Interference suppression method and device for ultrahigh frequency partial discharge signal detection

Abstract

The invention discloses an interference suppression method and device for ultrahigh frequency partial discharge signal detection. The method comprises the following steps: constructing a normalized envelope detection model of continuous partial discharge signals and a normalized envelope detection model of continuous mixed signals; based on the normalized envelope detection model of the continuous partial discharge signals, envelope characteristic parameters of all the partial discharge signals are solved, and based on the normalized envelope detection model of the continuous mixed signals, envelope characteristic parameters of all the mixed signals are solved; wherein the mixed signal refers to a signal mixed with the partial discharge signal and the interference signal; the envelope characteristic parameters at least comprise envelope root mean square error, skewness and gradient; and rejecting each partial discharge signal of which the deviation between the envelope characteristic parameter of the partial discharge signal and the envelope characteristic parameter of the corresponding mixed signal is greater than an error proportion to obtain an interference suppression result of the ultrahigh-frequency partial discharge signal.

Description

Technical Field

[0001] The present application relates to the technical field of partial discharge detection of high-voltage electrical equipment, and in particular to an interference suppression method and device for ultra-high frequency partial discharge signal detection. Background Art

[0002] Gas-insulated high-voltage electrical equipment has the advantages of compact structure and small footprint, so it can be combined and expanded according to actual needs. In addition, high altitudes and extreme climates have little impact on its operation, and it can operate stably in most harsh environments. However, in actual operation, insulation aging caused by long-term operation of equipment, assembly errors of electrical equipment, and residual conductive materials can easily cause partial discharge, damage the insulation strength of the equipment, and threaten the stability of high-voltage electrical equipment operation, so it is necessary to identify and analyze the partial discharge of the equipment.

[0003] When high-voltage electrical equipment generates partial discharge, it will generate ultra-high frequency electromagnetic signals, and the excitation form of ultra-high frequency electromagnetic signals is correlated with the power frequency voltage. Therefore, when identifying and judging ultra-high frequency partial discharge signals, the main method is to establish the correlation characteristics of power frequency voltage phase-partial discharge signal amplitude-discharge frequency (two-dimensional PRPD spectrum), and identify and analyze the discharge type based on the characteristic spectrum. When performing statistical spectrum feature analysis, the complexity of the spatial electromagnetic environment and the randomness of the background noise seriously affect the statistical spectrum characteristics, resulting in abnormal partial discharge identification and judgment, affecting the effective state perception of the operating equipment. Therefore, when detecting partial discharge, wavelet transform, digital filter, and ensemble empirical mode methods are used to effectively suppress external electromagnetic interference by processing and filtering the original signal.

[0004] However, in the actual on-site detection and analysis, the difficulty in collecting UHF raw signals and the high computational complexity make the above methods difficult to apply directly, resulting in the lack of reliable and practical interference suppression processing technology for UHF partial discharge online monitoring and intensive care equipment. Since the discharge frequency is one of the key parameters for measuring the partial discharge state when analyzing and determining the development state of UHF partial discharge, the interference signal directly affects the relevant parameters of the partial discharge signal, making it difficult to assess the discharge risk of the operating equipment. Summary of the invention

[0005] Based on the above-mentioned deficiencies of the prior art, the present application provides an interference suppression method and device for ultra-high frequency partial discharge signal detection to solve the problem that the prior art cannot effectively identify and suppress ultra-high frequency partial discharge signals.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] The first aspect of the present application provides an interference suppression method for ultra-high frequency partial discharge signal detection, comprising:

[0008] Construct a normalized envelope detection model for continuous partial discharge signals;

[0009] Based on the normalized envelope detection model of the continuous partial discharge signal, the envelope characteristic parameters of each partial discharge signal are obtained by solving; wherein the envelope characteristic parameters of the partial discharge signal at least include the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope and the steepness of the partial discharge signal envelope;

[0010] Constructing a normalized envelope detection model of a continuous mixed signal; wherein the mixed signal refers to a signal mixed with the partial discharge signal and the interference signal;

[0011] Based on the normalized envelope detection model of the continuous mixed signal, the envelope characteristic parameters of each mixed signal are obtained by solving; wherein the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope and the steepness of the mixed signal envelope;

[0012] Each of the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal are greater than the error ratio is eliminated to obtain the interference suppression result of the ultra-high frequency partial discharge signal.

[0013] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the step of constructing a normalized envelope detection model of a continuous partial discharge signal includes:

[0014] Calculating the number of sampling points of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal;

[0015] Calculating the time series of each of the partial discharge signals based on the number of sampling points of each of the partial discharge signals;

[0016] Using the time series, the first time constant, and the oscillation frequency of each of the partial discharge signals, a partial discharge signal duration model is constructed;

[0017] Establishing a time domain model of each of the partial discharge signals by using the partial discharge signal duration model, the disturbance vector and the starting time of the partial discharge signal;

[0018] Based on the time domain model of each of the partial discharge signals, Gaussian white noise and the full time series, a continuous partial discharge signal model is constructed;

[0019] Based on the continuous partial discharge signal model, a continuous partial discharge signal envelope characteristic model is obtained by solving;

[0020] The continuous partial discharge signal envelope characteristic model is divided by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

[0021] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the step of solving the continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model includes:

[0022] Performing Hilbert transform on the continuous partial discharge signal model to obtain a Hilbert transform result of the continuous partial discharge signal;

[0023] Combining the Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to construct an analytical signal model;

[0024] A modulo operation is performed on the analytical signal model to obtain the continuous partial discharge signal envelope characteristic model.

[0025] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the normalized envelope detection model based on the continuous partial discharge signal is used to solve the envelope characteristic parameters of each partial discharge signal, including:

[0026] Based on the normalized envelope detection model of the continuous partial discharge signal, solving the continuous duration of each of the partial discharge signals;

[0027] Calculating, based on the continuous duration of each of the partial discharge signals, a mean value of the envelope characteristics of each of the partial discharge signals in a normalized envelope detection model of the continuous partial discharge signals;

[0028] Calculating a root mean square error of each of the partial discharge signals based on a mean value of the envelope characteristics of each of the partial discharge signals;

[0029] Based on the mean of the envelope characteristics of each of the partial discharge signals and the root mean square error of each of the partial discharge signals, the skewness of the envelope of each of the partial discharge signals and the steepness of the envelope of each of the partial discharge signals are calculated.

[0030] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the normalized envelope detection model based on the continuous partial discharge signal is used to solve the continuous duration of each partial discharge signal, including:

[0031] Calculating a discrete representation of the envelope detection of the partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal;

[0032] Using the half-order of the sum differential filter, a static model of the filter is established;

[0033] Based on the discrete representation of the partial discharge signal envelope detection and the static model of the filter, a sum and differential output result is calculated;

[0034] Based on the sum and differential output results, calculating the envelope start time and envelope end time of each of the partial discharge signals;

[0035] Based on the half-order of the sum-difference filter, the sampling frequency of each of the partial discharge signals, the envelope start time and the envelope end time, the continuous duration of each of the partial discharge signals is calculated.

[0036] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the step of constructing a normalized envelope detection model of a continuous mixed signal includes:

[0037] Constructing an interference signal model by combining the second time constant, the time series of each of the partial discharge signals and the duration model;

[0038] Based on the interference signal model and the continuous partial discharge signal model, a continuous mixed signal model is constructed;

[0039] Based on the continuous mixed signal model, an envelope characteristic model of the mixed signal is obtained by solving;

[0040] The envelope characteristic model of the mixed signal and the envelope amplitude of each mixed signal are used to obtain a normalized envelope detection model of the continuous mixed signal.

[0041] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the step of solving an envelope characteristic model of the mixed signal based on the continuous mixed signal model includes:

[0042] Performing Hilbert transform on the continuous mixed signal model to obtain a Hilbert transform result of the continuous mixed discharge signal;

[0043] The Hilbert transform result of the continuous mixed discharge signal is combined with the continuous mixed discharge signal model to construct an envelope characteristic model of the mixed signal.

[0044] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal are greater than an error ratio are eliminated to obtain the interference suppression result of the ultra-high frequency partial discharge signal, including:

[0045] For each of the partial discharge signals, respectively, calculating the deviation between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal to obtain each deviation value corresponding to the partial discharge signal;

[0046] Determining whether each deviation value corresponding to the partial discharge signal is greater than an error ratio;

[0047] If it is determined that all deviation values ​​corresponding to the partial discharge signal are greater than the error ratio, the partial discharge signal is eliminated.

[0048] A second aspect of the present application provides an interference suppression device for ultra-high frequency partial discharge signal detection, comprising:

[0049] A partial discharge model building unit, used to build a normalized envelope detection model of continuous partial discharge signals;

[0050] A partial discharge parameter calculation unit, used for solving the envelope characteristic parameters of each partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal; wherein the envelope characteristic parameters of the partial discharge signal at least include the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope and the steepness of the partial discharge signal envelope;

[0051] A mixed model construction unit, used to construct a normalized envelope detection model of a continuous mixed signal; wherein the mixed signal refers to a signal mixed with the partial discharge signal and an interference signal;

[0052] A mixing parameter calculation unit, used for solving the envelope characteristic parameters of each of the mixed signals based on the normalized envelope detection model of the continuous mixed signal; wherein the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope and the steepness of the mixed signal envelope;

[0053] The suppression unit is used to eliminate each of the partial discharge signals whose deviation between the envelope characteristic parameter of the partial discharge signal and the corresponding envelope characteristic parameter of the mixed signal is greater than the error ratio, so as to obtain the interference suppression result of the ultra-high frequency partial discharge signal.

[0054] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the partial discharge model building unit includes:

[0055] A point number calculation unit, used to calculate the number of sampling point digits of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal;

[0056] A sequence calculation unit, used for calculating the time series of each of the partial discharge signals based on the number of sampling points of each of the partial discharge signals;

[0057] A time model building unit, used to build a local discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each of the local discharge signals;

[0058] A time series model building unit, used to build a time domain model of each of the local discharge signals by using the local discharge signal duration model, the disturbance vector and the starting time of the local discharge signal;

[0059] A continuous partial discharge model building unit, used to build a continuous partial discharge signal model based on the time domain model of each partial discharge signal, Gaussian white noise and the full time series;

[0060] A partial discharge envelope model building unit, used for solving and obtaining a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model;

[0061] The partial discharge model normalization unit is used to divide the continuous partial discharge signal envelope characteristic model by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

[0062] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the partial discharge envelope model building unit includes:

[0063] A first transformation unit, configured to perform a Hilbert transformation on the continuous partial discharge signal model to obtain a Hilbert transformation result of the continuous partial discharge signal;

[0064] An analytical model building unit, used for combining the Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to build an analytical signal model;

[0065] The modulo unit is used to perform a modulo operation on the analytical signal model to obtain the continuous partial discharge signal envelope characteristic model.

[0066] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the partial discharge parameter calculation unit includes:

[0067] A duration calculation unit, used for solving the continuous duration of each of the partial discharge signals based on a normalized envelope detection model of the continuous partial discharge signals;

[0068] A mean value calculation unit, configured to calculate a mean value of envelope features of each of the partial discharge signals in a normalized envelope detection model of the continuous partial discharge signals based on the continuous duration of each of the partial discharge signals;

[0069] A variance calculation unit, configured to calculate a root mean square error of each of the partial discharge signals based on a mean value of an envelope feature of each of the partial discharge signals;

[0070] The skewness and steepness calculation unit is used to calculate the skewness of each partial discharge signal envelope and the steepness of each partial discharge signal envelope based on the mean of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal.

[0071] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the duration calculation unit includes:

[0072] A discrete representation calculation unit, used for calculating a discrete representation of the envelope detection of the partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal;

[0073] A filter establishment unit, used for establishing a static model of the filter by using a half order of a sum differential filter;

[0074] A filtering unit, configured to calculate and obtain a differential output result based on the discrete representation of the partial discharge signal envelope detection and the static model of the filter;

[0075] A time calculation unit, used for calculating the envelope start time and envelope end time of each of the partial discharge signals based on the sum and differential output results;

[0076] The duration calculation unit is used to calculate the continuous duration of each of the partial discharge signals based on the half-order of the sum-difference filter, the sampling frequency of each of the partial discharge signals, the envelope start time and the envelope end time.

[0077] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the hybrid model building unit includes:

[0078] An interference signal model building unit, used to build an interference signal model by combining the second time constant, the time series of each of the partial discharge signals and the duration model;

[0079] A continuous mixed signal model building unit, used to build a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model;

[0080] A mixed envelope model building unit, used for solving and obtaining an envelope characteristic model of the mixed signal based on the continuous mixed signal model;

[0081] The mixed model normalization unit is used to obtain a normalized envelope detection model of the continuous mixed signal by combining the envelope characteristic model of the mixed signal and the envelope amplitude of each mixed signal.

[0082] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the mixed envelope model building unit includes:

[0083] A second transformation unit, configured to perform a Hilbert transformation on the continuous mixed signal model to obtain a Hilbert transformation result of the continuous mixed discharge signal;

[0084] A combining unit is used to combine the Hilbert transform result of the continuous mixed discharge signal with the continuous mixed discharge signal model to construct an envelope feature model of the mixed signal.

[0085] Optionally, in the above-mentioned interference suppression device for ultra-high frequency partial discharge signal detection, the suppression unit includes:

[0086] a deviation calculation unit, used for calculating the deviation between the envelope characteristic parameter of the partial discharge signal and the corresponding envelope characteristic parameter of the mixed signal for each partial discharge signal, to obtain each deviation value corresponding to the partial discharge signal;

[0087] A judging unit, used for judging whether each deviation value corresponding to the partial discharge signal is greater than an error ratio;

[0088] The elimination unit is used to eliminate the partial discharge signal when it is determined that each deviation value corresponding to the partial discharge signal is greater than the error ratio.

[0089] The present application provides an interference suppression method for ultra-high frequency partial discharge signal detection, constructing a normalized envelope detection model of continuous partial discharge signals, thereby obtaining an envelope detection model representing the partial discharge signal. Then, based on the normalized envelope detection model of the continuous partial discharge signal, the envelope characteristic parameters of each partial discharge signal are solved. Among them, the envelope characteristic parameters of the partial discharge signal at least include the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope, and the steepness of the partial discharge signal envelope, so that the parameters representing the envelope of the partial discharge signal can be obtained. Similarly, a normalized envelope detection model of a continuous mixed signal is constructed, thereby obtaining an envelope detection model representing the mixed signal. Among them, the mixed signal refers to a signal mixed with a partial discharge signal and an interference signal. Similarly, based on the normalized envelope detection model of the continuous mixed signal, the envelope characteristic parameters of each mixed signal are solved. Among them, the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope, and the steepness of the mixed signal envelope, so as to obtain the parameters representing the envelope of the mixed signal. Finally, the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signal and the envelope characteristic parameters of the corresponding mixed signal are greater than the error ratio are eliminated, that is, the partial discharge signals with envelope errors are eliminated to suppress the interference signals, thereby obtaining the interference suppression results of the ultra-high frequency partial discharge signals, and further realizing an effective method for suppressing the interference of the ultra-high frequency partial discharge signals, so that the discharge hazard level of the operating equipment can be accurately evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0091] Figure 1 A flow chart of an interference suppression method for ultra-high frequency partial discharge signal detection provided in an embodiment of the present application;

[0092] Figure 2 A flow chart of a method for constructing a normalized envelope detection model of a continuous partial discharge signal provided in an embodiment of the present application;

[0093] Figure 3 A flow chart of a method for solving a continuous partial discharge signal envelope characteristic model provided in an embodiment of the present application;

[0094] Figure 4 A flow chart of a method for solving envelope characteristic parameters of each partial discharge signal provided in an embodiment of the present application;

[0095] Figure 5 A flow chart of a method for calculating the continuous duration of each partial discharge signal provided in an embodiment of the present application;

[0096] Figure 6 A flowchart of a method for constructing a normalized envelope detection model of a continuous mixed signal provided in an embodiment of the present application;

[0097] Figure 7 A flow chart of a method for solving an envelope characteristic model of a mixed signal provided in an embodiment of the present application;

[0098] Figure 8 A flow chart of a method for removing partial discharge signals provided in an embodiment of the present application;

[0099] Fig. 9 A schematic diagram of the architecture of an interference suppression device for ultra-high frequency partial discharge signal detection provided in an embodiment of the present application. DETAILED DESCRIPTION

[0100] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0101] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0102] The present application embodiment provides an interference suppression method for ultra-high frequency partial discharge signal detection, such as Figure 1 As shown, the following steps are included:

[0103] S101. Construct a normalized envelope detection model for continuous partial discharge signals.

[0104] It should be noted that the envelope detection model of the partial discharge signal, that is, the model of the amplitude variation of the partial discharge signal, can be used to analyze abnormal signals, thereby processing them and further suppressing interference signals.

[0105] Since the collected local discharge signals are multiple discrete pulse signals, and a continuous unified signal needs to be analyzed during analysis, in an embodiment of the present application, a continuous, normalized envelope detection model of the local discharge signal is constructed based on each local discharge signal, that is, a normalized envelope detection model of the continuous local discharge signal.

[0106] Specifically, the correlation model of each partial discharge signal can be constructed based on the relevant information of each partial discharge signal, such as duration and sampling frequency, and then the model of the continuous partial discharge signal can be obtained based on each partial discharge signal. Further, based on the model of the continuous partial discharge signal, the normalized envelope detection model of the continuous partial discharge signal can be analyzed.

[0107] Optionally, in another embodiment of the present application, a specific implementation of step S101 is as follows: Figure 2 As shown, the following steps are included:

[0108] S201 , using the duration and sampling frequency of each partial discharge signal, calculate the number of sampling points of each partial discharge signal.

[0109] Specifically, the duration of the input partial discharge signal T p , sampling frequency f s , time constant. Then the duration of the partial discharge signal T p Multiply by the sampling frequency f s , then the number of sampling points of the partial discharge signal is obtained.

[0110] S202 : Calculate the time series of each partial discharge signal based on the number of sampling points of each partial discharge signal.

[0111] Specifically, according to the number of sampling points of each partial discharge signal and the combination of the acquisition time of each partial discharge signal, the time series of each partial discharge signal can be obtained.

[0112] S203 , constructing a local discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each local discharge signal.

[0113] Specifically, the constructed partial discharge signal duration model can be expressed as:

[0114]

[0115] Among them, A is the frequency factor, which is a constant; t Tp is the time series of each local discharge signal; f is the oscillation frequency; is the first time constant.

[0116] S204: Establish a time domain model of each partial discharge signal by using the partial discharge signal duration model, the disturbance vector and the start time of the partial discharge signal.

[0117] Specifically, using the local discharge signal duration model, for each local discharge information, the local discharge signal timing model established is S 0m (t Tp ), specifically expressed as:

[0118]

[0119] Where M is the number of partial discharge signals; is the disturbance vector of the mth partial discharge signal; t 0 That is the starting time.

[0120] S205 , constructing a continuous partial discharge signal model based on the time domain model of each partial discharge signal, Gaussian white noise and the full time series.

[0121] Specifically, the Gaussian white noise n(t) is input and the time domain model S of each partial discharge signal is combined 0m (t Tp ) and the full time series t, the continuous partial discharge signal model S(t) is constructed:

[0122]

[0123] S206. Based on the continuous partial discharge signal model, a continuous partial discharge signal envelope characteristic model is obtained by solving.

[0124] Specifically, after the continuous partial discharge signal model is obtained, the envelope characteristics of the continuous partial discharge signal model may be analyzed to obtain the continuous partial discharge signal envelope characteristic model.

[0125] Optionally, in another embodiment of the present application, a specific implementation of step S206 is as follows: Figure 3 As shown, the following steps are included:

[0126] S301 , performing Hilbert transform on a continuous partial discharge signal model to obtain a Hilbert transform result of the continuous partial discharge signal.

[0127] Specifically, the Hilbert transform result of the continuous partial discharge signal is:

[0128]

[0129] S302: Combining the Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to construct an analytical signal model.

[0130] Specifically, the analytical signal model is expressed as:

[0131]

[0132] Where j is the imaginary part of Z(t).

[0133] S303 , performing a modulo operation on the analytical signal model to obtain a continuous partial discharge signal envelope characteristic model.

[0134] Specifically, the continuous partial discharge signal envelope characteristic model is expressed as:

[0135]

[0136] S207 , dividing the continuous partial discharge signal envelope characteristic model by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

[0137] Therefore, the normalized envelope detection model of continuous partial discharge signal is specifically expressed as:

[0138]

[0139] Among them, A m is the envelope amplitude of the mth partial discharge signal.

[0140] S102 . Based on a normalized envelope detection model of continuous partial discharge signals, envelope characteristic parameters of each partial discharge signal are obtained by solving the model.

[0141] Among them, the envelope characteristic parameters of the partial discharge signal include at least the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope and the steepness of the partial discharge signal envelope. These three parameters can accurately reflect the change of the envelope of the partial discharge signal. Therefore, based on these three parameters, the interference signal can be analyzed and suppressed.

[0142] Optionally, in another embodiment of the present application, a specific implementation of step S102 is as follows: Figure 4 As shown, the following steps are included:

[0143] S401 . Based on a normalized envelope detection model of continuous partial discharge signals, the continuous duration of each partial discharge signal is solved.

[0144] It should be noted that in order to calculate the variance of the envelope characteristics of each partial discharge signal, it is necessary to determine the continuous duration of the envelope detection of each partial discharge signal so that the corresponding data can be used for calculation. The normalized envelope detection model of the continuous partial discharge signal represents the envelope detection of the partial discharge signal. Therefore, based on the normalized envelope detection model of the continuous partial discharge signal, the continuous duration of each partial discharge signal can be solved.

[0145] Optionally, in another embodiment of the present application, a specific implementation of step S401 is as follows: Figure 5 As shown, including:

[0146] S501 . Calculate a discrete representation of the envelope detection of the partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal.

[0147] Specifically, the discrete representation of the partial discharge signal envelope detection can be expressed as:

[0148]

[0149] S502: Establish a static model of the filter by using the half-order of the sum differential filter.

[0150] In order to filter the partial discharge signal envelope detection through the filter, the half-order number N of the input and differential filter is set up, and the static model h(k) of the filter is established:

[0151]

[0152] S503, based on the discrete representation of the partial discharge signal envelope detection and the static model of the filter, calculate and obtain the differential output results.

[0153] Specifically, the sum and differential output results are expressed as:

[0154]

[0155] Among them, H(k) is the static model h(k) of the filter.

[0156] S504: Calculate the envelope start time and envelope end time of each partial discharge signal based on the sum and differential output results.

[0157] Specifically, based on the sum and differential output results YH, the envelope starting y of M local party signals can be calculated. max and envelope cutoff time y min :

[0158]

[0159]

[0160] S505 , based on the half-order of the sum differential filter, the sampling frequency of each partial discharge signal, the envelope start time and the envelope end time, calculate and obtain the continuous duration of each partial discharge signal.

[0161] Specifically, based on the half-order of the sum differential filter, the sampling frequency of each partial discharge signal, the envelope start time and the envelope end time, the partial discharge signal time domain parameter T is calculated. oa and T oe :

[0162]

[0163]

[0164] The time domain parameter of the partial discharge signal is T oa and T oe The difference between the values ​​of , is the continuous duration PW of the partial discharge signal, so the continuous duration PW of the partial discharge signal is:

[0165]

[0166] S402 : Calculate the mean value of the envelope characteristics of each partial discharge signal in a normalized envelope detection model of continuous partial discharge signals based on the continuous duration of each partial discharge signal.

[0167] Specifically, the normalized envelope detection model of the continuous partial discharge signal is calculated, and the mean of the values ​​within the continuous duration of the partial discharge signal is obtained to obtain the mean of the envelope characteristics of the partial discharge signal. .

[0168] S403 . Calculate the root mean square error of each partial discharge signal based on the mean value of the envelope characteristics of each partial discharge signal.

[0169] Specifically, according to the difference between each value of the normalized envelope detection model of the continuous partial discharge signal and the mean value of the envelope characteristics of the partial discharge signal, the root mean square error of each partial discharge signal can be calculated:

[0170]

[0171] S404 . Based on the mean of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal, calculate the skewness of the envelope of each partial discharge signal and the steepness of the envelope of each partial discharge signal.

[0172] Specifically, based on the mean value of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal, the skewness of the envelope of each partial discharge signal is calculated:

[0173]

[0174] Similarly, based on the mean value of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal, the steepness of the envelope of each partial discharge signal is calculated:

[0175]

[0176] S103: construct a normalized envelope detection model for a continuous mixed signal.

[0177] The mixed signal refers to a signal mixed with a partial discharge signal and an interference signal.

[0178] Similarly, by constructing a normalized envelope detection model of a continuous mixed signal, the amplitude change of the mixed signal can be reflected. By comparing the amplitude change of the mixed signal with that of a pure partial discharge signal, the signal that needs to be suppressed in the mixed signal can be determined and suppressed. The construction method of the normalized envelope detection model of a continuous mixed signal is almost the same as that of the normalized envelope detection model of a continuous partial discharge signal, so it can be constructed in a corresponding manner.

[0179] Optionally, in another embodiment of the present application, a specific implementation of step S103 is as follows: Figure 6 As shown, including:

[0180] S601: Construct an interference signal model by combining the second time constant, the time series of each partial discharge signal and the duration model.

[0181] Specifically, the interference signal is consistent with the local signal, so according to the duration model, the interference signal model is constructed by using the second time constant and the time series of each local discharge signal accordingly:

[0182]

[0183] in, is the second time constant.

[0184] S602: construct a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model.

[0185] Since the mixed signal is a mixture of the interference signal and the partial discharge signal, the continuous mixed signal model can be constructed by combining the interference signal model and the continuous partial discharge signal model:

[0186]

[0187] Among them, S 0M (t Tp ) is the Mth continuous partial discharge signal model, that is, the model of the Mth partial discharge signal; and S L (t Tp ) is the Lth interference signal model.

[0188] S603: Based on the continuous mixed signal model, an envelope characteristic model of the mixed signal is obtained by solving.

[0189] Similarly, after obtaining the continuous mixed signal model, its envelope characteristics can be analyzed to obtain the envelope characteristic model of the mixed signal.

[0190] Optionally, in another embodiment of the present application, a specific implementation of step S603 is as follows: Figure 7 As shown, including:

[0191] S701, performing Hilbert transform on the continuous mixed signal model to obtain a Hilbert transform result of the continuous mixed discharge signal.

[0192] Specifically, the Hilbert transform result of the continuous mixed discharge signal is:

[0193]

[0194] S702: Combine the Hilbert transform result of the continuous mixed discharge signal with the continuous mixed discharge signal model to construct an envelope characteristic model of the mixed signal.

[0195] Specifically, the envelope characteristic model of the mixed signal is expressed as:

[0196]

[0197] S604: Divide the envelope characteristic model of the mixed signal by the envelope amplitude of each mixed signal to obtain a normalized envelope detection model of the continuous mixed signal.

[0198] Specifically, the normalized envelope detection model of the continuous mixed signal is:

[0199]

[0200] Among them, B i is the envelope amplitude of the i-th mixed signal.

[0201] S104: Based on the normalized envelope detection model of the continuous mixed signal, the envelope characteristic parameters of each mixed signal are obtained by solving.

[0202] The envelope characteristic parameters of the mixed signal at least include a root mean square error of the mixed signal envelope, a skewness of the mixed signal envelope, and a steepness of the mixed signal envelope.

[0203] It should be noted that the calculation method of the envelope characteristic parameters of the mixed signal is consistent with the calculation method of the envelope characteristic parameters of the partial discharge signal, and therefore will not be described in detail.

[0204] S105 , eliminating each partial discharge signal whose deviation between the envelope characteristic parameter of the partial discharge signal and the envelope characteristic parameter of the corresponding mixed signal is greater than the error ratio, to obtain an interference suppression result of the ultra-high frequency partial discharge signal.

[0205] It should be noted that the envelope characteristic parameters of the local discharge signal are the parameters corresponding to the envelope characteristics under normal circumstances. Therefore, if the deviation between the envelope characteristic parameters of the local discharge signal and the envelope characteristic parameters of the corresponding mixed signal is greater than the error ratio, it means that the error is too large and it is an interference signal. Therefore, it is necessary to eliminate the local discharge signal in the mixed signal to suppress interference.

[0206] Optionally, in another embodiment of the present application, a specific implementation of step S105 is as follows: Figure 8 As shown, the following steps are included:

[0207] S801 . For each partial discharge signal, calculate the deviation between the envelope characteristic parameter of the partial discharge signal and the envelope characteristic parameter of the corresponding mixed signal to obtain each deviation value corresponding to the partial discharge signal.

[0208] Therefore, the deviation values ​​corresponding to the partial discharge signal are:

[0209]

[0210]

[0211]

[0212] Among them, p all and p s are the RMS errors of the mixed signal and partial discharge signal envelopes, respectively; and are the skewness of the mixed signal and partial discharge signal respectively; Z all and Z s are the steepness of the mixed signal and partial discharge signal envelopes, respectively.

[0213] S802: Determine whether all deviation values ​​corresponding to the partial discharge signal are greater than the error ratio.

[0214] If it is determined that each deviation value corresponding to the partial discharge signal is greater than the error ratio, step S803 is executed.

[0215] S803: Eliminate the partial discharge signal.

[0216] The embodiment of the present application provides an interference suppression method for ultra-high frequency local discharge signal detection, constructs a normalized envelope detection model of continuous local discharge signals, and thus obtains an envelope detection model representing the local discharge signal. Then, based on the normalized envelope detection model of the continuous local discharge signal, the envelope characteristic parameters of each local discharge signal are solved. Among them, the envelope characteristic parameters of the local discharge signal at least include the root mean square error of the local discharge signal envelope, the skewness of the local discharge signal envelope, and the steepness of the local discharge signal envelope, so that the parameters representing the envelope of the local discharge signal can be obtained. Similarly, a normalized envelope detection model of a continuous mixed signal is constructed to obtain an envelope detection model representing the mixed signal. Among them, the mixed signal refers to a signal mixed with a local discharge signal and an interference signal. Similarly, based on the normalized envelope detection model of the continuous mixed signal, the envelope characteristic parameters of each mixed signal are solved. The envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope and the steepness of the mixed signal envelope, thereby obtaining the parameters representing the envelope of the mixed signal. Finally, the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal are greater than the error ratio are eliminated, that is, the partial discharge signals with envelope errors are eliminated to achieve suppression of interference signals, thereby obtaining the interference suppression results of the ultra-high frequency partial discharge signals, and further realizing a method for effectively suppressing the interference of ultra-high frequency partial discharge signals, so that the discharge hazard level of the running equipment can be accurately evaluated.

[0217] Another embodiment of the present application provides an interference suppression device for ultra-high frequency partial discharge signal detection, such as Fig. 9 As shown, including:

[0218] The partial discharge model building unit 901 is used to build a normalized envelope detection model of a continuous partial discharge signal.

[0219] The partial discharge parameter calculation unit 902 is used to solve and obtain the envelope characteristic parameters of each partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal.

[0220] The envelope characteristic parameters of the partial discharge signal at least include a root mean square error of the partial discharge signal envelope, a skewness of the partial discharge signal envelope, and a steepness of the partial discharge signal envelope.

[0221] The mixed model construction unit 903 is used to construct a normalized envelope detection model of a continuous mixed signal, wherein the mixed signal refers to a signal mixed with a partial discharge signal and an interference signal.

[0222] The mixed parameter calculation unit 904 is used to solve the envelope characteristic parameters of each mixed signal based on the normalized envelope detection model of the continuous mixed signal, wherein the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope, and the steepness of the mixed signal envelope.

[0223] The suppression unit 905 is used to remove each partial discharge signal whose deviation between the envelope characteristic parameter of the partial discharge signal and the envelope characteristic parameter of the corresponding mixed signal is greater than the error ratio, so as to obtain the interference suppression result of the ultra-high frequency partial discharge signal.

[0224] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the partial discharge model building unit includes:

[0225] The point number calculation unit is used to calculate the sampling point number of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal.

[0226] The sequence calculation unit is used to calculate the time series of each partial discharge signal based on the number of sampling points of each partial discharge signal.

[0227] The time model building unit is used to build a local discharge signal duration model by using the time series, the first time constant and the oscillation frequency of each local discharge signal.

[0228] The time series model building unit is used to build a time domain model of each local discharge signal by using the local discharge signal duration model, the disturbance vector and the starting time of the local discharge signal.

[0229] The continuous partial discharge model building unit is used to build a continuous partial discharge signal model based on the time domain model of each partial discharge signal, Gaussian white noise and the full time series.

[0230] The partial discharge envelope model building unit is used to solve and obtain a continuous partial discharge signal envelope characteristic model based on a continuous partial discharge signal model.

[0231] The partial discharge model normalization unit is used to divide the continuous partial discharge signal envelope characteristic model by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

[0232] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the partial discharge envelope model building unit includes:

[0233] The first transformation unit is used to perform Hilbert transformation on the continuous partial discharge signal model to obtain a Hilbert transformation result of the continuous partial discharge signal.

[0234] The analytical model building unit is used to combine the Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to build an analytical signal model.

[0235] The modulo unit is used to perform modulo operation on the analytical signal model to obtain a continuous partial discharge signal envelope characteristic model.

[0236] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the partial discharge parameter calculation unit includes:

[0237] The duration calculation unit is used to solve the continuous duration of each partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal.

[0238] The mean value calculation unit is used to calculate the mean value of the envelope characteristics of each partial discharge signal in the normalized envelope detection model of the continuous partial discharge signal based on the continuous duration of each partial discharge signal.

[0239] The variance calculation unit is used to calculate the root mean square error of each partial discharge signal based on the mean value of the envelope characteristics of each partial discharge signal.

[0240] The skewness and steepness calculation unit is used to calculate the skewness of each partial discharge signal envelope and the steepness of each partial discharge signal envelope based on the mean of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal.

[0241] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the duration calculation unit includes:

[0242] The discrete representation calculation unit is used to calculate the envelope detection discrete representation of the partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal.

[0243] The filter establishment unit is used to establish a static model of the filter by using the half order of the sum differential filter.

[0244] The filtering unit is used to calculate and obtain the differential output results based on the discrete representation of the partial discharge signal envelope detection and the static model of the filter.

[0245] The time calculation unit is used to calculate the envelope start time and envelope end time of each partial discharge signal based on the sum and differential output results.

[0246] The duration calculation unit is used to calculate the continuous duration of each partial discharge signal based on the half-order of the sum differential filter, the sampling frequency of each partial discharge signal, the envelope start time and the envelope end time.

[0247] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the hybrid model building unit includes:

[0248] The interference signal model building unit is used to build an interference signal model by combining the second time constant, the time series of each partial discharge signal and the duration model.

[0249] The continuous mixed signal model building unit is used to build a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model.

[0250] The mixed envelope model building unit is used to solve the envelope characteristic model of the mixed signal based on the continuous mixed signal model.

[0251] The mixed model normalization unit is used to obtain a normalized envelope detection model of the continuous mixed signal by combining the envelope characteristic model of the mixed signal and the envelope amplitude of each mixed signal.

[0252] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the mixed envelope model building unit includes:

[0253] The second transformation unit is used to perform Hilbert transformation on the continuous mixed signal model to obtain a Hilbert transformation result of the continuous mixed discharge signal.

[0254] The combining unit is used to combine the Hilbert transform result of the continuous mixed discharge signal with the continuous mixed discharge signal model to construct an envelope characteristic model of the mixed signal.

[0255] Optionally, in the interference suppression device for ultra-high frequency partial discharge signal detection provided in another embodiment of the present application, the suppression unit includes:

[0256] The deviation calculation unit is used to calculate the deviation between the envelope characteristic parameters of the partial discharge signal and the envelope characteristic parameters of the corresponding mixed signal for each partial discharge signal, so as to obtain each deviation value corresponding to the partial discharge signal.

[0257] The judging unit is used to judge whether each deviation value corresponding to the partial discharge signal is greater than the error ratio.

[0258] The elimination unit is used to eliminate the partial discharge signal when it is determined that each deviation value corresponding to the partial discharge signal is greater than the error ratio.

[0259] It should be noted that the specific working process of each unit provided in the above embodiments of the present application can refer to the implementation process of the corresponding steps in the above method embodiments, and will not be repeated here.

[0260] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0261] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An interference suppression method for ultra-high frequency partial discharge signal detection, characterized in that: include: Construct a normalized envelope detection model for continuous partial discharge signals; Based on the normalized envelope detection model of the continuous partial discharge signal, the envelope characteristic parameters of each partial discharge signal are obtained by solving; wherein the envelope characteristic parameters of the partial discharge signal at least include the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope and the steepness of the partial discharge signal envelope; Constructing a normalized envelope detection model of a continuous mixed signal; wherein the mixed signal refers to a signal mixed with the partial discharge signal and the interference signal; Based on the normalized envelope detection model of the continuous mixed signal, the envelope characteristic parameters of each mixed signal are obtained by solving; wherein the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope and the steepness of the mixed signal envelope; Each of the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal are greater than the error ratio is eliminated to obtain the interference suppression result of the ultra-high frequency partial discharge signal.

2. The method according to claim 1, characterized in that: The method of constructing a normalized envelope detection model of a continuous partial discharge signal includes: Calculating the number of sampling points of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal; Calculating the time series of each of the partial discharge signals based on the number of sampling points of each of the partial discharge signals; Using the time series, the first time constant, and the oscillation frequency of each of the partial discharge signals, a partial discharge signal duration model is constructed; Establishing a time domain model of each of the partial discharge signals by using the partial discharge signal duration model, the disturbance vector and the starting time of the partial discharge signal; Based on the time domain model of each of the partial discharge signals, Gaussian white noise and the full time series, a continuous partial discharge signal model is constructed; Based on the continuous partial discharge signal model, a continuous partial discharge signal envelope characteristic model is obtained by solving; The continuous partial discharge signal envelope characteristic model is divided by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

3. The method according to claim 2, characterized in that The method of solving a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model includes: Performing Hilbert transform on the continuous partial discharge signal model to obtain a Hilbert transform result of the continuous partial discharge signal; Combining the Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to construct an analytical signal model; A modulo operation is performed on the analytical signal model to obtain the continuous partial discharge signal envelope characteristic model.

4. The method according to claim 1, characterized in that: The normalized envelope detection model based on the continuous partial discharge signal is used to solve the envelope characteristic parameters of each partial discharge signal, including: Based on the normalized envelope detection model of the continuous partial discharge signal, solving the continuous duration of each of the partial discharge signals; Calculating, based on the continuous duration of each of the partial discharge signals, a mean value of the envelope characteristics of each of the partial discharge signals in a normalized envelope detection model of the continuous partial discharge signals; Calculating a root mean square error of each of the partial discharge signals based on a mean value of the envelope characteristics of each of the partial discharge signals; Based on the mean of the envelope characteristics of each of the partial discharge signals and the root mean square error of each of the partial discharge signals, the skewness of the envelope of each of the partial discharge signals and the steepness of the envelope of each of the partial discharge signals are calculated.

5. The method according to claim 4, characterized in that The normalized envelope detection model based on the continuous partial discharge signal is used to solve the continuous duration of each partial discharge signal, including: Calculating a discrete representation of the envelope detection of the partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal; Using the half-order of the sum differential filter, a static model of the filter is established; Based on the discrete representation of the partial discharge signal envelope detection and the static model of the filter, a sum and differential output result is calculated; Based on the sum and differential output results, calculating the envelope start time and envelope end time of each of the partial discharge signals; Based on the half-order of the sum-difference filter, the sampling frequency of each of the partial discharge signals, the envelope start time and the envelope end time, the continuous duration of each of the partial discharge signals is calculated.

6. The method according to claim 2, characterized in that The method of constructing a normalized envelope detection model of a continuous mixed signal includes: Constructing an interference signal model by combining the second time constant, the time series of each of the partial discharge signals and the duration model; Based on the interference signal model and the continuous partial discharge signal model, a continuous mixed signal model is constructed; Based on the continuous mixed signal model, an envelope characteristic model of the mixed signal is obtained by solving; The envelope characteristic model of the mixed signal and the envelope amplitude of each mixed signal are used to obtain a normalized envelope detection model of the continuous mixed signal.

7. The method according to claim 6, characterized in that The step of solving the envelope characteristic model of the mixed signal based on the continuous mixed signal model comprises: Performing Hilbert transform on the continuous mixed signal model to obtain a Hilbert transform result of the continuous mixed discharge signal; The Hilbert transform result of the continuous mixed discharge signal is combined with the continuous mixed discharge signal model to construct an envelope characteristic model of the mixed signal.

8. The method according to claim 1, characterized in that The step of removing the partial discharge signals whose deviations between the envelope characteristic parameters of the partial discharge signals and the corresponding envelope characteristic parameters of the mixed signal are greater than the error ratio, and obtaining the interference suppression result of the ultra-high frequency partial discharge signal, comprises: For each of the partial discharge signals, respectively, calculating the deviation between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal to obtain each deviation value corresponding to the partial discharge signal; Determining whether each deviation value corresponding to the partial discharge signal is greater than an error ratio; If it is determined that all deviation values ​​corresponding to the partial discharge signal are greater than the error ratio, the partial discharge signal is eliminated.

9. An interference suppression device for ultra-high frequency partial discharge signal detection, characterized in that: include: A partial discharge model building unit, used to build a normalized envelope detection model of continuous partial discharge signals; A partial discharge parameter calculation unit, used for solving the envelope characteristic parameters of each partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal; wherein the envelope characteristic parameters of the partial discharge signal at least include the root mean square error of the partial discharge signal envelope, the skewness of the partial discharge signal envelope and the steepness of the partial discharge signal envelope; A mixed model construction unit, used to construct a normalized envelope detection model of a continuous mixed signal; wherein the mixed signal refers to a signal mixed with the partial discharge signal and an interference signal; A mixing parameter calculation unit, used for solving the envelope characteristic parameters of each of the mixed signals based on the normalized envelope detection model of the continuous mixed signal; wherein the envelope characteristic parameters of the mixed signal at least include the root mean square error of the mixed signal envelope, the skewness of the mixed signal envelope and the steepness of the mixed signal envelope; The suppression unit is used to eliminate each of the partial discharge signals whose deviation between the envelope characteristic parameter of the partial discharge signal and the corresponding envelope characteristic parameter of the mixed signal is greater than the error ratio, so as to obtain the interference suppression result of the ultra-high frequency partial discharge signal.

10. The device according to claim 9, characterized in that The partial discharge model building unit comprises: A point number calculation unit, used to calculate the number of sampling point digits of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal; A sequence calculation unit, used for calculating the time series of each of the partial discharge signals based on the number of sampling points of each of the partial discharge signals; A time model building unit, used to build a local discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each of the local discharge signals; A time series model building unit, used to build a time domain model of each of the local discharge signals by using the local discharge signal duration model, the disturbance vector and the starting time of the local discharge signal; A continuous partial discharge model building unit, used to build a continuous partial discharge signal model based on the time domain model of each partial discharge signal, Gaussian white noise and the full time series; A partial discharge envelope model building unit, used for solving and obtaining a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model; The partial discharge model normalization unit is used to divide the continuous partial discharge signal envelope characteristic model by the envelope amplitude of each partial discharge signal to obtain a normalized envelope detection model of the continuous partial discharge signal.

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