Cable joint discharge signal denoising method and device and electronic equipment

Abstract

The invention discloses a cable joint discharge signal denoising method and device and electronic equipment. The method comprises the steps that a discharge signal sequence corresponding to a cable connector is acquired, and the discharge signal sequence comprises signal frequencies corresponding to a plurality of time points respectively; decomposing the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points to obtain a plurality of decomposed sequences corresponding to the discharge signal sequence; determining a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposition sequences; determining time sequence matrixes respectively corresponding to the plurality of decomposition sequences; and determining a target de-noising sequence corresponding to the discharge signal sequence according to the time sequence matrixes corresponding to the plurality of decomposition sequences and the residual signal sequence. The technical problem that the cable joint discharge detection is inaccurate due to the poor denoising effect of the cable joint discharge signal is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, and in particular, to a cable joint discharge signal denoising method and device and electronic equipment. BACKGROUND

[0002] In the related art, discharge detection needs to be performed on a cable joint to prevent insulation faults and ensure stable operation of a power system. However, when performing discharge detection on the cable joint in a complex environment, the discharge signal is subject to multiple interferences. In the related art, there is a technical problem of poor cable joint discharge signal denoising effect, which leads to inaccurate cable joint discharge detection.

[0003] To address the above problems, no effective solutions have been proposed so far. SUMMARY

[0004] Embodiments of the present application provide a cable joint discharge signal denoising method, device and electronic equipment to at least solve the technical problem of inaccurate cable joint discharge detection due to poor cable joint discharge signal denoising effect.

[0005] According to an aspect of an embodiment of the present application, a cable joint discharge signal denoising method is provided, including: obtaining a discharge signal sequence corresponding to a cable joint, wherein the discharge signal sequence includes signal frequencies corresponding to a plurality of time points respectively; decomposing the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points respectively to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; determining a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposition sequences; determining time sequence matrices corresponding to the plurality of decomposition sequences respectively, wherein a row of the corresponding time sequence matrix represents a signal frequency of the corresponding decomposition sequence in different time sequence dimensions, and a column of the corresponding time sequence matrix represents a signal frequency of the corresponding decomposition sequence in a corresponding different time sequence offset; and determining a target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrices corresponding to the plurality of decomposition sequences respectively and the residual signal sequence.

[0006] Optionally, the determining the target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrix corresponding to the plurality of decomposition sequences and the residual signal sequence comprises: determining a time characteristic parameter corresponding to the time sequence matrix corresponding to the plurality of decomposition sequences according to a row of the time sequence matrix corresponding to the plurality of decomposition sequences, and determining an offset characteristic parameter corresponding to the time sequence matrix corresponding to the plurality of decomposition sequences according to a column of the time sequence matrix corresponding to the plurality of decomposition sequences; determining a signal intensity parameter corresponding to the time sequence matrix corresponding to the plurality of decomposition sequences; determining a denoising decomposition sequence corresponding to the plurality of decomposition sequences according to the time characteristic parameter, the spatial characteristic parameter and the signal intensity parameter corresponding to the plurality of decomposition sequences; and determining the target denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences and the residual signal sequence.

[0007] Optionally, the decomposing the discharge signal sequence according to the signal frequency corresponding to the plurality of time points to obtain the plurality of decomposition sequences corresponding to the discharge signal sequence comprises: in the case of multiple decompositions, determining a plurality of first period segments corresponding to the discharge signal sequence according to the signal frequency corresponding to the plurality of time points in the execution order of the multiple decompositions, and determining an extreme value corresponding to the plurality of first period segments; determining a first decomposition sequence corresponding to the discharge signal sequence according to the extreme value corresponding to the plurality of first period segments; determining a next signal sequence according to the discharge signal sequence and the first decomposition sequence; determining a plurality of next period segments corresponding to the next signal sequence, and determining an extreme value corresponding to the plurality of next period segments; determining a next decomposition sequence corresponding to the next signal sequence according to the extreme value corresponding to the plurality of next period segments, until the multiple decompositions are completed, to obtain the plurality of decomposition sequences corresponding to the discharge signal sequence.

[0008] Optionally, the determining the first decomposition sequence corresponding to the discharge signal sequence according to the extreme value corresponding to the plurality of first period segments comprises: in the case that the extreme value corresponding to the plurality of first period segments respectively comprises a maximum value and a minimum value, determining a first fluctuation sequence corresponding to the discharge signal sequence according to the maximum value corresponding to the plurality of first period segments, wherein the maximum value is a maximum signal frequency in the corresponding first period segment, and the minimum value is a minimum signal frequency in the corresponding first period segment, and determining a second fluctuation sequence corresponding to the discharge signal sequence according to the minimum value corresponding to the plurality of first period segments; and determining the first decomposition sequence corresponding to the discharge signal sequence according to the first fluctuation sequence and the second fluctuation sequence.

[0009] Optionally, the determining the target denoising sequence corresponding to the discharge signal sequence according to the multiple denoising decomposition sequences and the residual signal sequence comprises: determining an initial denoising sequence corresponding to the discharge signal sequence according to the multiple denoising decomposition sequences; determining sequence features corresponding to the initial denoising sequence; and determining the target denoising sequence corresponding to the discharge signal sequence according to the sequence features corresponding to the initial denoising sequence.

[0010] Optionally, the decomposing the discharge signal sequence according to the signal frequencies corresponding to the multiple time points to obtain the multiple decomposition sequences corresponding to the discharge signal sequence comprises: decomposing the discharge signal sequence according to the signal frequencies corresponding to the multiple time points to obtain multiple candidate sequences corresponding to the discharge signal sequence; determining similarity indexes corresponding to the multiple candidate sequences according to the multiple candidate sequences and the discharge signal sequence, wherein the similarity indexes correspond to degrees of similarity between the candidate sequences and the discharge signal sequence; and screening the multiple decomposition sequences from the multiple candidate sequences according to the similarity indexes corresponding to the multiple candidate sequences, wherein the similarity indexes corresponding to the multiple decomposition sequences are greater than or equal to a similarity threshold.

[0011] Optionally, the determining the residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the multiple decomposition sequences comprises: determining a mean sequence corresponding to the multiple decomposition sequences; and determining the residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the mean sequence.

[0012] According to an aspect of an embodiment of the present application, a cable joint discharge signal denoising device is provided, comprising: an acquisition module configured to acquire a discharge signal sequence corresponding to a cable joint, wherein the discharge signal sequence comprises signal frequencies corresponding to multiple time points; a first determination module configured to decompose the discharge signal sequence according to the signal frequencies corresponding to the multiple time points to obtain multiple decomposition sequences corresponding to the discharge signal sequence, wherein the multiple decomposition sequences are used to represent fluctuation features of the discharge signal sequence in different frequency ranges; a second determination module configured to determine a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the multiple decomposition sequences; a third determination module configured to determine time sequence matrices corresponding to the multiple decomposition sequences, wherein rows of the time sequence matrices represent signal frequencies of the corresponding decomposition sequences in different time sequence dimensions, and columns of the time sequence matrices represent signal frequencies of the corresponding decomposition sequences in different time sequence offsets; and a fourth determination module configured to determine a target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrices corresponding to the multiple decomposition sequences and the residual signal sequence.

[0013] According to an aspect of the embodiments of the present application, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the cable joint discharge signal denoising method of any of the above.

[0014] According to an aspect of the embodiments of the present application, a computer readable storage medium is provided, when instructions in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the cable joint discharge signal denoising method of any of the above.

[0015] In the embodiments of the present application, by the above steps S102-S110, the discharge signal sequence corresponding to the cable joint is obtained, wherein the discharge signal sequence includes signal frequencies corresponding to a plurality of time points respectively; the discharge signal sequence is decomposed according to the signal frequencies corresponding to the plurality of time points respectively, to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; the residual signal sequence corresponding to the discharge signal sequence is determined according to the discharge signal sequence and the plurality of decomposition sequences; the time sequence matrix corresponding to the plurality of decomposition sequences is determined, wherein the row of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence dimensions, and the column of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence offsets; and the target denoising sequence corresponding to the discharge signal sequence is determined according to the time sequence matrix corresponding to the plurality of decomposition sequences respectively and the residual signal sequence. According to the signal frequencies corresponding to the plurality of time points respectively in the discharge signal sequence, the discharge signal sequence is decomposed according to different frequency ranges, to obtain the plurality of decomposition sequences and the residual signal sequence corresponding to the discharge signal sequence, which can accurately reflect the fluctuation characteristics of the discharge signal sequence in different frequency ranges. On this basis, the time sequence matrix corresponding to the plurality of decomposition sequences is determined to analyze the discharge signal sequence in different time sequence dimensions and different time sequence offsets, so that the accurate denoising of the discharge signal sequence can be realized by combining the corresponding time sequence matrix and the residual signal sequence, to improve the accuracy of the cable joint discharge detection, thereby solving the technical problem of inaccurate cable joint discharge detection due to poor cable joint discharge signal denoising effect. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0017] Figure 1is a flow chart of the cable joint discharge signal denoising method of the embodiment of the present application;

[0018] Figure 2 is a flow chart of the cable joint partial discharge signal denoising method of the optional embodiment of the present application;

[0019] Figure 3 is a circuit diagram of the partial discharge signal detection circuit of the optional embodiment of the present application;

[0020] Figure 4 is a schematic diagram of the partial discharge signal simulated by software of the optional embodiment of the present application;

[0021] Figure 5 is a schematic diagram of the noise signal added with white noise and periodic narrowband interference of the optional embodiment of the present application;

[0022] Figure 6 is a schematic diagram of the partial discharge signal after denoising of the optional embodiment of the present application;

[0023] Figure 7 is a structural block diagram of the cable joint discharge signal denoising device of the embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to make the personnel in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0025] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0026] First, some nouns or terms appearing in the process of describing the embodiments of the present application are applicable to the following explanations:

[0027] CEEMDAN algorithm: CEEMDAN is a signal processing algorithm that is an improvement on the Empirical Mode Decomposition (EMD) method.

[0028] SSA method: SSA method, i.e., singular spectrum analysis, is a non-parametric time series analysis method.

[0029] Singular Value Decomposition (SVD): Singular Value Decomposition (SVD) is a method of decomposing a matrix into the product of three specific matrices.

[0030] Hankel matrix: Hankel matrix is a special matrix whose elements are constant along the anti-diagonal direction.

[0031] Embodiment 1

[0032] According to an embodiment of the present application, an embodiment of a cable joint discharge signal denoising method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0033] Figure 1 is a flowchart of the cable joint discharge signal denoising method according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0034] S102, obtaining a discharge signal sequence corresponding to the cable joint, wherein the discharge signal sequence comprises signal frequencies corresponding to a plurality of time points respectively;

[0035] In step S102 provided in the present application, the discharge signal sequence corresponding to the cable joint is obtained.

[0036] Among them, the cable joint is used to connect the cable to make the cable line continuous. In the power system, the cable joint is used to connect different sections of the cable to ensure smooth transmission of current. Because the insulation structure at the cable joint is relatively complex, partial discharge phenomenon is easy to occur, so it needs to be detected and analyzed.

[0037] Among them, the discharge signal sequence is a sequence formed by arranging the signals generated by the partial discharge at the cable joint in a certain time in chronological order. These signals reflect the characteristics of partial discharge, including the intensity, frequency, duration, etc. of the discharge. By analyzing the discharge signal sequence, the insulation state of the cable joint can be determined.

[0038] The multiple time points refer to specific time instants at which the signals are collected and recorded in the discharge signal sequence. These time points are usually equally spaced and represent the state of the signal at different times. For example, during signal collection, the frequency of the signal is recorded at regular intervals (e.g., every 1 millisecond), and these recording instants are the multiple time points.

[0039] The signal frequency refers to the number of times a signal periodically changes within a unit of time, usually expressed in Hertz (Hz). In cable joint partial discharge detection, the signal frequency reflects the periodic characteristics of the discharge signal. Different discharge types and noise sources produce signals of different frequencies, and by analyzing the signal frequency, useful signals and noise can be distinguished.

[0040] Obtaining the discharge signal sequence corresponding to the cable joint allows us to understand the discharge signal frequency and other characteristics of the cable joint at different time points, providing an analysis basis for subsequent cable joint discharge signal denoising.

[0041] S104, according to the signal frequency corresponding to the multiple time points, decompose the discharge signal sequence to obtain multiple decomposition sequences corresponding to the discharge signal sequence, wherein the multiple decomposition sequences represent the fluctuation characteristics of the discharge signal sequence in different frequency ranges;

[0042] In step S104 provided in the present application, the discharge signal sequence is decomposed according to the signal frequency corresponding to the multiple time points, and multiple decomposition sequences corresponding to the discharge signal sequence are obtained.

[0043] The multiple decomposition sequences refer to multiple subsequences obtained by decomposing the discharge signal sequence according to different frequency ranges. Each decomposition sequence represents the fluctuation characteristics of the original signal in a specific frequency range.

[0044] By decomposing the discharge signal sequence, the complex signal can be decomposed into multiple relatively simple sub-signals with specific frequency characteristics, facilitating subsequent individual analysis and processing of signals with different frequency components.

[0045] S106, according to the discharge signal sequence and the multiple decomposition sequences, determine the residual signal sequence corresponding to the discharge signal sequence;

[0046] In step S106 provided in the present application, according to the discharge signal sequence and the multiple decomposition sequences, the residual signal sequence corresponding to the discharge signal sequence is determined.

[0047] The residual signal sequence is a difference between the discharge signal sequence and a sum of all the decomposition sequences after the discharge signal sequence is decomposed. The residual signal sequence contains residual information of the discharge signal sequence that is not completely represented by the decomposition sequences, including signal features that are not captured.

[0048] The residual signal sequence is determined according to the discharge signal sequence and the plurality of decomposition sequences, residual information that is not completely represented by the decomposition sequences can be extracted, and therefore subsequent in-depth analysis of signal features that are not captured in the discharge signal sequence can be facilitated, so that the composition of the signal is more comprehensively understood, and the accuracy of signal denoising and the reliability of partial discharge detection are improved.

[0049] In step S108 provided in the present application, a time sequence matrix corresponding to each of the plurality of decomposition sequences is determined. The row of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence dimensions, and the column of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence offsets.

[0050] In step S108 provided in the present application, a time sequence matrix corresponding to each of the plurality of decomposition sequences is determined. The row of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence dimensions, and the column of the corresponding time sequence matrix represents the signal frequency of the corresponding decomposition sequence in different time sequence offsets.

[0051] The time sequence matrix reflects the form of arranging the signal frequency of the decomposition sequence in different time dimensions. Each row of the time sequence matrix represents the signal frequency of the decomposition sequence at different time points, and each column represents the signal frequency of the decomposition sequence at different time offsets.

[0052] By constructing the time sequence matrix, the variation rule of the decomposition sequence in time can be more intuitively observed and analyzed, which provides convenience for subsequent signal processing and feature extraction.

[0053] In step S110 provided in the present application, a target denoising sequence corresponding to the discharge signal sequence is determined according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence.

[0054] In step S110 provided in the present application, a target denoising sequence corresponding to the discharge signal sequence is determined according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence.

[0055] The target denoising sequence is a final denoised signal sequence obtained by comprehensively analyzing and processing the time sequence matrix of the plurality of decomposition sequences and the residual signal sequence.

[0056] According to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence, the target denoising sequence is determined, which can retain as much useful information in the original discharge signal as possible while removing noise and other interference components, thereby improving the quality and analyzability of the signal, and further helping to improve the accuracy of the cable joint discharge detection.

[0057] Through the steps S102-S110, the discharge signal sequence corresponding to the cable joint is obtained, wherein the discharge signal sequence includes signal frequencies corresponding to a plurality of time points respectively; the discharge signal sequence is decomposed according to the signal frequencies corresponding to the plurality of time points respectively, to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; a residual signal sequence corresponding to the discharge signal sequence is determined according to the discharge signal sequence and the plurality of decomposition sequences; a time sequence matrix corresponding to each of the plurality of decomposition sequences is determined, wherein a row of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence dimensions, and a column of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence offsets; and a target denoising sequence corresponding to the discharge signal sequence is determined according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence. According to the signal frequencies corresponding to the plurality of time points in the discharge signal sequence, the discharge signal sequence is decomposed according to different frequency ranges, to obtain the plurality of decomposition sequences and the residual signal sequence corresponding to the discharge signal sequence, which can accurately reflect the fluctuation characteristics of the discharge signal sequence in different frequency ranges. On this basis, the time sequence matrix corresponding to each of the plurality of decomposition sequences is determined to analyze the discharge signal sequence in different time sequence dimensions and different time sequence offsets, so that the discharge signal sequence can be accurately denoised by combining the corresponding time sequence matrix and the residual signal sequence, to improve the accuracy of the cable joint discharge detection, thereby solving the technical problem that the cable joint discharge detection is inaccurate due to poor denoising effect of the discharge signal of the cable joint.

[0058] As an optional embodiment, determining the target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence includes: determining time characteristic parameters corresponding to each of the plurality of decomposition sequences according to the rows of the time sequence matrix corresponding to each of the plurality of decomposition sequences, and determining offset characteristic parameters corresponding to each of the plurality of decomposition sequences according to the columns of the time sequence matrix corresponding to each of the plurality of decomposition sequences; determining signal intensity parameters corresponding to each of the plurality of decomposition sequences according to the time sequence matrix corresponding to each of the plurality of decomposition sequences; determining denoising decomposition sequences corresponding to each of the plurality of decomposition sequences according to the time characteristic parameters, the spatial characteristic parameters and the signal intensity parameters corresponding to each of the plurality of decomposition sequences; and determining the target denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences and the residual signal sequence.

[0059] In this embodiment, the specific steps of determining the target denoised sequence corresponding to the discharge signal sequence according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence are described.

[0060] The time characteristic parameter is a parameter obtained by analyzing the rows of the time sequence matrix of the decomposition sequence, and is used to describe the signal frequency variation characteristics of the decomposition sequence at different time points. The time characteristic parameter reflects the fluctuation characteristics of the signal in the time dimension, such as periodicity, trend, etc.

[0061] The offset characteristic parameter is a parameter obtained by analyzing the columns of the time sequence matrix of the decomposition sequence, and is used to describe the signal frequency variation characteristics of the decomposition sequence at different time offsets. The offset characteristic parameter reflects the fluctuation characteristics of the signal in the time offset dimension, and is helpful for further analyzing the time sequence characteristics of the decomposition sequence.

[0062] The signal intensity parameter is a parameter obtained by analyzing the time sequence matrix of the decomposition sequence, and is used to describe the intensity characteristics (such as amplitude) of the signal in the decomposition sequence, and reflects the strength of the signal.

[0063] The denoised decomposition sequence is a sequence obtained by denoising each decomposition sequence after comprehensively considering the time characteristic parameter, the offset characteristic parameter and the signal intensity parameter. The denoised decomposition sequence retains the useful information in the decomposition sequence, while removing noise and other interference components, and is used for the construction of the target denoised sequence.

[0064] In the steps involved in this embodiment, first, the time characteristic parameters corresponding to the plurality of decomposition sequences are determined according to the rows of the time sequence matrix corresponding to each of the plurality of decomposition sequences, and the offset characteristic parameters corresponding to the plurality of decomposition sequences are determined according to the columns of the time sequence matrix corresponding to each of the plurality of decomposition sequences. Then, the signal intensity parameters corresponding to the plurality of decomposition sequences are determined according to the time sequence matrix corresponding to each of the plurality of decomposition sequences. Next, the denoised decomposition sequences corresponding to the plurality of decomposition sequences are determined according to the time characteristic parameters, the spatial characteristic parameters and the signal intensity parameters corresponding to each of the plurality of decomposition sequences. Finally, the target denoised sequence corresponding to the discharge signal sequence is determined according to the plurality of denoised decomposition sequences and the residual signal sequence.

[0065] Through the above steps, the time sequence matrix of the decomposition sequence is analyzed in multiple dimensions, the time characteristic parameter, the offset characteristic parameter and the signal intensity parameter are extracted, and these multi-dimensional characteristic parameters can accurately identify and retain useful signals, remove noise, and improve the denoising accuracy of the cable joint discharge signal.

[0066] As an optional embodiment, the discharge signal sequence is decomposed according to the signal frequencies corresponding to the multiple time points to obtain multiple decomposition sequences corresponding to the discharge signal sequence, including: in the case of multiple decompositions, according to the execution order of the multiple decompositions, determining multiple first period segments corresponding to the discharge signal sequence according to the signal frequencies corresponding to the multiple time points, and determining extreme values corresponding to the multiple first period segments, determining a first decomposition sequence corresponding to the discharge signal sequence according to the extreme values corresponding to the multiple first period segments; determining a next signal sequence according to the discharge signal sequence and the first decomposition sequence; determining multiple next period segments corresponding to the next signal sequence, and determining extreme values corresponding to the multiple next period segments, determining a next decomposition sequence corresponding to the next signal sequence according to the extreme values corresponding to the multiple next period segments, until the multiple decompositions are executed to obtain the multiple decomposition sequences corresponding to the discharge signal sequence.

[0067] In this embodiment, the specific steps of decomposing the discharge signal sequence according to the signal frequencies corresponding to the multiple time points to obtain the multiple decomposition sequences corresponding to the discharge signal sequence are described.

[0068] Among them, multiple decompositions are involved, which are the process of decomposing the discharge signal sequence multiple times step by step. Each decomposition extracts a part of the characteristics (such as fluctuations in a specific frequency range) from the signal and generates a new signal sequence for the next decomposition. This step-by-step decomposition method helps to analyze the different frequency components of the signal more carefully.

[0069] Among them, multiple first period segments are involved, which are the time segments with fluctuation frequency characteristics obtained by dividing the discharge signal sequence into multiple time segments according to the change of signal frequency in the first decomposition process. Each period segment represents a complete fluctuation period of the signal in a specific frequency range.

[0070] Among them, the first decomposition sequence is involved, which is the signal sequence extracted according to the extreme values of the multiple first period segments in the first decomposition process.

[0071] Among them, the extreme value is involved, which is the maximum value (maximum value) and minimum value (minimum value) of the signal frequency in each period segment.

[0072] Among them, the next signal sequence is involved, which is the remaining signal sequence obtained by subtracting the first decomposition sequence from the discharge signal sequence after the first decomposition. This sequence contains other frequency components in addition to the first decomposition sequence, which is used for the next decomposition.

[0073] The next cycle segments are time segments with similar fluctuation frequency characteristics, which are divided according to the signal frequency variation of the next signal sequence in the subsequent decomposition process.

[0074] The next decomposition sequence is a signal sequence extracted according to the extreme values of the next cycle segments in the subsequent decomposition process. The next decomposition sequence represents the fluctuation characteristics of the next main frequency component in the next signal sequence. Through multiple decompositions, multiple decomposition sequences are finally obtained, each sequence corresponding to a specific frequency range in the signal.

[0075] In the steps involved in this embodiment, in the case of decomposition into multiple decompositions, according to the execution order of the multiple decompositions, multiple first cycle segments corresponding to the discharge signal sequence are determined according to the signal frequencies corresponding to the multiple time points respectively, and extreme values corresponding to the multiple first cycle segments respectively are determined. A first decomposition sequence corresponding to the discharge signal sequence is determined according to the extreme values corresponding to the multiple first cycle segments respectively. Then, a next signal sequence is determined according to the discharge signal sequence and the first decomposition sequence. Next, multiple next cycle segments corresponding to the next signal sequence are determined, extreme values corresponding to the multiple next cycle segments respectively are determined, and a next decomposition sequence corresponding to the next signal sequence is determined according to the extreme values corresponding to the multiple next cycle segments respectively, and the above steps are repeated until the multiple decompositions are executed, obtaining multiple decomposition sequences corresponding to the discharge signal sequence.

[0076] In the process of multiple decompositions, multiple first cycle segments corresponding to the discharge signal sequence and their extreme values are determined step by step, and then the first decomposition sequence is determined, and the next signal sequence is obtained by subtracting the decomposition sequence from the original signal, and the above process is repeated, and finally multiple decomposition sequences are obtained, which realizes the decomposition of the complex discharge signal sequence into multiple sub-sequences with specific frequency ranges, so as to analyze the different frequency components of the signal more carefully, so as to more accurately identify and process the different frequency characteristics in the signal, and provide clearer basis for subsequent signal denoising.

[0077] As an optional embodiment, the first decomposition sequence corresponding to the discharge signal sequence is determined according to the extreme values corresponding to the plurality of first period segments, including: in the case that the extreme values corresponding to the plurality of first period segments respectively include maximum values and minimum values, the first fluctuation sequence corresponding to the discharge signal sequence is determined according to the maximum values corresponding to the plurality of first period segments, wherein the maximum value is the maximum signal frequency in the corresponding first period segment, and the minimum value is the minimum signal frequency in the corresponding first period segment, and the second fluctuation sequence corresponding to the discharge signal sequence is determined according to the minimum values corresponding to the plurality of first period segments; the first decomposition sequence corresponding to the discharge signal sequence is determined according to the first fluctuation sequence and the second fluctuation sequence.

[0078] In this embodiment, the specific steps of determining the first decomposition sequence corresponding to the discharge signal sequence according to the extreme values corresponding to the plurality of first period segments are illustrated.

[0079] The maximum value is the maximum value of the signal frequency in each period segment (such as the first period segment, the next period segment). These maximum values reflect the highest fluctuation points of the signal in the period segment.

[0080] The minimum value is the minimum value of the signal frequency in each period segment (such as the first period segment, the next period segment). These minimum values reflect the lowest fluctuation points of the signal in the period segment.

[0081] The first fluctuation sequence is a signal sequence determined according to the maximum values of the plurality of first period segments. The first fluctuation sequence represents the maximum fluctuation characteristics of the discharge signal sequence in each period segment, and reflects the upper envelope line of the discharge signal sequence.

[0082] The second fluctuation sequence is a signal sequence determined according to the minimum values of the plurality of first period segments. The second fluctuation sequence represents the minimum fluctuation characteristics of the discharge signal sequence in each period segment, and reflects the lower envelope line of the discharge signal sequence.

[0083] In the steps involved in this embodiment, in the case that the extreme values corresponding to the plurality of first period segments respectively include maximum values and minimum values, first, the first fluctuation sequence corresponding to the discharge signal sequence is determined according to the maximum values corresponding to the plurality of first period segments. And the second fluctuation sequence corresponding to the discharge signal sequence is determined according to the minimum values corresponding to the plurality of first period segments. Then, the first decomposition sequence corresponding to the discharge signal sequence is determined according to the first fluctuation sequence and the second fluctuation sequence.

[0084] In the case that multiple first cycle segments correspond to extreme values (maximum and minimum values) respectively, the process of determining the first decomposition sequence by determining the first fluctuation sequence and the second fluctuation sequence can more accurately characterize the up and down fluctuation range of the signal, so as to extract the main fluctuation characteristics from the complex discharge signal sequence, and provide an analysis basis for subsequent signal denoising.

[0085] As an optional embodiment, determining the target denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences and the residual signal sequence comprises: determining an initial denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences; determining sequence characteristics corresponding to the initial denoising sequence; and determining the target denoising sequence corresponding to the discharge signal sequence according to the sequence characteristics corresponding to the initial denoising sequence.

[0086] In this embodiment, specific steps of determining the target denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences and the residual signal sequence are described.

[0087] The initial denoising sequence is a signal sequence obtained by preliminarily integrating the plurality of denoising decomposition sequences. The initial denoising sequence is a preliminary denoising result formed by combining the denoised decomposition sequences after denoising each decomposition sequence. This sequence retains the main characteristics of the signal, but further optimization is needed to achieve better denoising effect.

[0088] The sequence characteristics are parameters or indexes extracted from the initial denoising sequence to describe the characteristics of the signal. The sequence characteristics include the amplitude, frequency, phase, energy distribution, etc. of the signal, and can also include more complex statistical characteristics or time-frequency domain characteristics.

[0089] In the steps involved in this embodiment, the initial denoising sequence corresponding to the discharge signal sequence is determined according to the plurality of denoising decomposition sequences. Then, the sequence characteristics corresponding to the initial denoising sequence are determined, and the target denoising sequence corresponding to the discharge signal sequence is determined according to the sequence characteristics corresponding to the initial denoising sequence.

[0090] By determining the initial denoising sequence according to the plurality of denoising decomposition sequences, extracting the sequence characteristics thereof, and optimizing the denoising effect accordingly to obtain a more accurate and clearer target denoising sequence, the fine processing of denoising is further realized, the denoising precision is improved, and the accuracy and reliability of the cable joint partial discharge detection are further enhanced.

[0091] As an optional embodiment, the step of decomposing the discharge signal sequence according to the signal frequencies corresponding to the time points respectively to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence comprises: decomposing the discharge signal sequence according to the signal frequencies corresponding to the time points respectively to obtain a plurality of candidate sequences corresponding to the discharge signal sequence; determining a similarity index corresponding to each of the plurality of candidate sequences according to the plurality of candidate sequences and the discharge signal sequence, wherein the similarity index corresponding to each of the plurality of candidate sequences represents a similarity degree of the corresponding candidate sequence to the discharge signal sequence; and screening a plurality of decomposition sequences from the plurality of candidate sequences according to the similarity index corresponding to each of the plurality of candidate sequences, wherein the similarity index corresponding to each of the plurality of decomposition sequences is greater than or equal to a similarity threshold.

[0092] In this embodiment, the specific steps of decomposing the discharge signal sequence according to the signal frequencies corresponding to the time points respectively to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence are described.

[0093] Among them, the plurality of candidate sequences are candidate sequences generated initially according to signal frequencies and other characteristics in the process of decomposing the discharge signal sequence. The plurality of candidate sequences are intermediate results in the decomposition process and have not been screened yet, containing useful signal components, noise or other irrelevant components.

[0094] Among them, the similarity index is a quantitative index for measuring the similarity degree of each candidate sequence to the original discharge signal sequence. The similarity index reflects the matching degree of the candidate sequence to the signal discharge sequence in terms of characteristics such as frequency, amplitude, etc.

[0095] Among them, the similarity threshold is a preset value used as a judgment standard when screening the decomposition sequences. Only when the similarity index of the candidate sequence is greater than or equal to the similarity threshold, the sequence will be selected as the final decomposition sequence. The similarity threshold can be adjusted according to specific applications and signal characteristics, with the purpose of ensuring that the screened decomposition sequences are representative enough to effectively reflect the most real characteristics of the discharge signal of the cable joint.

[0096] In the steps involved in this embodiment, the discharge signal sequence is decomposed according to the signal frequencies corresponding to the time points respectively to obtain a plurality of candidate sequences corresponding to the discharge signal sequence. Then, a similarity index corresponding to each of the plurality of candidate sequences is determined according to the plurality of candidate sequences and the discharge signal sequence. Finally, a plurality of decomposition sequences are screened from the plurality of candidate sequences according to the similarity index corresponding to each of the plurality of candidate sequences, wherein the similarity index corresponding to each of the plurality of decomposition sequences is greater than or equal to a similarity threshold.

[0097] Through the above steps, a plurality of candidate sequences are obtained by decomposing the discharge signal sequence, and a high-similarity sequence to the discharge signal sequence is screened out by using a similarity index, so that representative components can be quickly extracted from complex signals, and noise and irrelevant components can be preliminarily removed.

[0098] As an optional embodiment, determining the residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposed sequences comprises: determining a mean sequence corresponding to the plurality of decomposed sequences; and determining the residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the mean sequence.

[0099] In this embodiment, specific steps of determining the residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposed sequences are described.

[0100] The mean sequence is a sequence obtained by averaging the values of the plurality of decomposed sequences at each time point. The mean sequence reflects the average signal characteristics of the decomposed sequences at each time point and is used to represent the overall trend of the decomposed sequences.

[0101] In the steps described in this embodiment, the mean sequence corresponding to the plurality of decomposed sequences is determined, and the residual signal sequence corresponding to the discharge signal sequence is determined according to the discharge signal sequence and the mean sequence.

[0102] By determining the mean sequence of the decomposed sequence and comparing it with the discharge signal sequence, the remaining information that is not completely characterized by the decomposed sequence can be extracted, and the signal components in the obtained signal that are not processed by the decomposed processing can be accurately identified, providing analysis basis for subsequent signal analysis and noise removal, to improve the accuracy and reliability of signal processing.

[0103] Based on the above embodiments and optional embodiments, an optional implementation is provided, which is described in detail as follows.

[0104] In the related art, discharge detection needs to be performed on the cable joint to prevent insulation failure and ensure stable operation of the power system. However, when the discharge detection is performed on the cable joint in a complex environment, the discharge signal will be subjected to multiple interferences. In the related art, there is a technical problem that the discharge signal of the cable joint has poor denoising effect, resulting in inaccurate discharge detection of the cable joint.

[0105] At present, no effective solution has been proposed to solve the above problems.

[0106] Therefore, in the optional implementation of the present application, a cable joint discharge signal denoising method, which can also be referred to as a cable joint partial discharge signal denoising method, is provided, which can effectively solve the technical problem that the discharge signal of the cable joint has poor denoising effect in the related art, resulting in inaccurate discharge detection of the cable joint.

[0107] Figure 2 is a flow chart of the cable joint partial discharge signal denoising method in the optional embodiment of the present application, Figure 3 is a circuit diagram of the cable joint partial discharge signal detection circuit in the optional embodiment of the present application, Figure 4 is a schematic diagram of the partial discharge signal simulated by software in the optional embodiment of the present application, Figure 5 is a schematic diagram of the noise signal added with white noise and periodic narrowband interference in the optional embodiment of the present application, Figure 6 is a schematic diagram of the partial discharge signal after denoising in the optional embodiment of the present application. As Figure 2 , Figure 3 , Figure 4 , Figure 5 , and Figure 6 shown below are described in detail.

[0108] S1: Obtain the time-domain partial discharge signal at the cable joint (the same as the above discharge signal sequence).

[0109] Obtain the discharge signal sequence corresponding to the cable joint, wherein the discharge signal sequence includes signal frequencies corresponding to multiple time points respectively. The time-domain partial discharge signal at the cable joint is detected by a high-frequency current sensor, and the reference direction of the high-frequency current sensor points to the center of the monitored cable.

[0110] S2: CEEMDAN algorithm iteration denoising.

[0111] Add white noise to the original signal s(t), perform empirical mode (EMD) decomposition on the noise-added signal, obtain the intrinsic mode function (IMF) component and the residual error, and repeat the above process m times. Take the average of all obtained IMF components to obtain the IMF component of this decomposition, and calculate the residual error of this EMD decomposition. Perform EMD decomposition on the white noise, add the decomposed signal to the residual error, and mark it as a new target signal (the same as the above discharge signal sequence). Perform EMD decomposition on the new target signal, and repeat the above process m times. When the termination condition (the residual error obtained by EMD decomposition is monotonic) is met, the iteration process ends. The specific steps include:

[0112] S21: Add white noise n i (t) (i = 1, 2…m) to the original signal s(t), perform EMD decomposition on the noise-added signal, obtain the IMF component and the residual error, and repeat the above process m times. The decomposition process is as follows:

[0113]

[0114] Wherein:

[0115] E() represents EMD decomposition;

[0116] denotes the IMF component extracted from the noisy signal s(t) + n i (t) in the i-th noisy decomposition process;

[0117] r i denotes the residual signal left after extracting the IMF component from the noisy signal s(t) + n i (t) in the i-th noisy decomposition process.

[0118] S22: average all the obtained IMF components to obtain the IMF component imfi of this decomposition. Remove the imfi component from the original signal s(t) to obtain the residual ri(t) of this EMD decomposition, which is as follows:

[0119]

[0120] S23: perform EMD decomposition on n i (t) and add the obtained signal to the residual ri(t) to obtain a new target signal. Perform EMD decomposition on the new target signal, and repeat the above process m times. The decomposition process is as follows:

[0121]

[0122] wherein:

[0123] denotes the IMF component extracted from the new target signal in the i-th noisy decomposition process.

[0124] S24: repeat the above steps until the termination condition (the residual r i (t) obtained by EMD decomposition is monotonic) is met, and the iteration process ends. At this time, the original signal s(t) can be represented as the sum of several IMF components imf i (the above-mentioned multiple candidate sequences) and the residual r i (t) (the above-mentioned residual signal sequence):

[0125]

[0126] S3: denoise the IMF components using the SSA algorithm.

[0127] According to the EMD modal correlation sorting criterion, the IMF component irrelevant to the original signal frequency is separated, and the signal layer and the noise layer are determined. The modal correlation sorting criterion is determined by calculating the cross-correlation coefficient R between the modal function and the original signal (similar to the above-mentioned similarity index), and determining the noise and signal demarcation point k (similar to the above-mentioned similarity threshold), and the noise layer IMF component is removed based on the demarcation point. The remaining IMF component (similar to the above-mentioned plurality of decomposition sequences) is denoised by the SSA method, and then reconstructed after denoising. The denoised IMF component and the residual are added to obtain the preliminary denoised signal. The specific steps are as follows:

[0128] S31: According to the EMD modal correlation sorting criterion, the IMF component irrelevant to the original signal frequency is separated, and the signal layer and the noise layer are determined. The modal correlation sorting criterion is determined by calculating the cross-correlation coefficient R between the modal function and the original signal, as shown in the following formula:

[0129]

[0130] Wherein:

[0131] imf i represents the IMF component of the i-th decomposition;

[0132] cov() represents the covariance;

[0133] D s(t) represents the variance of the original signal s(t);

[0134] represents the variance of the IMF component of the i-th decomposition.

[0135] Then the noise and signal demarcation point k is:

[0136] k = argmin R (s (t), imf i )+1

[0137] The noise layer IMF component is removed based on the demarcation point.

[0138] S32: The remaining IMF component is denoised by the SSA method, and then reconstructed after denoising. Taking one of the IMF components as an example, the IMF component x = [x1, x2, …, x N′ ], the window length L is set, and the trajectory matrix X (similar to the above-mentioned time series matrix) is constructed:

[0139] X = [X1, X2, …, X K ]

[0140] Each column (similar to the column of the above-mentioned time series matrix) is represented as:

[0141]

[0142] wherein:

[0143] x N′ denotes the N'th element in the IMF component x;

[0144] X K denotes the K'th column in the trajectory matrix X;

[0145] denotes the i'th element in the K'th column X K n

[0146] Singular Value Decomposition (SVD) is performed on the trajectory matrix X to obtain singular values (same as the signal strength parameter described above). The first several principal components are retained (usually taking the cumulative singular value to reach more than 90% energy), and the remaining high-frequency noise singular components are discarded. The retained singular value items are used to reconstruct the matrix, and after diagonal averaging, the timing signal is reconstructed to obtain the denoised IMF component (same as the denoised decomposition sequence described above).

[0147] S33: Add the denoised IMF component to the residual obtained in step S24 to obtain a preliminary denoised signal (same as the initial denoising sequence described above).

[0148] S4: Construct a Hankel matrix for further denoising.

[0149] The preliminary denoised signal (same as the initial denoising sequence described above) is sampled and constructed into a Hankel matrix. Singular value decomposition is performed on the Hankel matrix to obtain singular values. The singular values are arranged in descending order from large to small. The remaining noise signal in the signal can be represented by the first several larger singular values, and other signals are represented by subsequent singular values. A reasonable threshold is set to find the first several singular values representing noise signals and reconstruct them to obtain a one-dimensional sequence corresponding to the remaining noise signal. Subtract the remaining noise signal from the preliminary denoised signal to obtain the final denoised partial discharge signal (same as the target denoising sequence described above). The specific steps are as follows:

[0150] S41: Sample the preliminary denoised signal to obtain a sequence S = {S(1), S(2), …, S(Num)}, where Num is the number of sampling points. The sequence is constructed into a Hankel matrix, and the form of the Hankel matrix is:

[0151]

[0152] wherein:

[0153] M denotes the number of rows of the matrix;

[0154] num denotes the number of columns of the matrix;

[0155] ​​M+num-1=Num, num is generally in the range of [Num / 20, Num / 2].

[0156] S42: For the M*num dimensional Hankel matrix H, there is an M*M dimensional orthogonal matrix U and a num*num dimensional orthogonal matrix V, such that:

[0157] H M×num =U M×M S M×num V num×num T

[0158] Wherein:

[0159] H M×num is an M*num dimensional Hankel matrix;

[0160] U M×M is an M*M dimensional orthogonal matrix;

[0161] V num×num is a num*num dimensional orthogonal matrix;

[0162] S M×num is an M*num dimensional non-negative diagonal matrix, that is, S M×num =diag(δ1,δ,...,δ s ), δ1,δ2,...,δ s are singular values of the matrix H, and are arranged in descending order from large to small, that is, δ1>δ2>...>δ s .

[0163] At this time, the remaining noise signal in the signal can be represented by the first few larger singular values, and other signals are represented by subsequent singular values.

[0164] S43: Set a reasonable threshold to find the first r singular values δ1,δ2,...,δ r , and reconstruct them, the reconstruction process is:

[0165] X ′ =U M×r S r×r V num×r T

[0166] Wherein:

[0167] X ′ is a dimension reduction matrix;

[0168] U M×r is a matrix composed of the first r columns of U M×M ;

[0169] Sr×r For from S M×num Take the diagonal matrix formed by the first r columns;

[0170] V num×r To from V num×num Take the matrix formed by the first r columns.

[0171] Let X ′ for:

[0172]

[0173] For the dimension reduction matrix X ′ The average of the anti-diagonal elements is used to obtain the one-dimensional reconstructed signal, i.e.:

[0174]

[0175] Therefore, the one-dimensional sequence X corresponding to the residual noise signal can be obtained. ′ ={x(1),x(2),...,x(Num)}.

[0176] S44: Subtract the remaining noise signal from the initial denoised signal to obtain the final denoised partial discharge signal.

[0177] The above optional implementation methods can achieve at least the following beneficial effects:

[0178] (1) Compared with related technologies, the present invention decomposes the discharge signal sequence according to different frequency ranges based on the signal frequencies corresponding to multiple time points in the discharge signal sequence, and obtains multiple decomposed sequences and residual signal sequences corresponding to the discharge signal sequence. This can accurately reflect the fluctuation characteristics of the discharge signal sequence in different frequency ranges. On this basis, the time series matrix corresponding to the multiple decomposed sequences is determined to analyze the discharge signal sequence in different time series dimensions and different time series offsets. Thus, by combining the corresponding time series matrix and the residual signal sequence, the discharge signal sequence can be accurately denoised, thereby improving the accuracy of cable joint discharge detection. This solves the technical problem of inaccurate cable joint discharge detection caused by poor denoising effect of cable joint discharge signal.

[0179] (2) Compared with related technologies, the present invention performs multi-dimensional analysis on the time matrix of the decomposed sequence, extracts time feature parameters, offset feature parameters and signal strength parameters, and uses these multi-dimensional feature parameters to accurately identify and retain useful signals, remove noise, and improve the noise reduction accuracy of cable joint discharge signals.

[0180] (3) Compared with the related art, the present application realizes the decomposition of the complex discharge signal sequence into multiple sub-sequences with specific frequency ranges by gradually determining the multiple first period segments and their extreme values corresponding to the discharge signal sequence in multiple decomposition processes, and then determining the first decomposition sequence, subtracting the decomposition sequence from the original signal to obtain the next signal sequence, and repeating the above process, so as to more accurately identify and process different frequency characteristics in the signal, thereby providing a clearer basis for subsequent signal denoising.

[0181] (4) Compared with the related art, the present application overcomes the problems of mode aliasing and end effect of the traditional EMD method by using the CEEMDAN algorithm for preliminary denoising, improves the stability and accuracy of decomposition, and makes fine distinction of different frequency components by introducing modal correlation analysis combined with SSA (singular spectrum analysis), so that noise and useful signal can be more effectively separated, and signal details are retained while irrelevant interference is suppressed. Finally, the Hankel matrix is further processed by singular value decomposition (SVD), to eliminate residual noise and effectively improve the signal-to-noise ratio and clarity of the final signal.

[0182] (5) Compared with the related art, the present application combines the CEEMDAN, SSA and SVD denoising strategies, uses the CEEMDAN algorithm for iterative denoising, uses the SSA algorithm with permutation entropy as the fitness function to optimize the selected IMF components in reconstruction, and then uses the SVD algorithm for further denoising, so as to obtain the denoised partial discharge signal, significantly improve the accuracy and reliability of partial discharge detection, and suppress white noise and periodic narrowband interference, with stronger universality and adaptive ability.

[0183] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0184] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software on a general hardware platform as necessary, and of course can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a part that contributes to the prior art, and the computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk), and includes a plurality of instructions for causing an end device (which can be a mobile phone, a computer, a server, or a network device) to execute the method of each embodiment of the present application.

[0185] Embodiment 2

[0186] According to the embodiments of the present application, a device for implementing the above cable joint discharge signal denoising method is also provided, Figure 7 is a structural block diagram of the cable joint discharge signal denoising device of the embodiments of the present application, as Figure 7 shown, the device includes an acquisition module 702, a first determination module 704, a second determination module 706, a third determination module 708, and a fourth determination module 710, which are described in detail below.

[0187] The acquisition module 702 is configured to acquire a discharge signal sequence corresponding to a cable joint, wherein the discharge signal sequence includes signal frequencies corresponding to a plurality of time points respectively; the first determination module 704 is connected to the acquisition module 702 and is configured to decompose the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points respectively to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; the second determination module 706 is connected to the first determination module 704 and is configured to determine a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposition sequences; the third determination module 708 is connected to the second determination module 706 and is configured to determine a time sequence matrix corresponding to the plurality of decomposition sequences respectively, wherein a row of the corresponding time sequence matrix represents a signal frequency of the corresponding decomposition sequence in a different time sequence dimension, and a column of the corresponding time sequence matrix represents a signal frequency of the corresponding decomposition sequence in a corresponding different time sequence offset; and the fourth determination module 710 is connected to the third determination module 708 and is configured to determine a target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrix corresponding to the plurality of decomposition sequences respectively and the residual signal sequence.

[0188] It should be noted that the above acquisition module 702, the first determination module 704, the second determination module 706, the third determination module 708 and the fourth determination module 710 correspond to steps S102 to S110 in the method for discharging noise of the cable joint signal, and the plurality of modules and the corresponding steps have the same instances and application scenarios as the above embodiment 1, but are not limited to the above embodiment 1.

[0189] Embodiment 3

[0190] According to another aspect of the embodiments of the present application, an electronic device is further provided, comprising: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the cable joint discharge signal denoising method of any one of the above.

[0191] Embodiment 4

[0192] According to another aspect of the embodiments of the present application, a computer readable storage medium is further provided, when the instructions in the computer readable storage medium are executed by the processor of the electronic device, the electronic device can execute the cable joint discharge signal denoising method of any one of the above.

[0193] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0194] In the above embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0195] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0196] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0197] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0198] When the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application, essentially or the part that contributes to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0199] The above is only the preferred embodiment of the present application, and it should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method of denoising a cable joint discharge signal, characterized by, The method comprises: obtaining a discharge signal sequence corresponding to a cable joint, wherein the discharge signal sequence comprises signal frequencies corresponding to a plurality of time points respectively; decomposing the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points respectively to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; determining a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposition sequences; determining time sequence matrices corresponding to the plurality of decomposition sequences respectively, wherein a row of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence dimensions, and a column of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence offsets; determining a target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrices corresponding to the plurality of decomposition sequences respectively and the residual signal sequence.

2. The method of claim 1, wherein, The method of determining the target denoising sequence corresponding to the discharge signal sequence according to the time sequence matrices corresponding to the plurality of decomposition sequences respectively and the residual signal sequence comprises: determining time characteristic parameters corresponding to the plurality of decomposition sequences according to the rows of the time sequence matrices corresponding to the plurality of decomposition sequences respectively, and determining offset characteristic parameters corresponding to the plurality of decomposition sequences according to the columns of the time sequence matrices corresponding to the plurality of decomposition sequences respectively; determining signal intensity parameters corresponding to the plurality of decomposition sequences according to the time sequence matrices corresponding to the plurality of decomposition sequences respectively; determining denoising decomposition sequences corresponding to the plurality of decomposition sequences according to the time characteristic parameters, the spatial characteristic parameters and the signal intensity parameters corresponding to the plurality of decomposition sequences respectively; determining the target denoising sequence corresponding to the discharge signal sequence according to the plurality of denoising decomposition sequences and the residual signal sequence.

3. The method of claim 1, wherein, The method of decomposing the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points respectively to obtain the plurality of decomposition sequences corresponding to the discharge signal sequence comprises: in the case of multiple decompositions, determining a plurality of first period segments corresponding to the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points respectively in the execution order of the multiple decompositions, and determining extreme values corresponding to the plurality of first period segments respectively, and determining a first decomposition sequence corresponding to the discharge signal sequence according to the extreme values corresponding to the plurality of first period segments respectively; determining a next signal sequence according to the discharge signal sequence and the first decomposition sequence; determining a plurality of next period segments corresponding to the next signal sequence, and determining extreme values corresponding to the plurality of next period segments respectively, and determining a next decomposition sequence corresponding to the next signal sequence according to the extreme values corresponding to the plurality of next period segments respectively, until the multiple decompositions are executed completely to obtain the plurality of decomposition sequences corresponding to the discharge signal sequence.

4. The method of claim 3, wherein, The method of determining the first decomposition sequence corresponding to the discharge signal sequence according to the extreme values corresponding to the plurality of first period segments respectively comprises: In a case where the extreme values corresponding to the plurality of first period sections respectively include maximum values and minimum values, a first fluctuation sequence corresponding to the discharge signal sequence is determined according to the maximum values corresponding to the plurality of first period sections, wherein the maximum value is the maximum signal frequency in the corresponding first period section, and a second fluctuation sequence corresponding to the discharge signal sequence is determined according to the minimum values corresponding to the plurality of first period sections; The first fluctuation sequence and the second fluctuation sequence are used to determine a first decomposition sequence corresponding to the discharge signal sequence.

5. The method of claim 2, wherein, The target denoising sequence corresponding to the discharge signal sequence is determined according to the plurality of denoising decomposition sequences and the residual signal sequence, including: An initial denoising sequence corresponding to the discharge signal sequence is determined according to the plurality of denoising decomposition sequences; Sequence characteristics corresponding to the initial denoising sequence are determined; The target denoising sequence corresponding to the discharge signal sequence is determined according to the sequence characteristics corresponding to the initial denoising sequence.

6. The method of claim 1, wherein, The discharge signal sequence is decomposed according to the signal frequencies corresponding to the plurality of time points to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, including: The discharge signal sequence is decomposed according to the signal frequencies corresponding to the plurality of time points to obtain a plurality of candidate sequences corresponding to the discharge signal sequence; Similarity indexes corresponding to the plurality of candidate sequences are determined according to the plurality of candidate sequences and the discharge signal sequence, wherein the corresponding similarity index represents the similarity between the corresponding candidate sequence and the discharge signal sequence; The plurality of decomposition sequences are selected from the plurality of candidate sequences according to the similarity indexes corresponding to the plurality of candidate sequences, wherein the similarity indexes corresponding to the plurality of decomposition sequences are greater than or equal to a similarity threshold.

7. The method according to any one of claims 1 to 6, characterized in that, The residual signal sequence corresponding to the discharge signal sequence is determined according to the discharge signal sequence and the plurality of decomposition sequences, including: A mean sequence corresponding to the plurality of decomposition sequences is determined; The residual signal sequence corresponding to the discharge signal sequence is determined according to the discharge signal sequence and the mean sequence.

8. A cable joint discharge signal denoising device, characterized by, The method includes: An acquisition module is configured to acquire a discharge signal sequence corresponding to a cable joint, wherein the discharge signal sequence includes signal frequencies corresponding to a plurality of time points; A first determination module is configured to decompose the discharge signal sequence according to the signal frequencies corresponding to the plurality of time points to obtain a plurality of decomposition sequences corresponding to the discharge signal sequence, wherein the plurality of decomposition sequences are used to represent fluctuation characteristics of the discharge signal sequence in different frequency ranges; A second determination module is configured to determine a residual signal sequence corresponding to the discharge signal sequence according to the discharge signal sequence and the plurality of decomposition sequences. a third determining module, configured to determine a time sequence matrix corresponding to each of the plurality of decomposition sequences, wherein a row of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence dimensions, and a column of the corresponding time sequence matrix represents signal frequencies of the corresponding decomposition sequence in different time sequence offsets; a fourth determining module, configured to determine a target denoised sequence corresponding to the discharge signal sequence according to the time sequence matrix corresponding to each of the plurality of decomposition sequences and the residual signal sequence.

9. An electronic device, comprising: comprise: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the cable joint discharge signal denoising method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer readable storage medium are executed by the processor of the electronic device, the electronic device is enabled to perform the cable joint discharge signal denoising method according to any one of claims 1 to 7.

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