CN115358267B - Submarine cable data interference filtering method, device, storage medium and system - Google Patents
Submarine cable data interference filtering method, device, storage medium and system Download PDFInfo
- Publication number
- CN115358267B CN115358267B CN202210982207.8A CN202210982207A CN115358267B CN 115358267 B CN115358267 B CN 115358267B CN 202210982207 A CN202210982207 A CN 202210982207A CN 115358267 B CN115358267 B CN 115358267B
- Authority
- CN
- China
- Prior art keywords
- matrix
- information
- processing
- decomposition
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
- G01R19/0092—Arrangements for measuring currents or voltages or for indicating presence or sign thereof measuring current only
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Filters That Use Time-Delay Elements (AREA)
Abstract
The invention discloses a submarine cable data interference filtering method, a submarine cable data interference filtering device, a submarine cable data interference filtering storage medium and a submarine cable data interference filtering system. The method, the device, the storage medium and the system for filtering submarine cable data interference can well restore original current waveforms because the preset matrix beam algorithm is adopted to reconstruct the current signals measured on site to obtain an expression of the current data, the expression can correspond to an extended Debye model, multiple polarization types exist in polymer insulation, polarization and relaxation phenomena of the expression widely follow the extended Debye model, different parts in the expression correspond to different branches in the Debye model, and the submarine cable data interference filtering method, the device, the storage medium and the system improve the effectiveness of submarine cable data interference filtering.
Description
Technical Field
The invention relates to the technical field of submarine cable data interference filtering, in particular to a submarine cable data interference filtering method, a submarine cable data interference filtering device, a computer-readable storage medium and a computer-readable storage medium system.
Background
With the development of economy, the demand for energy is also increased, and cross-sea power transmission is becoming particularly important. Submarine cables are used as important equipment for cross-sea power transmission, and the operation safety and stability of the submarine cables are particularly important. The submarine cable can cause cable insulation degradation under the actions of external stress, moisture, temperature and electric field in the operation process, and the operation reliability of the power system is affected. Therefore, it is necessary to monitor the insulation state of the cable and periodically perform insulation diagnosis on the cable. The submarine power cable has the advantages of thicker insulation thickness, higher rated voltage level, longer distance and more complex structure, and is different from a land cable, so that the traditional land cable insulation diagnosis technology (such as insulation resistance, power frequency dielectric loss factor measurement, ultra-low frequency dielectric loss measurement and the like) has poor effect when applied to the submarine cable.
In the prior art, insulation resistance measurements commonly used for insulation diagnostics of submarine cables are currently also applied by the scholars to submarine cable testing by polarization-depolarization amperometry (PDC).
However, the prior art still has the following defects: because the field environment is complex and various, the noise is large, the measured data interference is large, and the subsequent parameter calculation is difficult; meanwhile, because of the direct-current voltage applied by the PDC during testing, the conventional filtering algorithm is difficult to completely filter out the field low-frequency interference, and if the filtering is forced, the current signals required by users are filtered out together.
Accordingly, there is a need for a submarine cable data interference filtering method, apparatus, computer-readable storage medium, and system that overcomes the above-described deficiencies in the prior art.
Disclosure of Invention
The embodiment of the invention provides a submarine cable data interference filtering method, a submarine cable data interference filtering device, a computer-readable storage medium and a submarine cable data interference filtering system, so that the effectiveness of submarine cable data interference filtering is improved.
The embodiment of the invention provides a submarine cable data interference filtering method, which comprises the following steps: acquiring a current data set of the submarine cable for filtering interference data; according to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is carried out on the matrix beam to obtain a feature information set; the feature information set comprises first feature information and second feature information; and carrying out data reconstruction on the current data set according to the first characteristic information, the second characteristic information and a preset data reconstruction formula to obtain a reconstructed current data set.
As an improvement of the above solution, according to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is performed on the matrix beam to obtain a feature information set, which specifically includes: constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix; processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix; according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated; and calculating the first characteristic information and the second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group.
As an improvement of the above scheme, the preset data reconstruction formula specifically includes: Where a i is first feature information and τ i is second feature information.
As an improvement of the above solution, according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix, the first decomposition matrix and the Hankel matrix are processed to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix, which specifically includes: arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map; according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained; calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix; removing the first row of the second decomposition matrix to obtain a second processing matrix; the last row of the second decomposition matrix is removed to obtain a third processing matrix.
As an improvement of the above solution, according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solution method, the method specifically includes: constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix; constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix; and solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors.
As an improvement of the above solution, after solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain an information eigenvalue and an information eigenvector, the method further includes: judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition; if yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, and re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number.
As an improvement of the scheme, the method for acquiring the current data set of the submarine cable for filtering the interference data specifically comprises the following steps: measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage; processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set; the polarization current data set and the depolarization current data set are used as current data sets.
The invention further provides a submarine cable data interference filtering device correspondingly, which comprises a current acquisition unit, a matrix beam solving unit and a data reconstruction unit, wherein the current acquisition unit is used for acquiring a current data set of a submarine cable for filtering interference data; the matrix beam solving unit is used for constructing an information matrix beam according to the current data set and a preset matrix beam algorithm, and carrying out feature solving on the matrix beam to obtain a feature information set; the feature information set comprises first feature information and second feature information; the data reconstruction unit is used for carrying out data reconstruction on the current data set according to the first characteristic information, the second characteristic information and a preset data reconstruction formula so as to obtain a reconstructed current data set.
As an improvement of the above solution, the matrix beam solving unit is further configured to: constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix; processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix; according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated; and calculating the first characteristic information and the second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group.
As an improvement of the above solution, the matrix beam solving unit is further configured to: arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map; according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained; calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix; removing the first row of the second decomposition matrix to obtain a second processing matrix; the last row of the second decomposition matrix is removed to obtain a third processing matrix.
As an improvement of the above solution, the matrix beam solving unit is further configured to: constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix; constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix; and solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors.
As an improvement of the above solution, the matrix beam solving unit is further configured to: judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition; if yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, and re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number.
As an improvement of the above-described aspect, the current acquisition unit is further configured to: measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage; processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set; the polarization current data set and the depolarization current data set are used as current data sets.
Another embodiment of the present invention provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, and when the computer program runs, controls a device where the computer readable storage medium is located to execute a submarine cable data interference filtering method as described above.
Another embodiment of the present invention provides a submarine cable data interference filtering system comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the submarine cable data interference filtering method as described above when executing the computer program.
Compared with the prior art, the technical scheme has the following beneficial effects:
The invention provides a submarine cable data interference filtering method, a device, a computer readable storage medium and a system, wherein a preset matrix beam algorithm is adopted to reconstruct current signals measured on site to obtain an expression of current data, the expression can correspond to an extended Debye model, multiple polarization types exist in polymer insulation, polarization and relaxation phenomena of the expression widely follow the extended Debye model, different parts in the expression correspond to different branches in the Debye model, and therefore an original current waveform can be restored well.
Drawings
Fig. 1 is a schematic flow chart of a submarine cable data interference filtering method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a submarine cable data interference filtering device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Detailed description of the preferred embodiments
The embodiment of the invention firstly describes a submarine cable data interference filtering method. Fig. 1 is a schematic flow chart of a submarine cable data interference filtering method according to an embodiment of the present invention.
As shown in fig. 1, the submarine cable data interference filtering method includes:
And S1, acquiring a current data set of the submarine cable for filtering interference data.
Because the rated voltage of the submarine cable is high, the distance is long, the capacitance is large, and the low-frequency dielectric loss detection of the submarine cable is very difficult, the insulation resistance test is often adopted on site. The DC conductivity and low frequency dielectric loss characteristics of the cable can be obtained by using a polarization-depolarization amperometric method under DC voltage.
However, when submarine cables are tested, the submarine cables are generally tested at a terminal station, and because other equipment is running on site, site interference is serious; the interference frequency caused by corona is high, so that the interference can be filtered well, and some low-frequency interference on site is close to the frequency of a required signal and is difficult to filter.
For the above-mentioned drawbacks, the matrix-bundle algorithm constructs two special matrices using the sampled data. In this case, the information of the index signal is included in the generalized eigenvalue of the matrix, and the eigenvalue of the matrix may be obtained to obtain the information of the signal. The interference can be well filtered by reconstructing the data by utilizing the information of the obtained signals, and the accuracy is improved. And (3) carrying out data reconstruction on the current signal measured on site by adopting a matrix beam algorithm to obtain an expression of the current data. The expression can correspond to the extended Debye model, various polarization types exist in the polymer insulation, the polarization and relaxation phenomena of the expression widely follow the extended Debye model, and different parts in the expression correspond to different branches in the Debye model, so that the original current waveform can be well restored, the accuracy is improved, and the effect of filtering interference is achieved. Meanwhile, the method can avoid the problems of improper selection of filtering parameters and filtering methods when filtering methods such as S-G filtering, average filtering and the like are adopted. The method can automatically determine the current signal order, and can avoid errors caused by processing data in a fitting mode. Therefore, the PDC data measured on site is reconstructed according to a matrix beam algorithm to realize the filtering of the on-site low-frequency interference, meanwhile, the required signal loss is avoided, and the calculation accuracy of the direct current conductivity and the low-frequency dielectric loss characteristic can be improved.
In one embodiment, obtaining a current data set of the submarine cable for filtering interference data specifically includes: measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage; processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set; the polarization current data set and the depolarization current data set are used as current data sets. The processing flow of the polarization current data set and the depolarization current data set is identical in the whole process as described in the embodiment of the invention.
In one embodiment, the preset signal processing formula is:
Where x n is the signal sample and w n is the noise. Δ=1/N, n=0, 1, … N-1, r i is the amplitude of the first harmonic, the corresponding attenuation factors and angular frequencies are α i and ω i, respectively.
And S2, constructing an information matrix beam according to the current data set and a preset matrix beam algorithm, and carrying out feature solving on the matrix beam to obtain a feature information set.
The feature information set includes first feature information and second feature information.
In one embodiment, according to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is performed on the matrix beam to obtain a feature information set, which specifically includes: constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix; processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix; according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated; and calculating the first characteristic information and the second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group.
Illustratively, when constructed using polarized current data sets of the current data sets, the Hankel matrix is:
subsequently, the Hankel matrix is subjected to SVD decomposition according to a singular value decomposition method, and a corresponding singular value matrix V (described herein as a "first decomposition matrix") is extracted:
X＝SVDT；
Wherein S is an orthogonal matrix of (N-L) × (N-L) (described herein as a "third decomposition matrix"); d is an orthogonal matrix (described herein as a "second decomposition matrix") (l+1) × (l+1); v is a diagonal array of (N-L) X (L+1), the diagonal elements of which are the singular values of X.
After the first decomposition matrix is extracted, continuing processing is needed, specifically, arranging elements in V from large to small, drawing a singular value map, and recording the number of larger singular values as r (described as "the number of larger singular values" in the text); determining the value of r according to the singular value map; all other values except the front r columns of the singular value matrix V are assigned to 0, so that a new matrix V' is obtained; the last and first rows of matrix D are removed to obtain matrices D1 (described herein as "second processing matrices") and D2 (described herein as "third processing matrices"), respectively.
That is, in one embodiment, according to a preset decomposition matrix processing method, a first decomposition matrix, and the Hankel matrix, the first decomposition matrix and the Hankel matrix are processed to obtain a first processing matrix, a second processing matrix, a third processing matrix, and a third decomposition matrix, which specifically include: arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map; according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained; calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix; removing the first row of the second decomposition matrix to obtain a second processing matrix; the last row of the second decomposition matrix is removed to obtain a third processing matrix.
Subsequently, a first information matrix Z 1 and a second information matrix Z 2 are constructed using the first processing matrix, the second processing matrix, the third processing matrix, and a third decomposition matrix:
In constructing the first information matrix Z 1 and the second information matrix Z 2, the matrix bundle Z 2-λZ1 is formed by using the first information matrix Z 1 and the second information matrix Z 2. The generalized eigenvalue matrix of the matrix bundle can be expressed as follows:
Then, the information eigenvalue and the information eigenvector of the matrix G are obtained, and the first eigenvalue and the second eigenvalue are calculated according to the eigenvalue and the eigenvector. Solving the following equation:
Where λ 1,λ2,…,λi,λr is the information feature value and R i is the information feature vector.
In one embodiment, according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information eigenvalue and an information eigenvector are calculated, which specifically includes: constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix; constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix; and solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors.
In one embodiment, after solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain an information eigenvalue and an information eigenvector, the method further includes: judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition; if yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number, and re-constructing a solving method according to the new first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle to obtain a new information matrix bundle and calculate a new information characteristic value and a new information characteristic vector; and calculating new first characteristic information and new second characteristic information according to the new characteristic value, the new characteristic vector and a preset characteristic information calculation formula group.
And after the information characteristic value and the information characteristic vector are calculated and the fact that recalculation is not needed is confirmed, calculating the first characteristic information and the second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group.
In one embodiment, the preset feature information calculation formula set includes:
Ai＝|Ri|；
Wherein, ts is a sampling interval; if the solved value of a i is very small or if two τ i have similar values, the number of singular values taken is reduced, i.e. r=r-1, and the matrices D 1 and D 2 are recalculated.
And S3, carrying out data reconstruction on the current data set according to the first characteristic information, the second characteristic information and a preset data reconstruction formula so as to obtain a reconstructed current data set.
In one embodiment, the preset data reconstruction formula is specifically:
where a i is first feature information and τ i is second feature information.
The direct current conductivity and the low-frequency dielectric loss factor are calculated by adopting the reconstructed current data set after data reconstruction, so that low-frequency interference caused by measurement can be better filtered.
The embodiment of the invention describes a submarine cable data interference filtering method, which comprises the steps of carrying out data reconstruction on a current signal measured on site by adopting a preset matrix beam algorithm to obtain an expression of the current data, wherein the expression can correspond to an extended Debye model, a plurality of polarization types exist in polymer insulation, polarization and relaxation phenomena of the expression widely follow the extended Debye model, and different parts in the expression correspond to different branches in the Debye model, so that an original current waveform can be well restored, and the submarine cable data interference filtering method improves the effectiveness of submarine cable data interference filtering.
Second embodiment
Besides the method, the embodiment of the invention also discloses a submarine cable data interference filtering device. Fig. 2 is a schematic structural diagram of a submarine cable data interference filtering device according to an embodiment of the present invention.
As shown in fig. 2, the interference filtering apparatus includes a current acquisition unit 11, a matrix beam solving unit 12, and a data reconstruction unit 13.
The current acquisition unit 11 is used for acquiring a current data set of the submarine cable for filtering interference data.
In one embodiment, the current acquisition unit 11 is further configured to: measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage; processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set; the polarization current data set and the depolarization current data set are used as current data sets.
The matrix beam solving unit 12 is configured to construct an information matrix beam according to the current data set and a preset matrix beam algorithm, and perform feature solving on the matrix beam to obtain a feature information set; the feature information set includes first feature information and second feature information.
In one embodiment, the beam solving unit 12 is further configured to: constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix; processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix; according to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated; and calculating the first characteristic information and the second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group.
In one embodiment, the matrix beam solving unit 12 is further configured to: arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map; according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained; calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix; removing the first row of the second decomposition matrix to obtain a second processing matrix; the last row of the second decomposition matrix is removed to obtain a third processing matrix.
In one embodiment, the matrix beam solving unit 12 is further configured to: constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix; constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix; and solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors.
In one embodiment, the matrix beam solving unit 12 is further configured to: judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition; if yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, and re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number.
The data reconstruction unit 13 is configured to perform data reconstruction on the current data set according to the first feature information, the second feature information, and a preset data reconstruction formula to obtain a reconstructed current data set.
Wherein the integrated units of the submarine cable data interference filtering device may be stored in a computer-readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of each of the method embodiments described above when executed by a processor. Another embodiment of the present invention provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, and when the computer program runs, controls a device where the computer readable storage medium is located to execute a submarine cable data interference filtering method as described above.
The computer program comprises computer program code which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the device provided by the invention, the connection relation between the units indicates that the units have communication connection, and the connection relation can be specifically realized as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The embodiment of the invention describes a submarine cable data interference filtering device and a computer readable storage medium, wherein a preset matrix beam algorithm is adopted to reconstruct current signals measured on site to obtain an expression of current data, the expression can correspond to an extended Debye model, multiple polarization types exist in polymer insulation, polarization and relaxation phenomena of the expression widely follow the extended Debye model, different parts in the expression correspond to different branches in the Debye model, so that an original current waveform can be well restored, and the submarine cable data interference filtering device and the computer readable storage medium improve the submarine cable data interference filtering effectiveness.
Detailed description of the preferred embodiments
In addition to the method and the device, the embodiment of the invention also describes a submarine cable data interference filtering system.
The interference filtering system comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the submarine cable data interference filtering method as described above when executing the computer program.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processor, digital signal processor (DIGITAL SIGNAL processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf programmable gate array (field-programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is the control center of the device, connecting the various parts of the overall device using various interfaces and lines.
The memory may be used to store the computer program and/or modules, and the processor may implement various functions of the apparatus by running or executing the computer program and/or modules stored in the memory, and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The embodiment of the invention describes a submarine cable data interference filtering system, which is characterized in that a preset matrix beam algorithm is adopted to reconstruct data of a current signal measured on site to obtain an expression of the current data, the expression can correspond to an extended Debye model, multiple polarization types exist in polymer insulation, polarization and relaxation phenomena of the expression widely follow the extended Debye model, different parts in the expression correspond to different branches in the Debye model, so that an original current waveform can be well restored, and the submarine cable data interference filtering system improves the effectiveness of submarine cable data interference filtering.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (4)
1. The submarine cable data interference filtering method is characterized by comprising the following steps of:
acquiring a current data set of the submarine cable for filtering interference data;
according to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is carried out on the matrix beam to obtain a feature information set; the feature information set comprises first feature information and second feature information;
According to the first characteristic information, the second characteristic information and a preset data reconstruction formula, carrying out data reconstruction on the current data set to obtain a reconstructed current data set;
The preset data reconstruction formula specifically comprises the following steps:
；
Wherein A i is first characteristic information, and τ i is second characteristic information;
According to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is carried out on the matrix beam to obtain a feature information set, and the method specifically comprises the following steps:
Constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix;
Processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix;
According to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated;
Calculating first characteristic information and second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group;
According to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix, the first decomposition matrix and the Hankel matrix are processed to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix, which specifically comprise:
Arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map;
according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained;
calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix;
removing the first row of the second decomposition matrix to obtain a second processing matrix;
Removing the last row of the second decomposition matrix to obtain a third processing matrix;
According to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated, specifically including:
constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix;
constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix;
solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors;
after solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors, the method further comprises:
judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition;
If yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, and re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number;
The method for acquiring the current data set of the submarine cable for filtering the interference data specifically comprises the following steps:
measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage;
Processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set;
The preset signal processing formula is as follows:
；
Wherein x n is a signal sample, and w n is noise; =1/N,n=0,1,…N-1,Ri For the amplitude of the first harmonic, the corresponding attenuation factor and angular frequency are/> and/> , respectively;
taking the polarized current data set and the depolarization current data set as current data sets;
And adopting the reconstructed current data set after data reconstruction to calculate the direct current conductivity and the low-frequency dielectric loss factor.
2. The submarine cable data interference filtering device is characterized by comprising a current acquisition unit, a matrix beam solving unit and a data reconstruction unit,
The current acquisition unit is used for acquiring a current data set of the submarine cable for filtering interference data;
The matrix beam solving unit is used for constructing an information matrix beam according to the current data set and a preset matrix beam algorithm, and carrying out feature solving on the matrix beam to obtain a feature information set; the feature information set comprises first feature information and second feature information;
The data reconstruction unit is used for carrying out data reconstruction on the current data set according to the first characteristic information, the second characteristic information and a preset data reconstruction formula so as to obtain a reconstructed current data set;
The preset data reconstruction formula specifically comprises the following steps:
；
Wherein A i is first characteristic information, and τ i is second characteristic information;
According to the current data set and a preset matrix beam algorithm, an information matrix beam is constructed, and feature solution is carried out on the matrix beam to obtain a feature information set, and the method specifically comprises the following steps:
Constructing a Hankel matrix according to the current data set, and performing singular value decomposition on the Hankel matrix to obtain a first decomposition matrix;
Processing the first decomposition matrix and the Hankel matrix according to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix;
According to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated;
Calculating first characteristic information and second characteristic information according to the characteristic value, the characteristic vector and a preset characteristic information calculation formula group;
According to a preset decomposition matrix processing method, a first decomposition matrix and the Hankel matrix, the first decomposition matrix and the Hankel matrix are processed to obtain a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix, which specifically comprise:
Arranging elements in the first decomposition matrix from small to large to obtain a first arrangement matrix, drawing a singular value map according to the first arrangement matrix, and determining a larger singular value number according to a preset size measurement standard value and the singular value map;
according to the large singular value number, the corresponding column of the first arrangement matrix is assigned to be 0, and a first processing matrix is obtained;
calculating a second decomposition matrix and a third decomposition matrix of the Hankel matrix according to a preset singular value decomposition method, the first processing matrix and the Hankel matrix;
removing the first row of the second decomposition matrix to obtain a second processing matrix;
Removing the last row of the second decomposition matrix to obtain a third processing matrix;
According to the first processing matrix, the second processing matrix, the third decomposition matrix and a preset matrix bundle construction solving method, an information matrix bundle is obtained, and an information characteristic value and an information characteristic vector are calculated, specifically including:
constructing a first information matrix and a second information matrix according to the first processing matrix, the second processing matrix, the third processing matrix and the third decomposition matrix;
constructing an information matrix bundle according to the first information matrix and the second information matrix, and acquiring a corresponding generalized eigenvalue matrix;
solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors;
after solving the generalized eigenvalue matrix according to a preset eigenvalue solving method to obtain information eigenvalues and information eigenvectors, the method further comprises:
judging whether the information characteristic value and the information characteristic vector need to be recalculated according to a preset recalculation condition;
If yes, subtracting 1 from the larger singular value number to obtain a first larger singular value number, and re-obtaining a first processing matrix, a second processing matrix, a third processing matrix and a third decomposition matrix according to the first larger singular value number;
The method for acquiring the current data set of the submarine cable for filtering the interference data specifically comprises the following steps:
measuring a polarization current signal and a depolarization current signal of a polarization process of the submarine cable of which interference data is to be filtered under a preset polarization voltage;
Processing the polarized current signal and the depolarization current signal respectively through a preset signal processing formula to correspondingly obtain a polarized current data set and a depolarization current data set;
The preset signal processing formula is as follows:
；
wherein x n is a signal sample, and w n is noise; =1/N,n=0,1,…N-1,Ri For the amplitude of the first harmonic, the corresponding attenuation factor and angular frequency are/> and/> , respectively;
taking the polarized current data set and the depolarization current data set as current data sets;
And adopting the reconstructed current data set after data reconstruction to calculate the direct current conductivity and the low-frequency dielectric loss factor.
3. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program when run controls a device in which the computer readable storage medium is located to perform the submarine cable data interference filtering method according to claim 1.
4. A submarine cable data interference filtering system comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the submarine cable data interference filtering method of claim 1 when the computer program is executed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210982207.8A CN115358267B (en) | 2022-08-16 | 2022-08-16 | Submarine cable data interference filtering method, device, storage medium and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210982207.8A CN115358267B (en) | 2022-08-16 | 2022-08-16 | Submarine cable data interference filtering method, device, storage medium and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115358267A CN115358267A (en) | 2022-11-18 |
| CN115358267B true CN115358267B (en) | 2024-04-16 |
Family
ID=84001650
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210982207.8A Active CN115358267B (en) | 2022-08-16 | 2022-08-16 | Submarine cable data interference filtering method, device, storage medium and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115358267B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106443129A (en) * | 2016-09-26 | 2017-02-22 | 哈尔滨理工大学 | A Numerical Calculation Method of Recovery Voltage of Electrical Equipment and Insulating Materials |
| CN109507554A (en) * | 2018-12-10 | 2019-03-22 | 国网四川省电力公司电力科学研究院 | A kind of insulation of electrical installation state evaluating method |
| CN110133425A (en) * | 2019-06-10 | 2019-08-16 | 集美大学 | A submarine cable fault signal filtering method, terminal equipment and storage medium |
| CN114004254A (en) * | 2021-10-27 | 2022-02-01 | 云南电网有限责任公司昆明供电局 | Power cable partial discharge signal white noise and pulse type interference filtering algorithm |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FI115737B (en) * | 2003-09-26 | 2005-06-30 | Elekta Neuromag Oy | A method for using a multichannel measurement signal in source modeling |
| US20170097434A1 (en) * | 2014-03-28 | 2017-04-06 | Cgg Services Sa | Methods and data processing apparatus for cooperative de-noising of multi-sensor marine seismic data |
| CN113419147B (en) * | 2021-06-29 | 2022-07-19 | 广西电网有限责任公司电力科学研究院 | Radar spectrum diagram based visualized cable insulation state diagnosis and evaluation method |
-
2022
- 2022-08-16 CN CN202210982207.8A patent/CN115358267B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106443129A (en) * | 2016-09-26 | 2017-02-22 | 哈尔滨理工大学 | A Numerical Calculation Method of Recovery Voltage of Electrical Equipment and Insulating Materials |
| CN109507554A (en) * | 2018-12-10 | 2019-03-22 | 国网四川省电力公司电力科学研究院 | A kind of insulation of electrical installation state evaluating method |
| CN110133425A (en) * | 2019-06-10 | 2019-08-16 | 集美大学 | A submarine cable fault signal filtering method, terminal equipment and storage medium |
| CN114004254A (en) * | 2021-10-27 | 2022-02-01 | 云南电网有限责任公司昆明供电局 | Power cable partial discharge signal white noise and pulse type interference filtering algorithm |
Non-Patent Citations (3)
| Title |
|---|
| "基于矩阵束算法的XLPE 电力电缆绝缘介质响应参数辨识";张晨萌 等;《高电压技术》;第45卷(第5期);第1647-1653页 * |
| "水树老化电缆的绝缘评估图谱特征";马骁 等;《高电压技术》;第48卷(第4期);第1489-1497页 * |
| "海底电缆鬼波压制及陷频补偿方法研究";李继光 等;《热带海洋学报》;第37卷(第2期);第100-104页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115358267A (en) | 2022-11-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6738135B2 (en) | How to perform electrical cable fault detection on a computer | |
| DE102012219563B4 (en) | Method and circuit for insulation resistance monitoring for vehicles with high-voltage power network | |
| CN109507554B (en) | A method for evaluating the insulation state of electrical equipment | |
| DE69633492T2 (en) | Method and apparatus for processing time domain crosstalk data | |
| CN107609251B (en) | FDS-based modeling method for series polarization model of oiled paper condenser bushing | |
| CN109596944B (en) | Cable detection method and device and electronic equipment | |
| CN114089108B (en) | Cable sheath defect identification method, device, equipment and readable storage medium | |
| EP2207044A1 (en) | A signal phase difference measurement method, apparatus and system | |
| CN116087717A (en) | Submarine cable insulation aging evaluation method, submarine cable insulation aging evaluation device, submarine cable insulation aging evaluation equipment and storage medium | |
| CN113397552A (en) | Novel electroencephalogram signal acquisition method and system | |
| CN114217175A (en) | Power cable electric tree defect detection method and device and terminal | |
| CN114252748A (en) | Cable intermediate joint insulation state assessment method, system and device | |
| CN115358267B (en) | Submarine cable data interference filtering method, device, storage medium and system | |
| DE112011104803T5 (en) | Measurement error correction method and electronic component characteristic measurement device | |
| Naderi et al. | Modeling and detection of transformer internal incipient fault during impulse test | |
| CN114062852B (en) | Cable intermediate connector fault diagnosis method, device, equipment and readable storage medium | |
| CN107957515A (en) | The impedance measurement monitored by waveform | |
| CN112485616A (en) | Cable insulation aging detection method and device, storage medium and processor | |
| CN102908141B (en) | Inverse tangent method for reconstructing isopotential line back projection electrical impedance tomography image | |
| Zhang et al. | Kalman filter approach for line parameter estimation for long transmission lines | |
| CN113655098A (en) | Current test-based method for measuring micro-water content of silicone oil for cable terminal | |
| CN106124989B (en) | Turbine generators machines under rotor winding faults diagnostic method and device based on diagnostic model | |
| CN116819421A (en) | Harmonic transmission characteristic test method, device and equipment of capacitive voltage transformer | |
| CN114167133B (en) | Harmonic voltage evaluation method and device for newly built station in power transmission network | |
| CN116047368A (en) | Third harmonic-based lightning arrester state evaluation method, system, equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |