CN115840104A - 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 an initial distance parameter of a local outlier algorithm by using 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 the signal stability corresponding to each distance parameter by using a method for acquiring the signal stability corresponding to the initial distance parameter, and taking the distance parameter corresponding to the signal stability with the minimum difference with the reference stability as the optimal distance parameter; and performing local outlier algorithm on all the voltage signals by using the optimal distance parameter to obtain interference signals. The invention improves the accuracy of identifying the interference signal.
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
Various operating electrical devices are mutually associated and influenced in three modes of electromagnetic conduction, electromagnetic induction and electromagnetic radiation, and the electromagnetism can cause interference, influence and harm to the operating devices 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 the condition of a laboratory or an external field environment.
The electromagnetic interference belongs to noise signals for normally operating equipment, and the electromagnetic interference noise is generally suppressed by adding components such as a common mode filter, a differential mode filter, a capacitor and a resistor into an electronic circuit of the equipment during an electromagnetic compatibility experiment. The anti-electromagnetic interference and electromagnetic compatibility performance of the equipment can be evaluated by detecting the residual degree of the noise in the equipment operation signal, but the residual electromagnetic interference noise signal is possibly close to the amplitude of the normal operation signal of the equipment 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 the existing method for setting a filtering threshold value cannot identify residual electromagnetic interference signals.
The invention relates to 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 the 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 fitting curve, extracting peak points in the fitting curve, and obtaining initial distance parameters of a local outlier algorithm by using the distance between adjacent peak points on the fitting curve;
obtaining the reference stability of the voltage signal by using the local influence values of the voltage signals corresponding to all points except the peak point on the fitting curve;
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 using the local influence values of the rest voltage signals;
adjusting the initial distance parameter for multiple times to obtain a distance parameter after each adjustment, acquiring 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 minimum difference with the reference stability as an optimal distance parameter;
and performing local outlier algorithm on all the voltage signals by using the optimal distance parameter to obtain interference signals.
Further, the method for obtaining the local influence value of each voltage signal comprises the following steps:
obtaining the area of each voltage signal by utilizing the fixed integral of the Gaussian function of each voltage signal;
acquiring the sum of the areas of two adjacent voltage signals of each voltage signal;
and 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.
Further, the area of the voltage signal refers to the area occupied by the voltage signal in a time domain diagram of the voltage signal, the abscissa of the time domain diagram is time, and the ordinate is amplitude.
Further, the method for obtaining the gaussian function of each voltage signal comprises the following steps:
setting a Gaussian function of each voltage signal as
；
Wherein
Is the peak in the amplitude of the voltage signal,
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:
obtaining the average value of the distances between adjacent peak points on a fitting curve of the local influence values;
and taking the obtained distance mean 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:
acquiring 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 includes:
removing the voltage signal 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 invention has the beneficial effects that: 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, compared with the characteristic that the voltage signal is only represented through the time width or the amplitude peak value, the method 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 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 obtaining an initial distance parameter of a distance local outlier algorithm by using the distance between peak points of the fitting curve, namely determining the initial distance parameter of the minimum adaptation, iterating on the basis, and comparing the calculated signal stability with the reference stability to obtain the optimal distance parameter for local outlier detection to obtain the interference noise signal. Because the invention carries out local outlier detection based on the multidimensional characteristics of the voltage signal, the time width, the amplitude and the difference between adjacent signals, the problem of single characteristic limitation when the traditional noise identification is carried out by utilizing the characteristics of the signal amplitude and the frequency value is solved, and the optimal distance parameter is estimated by adjusting the initial distance parameter for many times and calculating the signal stability when different distance parameters are carried out, so that the optimal distance parameter not only can effectively eliminate the noise signal, keep the voltage fluctuation information, but also takes account of the operation speed of the 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 present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart illustrating the general steps of an embodiment of an emi signal identification method based on an emc experiment according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An embodiment of the method for identifying an interference signal based on an electromagnetic compatibility experiment according to the present invention is shown in fig. 1, and the method includes:
s1, acquiring a voltage signal of equipment in normal operation in an electromagnetic interference environment.
Specifically, in a laboratory environment, a voltage sensor is used for monitoring a voltage signal of an equipment running state, an electromagnetic interference device is used for interfering test equipment at the moment, and a filter, an electromagnetic compatibility element and the like which are arranged on the equipment can filter most noise signals.
And acquiring a voltage signal of the equipment under the electromagnetic interference of the electromagnetic interference device when the equipment normally operates.
S2, obtaining a Gaussian function of each voltage signal by using the time width and the amplitude peak value of each voltage signal, and obtaining a local influence value of each voltage signal by using the Gaussian function of each voltage signal and adjacent voltage signals.
In the operation process of the equipment, although the electromagnetic compatible element of the equipment can inhibit noise signals of most electromagnetic interference, the noise signals still remain, and besides high-frequency noise signals with obvious outstanding amplitude, low-amplitude noise signals mixed with normal operation signals of the equipment can exist.
Noise signals are randomly and discretely distributed in a signal time domain or a signal frequency domain, when equipment normally operates, the noise signals are discretely mixed in normal effective signals, residual noise signals of electromagnetic interference are 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 features such as time width, amplitude and relationship with adjacent voltage signals, and analysis of its time domain for which any one of the parameters is absent may affect the recognition result of the noise signal, so a characterization parameter covering all the features is required.
Specifically, the time width and the amplitude peak value of each voltage signal in a 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 a left zero point and a right zero point of the voltage signal in a time sequence, the shape of each voltage signal in the time domain diagram is regarded as a Gaussian curve and is represented by a Gaussian function, and the Gaussian function of each voltage signal is set to be
(ii) a Wherein
Is the peak in the amplitude of the voltage signal,
half the time width of the voltage signal. If it is first
An amplitude peak of the voltage signal is
Time width is
Then to the first
A Gaussian function of the voltage signal of
。
Obtaining the area of each voltage signal by utilizing the fixed integration of the Gaussian function of each signal, wherein the area of the voltage signal is the area occupied by the voltage signal in a time domain diagram of the voltage signal; acquiring the area sum of two adjacent voltage signals of each voltage signal; and 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 local influence value of each voltage signal is calculated specifically according to the following formula:
wherein the content of the first and second substances,
is shown as
A local influence value of the individual voltage signals;
represents the left zero of the ith voltage signal,
representing the right zero of the ith voltage signal,
represents 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,
is the Gaussian constant integration of the ith voltage signal, and the constant integration result represents the area of the voltage signal in a time domain graph.
In the same way
The left zero of the i-1 th voltage signal,
is the right zero of the i-1 th voltage signal,
the time width of the i-1 th voltage signal is shown,
representing the amplitude peak of the i-1 th voltage signal,
a gaussian function representing the i-1 th voltage signal,
the integral of the Gaussian constant of the ith-1 voltage signal is represented, and the integral is the area of the ith-1 voltage signal in the time domain diagram; in the same way
Represents the gaussian integration of the (i + 1) th voltage signal, i.e. the area of the (i + 1) th voltage signal in the time domain diagram. The ratio of a numerator to a denominator in the formula represents the ratio of the definite integral of the ith voltage signal to the sum of the definite integrals 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 a 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 voltage signal which normally and stably runs, the value should approach to 1/2, if the ith voltage signal is abnormal in a continuous relation, the value is larger than 1/2, and if the left and right adjacent voltage signals of the voltage signal are abnormal, the value is smaller than 1/2. The ith voltage signal is adjacent to the obtained ith voltage signal
The influence value in the local continuous region formed by the two signals is recorded as the local influence value of the ith voltage signal
。
Compared with the conventional method for calculating amplitude change, frequency value change and the like between continuous voltage signals, the method for analyzing the local influence value of the voltage signal is characterized in that the local influence value of the voltage signal is subjected to constant integration by a fitted Gaussian curve, namely the area can cover the continuous change condition of the signal on multi-dimensional characteristics such as the amplitude value, the frequency value and the like at the same time, and the influence ratio of the local influence value in the local continuous relation is described according to the ratio of the local influence value to the constant integration of adjacent signals, so that the analysis is more comprehensive and accurate than the analysis of a single independent characteristic.
And S3, fitting the local influence values of all the voltage signals to obtain a fitting curve, extracting peak points in the fitting curve, and obtaining initial distance parameters of the local outlier algorithm by using the distance between adjacent peak points on the fitting curve.
The local influence value characterizes the voltage signal itself and also characterizes its influence in a local continuity relationship. The larger the local influence value is, the more abnormal the frequency value and the amplitude of the local influence value are in the voltage signal of the stable operation of the equipment can be represented to a certain extent, but whether the local influence value is a noise signal or not can not be directly judged according to the value, and the local influence value is analyzed according to the dispersion. In the electromagnetic compatibility experiment, most of noise signals are filtered by the electromagnetic compatibility element of the detected equipment, so that the dispersion degree of the voltage signals in the time domain can be analyzed through the local influence values. Various characteristics of voltage signals of normal operation of equipment are similar and similar, amplitude and frequency values of noise signals can randomly appear, theoretically, only signals with similar and identical signal characteristics and continuity characteristics need to be classified, although the noise signals are random, a plurality of similar and similar noises even similar to certain normal signals can still appear when the total signal sampling amount is large, and therefore the noise signals are identified from the time sequence by using a local outlier algorithm.
The local reachable density and the local outlier factor are all related to the size of a distance parameter k, the k represents a kth distance neighborhood, a local outlier algorithm judges whether data are abnormal or not through the local outlier factor obtained through calculation, and results of judging data to be abnormal are different due to the fact that the local outlier factors obtained through 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 the local influence values of all the voltage signals to obtain a fitting curve, and first-order derivation is performed on a curve function of the fitting curve to obtain each voltage signalFirst derivative value of local influence value of voltage signal
Get all of
And is and
the time node of (d) is recorded as the peak point of the fitted curve.
Between every two peak points on the fitting curve, a continuous voltage signal which continuously changes in a certain state is formed in a time sequence, the peak points are voltage signals of which the continuous state changes, but the voltage signals at all the peak points are not abnormal signals, and the equipment has frequent voltage fluctuation when in normal operation, so that the purpose of obtaining all the peak points is to obtain the minimum value of the distance parameter k of the local outlier algorithm, namely the initial distance parameter.
Specifically, a distance average value between adjacent peak points on a fitting curve of the local influence value is obtained; taking the obtained distance mean value as an initial distance parameter of a local outlier algorithm
. The signal in every two peak point intervals is a signal which is stable and continuous in a certain state, the setting of the k value is that abnormal data needs to be searched in the k range, and then the minimum k value is the average interval length between all peak point nodes and represents that the minimum k value is an initial distance parameter which can take into account the minimum adaptation of all stable interval parts.
S4, obtaining the reference stability of the voltage signal by using the local influence values of the voltage signal corresponding to all points except the peak point on the fitting curve; 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 using the local influence values of the rest voltage signals.
Initial distance parameter
The method is only a minimum adaptive distance parameter and is not an optimal distance parameter of a local outlier algorithm, and the problems of excessive abnormal point detection and large algorithm running time exist when the distance parameter of the local outlier algorithm is used for operation. Therefore we derive the initial distance parameter
And starting to increase the size of the distance parameter upwards for iterative estimation to obtain the optimal distance parameter.
Firstly, supposing that the optimal distance parameter is obtained, if the optimal distance parameter is utilized to carry out local outlier detection on all voltage signals and eliminate 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, the actual local outlier detection result is unknown, and therefore the signal stability can be calculated through the local influence value of the voltage signals to carry out analysis on the optimal distance parameter.
Specifically, information entropy of local influence values of voltage signals corresponding to all points except a peak point on a fitting curve is obtained; and taking the obtained information entropy as the reference stability of the voltage signal. The reference stability of the voltage signal is calculated according to the following formula:
wherein the content of the first and second substances,
representing the reference stability of the voltage signal;
representing the number of all voltage signals;
representing the number of voltage signals corresponding to the peak point on the fitting curve;
for removing all peak pointsThe total number of voltage signals;
representing any kind of local influence value
The result of the value of (a) is,
represents the first
Class local influence value
The number of times that the result of the value of (a) appears in all the remaining voltage signals;
represents the first
Class local influence value
The probability of the occurrence of the frequency of the value results in all the remaining voltage signals, and Q represents all the local influence values occurring in the voltage signals
And (4) value type.
The stability of the voltage signal is represented by the information entropy of the local influence value for the information entropy calculation formula.
Removing the voltage signal 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, acquiring 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 with the reference stability as the optimal distance parameter; and performing local outlier algorithm on all the voltage signals by using the optimal distance parameter to obtain interference signals.
Because it is uncertain whether the peak points are noise signals or normal signals, but it can be determined that the peak points are necessarily discrete relative to adjacent signals, and if the peak points are removed, the stability of the whole signal is exhibited after the peak points are all removed when the noise signals are assumed. And the number of actual noise signals is less than or equal to the number of peak points. Then 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, the multiple adjustment means that upward iteration is started from the initial distance parameter, every time a distance parameter is obtained, each peak point in a fitted curve is taken as a center, and an abnormal outlier is removed in a distance parameter k range, namely the maximum local influence value in the k range
The abnormal outlier may be the peak itself or other corresponding voltage signals
The point corresponding to the value, and therefore the target peak point, may be eliminated or retained when k changes. 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 the distance parameter corresponding to the signal stability with the minimum difference between the reference stability is used as the optimal distance parameter.
The reference stability is the stability of the residual signal obtained after all peak points are subjected to limit assumption as noise points, but the actual number of noise signals is inevitably less than or equal to the number of peak points, and then the signal stability after actual denoising is also equal to or greater than the reference stabilityQualitatively, therefore, in the iterative process of the initial distance parameter, an abnormal outlier is removed by taking the peak point as the center and the distance parameter k as the range, namely, the maximum outlier in the range of the distance parameter k is removed
If all peak points have local influence values larger than the peak point in the range of the current distance parameter k, the peak point is reserved and larger peak points are eliminated from the voltage signals corresponding to the values
If the stability of the obtained residual voltage signal is closer to the reference stability, the more the voltage signal is, the less the influence on the stability of the whole signal is, even if the part of peak points are retained, the larger discrete data can be screened out by the current distance parameter k, and normal data fluctuation is retained. The optimal distance parameter is the optimal distance parameter, and the distance parameter is continuously iterated upwards, so that the obtained optimal distance parameter not only can effectively eliminate noise signals and keep data fluctuation information, but also can improve the operation speed of the algorithm relative to the initial distance parameter.
The optimal distance parameter is utilized to perform a local outlier algorithm on all the voltage signals to obtain an interference signal, the local outlier detection algorithm is the prior art and is not described herein any more, and the interference signal is a noise signal of electromagnetic interference.
And comparing the number of all the identified interference signals with the total number of the 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, and the smaller the distribution density of the residual noise is, 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, a gaussian function of each voltage signal is obtained through a time width and an amplitude peak value of the voltage signal, and more accurately and specifically, compared with a characteristic that the voltage signal is represented only through the time width or the amplitude peak value, a local influence value of the voltage signal is obtained through the gaussian function of each voltage signal and an adjacent voltage signal, so that a difference between each voltage signal and a normal voltage signal can be determined, that is, an abnormal degree of each voltage signal can be approximately obtained; and obtaining an initial distance parameter of a distance local outlier algorithm by using the distance between peak points of the fitting curve, namely determining the initial distance parameter of the minimum adaptation, iterating on the basis, and calculating the signal stability and comparing the signal stability with the reference stability to obtain the optimal distance parameter for local outlier detection to obtain the interference signal. Because the invention carries out local outlier detection based on the multidimensional characteristics of the voltage signal, the time width, the amplitude and the difference between adjacent signals, the problem of single characteristic limitation when the traditional noise identification is carried out by utilizing the characteristics of the signal amplitude and the frequency value is solved, and the optimal distance parameter is estimated by adjusting the initial distance parameter for many times and calculating the signal stability when different distance parameters are carried out, so that the optimal distance parameter not only can effectively eliminate the noise signal, keep the voltage fluctuation information, but also takes account of the operation speed of the 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 above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (7)
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 the 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 fitting curve, extracting peak points in the fitting curve, and obtaining initial distance parameters of a local outlier algorithm by using the distance between adjacent peak points on the fitting curve;
obtaining the reference stability of the voltage signal by using the local influence values of the voltage signal corresponding to all points except the peak point on the fitting curve;
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 using the local influence values of the rest voltage signals;
adjusting the initial distance parameter for multiple times to obtain a distance parameter after each adjustment, acquiring 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 minimum difference with the reference stability as an optimal distance parameter;
and performing local outlier algorithm on all the voltage signals by using the optimal distance parameter to obtain interference signals.
2. The method for identifying interference signals based on electromagnetic compatibility experiment according to claim 1, wherein the method for obtaining the local influence value of each voltage signal comprises:
obtaining the area of each voltage signal by utilizing the fixed integral of the Gaussian function of each voltage signal;
acquiring the sum of the areas of two adjacent voltage signals of each voltage signal;
and 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.
3. The method according to claim 2, wherein the area of the voltage signal is an area occupied by the voltage signal in a time domain diagram of the voltage signal, an abscissa of the time domain diagram is time, and an ordinate of the time domain diagram is amplitude.
4. The interference signal identification method based on the electromagnetic compatibility experiment as claimed in claim 1, wherein the method for obtaining the gaussian function of each voltage signal is:
setting a Gaussian function of each voltage signal to
；
Wherein
Is the peak in the amplitude of the voltage signal,
half the time width of the voltage signal.
5. The method for identifying interference signals based on electromagnetic compatibility (EMC) experiments as claimed in claim 1, wherein the method for obtaining the initial distance parameters of the local outlier algorithm comprises:
obtaining the average distance value between adjacent peak points on a fitting curve of the local influence value;
and taking the obtained distance mean value as an initial distance parameter of the local outlier algorithm.
6. The method for identifying the interference signal based on the electromagnetic compatibility experiment as claimed in claim 1, wherein the method for obtaining the reference stability of the voltage signal comprises:
acquiring 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.
7. The method for identifying interference signals based on electromagnetic compatibility experiments according to claim 1, wherein the method for obtaining the signal stability corresponding to the initial distance parameters comprises the following steps:
removing the voltage signal 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.
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