CN117630486A - Harmonic detection method, device and system - Google Patents
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Abstract
The invention provides a harmonic detection method, a device and a system, wherein the method comprises the following steps: the first window function and the second window function are convolved to obtain a third window function; windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function; correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function; correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected; and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected. The signal parameter obtained by adopting the harmonic detection method of the embodiment of the invention has high accuracy.
Description
Technical Field
The embodiment of the invention relates to the technical field of power grid detection, in particular to a harmonic detection method, device and system.
Background
Currently, for the detection of harmonic signals, the main methods adopted are: time domain analysis method, frequency domain analysis method. Specifically, the frequency domain analysis method further includes: an analog filter-based algorithm, a neural network-based algorithm, a fourier transform-based algorithm, and a wavelet transform-based algorithm.
However, the accuracy of the signal parameters obtained using the above harmonic detection method is low.
Disclosure of Invention
The embodiment of the invention provides a harmonic detection method, a device and a system, which are used for solving the problem of low accuracy of signal parameters obtained by adopting the existing harmonic detection method.
In order to solve the technical problems, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a harmonic detection method, including:
the first window function and the second window function are convolved to obtain a third window function;
windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function;
correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function;
correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected;
and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
Alternatively, the process may be carried out in a single-stage,
the interpolation algorithm is a four-spectral line interpolation algorithm.
Alternatively, the process may be carried out in a single-stage,
the obtaining of the signal parameters of the signal to be detected according to the corrected signal to be detected comprises the following steps:
and correcting the corrected signal to be detected by adopting an all-phase fast Fourier transform algorithm apFFT to obtain a signal parameter of the signal to be detected.
Alternatively, the process may be carried out in a single-stage,
the signal parameters include at least one of: frequency, amplitude and phase.
In a second aspect, an embodiment of the present invention provides a harmonic detection apparatus, including:
the convolution module is used for carrying out convolution on the first window function and the second window function to obtain a third window function;
the first execution module is used for windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function;
the second execution module is used for correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function;
the third execution module is used for correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected;
the third execution module is further used for obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
Optionally, the second execution module is further configured to modify the first DFT function by using a four-spectral line interpolation algorithm to obtain a second DFT function.
Optionally, the third execution module is further configured to modify the modified signal to be detected by using an apFFT algorithm, so as to obtain a signal parameter of the signal to be detected.
In a third aspect, an embodiment of the present invention provides a harmonic detection system, including:
the detection circuit is used for acquiring a signal to be detected;
a harmonic detection apparatus as claimed in any one of the second aspects.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including a processor, a memory, and a program or instructions stored on the memory and executable on the processor, the program or instructions, when executed by the processor, implementing the steps in the harmonic detection method as described in any one of the first aspects.
In a fifth aspect, an embodiment of the present invention provides a readable storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps in the harmonic detection method as described in any one of the first aspects.
In the embodiment of the invention, a third window function is obtained by mutually convolving the first window function and the second window function; windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function; correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function; correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected; the signal parameters of the signal to be detected are obtained according to the corrected signal to be detected, and the accuracy of the signal parameters obtained by adopting the harmonic detection method of the embodiment of the invention is high.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a schematic flow chart of a harmonic detection method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of an algorithm flow for applying the harmonic detection method according to the embodiment of the present invention;
FIG. 3 is a side lobe feature contrast plot of four Nuttall window functions to be selected;
FIG. 4 is a graph comparing three exemplary window functions to NNMCW;
FIG. 5 is a schematic diagram of a four-line interpolation polynomial approximation;
FIG. 6 is m 0 Full phase time shift phase difference correction flow chart when=1;
FIG. 7 is a diagram of an apFFT analysis architecture;
FIG. 8 is an amplitude measurement error curve;
FIG. 9 is a plot of phase measurement error;
FIG. 10 is a schematic diagram of a power harmonic detection system;
FIG. 11 is a schematic block diagram of a harmonic detection apparatus according to an embodiment of the present invention;
FIG. 12 is a schematic block diagram of a harmonic detection system according to an embodiment of the present invention;
fig. 13 is a functional block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Aiming at the detection problem of harmonic signals, different detection algorithms are provided by students at home and abroad according to different use environments, and two main categories based on time domain analysis and frequency domain analysis are mainly formed.
1. Time domain analysis
The design of the active filter mainly adopts a time domain analysis method, and is represented by an instantaneous reactive power algorithm. Japanese scholars H.Akagi et al propose a three-phase circuit instantaneous reactive power theory based on time domain analysis, which converts three-phase currents from a, b, c three-phase coordinate system to stationary alpha, beta two-phase coordinate system by Clark conversion, respectively calculates instantaneous current I p And I q Thereby obtaining a direct current component and a harmonic component in the signal to be measured. The method has the advantages of simple hardware circuit, high extraction precision and good dynamic response, is only suitable for the condition of symmetrical power supply voltage, is limited by a low-pass filter, and has larger time delay. The scholars have thereafter proposed i combining the phase detector in the PLL with Park conversion d -i q The novel detection algorithm eliminates detection errors caused by voltage distortion and three-phase asymmetry of the traditional algorithm, and saves operation time. Another idea is to replace the traditional i with a novel variable step LMS adaptive filtering algorithm p -i q The low-pass filter in the algorithm further improves the response speed of the algorithm. The harmonic detection algorithm based on the instantaneous reactive power theory measures the sum of all harmonic components, cannot be specific to a single harmonic component, and the accuracy of the obtained signal parameters is low.
2. Frequency domain analysis
(1) Algorithm based on analog filter
The basic idea of the analog filtering detection method is as follows: after the sampled harmonic signals pass through a series of band-pass filters, a detector is used for judging whether harmonic components with the frequency being the center frequency of each band-pass filter exist or not. The method has the advantages that the used circuit is simple in structure, low in cost of related devices, small in output impedance and easy to control quality factor, but only harmonic components with the frequency being the center frequency of a filter in the circuit can be detected, the detection accuracy depends on the circuit devices, meanwhile, as most of the used circuits are analog circuits, the possibility of being interfered by surrounding environment is high, so that the detection accuracy is greatly reduced, fundamental waves and harmonic waves can be separated only, each harmonic wave cannot be separated independently, and the accuracy of the obtained signal parameters is low.
(2) Neural network-based algorithm
With the rapid development of artificial intelligence, neural networks are widely used in the field of power harmonic detection. The application of neural networks in harmonic detection is mainly of two types: firstly, the harmonic detection of the power system based on the multilayer feedforward neural network is realized, and the method continuously adjusts the weight through the forward propagation of information and the reverse transmission of errors, so that the detection precision is higher; and secondly, the self-adaptive linear neural network is combined with the power harmonic detection performed by the self-adaptive noise cancellation system, so that the noise signal in the final output signal is greatly reduced by the application of the self-adaptive filter, the signal-to-noise ratio of the signal is effectively improved, and the harmonic detection precision is higher. These two algorithms have the disadvantages that the harmonic detection of the power system based on the multi-layer feedforward neural network has great uncertainty in the training process, a great deal of training is needed before application, and the selection of training samples affects the detection precision of the algorithm. The adaptive linear neural network model needs to take fundamental wave frequency as a priori condition to realize accurate detection of harmonic waves, and the obtained signal parameters have low accuracy. In addition, the power harmonic measurement method based on the neural network is not mature, is difficult to realize in hardware, and has great limitation in engineering application.
(3) Fourier transform-based algorithm
Fourier transform, which can transform signals from the time domain to the frequency domain, is the most classical harmonic and inter-harmonic analysis algorithm. Among them, fast Fourier Transform (FFT) is widely used in harmonic and inter-harmonic detection because of its fast processing speed and easy system implementation, and has been developed on the basis of Discrete Fourier Transform (DFT), by which an electrical signal is converted from a time domain to a frequency domain, and the amplitude, frequency and phase of the contained harmonic component can be conveniently solved using frequency domain information. However, because the signal frequency always varies continuously, when the asynchronous sampling or the non-integer period is cut off, frequency spectrum leakage and a fence effect are easy to generate, and further the analysis results of harmonic waves and inter-harmonic waves are affected, and the accuracy of the obtained signal parameters is low.
(4) Algorithm based on wavelet transformation
Wavelet transform utilizes a wavelet basis function that is scalable in translation to decompose a signal onto individual band segments. The method overcomes the limitation that Fourier transformation has no time domain localization, and is particularly suitable for analysis of non-stationary time-varying signals. It can analyze not only the waveform change of the signal, but also record the change time of the waveform. At present, a Mallat-based wavelet multi-resolution analysis method is adopted to detect harmonic and inter-harmonic signals, so that time-frequency information of the signals can be observed at the same time, and the detection precision of the harmonic and the inter-harmonic is high. However, the signal frequency band is unevenly divided, and when the frequencies of the harmonic component and the inter-harmonic component are similar, an inherent frequency spectrum aliasing phenomenon can be generated, the accuracy of the obtained signal parameters is low, and the problems that the wavelet basis is difficult to select, the calculated amount is large, the real-time performance is poor and the like are also caused.
The embodiment of the invention provides a harmonic detection method, referring to fig. 1, fig. 1 is one of flow diagrams of the harmonic detection method according to the embodiment of the invention, and the harmonic detection method comprises the following steps:
step 11: the first window function and the second window function are convolved to obtain a third window function;
step 12: windowing a signal to be detected by adopting a third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function;
step 13: correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function;
step 14: correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected;
step 15: and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
In the embodiment of the invention, in order to reduce the influence of spectrum leakage on detection precision, a window function used in harmonic detection must have excellent side lobe characteristics. Good side lobe characteristics, i.e. low side lobe peak levels of the selected window function and fast side lobe decay rates, are required.
Referring to fig. 2, fig. 2 is a schematic flow chart of an algorithm for applying the harmonic detection method according to the embodiment of the present invention, where a nutall window discrete time domain expression is:
where M is the number of terms of the window function, N is the data length to be windowed, b p The following constraints are satisfied as window coefficients:
referring to fig. 3, fig. 3 is a side lobe feature comparison chart of four nutall window functions to be selected, wherein: a 3-term minimum side lobe nuttal window function (top left), a 4-term minimum side lobe nuttal window function (top right), a 4-term 3-order nuttal window function (bottom left), and a 4-term 5-order nuttal window function (bottom right). As can be seen by comparing the sidelobe characteristics of 4 different Nuttall window functions, the sidelobe peak values of the 4-item 3-order Nuttall window (function) and the 4-item 5-order Nuttall window (function) are slightly lower than the minimum sidelobe Nuttall window, but the sidelobe attenuation rate is remarkably superior. Thus, the 4-term 3-order nuttal window is determined as a first window function, and the 4-term 5-order nuttal window function is determined as a second window function.
Further, the first window function and the second window function are convolved to obtain a third window function. In the example, the third window function is named NNMCW (four terms of third-order Nuttall and four terms of fifth-order Nuttall mutual convolution window, 4-item 3-order Nuttall and 4-item 5-order Nuttall deconvolution window) window function, where NNMCW window function has the expression:
w III (m) represents a 4-term 3-order Nuttall window, w IV (m) represents a 4-term 5-order Nuttall window, and the data length of both window functions is N, the convolution result w NN The data length of (m) is 2N-1, and zero is added at the end of the convolution sequence, so as to obtain NNMCW with the length of 2N (N is generally the power of 2 in fast Fourier transform FFT).
Referring to FIG. 4, FIG. 4 is a graph comparing three exemplary window functions to NNMCW. As a result, NNMCW (lower right) has more excellent side lobe characteristics than Blackman-Harris window function (upper left), hanning-nuttal window function (upper right) and Blackman-nuttal window function (lower left).
In step 12, a third window function is adopted to window the signal to be detected, and discrete fourier DFT is performed on the windowed signal to be detected to obtain a first DFT function. The NNMCW window function is adopted to window the signal to be detected, and discrete Fourier DFT conversion is carried out on the windowed signal to be detected, so that the expression of the first DFT function is obtained as follows:
where W (f) is the spectral function of the window function,the discrete sampling interval is Δf=f s N, N is the data cut-off length, frequency f 0 Position in the discrete spectrum l=f 0 And/Δf, j is an imaginary unit,is the initial phase angle of the signal, and the sampling time interval is T s ＝1/f s Wherein f s Is the sampling frequency.
And correcting the first DFT function by adopting a four-spectral-line interpolation algorithm to obtain a second DFT function. Wherein, peak value searching is carried out on the discrete Fourier spectrum after signal windowing to obtain the maximum value s of spectral line amplitude 1 Second maximum value s 2 Outside spectral line amplitude s 3 Outside spectral line amplitude s 4 The calculation is performed as a characteristic line. The reason why the characteristic lines are taken around as described above is as follows: the peak at these 4 near the main line is the largest and can be more correlated with the main line than at other locations.
The four spectral line amplitudes give 1,3,3,1 weight, and parameters are introducedAnd ψ:
the first DFT function s i ＝|X(l i Substitution of Δf) i into the above formula yields:
wherein:
the above is psi relative toIs recorded as a function of->Then the inverse function of ψ is +.>At this time, +.>
From this, the following frequency, amplitude and phase correction formula is derived:
the frequency correction formula is:
f 0 ＝lΔf＝[δ(ψ)+l 1 +0.5]Δf
the amplitude correction is to carry out weighted average on four spectral lines near the peak frequency point, and the amplitude correction formula is as follows:
the phase correction formula is:
when n=1024, in NNMCWIs as follows:
δ(ψ)＝4.4238ψ+1.3161ψ 3 +0.4213ψ 5 -0.2735ψ 7
when n=1024 is used,is +.>The method comprises the following steps:
delta (psi) is calculatedThe two approximations are substituted into the frequency, amplitude and phase correction formulas to obtain complete frequency, amplitude and phase correction formulas (which are equivalent to a second DFT function in the application, wherein the second DFT function comprises complete frequency, complete amplitude and complete phase correction formulas).
A complete frequency correction formula:
f 0 ＝[4.4238ψ+1.3161ψ 3 +0.4213ψ 5 -0.2735ψ 7 +l 1 +0.5]Δf
a complete amplitude correction formula:
a complete phase correction formula:
correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected; and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
In the embodiment of the invention, a third window function is obtained by mutually convolving the first window function and the second window function; windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function; correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function; correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected; according to the corrected signal to be detected, the signal parameters of the signal to be detected are obtained, the second DFT function can eliminate the frequency spectrum leakage problem caused by asynchronous sampling of the signal, so that the frequency spectrum energy is more concentrated, the detection precision of the harmonic parameters is improved, and the accuracy of the signal parameters obtained by adopting the harmonic detection method of the embodiment of the invention is high.
In some embodiments of the invention, optionally, the interpolation algorithm is a four-line interpolation algorithm.
Illustratively, a four-spectral-line interpolation algorithm is used to modify the first DFT function to obtain a second DFT function. Wherein, peak value searching is carried out on the discrete Fourier spectrum after signal windowing to obtain the maximum value s of spectral line amplitude 1 Second maximum value s 2 Outside spectral line amplitude s 3 Outside spectral line amplitude s 4 The calculation is performed as a characteristic line. The reason why the characteristic lines are taken around as described above is as follows: the peak at these 4 near the main line is the largest and can be more correlated with the main line than at other locations.
The four spectral line amplitudes give 1,3,3,1 weight, and parameters are introducedAnd ψ:
the first DFT function s i ＝|X(l i Substitution of Δf) i into the above formula yields:
wherein:
the above is psi relative toIs recorded as a function of->Then the inverse function of ψ is +.>At this time, +.>
From this, the following frequency, amplitude and phase correction formula is derived:
the frequency correction formula is:
f 0 ＝lΔf＝[δ(ψ)+l 1 +0.5]Δf
the amplitude correction is to carry out weighted average on four spectral lines near the peak frequency point, and the amplitude correction formula is as follows:
the phase correction formula is:
when n=1024, in NNMCWIs an approximation of delta (ψ)) The method comprises the following steps:
δ(ψ)＝4.4238ψ+1.3161ψ 3 +0.4213ψ 5 -0.2735ψ 7
when n=1024 is used,is +.>The method comprises the following steps:
delta (psi) is calculatedThe two approximations are substituted into the frequency, amplitude and phase correction formulas to obtain complete frequency, amplitude and phase correction formulas (which are equivalent to a second DFT function in the application, wherein the second DFT function comprises complete frequency, complete amplitude and complete phase correction formulas).
A complete frequency correction formula:
f 0 ＝[4.4238ψ+1.3161ψ 3 +0.4213ψ 5 -0.2735ψ 7 +l 1 +0.5]Δf
a complete amplitude correction formula:
a complete phase correction formula:
correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected; and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
In the embodiment of the invention, four spectral line interpolation correction endowed with new weight is selected, the problem of poor position of the true spectral line fitted by double spectral line interpolation is solved, and meanwhile, the new weight can make the two spectral lines of the maximum value and the second maximum value of the interpolation more prominent, thereby enabling the fitting to be closer to the true value and improving the detection precision.
In some embodiments of the present invention, optionally, obtaining the signal parameter of the signal to be detected according to the corrected signal to be detected includes:
and correcting the corrected signal to be detected by adopting an all-phase fast Fourier transform algorithm apFFT to obtain a signal parameter of the signal to be detected.
Exemplary, referring to FIG. 6, the delay displacement m is set in the full phase time shift phase difference correction method 0 =1, so as to eliminate the phase ambiguity phenomenon, and simplify the operation steps.
In the embodiment of the invention, the apFFT has phase invariance, the leakage of the spectrum is smaller than the decibel value of the FFT, and the problems of serious spectrum leakage and low precision of the traditional FFT are overcome. The phase invariance of the apFFT is utilized, the limit on the calculation of harmonic parameters is reduced (the calculated amount is reduced), and the detection precision is improved.
In some embodiments of the invention, optionally, the signal parameter includes at least one of: frequency, amplitude and phase.
In some embodiments of the present invention, optionally, referring to fig. 2 and 7, the convolution window w is a front window w of length N 1 And a flipped rear window w 2 Is windowed X by NNMCW window function W The formula of (m) is:
X W (m)＝w(m)X(m)
w(m)＝w 1 (m)*w 2 (-m)m∈(-N+1，N-1)
w 1 and w 2 NNMCW and inverted NNMCW, respectively.
The simulation experiment using the harmonic detection method of the embodiment of the invention is used for explaining that the high-precision signal parameters can be obtained
Experimental needleA set of signals containing fundamental and 11 th harmonic parameters is performed. The amplitude and phase of the signal are shown in Table 1, and the fundamental wave frequency f 0 = 49.13Hz, sampling frequency f s =3200 Hz, sample length n=1024.
TABLE 1 parameters of harmonic components of measured signals
The simulation experiment results are shown in fig. 8 and 9, wherein fig. 8 is an amplitude measurement error curve, and fig. 9 is a phase measurement error curve. It can be seen that when the method provided by the embodiment is adopted for harmonic signal analysis, the error change of each subharmonic parameter is stable, the maximum relative amplitude error of the harmonic is 1.17E-02, and the maximum absolute phase error is 0.0821 degrees. Experimental results show that the four-spectral-line interpolation apFFT harmonic detection method of the Nuttall mutual convolution window of the embodiment has excellent performance, can effectively inhibit spectrum leakage and fence effect, well eliminates interference between adjacent harmonics, and can realize accurate measurement of low-order harmonic parameters.
The embodiment of the invention provides a power harmonic detection system, which is shown in fig. 10 and comprises a three-phase alternating current standard power supply, an oscilloscope and a designed experiment platform. The test signal is generated by a three-phase alternating current standard power supply and is monitored by an oscilloscope; the test signal is converted into a small voltage signal through a signal preprocessing circuit and then is sent into an analog-to-digital converter for sampling; after sampling, the harmonic signal parameters are transmitted to a DSP (Digital Signal Processing ) through a serial port, and the DSP uses the detection algorithm provided by the invention to analyze the harmonic signal parameters; finally, the analysis result is sent to ARM (Advanced RISC Machines, microprocessor).
The harmonic parameters obtained by the detection system provided in this embodiment are shown in table 2. Where ARE represents the amplitude relative error estimate and PAE represents the phase absolute error estimate.
TABLE 2 harmonic parameter estimation
An embodiment of the present invention provides a harmonic detection device, referring to fig. 11, fig. 11 is a schematic block diagram of the harmonic detection device according to the embodiment of the present invention, and the harmonic detection device 90 includes:
a convolution module 91, configured to convolve the first window function with the second window function to obtain a third window function;
the first execution module 92 is configured to window the signal to be detected by using the third window function, and perform discrete fourier DFT on the windowed signal to be detected to obtain a first DFT function;
a second execution module 93, configured to modify the first DFT function by using an interpolation algorithm to obtain a second DFT function;
a third execution module 94, configured to correct the signal to be detected according to the second DFT function, so as to obtain a corrected signal to be detected;
the third execution module 94 is further configured to obtain a signal parameter of the signal to be detected according to the corrected signal to be detected.
In some embodiments of the invention, the method, optionally,
the second execution module 93 is further configured to correct the first DFT function by using a four-spectral line interpolation algorithm, so as to obtain a second DFT function.
In some embodiments of the invention, the method, optionally,
the third execution module 94 is further configured to modify the modified signal to be detected by using an apFFT algorithm to obtain a signal parameter of the signal to be detected.
The harmonic detection device provided in the embodiment of the present application can implement each process implemented by the embodiments of the methods of fig. 1 to 10, and achieve the same technical effects, so that repetition is avoided, and no further description is provided herein.
Referring to fig. 12, fig. 12 is a schematic block diagram of a harmonic detection system according to an embodiment of the present invention, and a harmonic detection system 100 includes:
a detection circuit 101 for acquiring a signal to be detected;
a harmonic detection apparatus 102 as claimed in any one of the embodiments of the present invention.
An embodiment of the present invention provides an electronic device 110, referring to fig. 13, and fig. 13 is a schematic block diagram of the electronic device 110 according to an embodiment of the present invention, including a processor 111, a memory 112, and a program or an instruction stored in the memory 112 and capable of running on the processor 111, where the program or the instruction implements steps in any one of the harmonic detection methods of the present invention when executed by the processor.
The embodiment of the invention provides a readable storage medium, on which a program or an instruction is stored, which when executed by a processor, implements each process of the embodiment of the harmonic detection method according to any one of the above embodiments, and can achieve the same technical effect, and in order to avoid repetition, a description is omitted here.
Wherein the readable storage medium is selected from Read-Only Memory (ROM), random access Memory (Random Access Memory RAM), magnetic disk or optical disk.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (10)
1. A method of harmonic detection, comprising:
the first window function and the second window function are convolved to obtain a third window function;
windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function;
correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function;
correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected;
and obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
2. The harmonic detection method according to claim 1, wherein:
the interpolation algorithm is a four-spectral line interpolation algorithm.
3. The harmonic detection method according to claim 1, wherein:
the obtaining of the signal parameters of the signal to be detected according to the corrected signal to be detected comprises the following steps:
and correcting the corrected signal to be detected by adopting an all-phase fast Fourier transform algorithm apFFT to obtain a signal parameter of the signal to be detected.
4. A harmonic detection method according to any one of claims 1 to 3, wherein:
the signal parameters include at least one of: frequency, amplitude and phase.
5. A harmonic detection apparatus, comprising:
the convolution module is used for carrying out convolution on the first window function and the second window function to obtain a third window function;
the first execution module is used for windowing the signal to be detected by adopting the third window function, and performing discrete Fourier DFT (discrete Fourier transform) on the windowed signal to be detected to obtain a first DFT function;
the second execution module is used for correcting the first DFT function by adopting an interpolation algorithm to obtain a second DFT function;
the third execution module is used for correcting the signal to be detected according to the second DFT function to obtain a corrected signal to be detected;
the third execution module is further used for obtaining signal parameters of the signal to be detected according to the corrected signal to be detected.
6. The harmonic detection method of claim 5, wherein:
the second execution module is further configured to correct the first DFT function by using a four-spectral line interpolation algorithm, so as to obtain a second DFT function.
7. The harmonic detection method of claim 5, wherein:
the third execution module is further configured to modify the modified signal to be detected by using an apFFT algorithm, so as to obtain a signal parameter of the signal to be detected.
8. A harmonic detection system, comprising:
the detection circuit is used for acquiring a signal to be detected;
a harmonic detection apparatus as claimed in any one of claims 5 to 7.
9. An electronic device, characterized in that: comprising a processor, a memory and a program or instructions stored on the memory and executable on the processor, which program or instructions when executed by the processor implement the steps in the harmonic detection method as claimed in any one of claims 1 to 4.
10. A readable storage medium, characterized by: the readable storage medium has stored thereon a program or instructions which, when executed by a processor, implement the steps in the harmonic detection method as claimed in any one of claims 1 to 4.
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