Interference suppression method and device for ultra-high frequency partial discharge signal detection

Abstract

The present application discloses an interference suppression method and apparatus for ultra-high frequency partial discharge signal detection. The method comprises: constructing a normalized envelope detection model for continuous partial discharge signals and a normalized envelope detection model for continuous mixed signals; solving for envelope characteristic parameters of each partial discharge signal based on the normalized envelope detection model for the continuous partial discharge signal, and solving for envelope characteristic parameters of each mixed signal based on the normalized envelope detection model for the continuous mixed signal; wherein a mixed signal refers to a signal that is a mixture of the partial discharge signal and an interference signal; the envelope characteristic parameters include at least a root mean square error, skewness, and steepness of the envelope; and eliminating each partial discharge signal for which the deviation between the envelope characteristic parameters of the partial discharge signal and the corresponding envelope characteristic parameters of the mixed signal is greater than an error ratio, thereby obtaining an interference suppression result for the ultra-high 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 boasts advantages such as compact structure and a small footprint, allowing for easy assembly and expansion based on actual needs. Furthermore, it is less susceptible to the effects of high altitudes and extreme climates, ensuring stable operation in most harsh environments. However, in actual operation, insulation aging caused by long-term operation, assembly errors, and residual conductive material can easily lead to partial discharge (PD), which can damage the insulation strength and threaten the operational stability of high-voltage electrical equipment. Therefore, identification and analysis of PD in these equipment is essential.

[0003] When high-voltage electrical equipment generates partial discharges, it produces ultra-high frequency (UHF) electromagnetic signals. The excitation pattern of UHF electromagnetic signals is correlated with the power frequency voltage. Therefore, current identification and judgment of UHF PD signals primarily relies on establishing a correlation feature (a two-dimensional PRPD spectrum)—the correlation between the power frequency voltage phase, the PD signal amplitude, and the discharge frequency—and then performing discharge type identification and analysis based on this characteristic spectrum. However, when performing statistical spectrum feature analysis, the complexity of the spatial electromagnetic environment and the randomness of background noise significantly impact the statistical spectrum characteristics, leading to PD identification errors and affecting the effective status perception of operating equipment. Therefore, current methods for PD detection employ wavelet transforms, digital filters, and ensemble empirical modes to effectively suppress external electromagnetic interference through raw signal processing and filtering.

[0004] However, the difficulty of acquiring raw UHF signals and the high computational complexity make these methods difficult to directly apply in field testing and analysis. Consequently, there is currently no reliable and practical interference suppression technology for UHF online partial discharge monitoring and critical care equipment. Since the discharge frequency is a key parameter in determining the development of UHF partial discharge, interference signals directly affect the relevant parameters of the partial discharge signal, making it difficult to assess the discharge risk level of 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] A 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 the problem; wherein the envelope characteristic parameters of the partial discharge signal include at least 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;

[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 the problem; wherein the envelope characteristic parameters of the mixed signal include at least 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] 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 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 constructing of a normalized envelope detection model of a continuous partial discharge signal includes:

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

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

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

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

[0018] 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;

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

[0020] The envelope characteristic model of the continuous partial discharge signal 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 solving of a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model includes:

[0022] Performing a 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] Calculating the continuous duration of each of the partial discharge signals based on a normalized envelope detection model of the continuous 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 (RMS) 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 value of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal, the skewness of each partial discharge signal envelope and the steepness of each partial discharge signal envelope are calculated.

[0030] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the step of solving the continuous duration of each partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal includes:

[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] Calculating the envelope start time and envelope end time of each of the partial discharge signals based on the sum and differential output results;

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

[0036] Optionally, in the above-mentioned interference suppression method for ultra-high frequency partial discharge signal detection, the constructing of 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] Constructing a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model;

[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, solving the envelope characteristic model of the mixed signal based on the continuous mixed signal model includes:

[0042] Performing a 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, eliminating each of the partial discharge signals for 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 ratio, to obtain an interference suppression result for the ultra-high frequency partial discharge signal, includes:

[0045] For each of the partial discharge signals, 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 respective deviation values ​​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, configured to obtain envelope characteristic parameters of each partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal; wherein the envelope characteristic parameters of the partial discharge signal include at least 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;

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

[0052] a mixing parameter calculation unit, configured to obtain envelope characteristic parameters of each of the mixed signals based on a normalized envelope detection model of the continuous mixed signal; wherein the envelope characteristic parameters of the mixed signal include at least 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;

[0053] The suppression unit is configured to eliminate each of the partial discharge signals 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 an error ratio, so as to obtain an 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, configured to calculate the number of sampling points of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal;

[0056] a sequence calculation unit, configured to calculate a 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, configured to build a partial discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each of the partial discharge signals;

[0058] a time series model building unit, configured to build 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;

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

[0060] A partial discharge envelope model building unit is used to solve and obtain 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 construction unit includes:

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

[0064] an analytical model building unit, configured to combine a Hilbert transform result of the continuous partial discharge signal with the continuous partial discharge signal model to build an analytical signal model;

[0065] A 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, configured to calculate 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 (RMS) of each of the partial discharge signals based on a mean value of the envelope characteristics of each of the partial discharge signals;

[0070] The skewness and steepness calculation unit is configured 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, configured to 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;

[0073] A filter establishment unit, for establishing a static model of the filter 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, configured to calculate an envelope start time and an envelope end time of each of the partial discharge signals based on the sum and difference output results;

[0076] The duration calculation unit is configured to calculate the continuous duration of each of the partial discharge signals based on the half-order of the sum and 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 construction unit includes:

[0078] an interference signal model building unit, configured 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 construction unit, configured to construct 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, configured to solve and obtain 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 hybrid envelope model construction unit includes:

[0083] a second transform unit, configured to perform a Hilbert transform on the continuous mixed signal model to obtain a Hilbert transform 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, configured to calculate, for each of the partial discharge signals, a deviation between an envelope characteristic parameter of the partial discharge signal and an envelope characteristic parameter of the corresponding mixed signal, to obtain respective deviation values ​​corresponding to the partial discharge signal;

[0087] a judging unit, configured to judge whether all deviation values ​​corresponding to the partial discharge signal are greater than an error ratio;

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

[0089] The present application provides an interference suppression method for ultra-high frequency partial discharge signal detection. A normalized envelope detection model is constructed for continuous partial discharge signals, thereby obtaining an envelope detection model representing the partial discharge signal. Based on the normalized envelope detection model for the continuous partial discharge signal, envelope characteristic parameters of each partial discharge signal are obtained. The envelope characteristic parameters of the partial discharge signal include at least the root mean square error (RMS) of the partial discharge signal envelope, the skewness of the partial discharge signal envelope, and the steepness of the partial discharge signal envelope. Thus, parameters representing the envelope of the partial discharge signal can be obtained. Similarly, a normalized envelope detection model is constructed for continuous mixed signals, thereby obtaining an envelope detection model representing the mixed signal. A mixed signal refers to a signal that is a mixture of a partial discharge signal and an interference signal. Based on the normalized envelope detection model for the continuous mixed signal, envelope characteristic parameters of each mixed signal are obtained. The envelope characteristic parameters of the mixed signal include at least the root mean square error (RMS) of the mixed signal envelope, the skewness of the mixed signal envelope, and the steepness of the mixed signal envelope. Thus, parameters representing the envelope of the mixed signal can be obtained. 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 following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0091] Figure 1 A flowchart 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 flowchart of a method for constructing a normalized envelope detection model for continuous partial discharge signals provided in an embodiment of the present application;

[0093] Figure 3 A flowchart 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 flowchart 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 determining 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 for a continuous mixed signal provided in an embodiment of the present application;

[0097] Figure 7 A flowchart 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 flowchart of a method for eliminating partial discharge signals provided in an embodiment of the present application;

[0099] Figure 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 this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts 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 "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

[0102] The embodiment of the present application 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 suppressing interference signals.

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

[0106] Specifically, a correlation model for each partial discharge signal can be constructed based on relevant information about the signal, such as duration and sampling frequency. Based on these individual partial discharge signals, a model for the continuous partial discharge signal can be derived. Furthermore, based on the model for the continuous partial discharge signal, a normalized envelope detection model for 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 : Calculate the number of sampling points of each partial discharge signal using the duration and sampling frequency 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 : Construct a partial discharge signal duration model using the time series, the first time constant, and the oscillation frequency of each partial 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 partial discharge signal; f is the oscillation frequency; is the first time constant.

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

[0117] Specifically, using the partial discharge signal duration model, for each partial discharge information, the established partial discharge signal timing model 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; t0 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, input Gaussian white noise n(t), combined with the time domain model S of each partial discharge signal 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, obtain a continuous partial discharge signal envelope characteristic model.

[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 envelope characteristic model of the continuous partial discharge signal 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, obtain envelope characteristic parameters of each partial discharge signal.

[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 changes in the envelope of the partial discharge signal. Therefore, based on these three parameters, interference signals 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 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 sum and 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 , calculating 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.

[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 T of the partial discharge signal oa and T oe The difference between the two 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, based on the continuous duration of each partial discharge signal, the mean value of the envelope characteristics of each partial discharge signal in a normalized envelope detection model of continuous partial discharge signals.

[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, the root mean square error of each partial discharge signal can be calculated based on 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:

[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 each partial discharge signal envelope 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 each partial discharge signal envelope 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 for a continuous mixed signal, we can reflect the amplitude variations of the mixed signal. By comparing this with the amplitude variations of a pure partial discharge signal, we can identify the signal within the mixed signal that needs to be suppressed and then suppress it. The construction method for the normalized envelope detection model for a continuous mixed signal is almost identical to that for a continuous partial discharge signal, so the same approach can be used.

[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:

[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 : Combining 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 a normalized envelope detection model of continuous mixed signals, solving and obtaining envelope characteristic parameters of each mixed signal.

[0202] The envelope characteristic parameters of the mixed signal include at least 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 partial discharge signals whose deviations between envelope characteristic parameters of the partial discharge signal and envelope characteristic parameters of the corresponding mixed signal are greater than an error ratio, to obtain interference suppression results of ultra-high frequency partial discharge signals.

[0205] It should be noted that the envelope characteristic parameters of the partial discharge signal are the parameters corresponding to the envelope characteristics under normal circumstances. Therefore, if the deviation between the envelope characteristic parameters of the partial 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 partial discharge signal from the mixed signal to suppress the 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 parameters of the partial discharge signal and the envelope characteristic parameters 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 envelope, 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 all deviation values ​​corresponding to the partial discharge signal are greater than the error ratio, step S803 is executed.

[0215] S803: Eliminate the partial discharge signal.

[0216] An embodiment of the present application provides an interference suppression method for detecting ultra-high frequency partial discharge signals. A normalized envelope detection model is constructed for continuous partial discharge signals, thereby obtaining an envelope detection model representing the partial discharge signal. Based on the normalized envelope detection model for the continuous partial discharge signal, envelope characteristic parameters of each partial discharge signal are obtained. The envelope characteristic parameters of the partial discharge signal include at least the root mean square error (RMS) of the partial discharge signal envelope, the skewness of the partial discharge signal envelope, and the steepness of the partial discharge signal envelope, thereby obtaining parameters representing the envelope of the partial discharge signal. Similarly, a normalized envelope detection model is constructed for a continuous mixed signal, thereby obtaining an envelope detection model representing the mixed signal. A mixed signal refers to a signal that is a mixture of a partial discharge signal and an interference signal. Based on the normalized envelope detection model for the continuous mixed signal, envelope characteristic parameters of each mixed signal are obtained. The envelope characteristic parameters of the mixed signal include at least the root mean square error (RMS) of the mixed signal envelope, the skewness of the mixed signal envelope, and the steepness of the mixed signal envelope, thereby obtaining parameters representing the mixed signal envelope. Finally, each partial discharge signal whose envelope characteristic parameter deviates from the corresponding envelope characteristic parameter of the mixed signal by more than an error ratio is eliminated. This eliminates the partial discharge signal with an envelope error, thereby suppressing the interference signal and obtaining an interference suppression result for the ultra-high frequency partial discharge signal. This effectively suppresses the interference of ultra-high frequency partial discharge signals, enabling accurate assessment of the discharge hazard level of operating equipment.

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

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

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

[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 configured to construct a normalized envelope detection model of a continuous mixed signal, wherein the mixed signal refers to a signal containing a mixture of a partial discharge signal and an interference signal.

[0222] The mixing parameter calculation unit 904 is configured to obtain envelope characteristic parameters of each mixed signal based on a normalized envelope detection model of the continuous mixed signal. The mixed signal envelope characteristic parameters include at least the root mean square error (RMS) 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 configured to remove 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, thereby obtaining an 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 partial discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each partial discharge signal.

[0228] The time series model building unit is used to build a time domain model of each partial discharge signal by using the partial discharge signal duration model, the disturbance vector and the starting time of the partial 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 the 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 construction 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 a 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 utilizing 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 construction 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 hybrid envelope model construction 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 feature 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, and obtain various deviation values ​​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 configured 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 above description has generally described the components and steps of each example according to their functions. 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 beyond the scope of this application.

[0261] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one 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 is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for suppressing interference in 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 the problem; wherein the envelope characteristic parameters of the partial discharge signal include at least 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; 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 the problem; wherein the envelope characteristic parameters of the mixed signal include at least 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; Eliminate the partial discharge signals whose envelope characteristic parameters of the partial discharge signal deviate from the corresponding envelope characteristic parameters of the mixed signal by more than an error ratio, to obtain an interference suppression result of the ultra-high frequency partial discharge signal; The construction of a normalized envelope detection model for continuous partial discharge signals includes: Calculating the number of sampling points of each partial discharge signal using the duration and sampling frequency of each partial discharge signal; Calculating a time series of each of the partial discharge signals based on the number of sampling points of each of the partial discharge signals; Constructing a partial discharge signal duration model using the time series, the first time constant, and the oscillation frequency of each of the partial discharge signals; Establishing a time domain model of each partial discharge signal by using the partial discharge signal duration model, the disturbance vector and the starting time of the partial discharge signal; 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; Based on the continuous partial discharge signal model, a continuous partial discharge signal envelope characteristic model is obtained by solving; 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; The method of constructing a normalized envelope detection model for 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; Constructing a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model; 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.

2. The method according to claim 1, characterized in that The step of obtaining a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model includes: Performing a 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.

3. 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: Calculating the continuous duration of each of the partial discharge signals based on a normalized envelope detection model of the continuous 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 (RMS) 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 value of the envelope characteristics of each partial discharge signal and the root mean square error of each partial discharge signal, the skewness of each partial discharge signal envelope and the steepness of each partial discharge signal envelope are calculated.

4. The method according to claim 3, characterized in that The method of solving the continuous duration of each partial discharge signal based on the normalized envelope detection model of the continuous partial discharge signal includes: 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; Calculating the envelope start time and envelope end time of each of the partial discharge signals based on the sum and differential output results; The continuous duration of each partial discharge signal is calculated based on the half-order of the sum-difference filter, the sampling frequency of each partial discharge signal, the envelope start time and the envelope end time.

5. The method according to claim 1, wherein The step of solving the envelope characteristic model of the mixed signal based on the continuous mixed signal model includes: Performing a 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 signal model to construct an envelope characteristic model of the mixed signal.

6. The method according to claim 1, wherein Eliminating 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 an error ratio to obtain an interference suppression result of the ultra-high frequency partial discharge signal includes: For each of the partial discharge signals, 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 respective deviation values ​​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.

7. 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, configured to obtain envelope characteristic parameters of each partial discharge signal based on a normalized envelope detection model of the continuous partial discharge signal; wherein the envelope characteristic parameters of the partial discharge signal include at least 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; A mixed model construction unit, configured 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, configured to obtain envelope characteristic parameters of each of the mixed signals based on a normalized envelope detection model of the continuous mixed signal; wherein the envelope characteristic parameters of the mixed signal include at least 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; a suppression unit, configured to eliminate each of the partial discharge signals for 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 ratio, thereby obtaining an interference suppression result of the ultra-high frequency partial discharge signal; Wherein, the partial discharge model building unit includes: a point number calculation unit, configured to calculate the number of sampling points of each partial discharge signal by using the duration and sampling frequency of each partial discharge signal; a sequence calculation unit, configured to calculate a 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, configured to build a partial discharge signal duration model by using the time series, the first time constant, and the oscillation frequency of each of the partial discharge signals; a time series model building unit, configured to build 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; A continuous partial discharge model building unit, configured to build a continuous partial discharge signal model based on a time domain model of each partial discharge signal, Gaussian white noise, and a full time series; A partial discharge envelope model construction unit is used to solve and obtain a continuous partial discharge signal envelope characteristic model based on the continuous partial discharge signal model; a partial discharge model normalization unit, configured 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; The hybrid model building unit includes: an interference signal model building unit, configured 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; A continuous mixed signal model construction unit, configured to construct a continuous mixed signal model based on the interference signal model and the continuous partial discharge signal model; A mixed envelope model building unit, configured to solve and obtain an envelope characteristic model of the mixed signal based on the continuous mixed signal model; 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.

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