CN115618213A - Charger voltage disturbance analysis method, system, equipment and storage medium - Google Patents
Charger voltage disturbance analysis method, system, equipment and storage medium Download PDFInfo
- Publication number
- CN115618213A CN115618213A CN202211246131.9A CN202211246131A CN115618213A CN 115618213 A CN115618213 A CN 115618213A CN 202211246131 A CN202211246131 A CN 202211246131A CN 115618213 A CN115618213 A CN 115618213A
- Authority
- CN
- China
- Prior art keywords
- frequency
- signal
- charger
- disturbance
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/0084—Arrangements for measuring currents or voltages or for indicating presence or sign thereof measuring voltage only
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a charger voltage disturbance analysis method, a charger voltage disturbance analysis system, a charger voltage disturbance analysis device and a charger voltage disturbance analysis storage medium. And then, performing Hilbert transformation on the plurality of intrinsic modal components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, thereby effectively distinguishing and identifying the voltage disturbance signals of the charger.
Description
Technical Field
The invention relates to the technical field of voltage disturbance analysis, in particular to a charger voltage disturbance analysis method and system, electronic equipment and a computer-readable storage medium.
Background
With the large-scale application of new energy technology in the field of automobiles, the high-speed development of electric automobiles is driven, and under the background of large-scale electric automobile development, an electric automobile charger serving as a matching measure for electric automobile energy charging is also deployed on a large scale and is put into a power grid to operate. The poor electric energy quality can cause huge loss to national industry and resident life, so that the effective division and identification of the electric energy disturbance signal of the electric vehicle charger have important practical significance for improving the electric energy quality problem and improving the safety and stability of an electric power system.
At present, the commonly used electric energy disturbance analysis methods mainly include fast fourier transform, short-time fourier transform, wavelet transform, S transform, hilbert-yellow transform and the like. The fast fourier transform has a good analysis effect on a harmonic component in a steady state, but the fast fourier transform results lose time information, so that the fast fourier transform is not suitable for analyzing non-stationary disturbance signals, and disturbance signals of the charger generally include non-stationary disturbance signals such as voltage sag and voltage interruption, so that the fast fourier transform cannot accurately separate and extract the disturbance signals included in the voltage signals of the charger. Although the short-time fourier transform considers both the time domain information and the frequency domain information, the short-time fourier transform adopts a fixed time window for all frequency components, and the frequencies of different disturbance signals are different, so that the short-time fourier transform cannot accurately separate and extract the disturbance signals. Compared with the fixed resolution of short-time Fourier transform, the wavelet transform has the characteristic of self-adaptive resolution, time windows with different sizes can be selected according to different frequency components, and the wavelet transform has the capability of representing local characteristics of signals more strongly, but a proper wavelet base needs to be selected in advance in the wavelet transform, different wavelet bases can generate different analysis effects on the same disturbance signal, but the type of the disturbance signal in a charger voltage signal cannot be predicted in advance in practical application, so that the disturbance signal contained in the charger voltage signal cannot be accurately separated and extracted through the wavelet transform. The S transform can be understood as a combination of short-time fourier transform and wavelet transform, which is a phase correction of wavelet transform, and also cannot accurately separate and extract disturbance signals included in the charger voltage signal. The Hilbert-Huang transform is a self-adaptive time-frequency analysis method based on data driving, firstly, EMD decomposition is utilized to decompose a signal into a group of intrinsic mode function components in a self-adaptive mode, and then Hilbert transform is utilized to extract instantaneous frequency and instantaneous amplitude of the signal components, but due to the defects of end point effect, mode aliasing and the like, corresponding disturbance signals cannot be accurately identified. Therefore, the traditional time-frequency transformation analysis method cannot accurately separate and extract the disturbance signals contained in the charger voltage signals.
Disclosure of Invention
The invention provides a charger voltage disturbance analysis method and system, electronic equipment and a computer readable storage medium, and aims to solve the technical problem that disturbance signals contained in a charger voltage signal cannot be accurately separated and extracted by a traditional time-frequency transformation analysis method.
According to an aspect of the present invention, there is provided a charger voltage disturbance analysis method, including the following steps:
collecting a charger voltage signal containing a disturbance signal;
carrying out time-frequency transformation on a voltage signal of the charger, and decomposing to obtain a fundamental wave signal and a plurality of intrinsic mode components;
performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain instantaneous amplitude values and instantaneous frequencies of the intrinsic mode components;
and identifying the type of the corresponding disturbance signal according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
Further, the process of performing time-frequency transformation on the voltage signal of the charger and decomposing to obtain a fundamental wave signal and a plurality of intrinsic modal components specifically comprises the following steps:
constructing short-time Fourier transform of a voltage signal of a charger;
constructing a matched instantaneous frequency estimation operator;
performing synchronous compression transformation on the short-time Fourier transformation based on the constructed matching instantaneous frequency estimation operator so as to rearrange the time-frequency coefficient of the short-time Fourier transformation only in the frequency direction;
and reconstructing the signal component of the charger voltage signal based on the short-time Fourier transform after the synchronous compression transform and the constraint condition that the frequency bands of the signal components are not overlapped to obtain a fundamental wave signal and a plurality of intrinsic mode components.
Further, the expression of the matching instantaneous frequency estimation operator is:
wherein the content of the first and second substances,
representing the matching instantaneous frequency estimation operator,
respectively representing an instantaneous frequency estimation operator, a frequency modulation rate estimation operator and a group delay estimation operator, which are defined based on short-time Fourier transform,
g (t, ω) represents the short-time fourier transform of the charger voltage signal, t represents time, and ω represents frequency.
Further, the process of performing synchronous compression transformation on the short-time fourier transform based on the constructed matching instantaneous frequency estimation operator specifically includes:
estimating operator according to constructed matching instantaneous frequency
Mapping time-frequency coefficients of a short-time Fourier transform from (t, ω) to
And obtaining short-time Fourier transform after synchronous compression and transformation, wherein the expression is as follows:
wherein, T m (t, ξ) represent the short-time fourier transform after the synchronous compression transform, ξ represent the angular frequency axis sequence, and δ () represent the discrete sequence.
Further, multiple compression operations are performed during the process of performing synchronous compression transformation to improve the energy concentration of signal time-frequency distribution, and the expression of the multiple compression operations is as follows:
wherein the content of the first and second substances,
is T m (t, ξ), N represents the number of iterations in a multiple compression operation, N ≧ 2, and η represents the overlap ratio.
Further, the reconstruction of the signal components is specifically performed based on the following formula:
where x (t) denotes the reconstructed signal component, d s Represents the width of signal reconstruction, g () represents a window function,
the first derivative of the phase function is represented,
Δ ω representing alternate frequency bins.
Further, when performing N-fold synchronous compression transformation, the corresponding matching instantaneous frequency estimation operator is:
in addition, the invention also provides a charger voltage disturbance analysis system, which comprises:
the signal acquisition module is used for acquiring a charger voltage signal containing a disturbance signal;
the time-frequency transformation module is used for performing time-frequency transformation on the voltage signal of the charger and decomposing the voltage signal to obtain a fundamental wave signal and a plurality of intrinsic modal components;
the disturbance component conversion module is used for performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component;
and the disturbance identification module is used for identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
In addition, the present invention also provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program, and the processor is used for executing the steps of the method by calling the computer program stored in the memory.
In addition, the present invention also provides a computer-readable storage medium for storing a computer program for performing a charger voltage disturbance analysis, where the computer program executes the steps of the method described above when running on a computer.
The invention has the following effects:
according to the charger voltage disturbance analysis method, time-frequency transformation is firstly carried out on a charger voltage signal, time-frequency coefficients are rearranged only in the frequency direction, dispersed time-frequency coefficients are rearranged to correct positions in a time-frequency matrix, the energy concentration degree of signal time-frequency distribution can be effectively improved, a fundamental wave signal and a plurality of intrinsic modal components are obtained through reconstruction according to a time-frequency transformation result, the plurality of intrinsic modal components contained in the charger voltage signal can be accurately separated and extracted, and each intrinsic modal component corresponds to one disturbance component. And then, performing Hilbert transformation on the plurality of intrinsic modal components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, thereby effectively distinguishing and identifying the voltage disturbance signals of the charger.
In addition, the charger voltage disturbance analysis system also has the advantages.
In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a charger voltage disturbance analysis method according to a preferred embodiment of the present invention.
Fig. 2 is a schematic circuit diagram of a conventional charger.
Fig. 3 is a schematic view of a sub-flow of step S2 in fig. 1.
FIG. 4 is a schematic time-domain waveform of a harmonic disturbance simulation signal according to an embodiment of the present invention.
Fig. 5 is a diagram illustrating the results of the mmstt analysis of the harmonic disturbance simulation signal of fig. 4.
FIG. 6 is a graphical representation of the results of EMD analysis of the harmonic disturbance simulation signal of FIG. 4.
FIG. 7 is a schematic time-domain waveform of a voltage sag disturbance simulation signal according to an embodiment of the invention.
Fig. 8 is a schematic diagram of the IMF component and the corresponding Hilbert transform obtained by the MMSST analysis of the voltage sag disturbance simulation signal in fig. 7.
FIG. 9 is a diagram illustrating IMF components and corresponding Hilbert transform results of EMD analysis of the voltage sag disturbance simulation signal of FIG. 7.
Fig. 10 is a schematic diagram of amplitude and frequency parameters obtained by using the mmstt analysis and the EMD analysis under different signal-to-noise ratios in an embodiment of the present invention.
Fig. 11 is a schematic time-domain waveform diagram of a charger voltage signal collected on site in another embodiment of the present invention.
Fig. 12 is a schematic diagram of a decomposition result of a charger voltage signal acquired on site by using MMSST analysis according to another embodiment of the present invention.
Fig. 13 is a schematic diagram illustrating an analysis result of EMD analysis performed on a charger voltage signal collected on site according to another embodiment of the present invention.
Fig. 14 is a schematic diagram of the instantaneous frequency of each IMF component obtained by performing EMD decomposition on a charger voltage signal collected on site according to another embodiment of the present invention.
Fig. 15 is a schematic block diagram of a charger voltage disturbance analysis system according to another embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be practiced in many different ways, which are defined and covered by the following.
As shown in fig. 1, a preferred embodiment of the present invention provides a charger voltage disturbance analysis method, which includes the following steps:
step S1: collecting a charger voltage signal containing a disturbance signal;
step S2: carrying out time-frequency transformation on a voltage signal of the charger, and decomposing to obtain a fundamental wave signal and a plurality of intrinsic mode components;
and step S3: performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain instantaneous amplitude values and instantaneous frequencies of the intrinsic mode components;
and step S4: and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
It can be understood that, according to the charger voltage disturbance analysis method of the embodiment, the time-frequency transformation is performed on the charger voltage signal, the time-frequency coefficients are rearranged only in the frequency direction, the dispersed time-frequency coefficients are rearranged to correct positions in the time-frequency matrix, the energy concentration of the signal time-frequency distribution can be effectively improved, the fundamental wave signal and the plurality of intrinsic modal components are obtained through reconstruction according to the time-frequency transformation result, the plurality of intrinsic modal components contained in the charger voltage signal can be accurately separated and extracted, and each intrinsic modal component corresponds to one disturbance component. And then, performing Hilbert transformation on the plurality of intrinsic modal components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, thereby effectively distinguishing and identifying the voltage disturbance signals of the charger.
It will be understood that the charger commonly used at present consists of an uncontrolled rectifier device and a DC/DC converter, as shown in fig. 2, the three-phase uncontrolled rectifier device rectifying the three-phase alternating current through a resistor R f Inductor L f And a capacitor C f After the formed filter current is filtered, direct current input is provided for the DC/DC power conversion device, and then the direct current input is used for charging the storage battery of the electric automobile after passing through the output filter circuit. Because the charger adopts a three-phase bridge type uncontrolled rectifying circuit, harmonic current on the alternating current side of the charger is mainly 6k +/-1 times, k =1,2,3 and …, namely 5 times, 7 times, 11 times, 13 times and the like, and the higher the harmonic frequency is, the smaller the effective value is. Moreover, because the power factor of the electric vehicle charging station is relatively low, as the charging load of the electric vehicle increases, the reactive transmission of the electric vehicle also increases correspondingly, and the line impedance in the power distribution network is relatively large and cannot be ignored, if a large number of electric vehicles are charged by the charger at the same time, the system load increases, and the problem of obvious electric energy quality such as voltage drop can also be caused. Therefore, the charger serves as a nonlinear load, a rectifying device of the charger can bring harmonic interference to a power grid, the harmonic output characteristics of the charging station are more complex due to the fact that the number of the chargers used in the charging station and the charging mode are constantly changed, and meanwhile the problem of voltage drop caused by large-scale charging use is solved. Therefore, the method has important significance for analyzing and identifying the power quality problem caused by the charger to the power grid and improving the safety and stability of the power system.
In addition, the voltage disturbance signal generated by the charger is composed of a fundamental wave signal of 50Hz and each disturbance component, and can be expressed as:
wherein A is k 、ω k 、φ k Respectively representing the amplitude, frequency and initial phase of the kth disturbance component.
It can be understood that, as shown in fig. 3, the process of performing time-frequency transformation on the voltage signal of the charger in step S2 and obtaining the fundamental wave signal and the plurality of intrinsic modal components by decomposition specifically includes:
step S21: constructing short-time Fourier transform of a voltage signal of a charger;
step S22: constructing a matched instantaneous frequency estimation operator;
step S23: performing synchronous compression transformation on the short-time Fourier transformation based on the constructed matching instantaneous frequency estimation operator so as to rearrange the time-frequency coefficient of the short-time Fourier transformation only in the frequency direction;
step S24: and reconstructing the signal component of the charger voltage signal based on the short-time Fourier transform after the synchronous compression transform and the constraint condition that the frequency bands of the signal components are not overlapped to obtain a fundamental wave signal and a plurality of intrinsic mode components.
Specifically, for a collected charger voltage signal x (u), establishing short-time fourier transform thereof, wherein the expression is as follows:
where g () represents a real symmetric window function.
Due to the existence of the bandwidth of the window function, the time-frequency coefficient of the short-time Fourier transform of the charger voltage signal is distributed around the real signal frequency, and the purpose of synchronous compression transform is to rearrange the dispersed time-frequency coefficient to the correct position in the time-frequency matrix.
Therefore, a Matching Instantaneous Frequency estimator (MIF) is defined from the short-time fourier transform result, and the expression of the Matching Instantaneous Frequency estimator is:
wherein the content of the first and second substances,
representing the matching instantaneous frequency estimation operator,
respectively representing an instantaneous frequency estimation operator, a frequency modulation rate estimation operator and a group delay estimation operator, which are defined based on short-time Fourier transform,
g (t, ω) represents the short-time fourier transform of the charger voltage signal, t represents time, ω represents frequency.
The matched instantaneous frequency estimation operator constructed by the invention combines the group delay estimation operator and the frequency modulation rate estimation operator on the basis of the conventional instantaneous frequency estimation operator, thereby effectively improving the time-frequency resolution and more truly reflecting the time-frequency characteristics of non-stationary signals.
Then, based on the constructed matching instantaneous frequency estimation operator, synchronous compression transformation is carried out on the short-time Fourier transform, and the specific process is as follows:
estimating operators from constructed matching instantaneous frequencies
Mapping time-frequency coefficients of a short-time Fourier transform from (t, ω) to
And obtaining short-time Fourier transform after synchronous compression and transformation, wherein the expression is as follows:
wherein, T m (t, ξ) represents a short-time fourier transform after the synchronous compression transform, ξ represents an angular frequency axis sequence, and δ () represents a discrete sequence.
It will be appreciated that the time-frequency coefficients are mapped from (t, ω) to the short-time Fourier transform by mapping the time-frequency coefficients from (t, ω)
Compared with the traditional linear time-frequency transformation, the method can effectively improve the energy concentration of signal time-frequency distribution, and for pure harmonic signals or components which can be locally approximate to harmonic signals, the matched instantaneous frequency estimation operator is almost unbiased, and an almost ideal time-frequency representation can be obtained.
In addition, the synchronous compression transformation has a good identification effect on weak frequency modulation disturbance signals such as harmonic waves, but for strong frequency modulation disturbance signals such as voltage flicker, voltage oscillation and the like, a large deviation exists between an instantaneous frequency estimation obtained by the synchronous compression transformation and a true frequency of the signal, so that a fuzzy time-frequency coefficient cannot be rearranged to a correct position, and the time-frequency resolution cannot be improved. Therefore, as a preferable mode, multiple compression operations are performed during the synchronous compression transformation to improve the energy concentration of the time-frequency distribution of the signal, and the expression of the multiple compression operations is:
wherein the content of the first and second substances,
is T m (t, ξ), N represents the number of iterations in the multiple compression operation, N ≧ 2, and η represents the overlap ratio. When N-fold synchronous compression transformation is carried out, the corresponding matched instantaneous frequency estimation operator is as follows:
the MIF estimation operator is provided to rearrange the time-frequency coefficient of the short-time Fourier transform, the energy concentration precision of signal time-frequency distribution is effectively improved, multiple compression operation is introduced to iteratively update the MIF estimation operator, and the updating process of the MIF estimation operator is also the rearranging process of the time-frequency coefficient each time, so that the accuracy of the MIF estimation operator is greatly improved through the iterative updating of the MIF estimation operator and the iterative rearrangement of the time-frequency coefficient, the estimation error is remarkably reduced, for emphasizing frequency disturbance signals, the time-frequency resolution is greatly improved, and strong frequency modulation disturbance components can be accurately separated and extracted.
Then, according to the short-time Fourier transform after the multiple matching synchronous compression transform, with the condition that the frequency bands of the signal components are not overlapped as a constraint condition, reconstructing the signal components based on the following formula:
where x (t) represents the reconstructed signal component, i.e. the implicit modal component, d s Representing the width of the signal reconstruction, g () representing a window function,
the first derivative of the phase function is represented,
Δ ω representing alternate frequency bins.
It can be understood that, on the basis of the analysis result of the multiple matching synchronous compression transformation, by means of reasonable frequency band division and by means of the reconstruction formula, the present invention can accurately separate and extract each intrinsic modal component in the charger voltage signal from the time-frequency result of the multiple matching synchronous compression transformation, and subsequently measure the parameter of each intrinsic modal component, so that each disturbance signal component contained in the charger voltage signal can be effectively identified, and accurate disturbance identification is realized.
It can be understood that, in the step S2, each intrinsic mode component of the charger voltage signal is extracted based on the multiple matching synchronous compression transformation, and each intrinsic mode component corresponds to a different disturbance component, and in order to identify the disturbance components of different types, only the amplitude information and the frequency information of each disturbance component need to be calculated.
In step S3 and step S4, hilbert transform is respectively applied to each extracted intrinsic mode component:
and constructing an analytic signal:
then the instantaneous amplitude A k And instantaneous phase phi k Respectively as follows:
instantaneous frequency omega k Comprises the following steps:
then, the corresponding disturbance signal type can be identified according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
It can be understood that, in order to verify the effectiveness of the charger voltage disturbance analysis method based on the multiple matching synchronous compression transformation, the method adopts an Empirical Mode Decomposition (EMD) algorithm to compare with the battery voltage disturbance analysis method, and performs simulation analysis on two types of disturbance signals, namely voltage disturbance containing harmonic signals and voltage disturbance containing voltage sag. The specific process is as follows:
the voltage signal containing harmonic disturbance has the expression:
s(t)＝380sin(2π50t)+75sin(2π250t)+65sin(2π350t)+55sin(2π550t)。
sampling frequency f of signal s 4096Hz, sample points 4096, signal to Noise Ratio (SNR) set to 20Db, and in order to simulate real-world conditions, the amplitude of the harmonic componentsThe time domain waveform of the simulated signal decreases as the number of harmonics increases as shown in figure 4.
Firstly, voltage signals containing harmonic disturbance are respectively subjected to MMSST (Multiple Matching synchronous compressing Transform) and EMD (empirical mode decomposition) analysis, and IMF (intrinsic mode function) components obtained by the two methods are respectively shown in FIGS. 5 and 6. The result shows that the MMSST can effectively separate each harmonic component, the decomposition effect is good, the EMD can not effectively decompose all the harmonic components, the EMD only effectively separates the fundamental component of 50Hz, the decomposed IMF1 and IMF2 components are not fixed values, and the frequency variation range of the IMF1 is 400-1000 Hz and the frequency variation range of the IMF2 is 200-300 Hz, which is known from Hilbert transformation. The amplitude frequencies of the components extracted by MMSST and EMD are shown in Table 1, and the results show that the MMSST method provided by the invention can effectively separate the components containing harmonic disturbance, the resolution accuracy is high, and the EMD can not effectively separate all the components and the modal aliasing phenomenon exists.
Table 1, MMSST and EMD component parameter detection results
The voltage signal expression containing the voltage sag is:
s(t)＝[1-0.55(u(t-0.45)-u(t-0.75))]cos(100πt)。
sampling frequency f of voltage containing voltage sag s 4096Hz, the signal length is 4096 samples, the signal-to-noise ratio is set to 20dB, and the time domain waveform of the signal is shown in figure 7. The results of the IMF component obtained by the mmstt analysis and the Hilbert transform of the component are shown in fig. 8, and the voltage sag disturbance occurring in the voltage signal can be obviously found from the amplitude curve of the decomposed modal component. And 6 IMF components are obtained through EMD decomposition, wherein the IMF component of the 3 rd IMF component is related to the voltage sag disturbance, and the time domain waveform and the corresponding Hilbert transformation result are shown in figure 9. From the decomposed IMF componentVoltage sag phenomenon of the voltage signal can be found in the time domain waveform, but compared with the IMF component extracted by MMSST, the IMF component extracted by EMD is distorted in the voltage sag process. In addition, the frequency and amplitude parameters of disturbance estimated after the IMF components decomposed by MMSST and EMD are subjected to Hilbert transformation are shown in Table 2, and from the result, the error between the frequency estimated by EMD and the real frequency of the signal is large, and the frequency estimated by MMSST is very close to the real power frequency. Since the estimated parameter is the average value of the instantaneous amplitude obtained in the voltage sag process, although the instantaneous amplitude estimated by EMD and the instantaneous amplitude estimated by MMSST are close, the IMF component decomposed by MMSST is closer to a real signal as can be seen from the instantaneous amplitude curves of the Hilbert transform of the EMD and the MMSST, and the IMF decomposed by EMD has signal distortion.
Table 2, MMSST and EMD component parameter detection results
Finally, in order to verify the robustness of the algorithm provided herein, the parameter estimation accuracy of the two methods under different signal-to-noise ratios is respectively tested, the analysis result is shown in fig. 10, and for frequency estimation, the frequency estimation parameter obtained by the mmstt can obtain a very accurate result no matter under the conditions of low signal-to-noise ratio or high signal-to-noise ratio, and the frequency parameter obtained by the EMD is greatly influenced by noise. For the amplitude parameter estimation, the accuracy of the parameter estimation obtained by MMSST is slightly reduced with the reduction of the signal-to-noise ratio, but still within an acceptable range, while the amplitude parameter obtained by EMD is greatly influenced by noise as well as the frequency parameter, and in some cases, the EMD cannot accurately resolve the dip disturbance due to the influence of the noise, so that signal distortion occurs, and the parameter obtained by Hilbert transform has larger deviation.
In addition, the MMSST method and the existing EMD method of the invention are respectively adopted to identify the disturbing signals of the charger voltage signals collected on site, the measuring equipment comprises a portable instrument TD1320 and a direct current adjustable resistive load box TK4830, the portable instrument TD1320 is used for detecting the direct current charger of the electric vehicle on site, the TD1320 is used for measuring the voltage signals of the charger, the sampling frequency of the signals is 2000Hz, the sampling time is 1s, and the time domain waveform of the collected charger voltage signals is shown in figure 11.
The collected charger voltage signals are respectively subjected to MMSST decomposition and EMD decomposition, and the obtained decomposition results are respectively shown in fig. 12 and 13. From the results, MMSST decomposes the voltage signal into 5 IMF components, and the resulting 5 IMF components are all pure harmonic signals, and the frequency and amplitude of each IMF component obtained by the Hilbert transform are shown in table 3.
TABLE 3 MMSST parameter estimation results
As can be seen from table 3, the charger voltage signal has 3 rd, 7 th, and 13 th harmonics and 120Hz inter-harmonics besides the fundamental signal, so that the mmstt algorithm can effectively decompose each harmonic and inter-harmonic component in the charger voltage signal. The EMD decomposes the acquired voltage signal into 6 IMF components, and Hilbert transform is performed on the 6 IMF components to obtain the instantaneous frequency of each IMF component, as shown in fig. 14, where the instantaneous frequencies of IMF1, IMF2, and IMF3 fluctuate with time, and the instantaneous frequencies of IMF4, IMF5, and IMF6 are stable, but the frequencies of the three components are all lower than 50Hz, as can be seen from the decomposition property of the EMD, the latter three IMF components are false, and no component with a large amplitude below 50Hz is found after fourier transformation is performed on the charger voltage signal, so that the EMD decomposition cannot effectively decompose and detect whether the charger voltage signal contains harmonic and inter-harmonic signals.
Therefore, as can be seen from the simulation analysis result and the field signal detection result, compared with the conventional EMD decomposition, the charger disturbance signal analysis method based on the multiple matching synchronous compression transformation (MMSST) of the present invention has a more accurate modal decomposition capability, can more accurately extract the fundamental wave signal and various disturbance signals in the disturbance signals, and does not have the problems of modal aliasing and signal distortion.
In addition, as shown in fig. 15, another embodiment of the present invention further provides a charger voltage disturbance analysis system, preferably adopting the method described above, including:
the signal acquisition module is used for acquiring a charger voltage signal containing a disturbance signal;
the time-frequency transformation module is used for performing time-frequency transformation on the voltage signal of the charger and decomposing the voltage signal to obtain a fundamental wave signal and a plurality of intrinsic modal components;
the disturbance component conversion module is used for performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component;
and the disturbance identification module is used for identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
It can be understood that, the charger voltage disturbance analysis system of this embodiment performs time-frequency transformation on the charger voltage signal, rearranges the time-frequency coefficients only in the frequency direction, rearranges the dispersed time-frequency coefficients to the correct positions in the time-frequency matrix, can effectively improve the energy concentration of the signal time-frequency distribution, reconstructs the fundamental wave signal and the multiple intrinsic modal components according to the time-frequency transformation result, can accurately separate and extract the multiple intrinsic modal components contained in the charger voltage signal, and each intrinsic modal component corresponds to one disturbance component. And then, performing Hilbert transformation on the plurality of intrinsic modal components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic modal component, thereby effectively distinguishing and identifying the voltage disturbance signals of the charger.
It can be understood that each module in the system of this embodiment corresponds to each step of the method embodiment, and therefore specific working principles and working processes of each module are not described herein again, and reference may be made to the method embodiment.
In addition, another embodiment of the present invention further provides an electronic device, which includes a processor and a memory, wherein the memory stores a computer program, and the processor is used for executing the steps of the method described above by calling the computer program stored in the memory.
In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for performing charger voltage disturbance analysis, where the computer program executes the steps of the method described above when running on a computer.
Typical forms of computer-readable storage media include: floppy disk (floppy disk), flexible disk (flexible disk), hard disk, magnetic tape, any of its magnetic media, CD-ROM, any of the other optical media, punch cards (punch cards), paper tape (paper tape), any of the other physical media with patterns of holes, random Access Memory (RAM), programmable Read Only Memory (PROM), erasable Programmable Read Only Memory (EPROM), FLASH erasable programmable read only memory (FLASH-EPROM), any of the other memory chips or cartridges, or any of the other media from which a computer can read. The instructions may further be transmitted or received by a transmission medium. The term transmission medium may include any tangible or intangible medium that is operable to store, encode, or carry instructions for execution by the machine, and includes digital or analog communications signals or intangible medium that facilitates communication of the instructions. Transmission media include coaxial cables, copper wire and fiber optics, including the wires that comprise a bus for transmitting a computer data signal.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A charger voltage disturbance analysis method is characterized by comprising the following steps:
collecting a charger voltage signal containing a disturbance signal;
carrying out time-frequency transformation on a voltage signal of the charger, and decomposing to obtain a fundamental wave signal and a plurality of intrinsic mode components;
performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain instantaneous amplitude values and instantaneous frequencies of the intrinsic mode components;
and identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
2. The method for analyzing voltage disturbance of the charger according to claim 1, wherein the process of performing time-frequency transformation on the voltage signal of the charger and decomposing the voltage signal to obtain a fundamental wave signal and a plurality of intrinsic mode components specifically comprises the following steps:
constructing short-time Fourier transform of a charger voltage signal;
constructing a matched instantaneous frequency estimation operator;
performing synchronous compression transformation on the short-time Fourier transformation based on the constructed matching instantaneous frequency estimation operator so as to rearrange the time-frequency coefficient of the short-time Fourier transformation only in the frequency direction;
and reconstructing the signal component of the charger voltage signal based on the short-time Fourier transform after the synchronous compression transform and the constraint condition that the frequency bands of the signal components are not overlapped to obtain a fundamental wave signal and a plurality of intrinsic mode components.
3. The charger voltage disturbance analysis method according to claim 2, characterized in that the expression of the matching instantaneous frequency estimation operator is:
wherein the content of the first and second substances,
representation matchingAn instantaneous frequency estimation operator for estimating the frequency of the signal,
respectively representing an instantaneous frequency estimation operator, a frequency modulation rate estimation operator and a group delay estimation operator, which are defined based on short-time Fourier transform,
g (t, ω) represents the short-time fourier transform of the charger voltage signal, t represents time, and ω represents frequency.
4. The charger voltage disturbance analysis method according to claim 3, wherein the process of performing synchronous compression transformation on the short-time Fourier transform based on the constructed matching instantaneous frequency estimation operator specifically comprises:
estimating operators from constructed matching instantaneous frequencies
Mapping time-frequency coefficients of short-time Fourier transform from (t, omega) to
And obtaining short-time Fourier transform after synchronous compression and transformation, wherein the expression is as follows:
wherein, T m (t, ξ) represents a short-time fourier transform after the synchronous compression transform, ξ represents an angular frequency axis sequence, and δ () represents a discrete sequence.
5. The charger voltage disturbance analysis method according to claim 4, characterized in that multiple compression operations are performed during the synchronous compression transformation to improve the energy concentration of the signal time-frequency distribution, and the expression of the multiple compression operations is:
wherein, the first and the second end of the pipe are connected with each other,
is T m (t, ξ), N represents the number of iterations in a multiple compression operation, N ≧ 2, and η represents the overlap ratio.
6. The charger voltage disturbance analysis method according to claim 5, characterized in that the reconstruction of the signal components is performed specifically based on the following formula:
where x (t) denotes the reconstructed signal component, d s Representing the width of the signal reconstruction, g () representing a window function,
the first derivative of the phase function is represented,
Δ ω are spaced frequency bins.
7. The charger voltage disturbance analysis method according to claim 6, characterized in that when performing N-resynchronized compression transformation, the corresponding matching instantaneous frequency estimation operator is:
8. a charger voltage disturbance analysis system is characterized by comprising:
the signal acquisition module is used for acquiring a charger voltage signal containing a disturbance signal;
the time-frequency transformation module is used for performing time-frequency transformation on the voltage signal of the charger and decomposing the voltage signal to obtain a fundamental wave signal and a plurality of intrinsic modal components;
the disturbance component conversion module is used for performing Hilbert transformation on the plurality of intrinsic mode components respectively to obtain the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component;
and the disturbance identification module is used for identifying the corresponding disturbance signal type according to the instantaneous amplitude and the instantaneous frequency of each intrinsic mode component.
9. An electronic device, characterized in that it comprises a processor and a memory, in which a computer program is stored, said processor being adapted to carry out the steps of the method according to any one of claims 1 to 7 by invoking said computer program stored in said memory.
10. A computer-readable storage medium for storing a computer program for performing a charger voltage disturbance analysis, characterized in that the computer program, when running on a computer, performs the steps of the method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211246131.9A CN115618213A (en) | 2022-10-12 | 2022-10-12 | Charger voltage disturbance analysis method, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211246131.9A CN115618213A (en) | 2022-10-12 | 2022-10-12 | Charger voltage disturbance analysis method, system, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115618213A true CN115618213A (en) | 2023-01-17 |
Family
ID=84861881
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211246131.9A Pending CN115618213A (en) | 2022-10-12 | 2022-10-12 | Charger voltage disturbance analysis method, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115618213A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116125235A (en) * | 2023-04-14 | 2023-05-16 | 南昌工程学院 | GIS partial discharge fault diagnosis method based on ultrasonic signals |
| CN116226766A (en) * | 2023-05-08 | 2023-06-06 | 南洋电气集团有限公司 | High-voltage electrical apparatus running state monitoring system |
-
2022
- 2022-10-12 CN CN202211246131.9A patent/CN115618213A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116125235A (en) * | 2023-04-14 | 2023-05-16 | 南昌工程学院 | GIS partial discharge fault diagnosis method based on ultrasonic signals |
| CN116226766A (en) * | 2023-05-08 | 2023-06-06 | 南洋电气集团有限公司 | High-voltage electrical apparatus running state monitoring system |
| CN116226766B (en) * | 2023-05-08 | 2023-08-18 | 南洋电气集团有限公司 | High-voltage electrical apparatus running state monitoring system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115618213A (en) | Charger voltage disturbance analysis method, system, equipment and storage medium | |
| CN107329932B (en) | Time-frequency domain modal parameter identification method based on nonlinear frequency modulation component decomposition | |
| Gu et al. | Estimating interharmonics by using sliding-window ESPRIT | |
| Song et al. | Second generation wavelet transform for data denoising in PD measurement | |
| CN107543962B (en) | Calculation method of dominant inter-harmonic frequency spectrum distribution | |
| CN110389312B (en) | Calibrator phasor measurement method suitable for field PMU test | |
| Bruna et al. | Selection of the most suitable decomposition filter for the measurement of fluctuating harmonics | |
| CN108197073B (en) | Improved electric vehicle charging electric energy signal characteristic analysis method | |
| CN111398814A (en) | Motor fault detection and intelligent rapid diagnosis method controlled by soft starter | |
| CN104655965B (en) | A kind of phasor measurement method in power system | |
| Amin et al. | Differential equation fault location algorithm with harmonic effects in power system | |
| Zhu et al. | A novel voltage sag detection method for analyzing charging quality of electric vehicle | |
| Zhang et al. | Application of signal processing techniques to on-line partial discharge detection in cables | |
| Rodrigues et al. | Low-cost embedded measurement system for power quality frequency monitoring | |
| CN108334822B (en) | Kalman and modified wavelet transform filtering method based on electric vehicle charging nonlinear load characteristics | |
| CN112729531B (en) | Fault studying and judging method and system for distribution transformer equipment | |
| CN113095170B (en) | Fault diagnosis method based on adjustable Q wavelet motor | |
| CN113092931A (en) | Power grid harmonic source positioning detection method | |
| CN113740678A (en) | Noise reduction method and system suitable for corona current measurement data | |
| Goryunov et al. | The application of wavelet transform for identification of single phase to earth fault in power system | |
| Shadmehr et al. | Beyond FFT algorithm in analyzing harmonics at frequency range of 2 kHz to 500 kHz | |
| CN114184838A (en) | Power system harmonic detection method, system and medium based on SN mutual convolution window | |
| Li et al. | A simple and fast measurement algorithm for power system flicker severity evaluation | |
| Li-Xue et al. | Partial discharge diagnosis on GIS based on envelope detection | |
| CN113092850B (en) | Time-frequency spectrum analysis method and system for simplifying S transformation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |