for the N (%) of whole period, be not less than p _NThe number of all p also should account for the N (%) of p sum in this period, i.e. p _NIt is the large value of (100-N) % probability of p sequence in this period.The p sequence by rearranging from big to small, and is obtained every large value p of probability in sequence as stated above _NCorresponding probability (100-N) % within the period.

Described in step 1 synchronized sampling is carried out in measured signal before, three phase network voltage, current analog signal access respectively resistance pressure-dividing network and TA resistance sampling network carries out signal condition.

Sample frequency f described in step 1 _sSpan be 400Hz～52KHz.

The span of the form parameter β of the Kaiser window function described in step 2 is 20～50.

Long-time flickering value P _ltBy each short time flicker value P that records in the Measuring Time section _stkFor

$P_{\mathrm{lt}}=\sqrt[3]{\frac{1}{M}\underset{k=1}{\overset{M}{\mathrm{\&Sigma;}}}{\left(P_{\mathrm{stk}}\right)}^3}$

In formula, M=120, namely Measuring Time is 2h.

A kind of voltage fluctuation and flicker pick-up unit based on energy operator and Spectrum Correction adopts method described above to detect the voltage fluctuation and flicker device, comprises signal condition unit, data processing unit and data storage and display unit; Signal condition unit, data processing unit and data storage and display unit are connected successively;

Wherein, the signal condition unit comprises reaching for the electric resistance partial pressure modulate circuit that is connected with voltage signal output end, the TA resistance sampling circuit that is used for being connected with current signal and synchronizes the ADC converter; Electric resistance partial pressure modulate circuit and TA resistance sampling circuit all with synchronize the ADC converter and be connected.

Described data processing unit comprises Teager-Kaiser energy operator extraction module, Kaiser window Spectrum Correction module, visual sense degree processing module and flickering signal sequencing statistical module.

Described data storage and display unit comprises data processor, clock circuit, storer, telecommunication circuit and display module, and clock circuit, storer, telecommunication circuit and display module all are connected with data processor.

The synchronous ADC converter of described signal condition unit adopts SPI to be connected with data processing unit; It is characterized in that, described data processing unit adopts asynchronous serial bus UART to be connected with the data storage and display unit.

Described synchronous ADC converter is ADS1178, and described data processing unit adopts the TMS320VC6745/6747 chip, and described data storage and display unit data processor adopts PIC32MX460F512L, and described display module is 256 look TFT bus-type touch LCD screens.

Utilize the Kaiser window function to amplitude A _iAdopt polynomial expression to approach approximating method correction, detailed step is as follows:

1) make λ=(y ₂-y ₁)/(y ₂+ y ₁), α=k _i-k _i1-0.5, α span is [0.5,0.5], is calculated as follows α:

$\mathrm{\&lambda;}=\frac{\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}+0.5)}{N}\right)\right|-\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}-0.5)}{N}\right)\right|}{\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}+0.5)}{N}\right)\right|+\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}-0.5)}{N}\right)\right|}---\left(7\right)$

2) the spectrum amplitude function of Kaiser window is

$W\left(w\right)=\frac{N-1}{I_0\left(\mathrm{\&beta;}\right)}\&CenterDot;\frac{\sinh \left(\sqrt{{\left(\mathrm{\&beta;}\right)}^2-{[(N-1)w/2]}^2}\right)}{\sqrt{{\left(\mathrm{\&beta;}\right)}^2-{[(N-1)w/2]}^2}}\&CenterDot;e^{-j\frac{N-1}{2}w}---\left(8\right)$

Make w=2 π kN, can get

$W\left(\frac{2\mathrm{\&pi;k}}{N}\right)=\frac{N-1}{I_0\left(\mathrm{\&beta;}\right)}\&CenterDot;\frac{\sinh \left(\sqrt{{\mathrm{\&beta;}}^2-{[(N-1)\mathrm{\&pi;k}/N]}^2}\right)}{\sqrt{{\mathrm{\&beta;}}^2-{[\left(N-1\right)\mathrm{\&pi;k}/N]}^2}}\&CenterDot;e^{-j\frac{N-1}{N}\mathrm{\&pi;k}}---\left(9\right)$

Will

Substitution formula (9), by

And N is generally larger, can get

$\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}\&PlusMinus;0.5)}{N}\right)\right|\&ap;|\frac{N-1}{I_0\left(\mathrm{\&pi;\&epsiv;}\right)}\&CenterDot;\frac{\sinh \left|\mathrm{\&pi;}\sqrt{{\mathrm{\&epsiv;}}^2-k^2}\right|}{\mathrm{\&pi;}\sqrt{{\mathrm{\&epsiv;}}^2-k^2}}|---\left(10\right)$

Formula (10) substitution formula (7) is utilized in the Matlab platform curve polyfit () function to carry out fitting of a polynomial and is approached, and can get α=f ¹(λ) approximant is

α=F(λ) (11)

Can obtain parameter alpha by λ, the amplitude correction of i item modulated wave is to k _i1And k _i2Two spectral lines are weighted on average, and its computing formula is

$A_i=\frac{A_{i2}\left|W(2\mathrm{\&pi;}(k_{i2}-k_i)/N)\right|+A_{i1}\left|W(2\mathrm{\&pi;}(k_{i1}-k_i)/N)\right|}{\left|W(2\mathrm{\&pi;}(k_{i2}-k_i)/N)\right|+\left|W(2\mathrm{\&pi;}(k_{i1}-k_i)/N)\right|}$

$=\frac{2(y_1+y_2)}{|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}+0.5)}{N}\right)|+\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}-0.5)}{N}\right)\right|}---\left(12\right)$

In formula: y ₁=| U _W(k _i1Δ f) | and y ₂=| U _W(k _i2Δ f) |.

When the N value was larger, formula (12) can be reduced to

A _i=N ^-1(y ₁+y ₂)v(α) (13)

In like manner, adopt polynomial expression to approach, can get it and approximantly be

A _i=N ^-1(y ₁+y ₂)g(α) (14)

In get one group of α value, obtain corresponding one group of λ and v (α) value by formula (7) and formula (13) respectively, call polyfit in the Matlab platform (α, λ, m) function and carry out anti-fitting, obtain the coefficient of polynomial expression F (λ), (m) function is obtained the coefficient of polynomial expression g (α) for α, v (α) to call polyfit again, wherein, m is the polynomial exponent number of approach.Can be based on the interpolation correction formula of Kaiser window:

α=H(λ)=4.26201515λ+0.50674586λ ³+0.22516483λ ⁵+0.13687018λ ⁷

g(α)=3.81160858+0.79465173α ²+0.08673112α ⁴+0.00679640α ⁶ （15）

, fluctuation amplitude correction formula is:

$A=\frac{(y_1+y_2)}{N}\&CenterDot;(3.81160858+0.79465173{\mathrm{\&alpha;}}^2+0.08673112{\mathrm{\&alpha;}}^4+0.00679640{\mathrm{\&alpha;}}^6)$

Beneficial effect

The invention provides a kind of voltage fluctuation and flicker detection method and device based on energy operator and Spectrum Correction, by utilizing the Teager-Kaiser energy operator to extract the envelope signal of voltage flicker signal, accelerate arithmetic speed, the impact that changed by the parameters such as signal frequency, waveform, amplitude and sampled data length realizes detecting in real time fast of flickering signal; Employing can freely select the Kaiser window function of the proportion between main lobe width and secondary lobe height to improve the analysis of Fast Fourier Transform (FFT) Spectrum Correction to the voltage flicker signal, change when excessive in flickering signal frequency, waveform, amplitude, accurately obtain frequency component and the amplitude components of voltage flicker signal; Apparatus structure based on the method is simple, is easy to realize, comprises signal condition unit, data processing unit and data storage and display unit; Signal condition unit, data processing unit and data storage and display unit are connected successively; The signal condition unit comprises reaching for the electric resistance partial pressure modulate circuit that is connected with voltage signal output end, the TA resistance sampling circuit that is used for being connected with current signal synchronizes the ADC converter; Electric resistance partial pressure modulate circuit and TA resistance sampling circuit all with synchronize the ADC converter and be connected.This detection method is convenient to fast in real time Check processing and the Implementation of Embedded System of signal, can be continuously, for a long time measured signal is detected.

Description of drawings

Fig. 1 is voltage flicker parameter detecting of the present invention and flickering value calculation process block diagram;

Fig. 2 is apparatus structure block diagram of the present invention;

Fig. 3 is voltage flicker of the present invention and fluctuation measuring principle block diagram;

Kaiser window discrete time-domain performance plot when Fig. 4 is β=[0,4,8,11];

Kaiser window amplitude versus frequency characte figure when Fig. 5 is β=[0,4,8,11];

Fig. 6 is Kaiser window FFT double spectral line interpolation algorithm schematic diagram;

Fig. 7 is the graph of relation of each frequency of instantaneous flicker amount of the present invention and magnitude of a voltage fluctuation.

Embodiment

The present invention will be further described below in conjunction with accompanying drawing.

The present embodiment is the flickering cell board flickering parameter detecting part that can be used for realizing power system voltage fluctuation and flicker detection device, equipment for monitoring power quality.

In setting the present embodiment, ADC selects 16 high speeds, 8 Channel Synchronous sampling A/D chip ADS1178, and dsp processor is selected TMS320VC6745, and major parameter is selected as follows:

(1) sampling rate: f _s=52k;

(2) electrical network fundamental frequency: in 50Hz left and right fluctuation;

(3) FFT operational data length: N=512;

(4) flickering input frequency range: 0.05～35Hz.

As shown in Figure 1, be voltage flicker parameter detecting of the present invention and flickering value calculation process block diagram, concrete steps are as follows:

Step 1: fixed sampling frequency f is set _sWith sampling number N, wherein, N is natural number, synchronized sampling and analog-to-digital conversion process are carried out in measured signal, obtain voltage flicker discrete signal u (n), utilize the Teager-Kaiser energy operator to extract envelope to u (n), namely u (n) is carried out demodulation process, obtain envelope signal U _r(n);

$U_r\left(n\right)=\mathrm{TK}\left(u\left(n\right)\right)-\frac{1}{N}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}\mathrm{TK}\left(n\right)$

Wherein, TK (n) is the Teager-Kaiser energy operator of voltage flicker signal;

The voltage flicker signal is take power-frequency voltage as carrier signal, and by the result of low frequency modulated wave signal modulation, the expression formula of flickering voltage u (t) is as follows:

u(t)=[1+v(t)]cos(2πf ₀t+φ ₀)

In formula, v (t) is the modulated wave voltage signal; f ₀It is the frequency of work frequency carrier signal; f _iIt is the frequency of modulated wave signal; A _iThat the flicker envelope fluctuation is the amplitude of modulated wave; φ ₀It is the initial phase angle of carrier signal;

It is the initial phase angle of modulated wave signal; H represents to comprise the item number of modulated wave signal;

Step 2: build the Kaiser window sequence, its discrete expression is W (n), utilizes the Kaiser window sequence to U _r(n) improve Fast Fourier Transform (FFT) FFT after windowing, then obtain through after discrete processes

The spectral line U of frequency place _W(k Δ f),

To U _W(k Δ f) carries out two spectral line difference computings, obtains the spectrum component f of envelope signal _iWith amplitude A _i

$W\left(n\right)=\frac{I_0\left(\mathrm{\&beta;}\sqrt{1-{\left(\frac{n}{N/2}\right)}^2}\right)}{I_0\left(\mathrm{\&beta;}\right)},0\&le;\left|n\right|\&le;N/2---\left(2\right)$

Wherein, I ₀Be (β) the 1st class distortion zero Bessel function, β is the form parameter of Kaiser window function, is the positive count value, as shown in Figure 4 and Figure 5; N is the length of Kaiser window sequence, i.e. sampling number, and the N value is 512; N is the sample variance point; The present embodiment is selected the Kaiser window of β=20 o'clock to carry out FFT to process.

f _i=k _iΔf=(α+k _i1+0.5)Δf

$A_i=\frac{2(y_1+y_2)}{|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}+0.5)}{N}\right)|+\left|W\left(\frac{2\mathrm{\&pi;}(-\mathrm{\&alpha;}-0.5)}{N}\right)\right|}---\left(3\right)$

Wherein, W () is the continuous frequency spectrum function of Kaiser window, and N is the length of Kaiser window function, at peak value frequency f _iCorresponding spectral line k _iThe first amplitude and the second amplitude spectral line that near sampling obtains are respectively k _i1And k _i2, k _i1≤ k _i≤ k _i2(k _i2=k _i1+ 1), the amplitude of these two spectral lines is respectively y ₁=| U _W(k _i1Δ f) | and y ₂=| U _W(k _i2Δ f) |;

In the present embodiment the schematic diagram of double spectral line interpolation algorithm as shown in Figure 6, k _i1And k _i2Represent respectively near two spectral lines that actual frequency point is, with the modulated wave frequency f _i=2.2Hz is example, k _i1And k _i2To be positioned at 2～3Hz frequency range.

Envelope signal is the discrete Fourier transformation expression formula U of modulated wave signal _W(k Δ f) is as follows:

I item flicker envelope signal is the discrete Fourier transformation expression formula U of modulated wave signal _W(k Δ f) is as follows:

Wherein: A _iIt is the amplitude of i item flicker envelope modulated wave;

It is the initial phase angle of i item modulated wave signal; H represents to comprise the item number of modulated wave signal;

Utilize the Kaiser window function to amplitude A _iAdopt polynomial expression to approach approximating method correction:

$A=\frac{(y_1+y_2)}{N}(3.81160858+0.79465173{\mathrm{\&alpha;}}^2+0.08673112{\mathrm{\&alpha;}}^4+0.00679640{\mathrm{\&alpha;}}^6)---\left(5\right)$

Wherein, α=k _i-k _i1-0.5, α span is [0.5,0.5];

Step 3: calculate instantaneous flicker value p:

$p=\underset{i=1}{\overset{l}{\mathrm{\&Sigma;}}}{\left[\frac{{\mathrm{\&Delta;U}}_f\left(f_i\right)}{{\mathrm{du}}_i}\right]}^2$

Wherein, du _iCorresponding frequencies f during for instantaneous flicker value p=1 _iCorresponding voltage fluctuation standard value d (%); L is maximum flickering occurrence frequency f in this frequency spectrum _iCorresponding numerical value, Δ U _f(f _i) be discrete magnitude of a voltage fluctuation ordered series of numbers, Δ U _f(f _i)=2 * | U _f(f _i) |;

Step 4: the short time flicker value is calculated

Repeating step 1 calculates each instantaneous flicker value p in 10 minutes successively to step 3, finds out the large value of probability corresponding to 99.9%, 99%, 97%, 90% and 50% probability from the p sequence by linear interpolation algorithm, is designated as respectively successively p _0.1, p ₁, p ₃, p ₁₀And p ₅₀, calculate short time flicker value P _st:

$P_{\mathrm{st}}=\sqrt{{0.0314}_{p_{0.1}}+{0.0525}_{p_1}+{0.0657}_{{\mathrm{<figure-callout\; id="3"\; label="p"\; filenames="HDA00002827480000031.png"\; state="\{\{state\}\}">p</figure-callout>}}_3}+{0.28}_{{\mathrm{<figure-callout\; id="10"\; label="p"\; filenames="HDA00002827480000031.png,HDA00002827480000042.png"\; state="\{\{state\}\}">p</figure-callout>}}_{10}}+0.08_{p_{50}}}---\left(6\right)$

In formula, p _0.1, p ₁, p ₃, p ₁₀, p ₅₀Be respectively the instantaneous flicker value of 10min voltage fluctuation cumulative probability function (CPF) curve ordinate 0.1%, 1%, 3%, 10%, 50% correspondence.

Long-time flickering value P _ltBy each short time flicker value P that records in the Measuring Time section _stkFor

$P_{\mathrm{lt}}=\sqrt[3]{\frac{1}{M}\underset{k=1}{\overset{M}{\mathrm{\&Sigma;}}}{\left(P_{\mathrm{stk}}\right)}^3}$

In formula, M=120, namely Measuring Time is 2h.

During due to the instantaneous flicker amount p=1 that provides in the IEC61000-4-15 standard, the value of the corresponding relation of frequency and sinusoidal voltage undulating quantity d is limited, and the frequency that is drawn by spectrum analysis differs and establishes a capital in table.Therefore, the present invention adopts in the spline method his-and-hers watches data to carry out interpolation and curve, the relation curve of magnitude of a voltage fluctuation and frequency when finding out instantaneous flicker amount p=1, thus obtain improving through the Kaiser window each frequency f that the FFT spectrum analysis draws _iCorresponding voltage fluctuation standard value du _i, the weighting of visual sense degree is carried out in the voltage fluctuation of this frequency is processed.In the present embodiment, during instantaneous flicker amount p=1, the relation curve of each frequency and relevant voltage undulating quantity as shown in Figure 7.

As shown in Figure 2, be structured flowchart of the present invention, a kind of voltage fluctuation and flicker pick-up unit based on energy operator and Spectrum Correction comprises signal condition unit, data processing unit and data storage and display unit; Signal condition unit, data processing unit and data storage and display unit are connected successively;

Wherein, the signal condition unit comprises reaching for the electric resistance partial pressure modulate circuit that is connected with voltage signal output end, the TA resistance sampling circuit that is used for being connected with current signal and synchronizes the ADC converter; Electric resistance partial pressure modulate circuit and TA resistance sampling circuit all with synchronize the ADC converter and be connected.

Described data processing unit comprises Teager-Kaiser energy operator extraction module, Kaiser window Spectrum Correction module, visual sense degree processing module and flickering signal sequencing statistical module.

Described data storage and display unit comprises data processor, clock circuit, storer, telecommunication circuit and display module, and clock circuit, storer, telecommunication circuit and display module all are connected with data processor.

The synchronous ADC converter of described signal condition unit adopts SPI to be connected with data processing unit; It is characterized in that, described data processing unit adopts asynchronous serial bus UART to be connected with the data storage and display unit.

Described synchronous ADC converter is ADS1178, and described data processing unit adopts the TMS320VC6745/6747 chip, and described data storage and display unit data processor adopts PIC32MX460F512L, and described display module is 256 look TFT bus-type touch LCD screens.

As shown in Figure 3, be measuring principle schematic diagram of the present invention, three phase network voltage, current analog signal carry out signal condition through resistance pressure-dividing network and TA resistance sampling network respectively, obtain≤AC signal of 2.5V.The RC low-pass filter that the rear class access parameter is identical, the phase differential before and after keeping sampling between voltage, electric current is consistent.TA rear end access switching diode 1SS123 amplitude limit prevents the excessive damage device of Current Transmit primary side current.The reference power supply ADR121 that selects high precision and high thermal stability provides+the external reference voltage V of 2.5V for ADS1178 _REF, guarantee that sample circuit has higher precision and thermal stability.

Deliver to the TMS320VC6745 data processing unit by the SPI interface after sampled data A/D conversion (analog to digital conversion), complete the extraction of Teager-Kaiser energy operator, Kaiser window improvement FFT analysis of spectrum, visual sense degree weighted quadratic, sequence permutation statistics by TMS320VC6745, obtain the flickering statistical parameter.

With reference to standard GB/T/T12326-2008 and power industry standard DL/T1028-2006, the flickering parameter detecting error result of the present embodiment is as follows:

The actual test of table 1 flickering value relative error (%)

The present embodiment has also adopted other classical windows to test, result shows, adopt the basic window function such as rectangular window and classical cosine window function to signal weighting, be subject to the fixedly restriction of side lobe performance of window function for the dynamic signal analysis effect, the Kaiser window has good spectrum leakage inhibiting effect, design realizes flexibly, calculates simple based on the voltage flicker detection algorithm of Teager-Kaiser energy operator Kaiser window Spectrum Correction, is conducive in real time, the Implementation of Embedded System of the flicker detection algorithm of pin-point accuracy.

Claims (10)

1. A voltage fluctuation and flicker detection method based on energy operator and spectrum correction, is characterized in that, comprises the following steps: Step 1: Set the fixed sampling frequency f _s and the number of sampling points N, where N is a natural number, perform synchronous sampling and analog-to-digital conversion processing on the measured signal, obtain the discrete signal u(n) of voltage flicker, and use the Teager-Kaiser energy calculation The sub-pair u(n) extracts the envelope, that is, demodulates u(n) to obtain the envelope signal U _r (n): ${\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; TK</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}}\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; TK</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$ Among them, TK(n) is the Teager-Kaiser energy operator of the voltage flicker signal; Step 2: Construct a Kaiser window sequence, whose discrete expression is W(n), use the Kaiser window sequence to window U _r (n) and perform an improved Fast Fourier Transform FFT, and then obtain after discrete processing

Spectral line U _W (kΔf) at frequency,

Perform bispectral difference calculation on U _W (kΔf) to obtain the spectral component f _i and amplitude A _i of the envelope signal; $\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&beta;</span>}\sqrt{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; \&le;</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$ Among them, I ₀ (β) is the first kind of deformed zero-order Bessel function, β is the shape parameter of the Kaiser window function, which is any positive value; N is the length of the Kaiser window sequence, that is, the number of sampling points; n is the sampling discrete point ; f _i =k _i Δf=(α+k _i1 +0.5)Δf ${\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; W</span><span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 0.5</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; +</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&pi;</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 0.5</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$ Among them, W( ) is the continuous spectrum function of the Kaiser window, N is the length of the Kaiser window function, and the first and second amplitude spectral lines obtained by sampling near _the peak frequency f _i corresponding to the spectral line ki are respectively k _i1 and k _i2 , k _i1 ≤ki _{≤k i2} (k _i2 =k _i1 +1), the amplitudes of these two spectral lines are y ₁ =|U _W (k _i1 Δf)| and y ₂ = |U _W (k _i2 Δf)|; The discrete Fourier transform expression U _W (kΔf) of the i-th flicker envelope signal, that is, the AM wave signal, is as follows: Wherein, A _i is the amplitude of the i-th flicker envelope amplitude modulation wave;

is the initial phase angle of the i-th AM wave signal; f is the discrete sampling interval; Use the Kaiser window function to correct the amplitude A _i using the polynomial approximation fitting method: $\mathrm{<span\; class="notranslate">\; A</span>}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3.81160858</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 0.79465173</span>}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 0.08673112</span>}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; 4</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 0.00679640</span>}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}^{\mathrm{<span\; class="notranslate">\; 6</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$ Among them, α=k _i -k _i1 -0.5, and the value range of α is [-0.5, 0.5]; Step 3: Calculate the instantaneous flicker value p: $\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; l</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;\; U</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; du</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}$ Among them, du _i is the voltage fluctuation standard value d(%) corresponding to the corresponding frequency f _i when the instantaneous flicker value p=1; l is the value corresponding to the maximum flicker occurrence frequency f _i in the frequency spectrum, ΔU _f (f _i ) is a discrete sequence of voltage fluctuation values, ΔU _f (f _i )=2×|U _f (f _i )|; Step 4: Calculation of short-term flicker value Repeat steps 1 to 3, calculate the instantaneous flicker values p within 10 minutes in sequence, and find out the high probability values corresponding to 99.9%, 99%, 97%, 90% and 50% probabilities from the p sequence according to the linear interpolation algorithm, Record them respectively as p _0.1 , p ₁ , p ₃ , p ₁₀ and p ₅₀ respectively, and calculate the short-term flicker value P _st : ${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; st</span>}}<span\; class="notranslate">\; =</span>\sqrt{{\mathrm{<span\; class="notranslate">\; 0.0314</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 0.1</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; 0.0525</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; 0.0657</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; 0.28</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 10</span>}}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 0.0</span>}{\mathrm{<span\; class="notranslate">\; 8</span>}}_{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 50</span>}}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$ In the formula, p _0.1 , p ₁ , p ₃ , p ₁₀ , and p ₅₀ are the instantaneous flicker corresponding to 0.1%, 1%, 3%, 10%, and 50% of the ordinate of the 10-min voltage fluctuation cumulative probability function (CPF) curve, respectively value. 2. The voltage fluctuation and flicker detection method based on energy operator and spectrum correction according to claim 1, characterized in that, before the synchronous sampling of the measured signal described in step 1, the three-phase grid voltage, The current analog signal is respectively connected to the resistance voltage divider network and the TA resistance sampling network for signal conditioning. 3. The voltage fluctuation and flicker detection method based on energy operator and spectrum correction according to claim 1 or 2, characterized in that the sampling frequency f _s described in step 1 ranges from 400Hz to 52KHz. 4. The voltage fluctuation and flicker detection method based on energy operator and spectrum correction according to claim 1, characterized in that, the value range of the shape parameter β of the Kaiser window function described in step 2 is 20 to 50 . 5. the voltage fluctuation and flicker detection method based on energy operator and spectral correction according to claim 1, is characterized in that, the long-term flicker value P _lt is by each short-time flicker value that records in the measurement period P _stk is: ${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; lt</span>}}<span\; class="notranslate">\; =</span>\sqrt[\mathrm{<span\; class="notranslate">\; 3</span>}]{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; stk</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 3</span>}}}$ In the formula, M=120, that is, the measurement time is 2h. 6. A voltage fluctuation and flicker detection device based on energy operator and spectrum correction, characterized in that, the method for detecting voltage fluctuation and flicker according to any one of claims 1-5 includes a signal conditioning unit , a data processing unit and a data storage display unit; the signal conditioning unit, the data processing unit and the data storage display unit are connected in sequence; Wherein, the signal conditioning unit includes a resistance voltage divider conditioning circuit connected to the output terminal of the voltage signal, a TA resistance sampling circuit connected to the current signal and a synchronous ADC converter; both the resistance voltage divider conditioning circuit and the TA resistance sampling circuit are connected with the synchronous ADC converter connected. 7. A voltage fluctuation and flicker detection device based on energy operators and spectrum correction according to claim 6, wherein the data processing unit includes a Teager-Kaiser energy operator extraction module, a Kaiser window spectrum correction module, visual sensitivity processing module and flicker signal sorting and statistics module. 8. A voltage fluctuation and flicker detection device based on energy operator and spectrum correction according to claim 6 or 7, wherein the data storage and display unit includes a data processor, a clock circuit, a memory, a communication The circuit and the display module, the clock circuit, the memory, the communication circuit and the display module are all connected with the data processor. 9. A kind of voltage fluctuation and flicker detection device based on energy operator and spectrum correction according to claim 8, it is characterized in that, the synchronous ADC converter of described signal conditioning unit is connected with data processing unit by SPI; Its The feature is that the data processing unit and the data storage and display unit are connected by an asynchronous serial bus UART. 10. A voltage fluctuation and flicker detection device based on energy operator and spectrum correction according to claim 8, wherein the synchronous ADC converter is ADS1178, and the data processing unit adopts TMS320VC6745/6747 chip The data processor of the data storage and display unit adopts PIC32MX460F512L, and the display module is a 256-color TFT bus type touch liquid crystal screen.

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