Novel inrush current-free switching device and control method thereof

Abstract

The invention relates to the technical field of inrush current-free switching control, in particular to a novel inrush current-free switching device and a control method thereof, and the method comprises the steps: obtaining the data of each electrical parameter on a diode circuit; performing frequency domain analysis on the data of each electrical parameter, performing clustering processing on the frequency domain data of each electrical parameter, calculating frequency complexity and intra-cluster confusion degree of each cluster, further obtaining noise distribution difference degree of each electrical parameter, and obtaining noise distribution complexity of each electrical parameter in combination with an average level of the intra-cluster confusion degree of all the cluster clusters; analyzing principal components of modal components of the electrical parameters, obtaining steady-state change factors of the electrical parameters in combination with noise distribution complexity, adjusting step length factors of a filter, filtering data of the electrical parameters on a diode circuit, and controlling a relay according to the filtered electrical parameter data, so as to complete inrush current-free switching control of the capacitor. According to the invention, the control precision of non-inrush current switching can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of surge-free switching control, and in particular to a novel surge-free switching device and a control method thereof. Background Art

[0002] Due to the need for reactive power compensation in the power grid, capacitors need to be put into the power grid or removed from the power grid at the right time through relays to reduce energy waste, improve the effective utilization of electric energy, and ensure the stable operation of the power grid. At present, the microcontroller analyzes the half-wave conduction characteristics of the diode through the current and voltage on the diode circuit, and controls the relay to operate and remove the relay without inrush current under half-wave conduction, thereby realizing the capacitor switching in the power grid to reduce energy waste and improve the effective utilization of electric energy.

[0003] However, during the inrush current switching control process, the capacitor needs to be frequently switched according to the current and voltage conditions in the diode. However, due to the background noise interference in the actual power grid, these background noises will seriously interfere with the current and voltage in the diode circuit, causing the current and voltage in the diode circuit to deviate from normal values, affecting the accuracy of subsequent inrush current switching control, and unable to ensure the safety of the capacitor and the service life of the switching device. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a new type of inrush current switching device and a control method thereof. The technical solutions adopted are as follows: The embodiment of the present application provides a novel inrush current switching control method, comprising the following steps: Obtaining data of various electrical parameters on the diode circuit, the electrical parameters including current and voltage; Perform frequency domain analysis on the data of each electrical parameter, and perform clustering processing on the frequency domain data of each electrical parameter respectively; For each electrical parameter, the frequency change and fluctuation degree of the frequency domain data within each cluster are analyzed to obtain the frequency complexity of each cluster. Combined with the amplitude change of the frequency domain data within each cluster, the intra-cluster chaos of each cluster is obtained. According to the differences in the average frequency level of the frequency domain data within the cluster and the average amplitude level of the frequency domain data within the cluster, the noise distribution difference of each electrical parameter is obtained. Combined with the average level of the intra-cluster chaos of all clusters, the noise distribution complexity of each electrical parameter is obtained. Performing modal decomposition on the data of each electrical parameter and performing principal component analysis on the modal components, obtaining the steady-state variation factor of each electrical parameter in combination with the complexity of the noise distribution, and adjusting the step size factor of the filter according to the steady-state variation factor and the autocorrelation characteristics of the data of each electrical parameter; The data of each electrical parameter on the diode circuit is filtered based on the adjusted step factor, and the relay is controlled according to the filtered electrical parameter data, thereby completing the inrush current-free switching control of the capacitor.

[0005] Preferably, the frequency complexity of each cluster is obtained by: The frequencies of all frequency domain data in each cluster are arranged in ascending order to form the frequency sequence of each cluster. The product of the mean and variance of all elements in the first-order difference sequence of the frequency sequence is taken as the frequency complexity of each cluster.

[0006] Preferably, the method for obtaining the intra-cluster chaos degree of each cluster is: calculating the information entropy of the frequency domain data amplitude within each cluster, and taking the product of the information entropy and the frequency complexity as the intra-cluster chaos degree of each cluster.

[0007] Preferably, the calculation method of the noise distribution difference of each electrical parameter is: The calculation formula of the current noise distribution difference is: ; In the formula, is the noise distribution difference of the current, is the number of clusters of all frequency domain data points in the current time series, and are the frequency means of all frequency domain data points in the i-th and i-1-th clusters, respectively. and are the mean frequency domain amplitudes of all frequency domain data points in the i-th and i-1-th clusters, respectively.

[0008] Preferably, the method for constructing the current time series is: arranging the currents within a preset time period before the current moment in chronological order to obtain the current time series.

[0009] Preferably, the noise distribution complexity of each electrical parameter is obtained by taking the product of the mean of the intra-cluster chaos of all clusters corresponding to each electrical parameter and the noise distribution difference as the noise distribution complexity of each electrical parameter.

[0010] Preferably, the calculation method of the steady-state change factor of each electrical parameter is: For current data, the calculation formula of the steady-state change factor V of the current is: ; In the formula, is the noise distribution complexity of the current, is the mean of the variance contribution rates of all principal components in the modal matrix corresponding to the current time series, To avoid constants with zero denominators.

[0011] Preferably, the method for acquiring the modal matrix corresponding to the current time series is: performing modal decomposition on the current time series, taking each modal component as each row vector, and forming the modal matrix corresponding to the current time series.

[0012] Preferably, the adjusted step size factor is calculated as follows: ; In the formula, is the step size factor of the adjusted LMS adaptive filter, To find the integral function upward, is the maximum eigenvalue in the autocorrelation matrix of the current time series and the voltage time series, is an exponential function with a natural constant as base, and are the steady-state change factors of current and voltage respectively.

[0013] An embodiment of the present application also provides a novel inrush current switching device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of the novel inrush current switching control method described in any one of the above items are implemented.

[0014] From the above, it can be seen that the novel non-surge current switching device and control method thereof provided by the present application have at least the following beneficial effects: The present application performs cluster analysis on the frequency domain data of the electrical parameters in the diode circuit, and uses intra-cluster analysis and inter-cluster analysis methods to accurately measure the distribution complexity characteristics of the frequency domain noise, so that the step size factor of the LMS adaptive filter can be adjusted more accurately in the subsequent step. This application takes into account the distribution complexity characteristics of frequency domain noise and the variance contribution rate characteristics of modal components, accurately measures the steady-state change characteristics of electrical parameters in the diode circuit, and accurately adjusts the step size factor in the LMS adaptive filter through the steady-state change characteristics of electrical parameters in the diode circuit, thereby eliminating the interference of complex noise in the actual power grid on subsequent switching control; The present application eliminates the complex background noise in the actual power grid by accurately adjusting the step factor in the LMS adaptive filter, thereby improving the accuracy of controlling the inrush current-free switching, and can effectively ensure the safety of the capacitor and the service life of the switching device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flow chart of the steps of a novel inrush current switching control method provided in this application. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of a new type of non-surge switching device and its control method proposed in accordance with the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless otherwise specified and limited, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application.

[0019] The specific scheme of a novel surge-free switching device and a control method thereof provided by the present application is described in detail below with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flow chart of a novel inrush current switching control method provided by an embodiment of the present application, comprising the following steps: Step 1: Obtain electrical parameter data on the diode circuit, the electrical parameters including current and voltage.

[0021] In the control method for inrush-free switching, it is first necessary to filter the electrical parameters of the diode circuit to eliminate the interference of complex noise in the actual power grid on subsequent switching control, thereby improving the accuracy of subsequent control of inrush-free switching, wherein the electrical parameters in this embodiment include current and voltage.

[0022] In order to improve the accuracy of inrush-free switching control, the current and voltage on the diode circuit are collected through current sensors and voltage sensors with a collection frequency of 1kHz. In actual application scenarios, implementers can set the sampling frequency by themselves.

[0023] Furthermore, in order to improve the accuracy of filtering the current and voltage on the diode circuit by the adaptive filter, the current and voltage within one minute before the current moment are sorted in chronological order to obtain a current time series and a voltage time series.

[0024] Step 2: Perform frequency domain analysis on the data of each electrical parameter, and perform clustering processing on the frequency domain data of each electrical parameter respectively.

[0025] In order to improve the accuracy of capacitor no-inrush switching control, the current signal and voltage signal on the diode circuit are filtered by LMS adaptive filter to eliminate the interference of complex noise in the actual power grid on the subsequent no-inrush switching control.

[0026] However, due to the complexity of noise interference in the actual power grid, it is necessary to adjust the step size factor of the LMS adaptive filter according to the complex noise interference characteristics on the current and voltage in the diode circuit, in order to improve the accuracy of filtering the current and voltage on the diode circuit, so as to more accurately control the inrush-free operation and removal operation of the relay under half-wave conduction, and realize the capacitor switching on and off the power grid.

[0027] The frequency domain characteristics of the current and voltage in the diode circuit are analyzed. There are many existing frequency domain transformation methods, among which Fourier transform includes discrete Fourier transform or fast Fourier transform. The current time series is input into the Fourier transform. This embodiment uses fast Fourier transform to obtain all frequency domain data in the current time series. The horizontal axis of the frequency domain data is frequency, and the vertical axis is the frequency domain amplitude. Fourier transform is a well-known technology, and the specific process will not be repeated here.

[0028] Furthermore, in order to accurately analyze the complex distribution characteristics of noise under the influence of noise interference, so as to more accurately adjust the step size factor of the LMS adaptive filter, all frequency domain data in the current time series are input into the clustering algorithm. The clustering algorithm can be DBSCAN clustering or DPC density peak clustering. This embodiment uses DPC density peak clustering to obtain each clustering cluster of all frequency domain data in the current time series. DPC density peak clustering is a well-known technology and will not be elaborated on in detail.

[0029] By using a clustering algorithm to perform cluster analysis on frequency domain data, it is possible to accurately analyze the complex analysis of the frequency domain amplitudes corresponding to different frequencies in the current time series, which can be used to more accurately adjust the step size factor of the LMS adaptive filter in the subsequent process, so as to eliminate the interference of complex noise in the actual power grid on the subsequent switching control, thereby improving the accuracy of the inrush current switching control.

[0030] Step 3: For each electrical parameter, analyze the frequency change and fluctuation degree of the frequency domain data within each cluster to obtain the frequency complexity of each cluster. Combined with the amplitude change of the frequency domain data within each cluster, obtain the intra-cluster chaos of each cluster. According to the differences in the average frequency level and the average amplitude level of the frequency domain data within the cluster among different clusters, obtain the noise distribution difference of each electrical parameter. Combined with the average level of chaos within all clusters, obtain the noise distribution complexity of each electrical parameter.

[0031] The greater the complex interference to the current in the diode circuit in the power grid environment, the higher the complexity of the frequency domain data within the same cluster in the clustering result of the frequency domain data, and the greater the difference in the frequency domain data between different clusters, the more it can reflect the complex characteristics of the noise distribution under the influence of noise interference.

[0032] Furthermore, the frequencies of all frequency domain data in each cluster are arranged in ascending order to form a frequency sequence of each cluster, and the first-order difference sequence of the frequency sequence is calculated. The first-order difference sequence reflects the continuous difference in the frequencies of all frequency domain data points in each cluster. The larger and more discrete the continuous frequency difference is, the more it can reflect the complexity of the continuous frequency difference within the cluster.

[0033] Therefore, the product of the mean and variance of all elements in the first-order difference sequence is taken as the frequency complexity of each cluster. The frequency complexity reflects the complexity of the continuous frequency difference within the cluster. If the complexity of the continuous frequency difference within the cluster and the complexity of the frequency domain amplitude within the cluster are higher, the degree of chaos of the frequency domain data within the cluster can be more comprehensively reflected.

[0034] Furthermore, the information entropy of the frequency domain data amplitude within each cluster is calculated, and the product of the information entropy and the frequency complexity is used as the intra-cluster chaos degree of each cluster. The intra-cluster chaos degree reflects the complexity of the frequency domain data within each cluster. If the complexity of the frequency domain data within the cluster is higher, it means that the frequency domain data is more likely to contain frequency components and frequency domain amplitudes corresponding to noise, thereby reflecting the complex characteristics of the noise distribution.

[0035] At the same time, the frequency mean and amplitude mean of all frequency domain data points in each cluster are calculated respectively. If the current in the diode circuit is more complexly interfered by external noise, different clusters are more likely to contain the frequency and frequency domain amplitude corresponding to the noise, and the differences between different types of noise are large, which will show obvious differences in noise distribution.

[0036] Through the above analysis, the noise distribution difference of the current is calculated: ; In the formula, is the noise distribution difference of the current, is the number of clusters of all frequency domain data points in the current time series, and are the frequency means of all frequency domain data points in the i-th and i-1-th clusters, respectively. and are the mean frequency domain amplitudes of all frequency domain data points in the i-th and i-1-th clusters, respectively.

[0037] The difference in noise distribution reflects the degree of difference in the distribution of different types of noise under the influence of noise interference. If the difference in the distribution of different types of noise is greater and the complexity of the frequency domain data in each cluster is higher, the more it can significantly reflect the complexity characteristics of the noise distribution. At this time, the step size factor of the LMS adaptive filter should be adjusted to further eliminate the interference caused by the complex noise in the actual power grid to the subsequent switching control.

[0038] Furthermore, the mean of the intra-cluster chaos of all clusters corresponding to the frequency domain data of the current time series is calculated, and the product of the mean of the intra-cluster chaos and the noise distribution difference is recorded as the noise distribution complexity of the current.

[0039] Accordingly, for voltage data, the voltage time series is processed using the method of this embodiment to obtain the noise distribution complexity of the voltage.

[0040] The noise distribution complexity can reflect the distribution complexity characteristics of frequency domain noise in current time series and voltage time series. By clustering the frequency domain data in current time series and voltage time series and using intra-cluster analysis and inter-cluster analysis methods, the distribution complexity characteristics of frequency domain noise can be accurately measured, so that the step size factor of the LMS adaptive filter can be adjusted more accurately in the subsequent process, thereby more accurately controlling the inrush-free operation and removal operation of the relay under half-wave conduction, and finally realizing the capacitor switching on and off the power grid.

[0041] Step 4: Perform modal decomposition on the data of each electrical parameter and perform principal component analysis on the modal components. Combined with the complexity of the noise distribution, the steady-state change factor of each electrical parameter is obtained. The step size factor of the filter is adjusted according to the steady-state change factor and the autocorrelation characteristics of the electrical parameter data.

[0042] In order to more accurately adjust the step factor of the LMS adaptive filter, the steady-state change characteristics of the electrical parameters in the diode circuit are comprehensively analyzed according to the complexity of the noise interference of the current and voltage and the variance contribution rate characteristics of the time domain modes of the current and voltage in the diode circuit.

[0043] More specifically, the current time series is input into a modal decomposition algorithm, wherein there are many existing modal decomposition algorithms: empirical mode decomposition or variational mode decomposition. This embodiment adopts empirical mode decomposition to obtain each modal component sequence of the current time series, wherein empirical mode decomposition is a well-known technology and is not described in detail in this embodiment.

[0044] Due to the influence of grid noise interference, each modal component will show significant variation characteristics, and the more complex the fluctuation changes on the modal components, the more they can highlight the non-steady-state changes under the influence of noise interference.

[0045] Therefore, each modal component sequence is used as each row vector of the modal matrix, and the modal matrix composed of each modal component sequence is input into the PCA principal component analysis algorithm (Principal Components Analysis). The PCA principal component analysis algorithm is used to obtain the variance contribution rate of each principal component in the modal matrix. The larger the variance contribution rate, the greater the variation characteristics and fluctuation characteristics under the influence of noise interference in the corresponding modal component sequence. The PCA principal component analysis algorithm and the process of obtaining the variance contribution rate are well-known technologies and will not be repeated in this embodiment.

[0046] Through the above analysis, the steady-state change factor of the current is calculated: ; In the formula, is the steady-state variation factor of the current, is the noise distribution complexity of the current, is the mean of the variance contribution rates of all principal components in the modal matrix corresponding to the current time series, To avoid constants with zero denominators, The value range of is (0.001, 0.01), which is a small constant. The value is 0.001.

[0047] The steady-state change factor reflects the steady-state change characteristics in the current time series. If the degree of variation and fluctuation of the current time series in the time domain is higher, it means that the steady-state change characteristics under the influence of noise interference are smaller. At the same time, if the noise distribution complexity of the current time series in the frequency domain is higher, the current change in the current time series is difficult to maintain a steady-state change, indicating that the influence of noise interference is greater. At this time, the step size factor of the LMS adaptive filter should be increased, so that the LMS adaptive filter can more quickly and accurately eliminate the interference of complex noise in the actual power grid on the subsequent switching control, thereby improving the accuracy of the inrush current switching control.

[0048] Accordingly, for the voltage data, the method for obtaining the steady-state change factor of the current in this embodiment is used to process the voltage time series and obtain the steady-state change factor of the voltage.

[0049] Furthermore, the step size factor in the LMS adaptive filter is adjusted by the steady-state change factors of current and voltage: ; In the formula, is the step size factor of the adjusted LMS adaptive filter, To find the integral function upward, is the maximum eigenvalue in the autocorrelation matrix of the current time series and the voltage time series, is an exponential function with a natural constant as base, and are steady-state variation factors of current and voltage respectively. The acquisition of the autocorrelation matrix and the calculation of the maximum eigenvalue are well-known technologies and will not be described in detail in this embodiment.

[0050] When the maximum eigenvalue in the autocorrelation matrix of the current and voltage data is smaller, and the steady-state change factor of the current and voltage data is smaller, it means that the current and voltage in the diode circuit are greatly affected by the noise interference in the power grid. At this time, the larger the step size factor of the adaptive filter is, the faster the current and voltage in the diode circuit converge to the steady state, thereby improving the effect of filtering the current and voltage in the diode circuit; conversely, it means that the current and voltage in the diode circuit are less affected by the noise interference in the power grid. At this time, the smaller the step size factor of the adaptive filter is, the more stable the filtering effect of the adaptive filter is, thereby improving the effect of filtering the current and voltage in the diode circuit, so that the interference of complex noise in the actual power grid to the subsequent switching control can be eliminated more quickly and accurately, thereby improving the accuracy of the inrush current switching control.

[0051] Step 5: Filter the data of each electrical parameter on the diode circuit based on the adjusted step size factor, and control the relay according to the filtered electrical parameter data, thereby completing the inrush current-free switching control of the capacitor.

[0052] Further, the capacitor is switched on and off. The inrush current switching device in this embodiment includes a capacitor, a microcontroller, a relay, a current sensor, a voltage sensor, and an LMS adaptive filter. The adjusted step size factor of the LMS adaptive filter is used as the step size factor in the process of the LMS adaptive filter filtering the electrical parameters. The LMS adaptive filter is used to filter the electrical parameters on the diode circuit. It should be noted that the specific filtering process is a prior art and is not elaborated in detail in this embodiment. The electrical parameters include current and voltage. The interference of complex noise in the actual power grid on the subsequent switching control is eliminated. The filtered current and voltage are transmitted to the microcontroller. The microcontroller outputs a control signal according to the half-wave conduction performance of the diode. The control signal controls the input or removal of the relay. It should be noted that the microcontroller outputs the control signal and the specific control process of the control signal is a well-known technology for those skilled in the art and is not repeated in this embodiment. Therefore, further, the control signal controls the input or removal of the relay, so that the capacitor is switched into the power grid through the control of the relay, thereby completing the inrush current switching control of the capacitor.

[0053] Based on the same inventive concept as the above method, an embodiment of the present application also provides a new type of inrush current-free switching device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above-mentioned new types of inrush current-free switching control methods are implemented.

[0054] It is to be understood that the sequence of the embodiments of the present application described above is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of the present specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0055] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0056] The above content is only an implementation method of the present application and is not intended to limit the scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the protection scope of the present application.

Claims

1. A novel inrush current switching control method, characterized in that: The following steps are involved: Obtaining data of various electrical parameters on the diode circuit, the electrical parameters including current and voltage; Perform frequency domain analysis on the data of each electrical parameter, and perform clustering processing on the frequency domain data of each electrical parameter respectively; For each electrical parameter, the frequency change and fluctuation degree of the frequency domain data within each cluster are analyzed to obtain the frequency complexity of each cluster. Combined with the amplitude change of the frequency domain data within each cluster, the intra-cluster chaos of each cluster is obtained. According to the differences in the average frequency level of the frequency domain data within the cluster and the average amplitude level of the frequency domain data within the cluster, the noise distribution difference of each electrical parameter is obtained. Combined with the average level of the intra-cluster chaos of all clusters, the noise distribution complexity of each electrical parameter is obtained. Performing modal decomposition on the data of each electrical parameter, and performing principal component analysis on the modal components, obtaining the steady-state variation factor of each electrical parameter in combination with the complexity of the noise distribution, and adjusting the step size factor of the filter according to the steady-state variation factor and the autocorrelation characteristics of the data of each electrical parameter; The data of each electrical parameter on the diode circuit is filtered based on the adjusted step factor, and the relay is controlled according to the filtered electrical parameter data, thereby completing the inrush current-free switching control of the capacitor.

2. A novel inrush current switching control method as claimed in claim 1, characterized in that: The method for obtaining the frequency complexity of each cluster is: The frequencies of all frequency domain data in each cluster are arranged in ascending order to form the frequency sequence of each cluster. The product of the mean and variance of all elements in the first-order difference sequence of the frequency sequence is taken as the frequency complexity of each cluster.

3. A novel inrush current switching control method as claimed in claim 1, characterized in that: The method for obtaining the intra-cluster chaos degree of each cluster is: calculating the information entropy of the frequency domain data amplitude in each cluster, and taking the product of the information entropy and the frequency complexity as the intra-cluster chaos degree of each cluster.

4. A novel inrush current switching control method as claimed in claim 1, characterized in that: The calculation method of the noise distribution difference of each electrical parameter is: The calculation formula of the current noise distribution difference is: ; In the formula, is the noise distribution difference of the current, is the number of clusters of all frequency domain data points in the current time series, and are the frequency means of all frequency domain data points in the i-th and i-1-th clusters, respectively. and are the mean frequency domain amplitudes of all frequency domain data points in the i-th and i-1-th clusters, respectively.

5. A novel inrush current switching control method as claimed in claim 4, characterized in that: The method for constructing the current time series is as follows: the currents within a preset time period before the current moment are arranged in chronological order to obtain the current time series.

6. A novel inrush current switching control method as claimed in claim 1, characterized in that: The method for obtaining the noise distribution complexity of each electrical parameter is: taking the product of the mean of the intra-cluster chaos degree of all clusters corresponding to each electrical parameter and the noise distribution difference as the noise distribution complexity of each electrical parameter.

7. A novel inrush current switching control method as claimed in claim 5, characterized in that: The calculation method of the steady-state change factor of each electrical parameter is: For current data, the calculation formula of the steady-state change factor V of the current is: ; In the formula, is the noise distribution complexity of the current, is the mean of the variance contribution rates of all principal components in the modal matrix corresponding to the current time series, To avoid constants with zero denominators.

8. A novel inrush current switching control method as claimed in claim 7, characterized in that: The method for obtaining the modal matrix corresponding to the current time series is: performing modal decomposition on the current time series, taking each modal component as each row vector, and forming the modal matrix corresponding to the current time series.

9. A novel inrush current switching control method as claimed in claim 5, characterized in that: The calculation method of the adjusted step size factor is: ； In the formula, is the step size factor of the adjusted LMS adaptive filter, To find the integral function upward, is the maximum eigenvalue in the autocorrelation matrix of the current time series and the voltage time series, is an exponential function with a natural constant as base, and are the steady-state change factors of current and voltage respectively.

10. A novel inrush current switching device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of a novel inrush current switching control method as described in any one of claims 1 to 9 are implemented.

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