CN115840104B - Interference signal identification method based on electromagnetic compatibility experiment - Google Patents
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Abstract
The invention discloses an interference signal identification method based on an electromagnetic compatibility experiment, which relates to the technical field of electronic data processing, and comprises the following steps: acquiring a voltage signal of equipment in normal operation under an electromagnetic interference environment; obtaining a local influence value of each voltage signal by using a Gaussian function of each voltage signal and adjacent voltage signals; obtaining initial distance parameters of a local outlier algorithm by utilizing the distance between adjacent peak points on a fitting curve of the local influence value; acquiring signal stability corresponding to the initial distance parameter; acquiring signal stability corresponding to each distance parameter by using a method for acquiring signal stability corresponding to the initial distance parameter, and taking the distance parameter corresponding to the signal stability with the smallest difference between the reference stability as the optimal distance parameter; and carrying out a local outlier algorithm on all the voltage signals by utilizing the optimal distance parameters to obtain interference signals. The invention improves the accuracy of identifying the interference signals.
Description
Technical Field
The invention relates to the technical field of electronic data processing, in particular to an interference signal identification method based on an electromagnetic compatibility experiment.
Background
The various operating power equipment are mutually related and mutually influenced in three modes of electromagnetic conduction, electromagnetic induction and electromagnetic radiation, and the electromagnetic can cause interference, influence and harm to the operating equipment and personnel under certain conditions. The electromagnetic compatibility test is a test for checking the electromagnetic compatibility of equipment by using electromagnetic interference detection equipment and electromagnetic interference generation equipment under laboratory or external field environment conditions.
Electromagnetic interference belongs to noise signals for equipment which normally operates, and electromagnetic interference noise is generally restrained by adding components such as a common mode filter, a differential mode filter, a capacitor, a resistor and the like into an electronic circuit of the equipment when an electromagnetic compatibility experiment is carried out. The anti-electromagnetic interference and electromagnetic compatibility of the equipment can be evaluated by detecting the noise residual degree in the equipment operation signal, but the residual electromagnetic interference noise signal can be similar to the amplitude of the equipment normal operation signal or lower than the normal operation signal, and the residual electromagnetic interference noise signal is difficult to accurately identify by a conventional method for setting a filtering threshold value.
Disclosure of Invention
The invention provides an interference signal identification method based on an electromagnetic compatibility experiment, which aims to solve the problem that residual electromagnetic interference signals cannot be identified by a conventional method for setting a filtering threshold.
The invention discloses an interference signal identification method based on an electromagnetic compatibility experiment, which adopts the following technical scheme:
acquiring a voltage signal of equipment in normal operation under an electromagnetic interference environment;
acquiring a Gaussian function of each voltage signal by using the time width and amplitude peak value of each voltage signal, and acquiring a local influence value of each voltage signal by using the Gaussian function of each voltage signal and adjacent voltage signals;
fitting the local influence values of all the voltage signals to obtain a fitted curve, extracting peak points in the fitted curve, and obtaining initial distance parameters of a local outlier algorithm by utilizing the distance between adjacent peak points on the fitted curve;
utilizing the local influence values of the voltage signals corresponding to all points except the peak point on the fitting curve to obtain the reference stability of the voltage signals;
removing the voltage signal corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point, and obtaining the signal stability corresponding to the initial distance parameter by utilizing the local influence value of the residual voltage signal;
the method comprises the steps of adjusting an initial distance parameter for multiple times to obtain a distance parameter after each adjustment, obtaining signal stability corresponding to the distance parameter after each adjustment by using a method for obtaining signal stability corresponding to the initial distance parameter, and taking the distance parameter corresponding to the signal stability with the smallest difference between reference stability as an optimal distance parameter;
and carrying out a local outlier algorithm on all the voltage signals by utilizing the optimal distance parameters to obtain interference signals.
Further, the method for obtaining the local influence value of each voltage signal comprises the following steps:
the area of each voltage signal is obtained by utilizing the fixed integration of the Gaussian function of each voltage signal;
acquiring the sum of the areas of two adjacent voltage signals of each voltage signal;
the ratio of the area of each voltage signal to the sum of the areas of two adjacent voltage signals is taken as the local influence value of each voltage signal.
Further, the area of the voltage signal refers to the area occupied by the voltage signal in the time domain of the voltage signal, and the abscissa of the time domain represents time and the ordinate represents amplitude.
Further, the method for obtaining the Gaussian function of each voltage signal is as follows:
setting the Gaussian function of each voltage signal as
；
Wherein the method comprises the steps of
Is the peak value of the amplitude of the voltage signal,
is half the time width of the voltage signal.
Further, the method for obtaining the initial distance parameter of the local outlier algorithm comprises the following steps:
acquiring a distance average value between adjacent peak points on a fitting curve of the local influence value;
and taking the obtained distance average value as an initial distance parameter of the local outlier algorithm.
Further, the method for obtaining the reference stability of the voltage signal comprises the following steps:
obtaining information entropy of local influence values of voltage signals corresponding to all points except the peak point on the fitting curve;
and taking the obtained information entropy as the reference stability of the voltage signal.
Further, the method for obtaining the signal stability corresponding to the initial distance parameter comprises the following steps:
removing voltage signals corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point;
and taking the information entropy of the local influence value of the residual voltage signal as the signal stability corresponding to the initial distance parameter.
The beneficial effects of the invention are as follows: according to the interference signal identification method based on the electromagnetic compatibility experiment, the Gaussian function of each voltage signal is obtained through the time width and the amplitude peak value of the voltage signal, and compared with the characteristic that the voltage signal is represented only through the time width or the amplitude peak value, the interference signal identification method based on the electromagnetic compatibility experiment is more accurate and specific, the local influence value of the voltage signal is obtained through the Gaussian function of each voltage signal and the Gaussian function of the adjacent voltage signals, the difference between each voltage signal and the normal voltage signal can be determined, and the abnormal degree of each voltage signal can be approximately obtained; and (3) obtaining initial distance parameters of a distance local outlier algorithm by utilizing the distance between peak points of the fitting curve, namely determining the initial distance parameters of minimum adaptation, iterating on the basis of the initial distance parameters, and obtaining the optimal distance parameters for local outlier detection by comparing the calculated signal stability with the reference stability to obtain an interference noise signal. The invention is based on the multidimensional characteristic of the voltage signal, the time width, the amplitude and the difference between adjacent signals are used for local outlier detection, so that the problem of single characteristic limitation in the traditional noise identification by utilizing the signal amplitude and the frequency value characteristic is avoided, and the optimal distance parameter is estimated by adjusting the initial distance parameter for a plurality of times and calculating the signal stability when different distance parameters are calculated, so that the optimal distance parameter can effectively remove noise signals, retain the voltage fluctuation information and give consideration to the operation speed of an algorithm. Therefore, compared with the traditional filtering threshold algorithm, the method is more superior in detection of the residual interference noise signal and higher in reliability.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart illustrating the overall steps of an embodiment of an interference signal recognition method based on an electromagnetic compatibility experiment according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
An embodiment of an interference signal identification method based on an electromagnetic compatibility experiment of the present invention is shown in fig. 1, and the method includes:
s1, acquiring a voltage signal of equipment in normal operation under an electromagnetic interference environment.
Specifically, in a laboratory environment, voltage signals of the running state of the equipment are monitored by using a voltage sensor, at the moment, the test equipment is interfered by using an electromagnetic interference device, and most noise signals can be filtered by using a filter, an electromagnetic compatibility element and the like which are arranged on the equipment.
And acquiring a voltage signal under electromagnetic interference of the electromagnetic interference device when the equipment normally operates.
S2, utilizing the time width and amplitude peak value of each voltage signal to obtain a Gaussian function of each voltage signal, and utilizing the Gaussian function of each voltage signal and adjacent voltage signals to obtain a local influence value of each voltage signal.
During operation of the device, although its own electromagnetic compatibility element suppresses most of the electromagnetic interference noise signals, there is still noise signal residue, and in addition to the high frequency noise signals with significant amplitude, there may be low amplitude noise signals mixed with the normal operation signals of the device.
The noise signals are randomly and discretely distributed in the signal time domain or the frequency domain, the noise signals are discretely mixed in the normal effective signals when the equipment is in normal operation, the residual electromagnetic interference noise signals are generally extracted through the difference between the characteristics of the effective signals and the characteristics of the noise signals, but the characteristic expression of the effective signals is multidimensional, and the characteristic expression of the discrete noise signals is also multidimensional. The dispersion of a voltage signal is represented by its amplitude dispersion and frequency dispersion, including time width, amplitude, and relation with adjacent voltage signals, and analysis of its time domain may affect the recognition result of noise signals regardless of which parameter is missing, so a characterization parameter is required that can cover all the features.
Specifically, the time width and amplitude peak value of each voltage signal in the time domain diagram are obtained, the abscissa of the time domain diagram is time, the ordinate is amplitude, the time width refers to the width of the zero point at the left side and the zero point at the right side of the time sequence of the voltage signal, and the shape of each voltage signal in the time domain diagram is regarded as a Gaussian curve, so thatExpressed by a Gaussian function, the Gaussian function of each voltage signal is set as
The method comprises the steps of carrying out a first treatment on the surface of the Wherein the method comprises the steps of
Is the peak value of the amplitude of the voltage signal,
is half the time width of the voltage signal. If at first
The peak value of the amplitude of each voltage signal is
Time width of
Then (1)
The Gaussian function of the voltage signal is
。
The area of each voltage signal is obtained by utilizing the fixed integration of the Gaussian function of each signal, and the area of the voltage signal refers to the area occupied by the voltage signal in the time domain diagram of the voltage signal; acquiring the sum of the areas of two adjacent voltage signals of each voltage signal; the ratio of the area of each voltage signal to the sum of the areas of two adjacent voltage signals is taken as the local influence value of each voltage signal.
The local influence value of each voltage signal is calculated specifically according to the following formula:
wherein,,
represent the first
Local influence values of the individual voltage signals;
representing the left zero of the ith voltage signal,
representing the right zero of the ith voltage signal,
representing the time width of the ith voltage signal,
representing the peak amplitude of the ith voltage signal,
a gaussian function representing the ith voltage signal,
the Gao Siding integral of the ith voltage signal is taken as the constant integral result representing the area of the voltage signal in the time domain diagram.
Same reason
For the left zero of the i-1 st voltage signal,
is the right zero point of the i-1 th voltage signal,
representing the time width of the i-1 st voltage signal,
representing the peak amplitude of the i-1 st voltage signal,
a gaussian function representing the i-1 st voltage signal,
then represent the firstGao Siding integral of the i-1 voltage signal is the area of the i-1 voltage signal in the time domain diagram; same reason
Representing Gao Siding integral of the i+1th voltage signal, i.e. the area of the i+1th voltage signal in the time domain plot. The ratio of numerator to denominator in the formula represents the ratio of the fixed integral of the ith voltage signal to the sum of the fixed integral of the left and right adjacent voltage signals i-1 and i+1, namely the ratio of the area of the ith voltage signal in the time domain diagram to the sum of the areas of the left and right adjacent voltage signals i-1 and i+1 in the time domain diagram, if the ith voltage signal is a normal and steady operation voltage signal, the value is close to 1/2, if the value is abnormal in a continuous relation, the value is larger than 1/2, and if the voltage signal is abnormal, the value is smaller than 1/2. Will obtain the ith voltage signal adjacent thereto
The influence value in the local continuous area formed by the two signals is recorded as the local influence value of the ith voltage signal
。
Compared with the conventional calculation of amplitude change, frequency change and the like between continuous voltage signals, the partial influence value of the analyzed voltage signals is calculated by using the fitted Gaussian curve definite integral, namely the continuous change condition of the signals on the multidimensional characteristics such as amplitude, frequency and the like can be covered by the area, and the influence duty ratio of the analyzed voltage signals in the partial continuous relation is described according to the ratio of the analyzed voltage signals to the adjacent signals, so that the analysis of the single independent characteristic is more comprehensive and accurate.
And S3, fitting the local influence values of all the voltage signals to obtain a fitted curve, extracting peak points in the fitted curve, and obtaining initial distance parameters of a local outlier algorithm by utilizing the distance between adjacent peak points on the fitted curve.
The local influence value represents the characteristics of the voltage signal and also represents the influence of the voltage signal in the local continuous relation. The larger the local influence value is, the more abnormal the frequency value and amplitude value of the local influence value can be represented in a voltage signal of stable operation of equipment to a certain extent, but whether the local influence value is a noise signal cannot be directly judged according to the value, and the local influence value is analyzed according to the dispersion. Since most of noise signals are filtered out by the electromagnetic compatibility element of the detected equipment in the electromagnetic compatibility experiment, the dispersion analysis can be carried out on the voltage signals in the time domain through the local influence value. All characteristics of voltage signals of normal operation of the equipment are similar and similar, amplitude and frequency values of noise signals can be randomly generated, in theory, only signals with similar, same signal characteristics and continuity characteristics are needed to be classified, however, the noise signals are random, a plurality of similar and similar noises even similar to some normal signals can still appear when the total signal sampling amount is large, and therefore the scheme utilizes a local outlier algorithm to identify the noise signals in time sequence.
The local reachable density and the local outlier factor are related with the size of a distance parameter k, k represents a k-th distance neighborhood, the local outlier algorithm is used for judging whether the data is abnormal or not through the calculated local outlier factor, and the abnormal result of the judging data is different due to the fact that the local outlier factors obtained by different distance parameters k are different. Therefore, the optimal distance parameter k is analyzed by the scheme, so that the obtained local outlier factor is more accurate, and the identified noise signal is more accurate.
Specifically, polynomial curve fitting is performed on local influence values of all voltage signals to obtain a fitted curve, and first-order derivation is performed on a curve function of the fitted curve to obtain a first derivative value of the local influence value of each voltage signal
Obtain all of
And (2) and
is noted as the peak point of the fitted curve.
The method comprises the steps of fitting a continuous voltage signal with a certain state change between every two peak points on a curve, wherein the continuous voltage signal is a voltage signal with the state change in a time sequence, the peak points are voltage signals with the state change in the continuous state, but the voltage signals at all the peak points are abnormal signals, and the method is characterized in that frequent voltage fluctuation exists in the device during normal operation, and the purpose of acquiring all the peak points is to acquire the minimum value of a distance parameter k of a local outlier algorithm, namely an initial distance parameter.
Specifically, obtaining a distance average value between adjacent peak points on a fitting curve of a local influence value; taking the obtained distance average value as an initial distance parameter of a local outlier algorithm
. The signal in every two peak point intervals is a stable and continuous signal in a certain state, the setting of k value is that abnormal data needs to be searched in the k range, and the minimum k value is the average interval length between all peak point nodes and represents the initial distance parameter which can give consideration to the minimum adaptation of all stable interval parts.
S4, utilizing local influence values of voltage signals corresponding to all points except the peak point on the fitting curve to obtain reference stability of the voltage signals; and removing the voltage signal corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point, and obtaining the signal stability corresponding to the initial distance parameter by utilizing the local influence value of the residual voltage signal.
Initial distance parameter
Only the minimum adaptive distance parameter is not the optimal distance parameter of the local outlier algorithm, and the operation of taking the minimum adaptive distance parameter as the distance parameter of the local outlier algorithm may have the problems of excessive outlier detection and larger algorithm running time. We therefore follow from the initial distance parameter
And starting to increase the size of the distance parameter upwards to perform iterative estimation, and obtaining the optimal distance parameter.
Firstly, assuming that the optimal distance parameter is obtained, if the optimal distance parameter is utilized to perform local outlier detection on all the voltage signals and remove noise signals, the stability of the obtained residual voltage signals is the best, the stability is represented by the information entropy of the local influence value of the voltage signals, but the optimal distance parameter is not obtained yet, and the actual local outlier detection result is unknown, so that the analysis of the optimal distance parameter can be performed by calculating the signal stability through the local influence value of the voltage signals.
Specifically, obtaining information entropy of local influence values of voltage signals corresponding to all points except the peak point on the fitting curve; and taking the obtained information entropy as the reference stability of the voltage signal. Calculating a reference stability of the voltage signal according to:
wherein,,
representing a reference stability of the voltage signal;
representing the number of all voltage signals;
representing the number of voltage signals corresponding to peak points on the fitted curve;
the total number of the voltage signals after all peak points are removed;
representing local influence values of any kind
As a result of the value of (a),
represents the first
Class local influence value
The number of times the value result of (a) appears in all the remaining voltage signals;
represents the first
Class local influence value
Probability of the number of occurrences of the value result in all remaining voltage signals, Q representing all local influence values occurring in the voltage signals
The value type.
And (3) representing the stability of the voltage signal by using the information entropy of the local influence value as an information entropy calculation formula.
Removing voltage signals corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point; and taking the information entropy of the local influence value of the residual voltage signal as the signal stability corresponding to the initial distance parameter.
S5, adjusting the initial distance parameter for multiple times to obtain the distance parameter after each adjustment, obtaining the signal stability corresponding to the distance parameter after each adjustment by using a method for obtaining the signal stability corresponding to the initial distance parameter, and taking the distance parameter corresponding to the signal stability with the minimum difference between the reference stability as the optimal distance parameter; and carrying out a local outlier algorithm on all the voltage signals by utilizing the optimal distance parameters to obtain interference signals.
Since it is not determined whether the peak points are noise signals or normal signals, it is possible to determine that the peak points must have a dispersion with respect to adjacent signals, and the peak points are removed, and if the peak points are all noise signals, the stability of the whole signal is exhibited after all the peak points are removed. And the actual noise signal number must be equal to or less than the peak point number. We analyze the optimal distance parameter by iterating the initial distance parameter.
Specifically, the initial distance parameter is adjusted for multiple times to obtain multiple distance parameters, wherein the multiple times of adjustment means that the initial distance parameter is iterated upwards, each distance parameter is obtained, each peak point in the fitting curve is taken as the center, and an abnormal outlier, namely the largest local influence value in the k range, is removed in the k range of the distance parameter
The corresponding voltage signal may be the peak value itself or other
The point corresponding to the value, so when k changes, the target peak point may be removed or may be reserved. And taking the information entropy of the local influence value of the residual voltage signal as the signal stability corresponding to each distance parameter.
And continuously iterating to obtain new distance parameters, wherein different distance parameters correspond to different signal stabilities, and taking the distance parameter corresponding to the signal stability with the smallest difference between the reference stabilities as the optimal distance parameter.
The reference stability is the stability of the residual signal obtained after taking all peak points as limits and assuming the noise points, but the actual noise signal quantity is necessarily smaller than or equal to the peak point quantity, and the signal stability after actual denoising should be larger than or equal to the reference stability, so that in the iterative process of the initial distance parameter, the peak point is taken as the center, the distance parameter k is taken as the range, and an abnormal outlier, namely the maximum distance parameter k is removed
If all peak points of the voltage signals corresponding to the values have local influence values larger than the peak points in the range of the current distance parameter k, the peak points are reserved and larger values are removed
If the stability of the obtained residual voltage signal is closer to the reference stability, the stability of the residual voltage signal is more new, and the stability of the residual voltage signal is less influenced on the whole section of signal stability even if the peak value point is reserved in the range of the current distance parameter k, so that the larger discrete data can be screened out by the current distance parameter k, and normal data fluctuation is reserved. The optimal distance parameter is the optimal distance parameter and is iterated upwards continuously, so that the obtained optimal distance parameter can effectively remove noise signals, keep data fluctuation information and improve the operation speed of an algorithm relative to the initial distance parameter.
The interference signal is obtained by performing a local outlier algorithm on all the voltage signals by using the optimal distance parameter, wherein the local outlier detection algorithm is in the prior art, and is not described herein in detail, and the interference signal is an electromagnetic interference noise signal.
And comparing the number of all the identified interference signals with the total number of signals to obtain the distribution density of the residual noise, wherein the larger the distribution density of the residual noise is, the poorer the electromagnetic compatibility of the equipment is, the smaller the distribution density of the residual noise is, and the better the electromagnetic compatibility of the equipment is.
In summary, the invention provides an interference signal identification method based on an electromagnetic compatibility experiment, which obtains a gaussian function of each voltage signal through a time width and an amplitude peak value of the voltage signal, and compared with the characteristic that the voltage signal is only represented through the time width or the amplitude peak value, the interference signal identification method is more accurate and specific, obtains a local influence value of the voltage signal through the gaussian function of each voltage signal and adjacent voltage signals, and can determine the difference between each voltage signal and a normal voltage signal, namely, can approximately obtain the abnormality degree of each voltage signal; and (3) obtaining initial distance parameters of a distance local outlier algorithm by utilizing the distance between peak points of the fitting curve, namely determining the initial distance parameters of the minimum adaptation, iterating on the basis of the initial distance parameters, and obtaining the optimal distance parameters for local outlier detection by comparing the calculated signal stability with the reference stability to obtain the interference signals. The invention is based on the multidimensional characteristic of the voltage signal, the time width, the amplitude and the difference between adjacent signals are used for local outlier detection, so that the problem of single characteristic limitation in the traditional noise identification by utilizing the signal amplitude and the frequency value characteristic is avoided, and the optimal distance parameter is estimated by adjusting the initial distance parameter for a plurality of times and calculating the signal stability when different distance parameters are calculated, so that the optimal distance parameter can effectively remove noise signals, retain the voltage fluctuation information and give consideration to the operation speed of an algorithm. Therefore, compared with the traditional filtering threshold algorithm, the method is more superior in detection of the residual interference signal and higher in reliability.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (3)
1. An interference signal identification method based on an electromagnetic compatibility experiment is characterized by comprising the following steps:
acquiring a voltage signal of equipment in normal operation under an electromagnetic interference environment;
acquiring a Gaussian function of each voltage signal by using the time width and amplitude peak value of each voltage signal, and acquiring a local influence value of each voltage signal by using the Gaussian function of each voltage signal and adjacent voltage signals;
the time width refers to the width of the left zero point and the right zero point of the voltage signal in time sequence;
the method for obtaining the local influence value of each voltage signal comprises the following steps:
the area of each voltage signal is obtained by utilizing the fixed integration of the Gaussian function of each voltage signal;
acquiring the sum of the areas of two adjacent voltage signals of each voltage signal;
taking the ratio of the area of each voltage signal to the sum of the areas of two adjacent voltage signals as the local influence value of each voltage signal;
the area of the voltage signal refers to the area occupied by the voltage signal in the time domain of the voltage signal, the abscissa of the time domain is time, and the ordinate is amplitude
Fitting the local influence values of all the voltage signals to obtain a fitted curve, extracting peak points in the fitted curve, and obtaining initial distance parameters of a local outlier algorithm by utilizing the distance between adjacent peak points on the fitted curve;
utilizing the local influence values of the voltage signals corresponding to all points except the peak point on the fitting curve to obtain the reference stability of the voltage signals;
the method for obtaining the reference stability of the voltage signal comprises the following steps:
obtaining information entropy of local influence values of voltage signals corresponding to all points except the peak point on the fitting curve;
taking the obtained information entropy as the reference stability of the voltage signal;
removing the voltage signal corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point, and obtaining the signal stability corresponding to the initial distance parameter by utilizing the local influence value of the residual voltage signal;
the method for obtaining the signal stability corresponding to the initial distance parameter comprises the following steps:
removing voltage signals corresponding to the maximum local influence value in the range of the initial distance parameter of each peak point;
taking the information entropy of the local influence value of the residual voltage signal as the signal stability corresponding to the initial distance parameter;
the method comprises the steps of adjusting an initial distance parameter for multiple times to obtain a distance parameter after each adjustment, obtaining signal stability corresponding to the distance parameter after each adjustment by using a method for obtaining signal stability corresponding to the initial distance parameter, and taking the distance parameter corresponding to the signal stability with the smallest difference between reference stability as an optimal distance parameter;
and carrying out a local outlier algorithm on all the voltage signals by utilizing the optimal distance parameters to obtain interference signals.
2. The method for identifying interference signals based on electromagnetic compatibility experiments according to claim 1, wherein the method for obtaining the gaussian function of each voltage signal is as follows:
setting the Gaussian function of each voltage signal as
；
Wherein the method comprises the steps of
Is the peak value of the amplitude of the voltage signal, < >>
Is half the time width of the voltage signal.
3. The method for identifying interference signals based on electromagnetic compatibility experiments as claimed in claim 1, wherein the method for obtaining the initial distance parameters of the local outlier algorithm is as follows:
acquiring a distance average value between adjacent peak points on a fitting curve of the local influence value;
and taking the obtained distance average value as an initial distance parameter of the local outlier algorithm.
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