Cable fault ranging signal joint noise reduction method and system based on improved TVFEMD-CEMDF

Abstract

The invention discloses a cable fault ranging signal joint noise reduction method and system based on improved TVFEMD-CEMDF, and the method comprises the steps: injecting a low-voltage pulse at a detection point, and obtaining an original low-voltage pulse reflection wave signal x (t); secondly, performing time-varying filtering empirical mode decomposition (TVFEMD) on the original low-voltage pulse reflected wave signal x (t) to obtain N intrinsic mode components; the N IMFs are separated, and a noisy mode component p (t) and a non-noisy mode component q (t) are obtained; carrying out noise reduction processing on the noisy mode component p (t) by using combined form difference filtering CEMDF to obtain a de-noised mode component s (t); and finally, combining and reconstructing the de-noised modal component s (t) and the non-noised modal component q (t) to obtain a de-noised signal f (t). According to the technical scheme, a solution is provided for the problems of low signal-to-noise ratio and strong interference of detection signals in cable fault pre-positioning.

Description

Technical Field

[0001] The invention belongs to the field of cable fault diagnosis, relates to a signal noise reduction technology in cable fault ranging, and in particular to a cable fault ranging signal joint noise reduction method and system based on improved TVFEMD-CEMDF. Background Art

[0002] With the rapid development of cities, underground cables have many advantages over overhead cables and are widely used. However, with the growth of social economy, the continuous increase in cable load and the barbaric construction on the ground, underground cables are prone to failure. In addition, due to the transformation of the power grid, the relocation and repair of cables, and the changes in the landform, the original drawings can no longer reflect the direction and depth of the cables, and the maintenance and management problems of underground cables are increasing. Because the underground cables span a large area, it is very difficult to find the fault point. If the cable fault cannot be repaired in time, it will not only waste a lot of manpower and material resources, but may also cause power outages. Therefore, it is of urgent practical significance to quickly and accurately locate the cable fault point.

[0003] Pre-location of cable fault distance requires extracting weak useful signals under strong background noise and interference signals. Pre-location of power cable faults is the most basic step in the detection of power cable faults, and is also the prerequisite for the subsequent precise positioning and identification of cable faults. The traveling wave ranging method is the most commonly used method for cable fault pre-location. It uses the time difference between the transmitted wave and the reflected wave arriving at the test point to calculate the distance between the fault point and the test point. However, when the traveling wave is transmitted on the cable, the energy will decay with the transmission distance, and the cable is located in an environment with high noise and strong interference, resulting in the reflected wave with weak intensity, low signal-to-noise ratio and difficult extraction.

[0004] Time domain denoising methods directly eliminate signal noise points from the signal time history curve, or select effective components from different scale information components and reconstruct them to achieve denoising. Common methods include wavelet transform, empirical mode decomposition, and adaptive noise complete set mode decomposition. Although wavelet transform can extract effective signals from measured signals, wavelet basis functions are difficult to select, and the denoising effects of different wavelet bases are inconsistent. Empirical mode decomposition and other methods are prone to problems such as modal aliasing and endpoint effects when decomposing signals.

[0005] In contrast, TVFEMD no longer requires the symmetry of the upper and lower envelopes during the decomposition and transformation process, and adds a time-varying filter to preserve the time-varying characteristics of the signal, effectively solving the problems of modal aliasing and decomposition error accumulation that are prone to occur in methods such as empirical mode decomposition. CEMDF can suppress noise and highlight signal features, thus better completing the noise reduction process. Summary of the invention

[0006] The purpose of the present invention is to provide a cable fault ranging signal joint noise reduction method and system based on improved TVFEMD-CEMDF, which provides a solution to the problems of low signal-to-noise ratio and strong interference of detection signals in cable fault pre-location.

[0007] In order to achieve the above object, the solution of the present invention is:

[0008] A cable fault location signal joint noise reduction method based on improved TVFEMD-CEMDF includes the following steps:

[0009] Step 1: inject a low-pressure pulse at the detection point to obtain the original low-pressure pulse reflected wave signal x(t);

[0010] Step 2, performing time-varying filtering empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components;

[0011] Step 3, separating the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t);

[0012] Step 4: Use the combined morphological difference filter CEMDF to perform denoising on the noisy modal component p(t) to obtain the denoised modal component s(t);

[0013] Step 5: Reconstruct the denoised modal component s(t) and the unnoised modal component q(t) to obtain the denoised signal f(t).

[0014] The specific process of step 2 above is:

[0015] Step 21, determine the instantaneous amplitude A(t) and instantaneous phase of the original low-pressure pulse reflected wave signal x(t)

[0016] Step 22, determining the analytical signal definition of the original low-pressure pulse reflection wave signal x(t) is:

[0017]

[0018] Where a1, a2 are constants;

[0019] Further inference:

[0020]

[0021] Step 23, find the local cutoff frequency

[0022] Step 24, filtering the uncalculated signal using a time-varying filter to obtain a local mean and calculating a stop boundary condition θ(t);

[0023] Step 25, determine if θ(t)≤ξ of the original low-voltage pulse reflected wave signal x(t), where ξ is the bandwidth threshold, and then consider x(t) to be an intrinsic mode component at this time; otherwise, update x(t) and repeat steps 21-25 until the decomposition is completed.

[0024] In the above step 23, the calculation formula is as follows:

[0025]

[0026] In the formula, is the instantaneous phase at different times; η1(t) and η2(t) are obtained by interpolation.

[0027] In the above step 25, the stop boundary condition θ(t) is calculated according to the following formula:

[0028]

[0029] In the formula, B Loughlin (t) is the Loughlin instantaneous bandwidth; is the weighted mean instantaneous frequency.

[0030] In step 3 above, the eigenmode components are separated using the correlation coefficient method and kurtosis analysis. The calculation formula is:

[0031]

[0032] In the formula, α and β are constants; r i is the correlation coefficient, k i is the kurtosis; x i is the i-th eigenmode component; is the average value of the signal; y is the original reflected wave signal, is the original reflected wave signal mean; X rms is the standard deviation of the signal.

[0033] In step 4 above, CEMDF is used to denoise the noisy modal component p(t). The denoising formula is:

[0034] f CEDMF =f GCD (n)-f GOE (n)

[0035] In the formula, f GCD is a generalized closed-expansion operator, f GOE is the generalized opening-erosion operator, and its calculation formulas are:

[0036]

[0037] In the formula, g1 and g2 are different structural elements; the solid origin represents the closing operation, and the hollow origin represents the opening operation.

[0038] In step 5 above, the denoised modal component s(t) and the unnoised modal component q(t) are combined and reconstructed using the following formula:

[0039]

[0040] Among them, f(t) is the denoised signal.

[0041] A cable fault location signal joint noise reduction system based on improved TVFEMD-CEMDF, comprising:

[0042] The original low-pressure pulse reflected wave signal acquisition module is configured to acquire the original low-pressure pulse reflected wave signal x(t) after the low-pressure pulse is injected into the detection point;

[0043] A time-varying filter empirical mode decomposition module is configured to perform a time-varying filter empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components;

[0044] A separation module is configured to separate the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t);

[0045] A denoising module is configured to perform denoising on the noisy modal component p(t) using a combined morphological difference filter CEMDF to obtain a denoised modal component s(t); and,

[0046] The reconstruction module is configured to reconstruct the denoised modal component s(t) and the non-noised modal component q(t) to obtain the denoised signal f(t).

[0047] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps of the cable fault location signal joint noise reduction method based on improved TVFEMD-CEMDF as described above are implemented.

[0048] A computer-readable storage medium stores a computer program; when the computer program is executed by a processor, the steps of the cable fault location signal joint noise reduction method based on improved TVFEMD-CEMDF as described above are implemented.

[0049] After adopting the above scheme, the beneficial effect of the present invention is that it provides a solution to the problem of low signal-to-noise ratio and strong interference of detection signals in cable fault pre-location. First, the detection signal is decomposed by TVFEMD to obtain the intrinsic modal components, which can better retain the time-varying characteristics of the detection signal and is not prone to modal aliasing and decomposition errors. Secondly, the intrinsic modal components are separated into noisy components and non-noisy components by correlation coefficient method and kurtosis analysis, and the noisy components are denoised by CEMDF, which can further reduce noise interference. Finally, the signal is reconstructed by adjusting the proportion of the denoised modal component s(t) in the final signal, thereby improving the reliability of the denoising result. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Schematic diagram of traveling wave ranging when phase A is fault-grounded in an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the low-voltage pulse reflection wave signal when the A phase is grounded due to a fault;

[0052] Figure 3 The present invention is a flow chart of a cable fault distance measurement signal joint noise reduction method based on improved TVFEMD-CEMDF. DETAILED DESCRIPTION

[0053] The technical solutions and beneficial effects of the present invention will be described in detail below with reference to the accompanying drawings.

[0054] like Figure 3 As shown, the present invention provides a cable fault location signal joint noise reduction method based on improved TVFEMD-CEMDF, comprising the following steps:

[0055] Step 1: inject a low-pressure pulse at the detection point to obtain the original low-pressure pulse reflected wave signal x(t);

[0056] Step 2, performing time-varying filtering empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components;

[0057] Step 3, separating the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t);

[0058] Step 4: Use the combined morphological difference filter CEMDF to perform denoising on the noisy modal component p(t) to obtain the denoised modal component s(t);

[0059] Step 5: Reconstruct the denoised modal component s(t) and the unnoised modal component q(t) to obtain the denoised signal f(t).

[0060] The embodiment of the present invention also provides a cable fault location signal joint noise reduction system based on improved TVFEMD-CEMDF, comprising:

[0061] The original low-pressure pulse reflected wave signal acquisition module is configured to acquire the original low-pressure pulse reflected wave signal x(t) after the low-pressure pulse is injected into the detection point;

[0062] A time-varying filter empirical mode decomposition module is configured to perform a time-varying filter empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components;

[0063] A separation module is configured to separate the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t);

[0064] A denoising module is configured to perform denoising on the noisy modal component p(t) using a combined morphological difference filter CEMDF to obtain a denoised modal component s(t); and,

[0065] The reconstruction module is configured to reconstruct the denoised modal component s(t) and the non-noised modal component q(t) to obtain the denoised signal f(t).

[0066] The embodiment of the present invention takes the pre-location of a phase A ground fault as an example. Figure 1 A schematic diagram of traveling wave ranging when phase A is fault-grounded is given. The method includes the following steps:

[0067] Step 1: Original signal acquisition: Inject a low-voltage pulse at the detection point and record the original low-voltage pulse reflected wave signal x(t), which is also the cable fault distance measurement signal to be processed.

[0068] The low voltage pulse reflected wave signal when phase A is grounded is as follows: Figure 2 shown.

[0069] Step 2: Obtain intrinsic mode components. Based on the time-varying filtered empirical mode decomposition (TVFEMD)’s ability to preserve the time-varying characteristics of the reflected wave signal and its advantage of not easily generating modal aliasing and decomposition errors, the original signal is decomposed by TVFEMD to obtain N intrinsic mode components (IMFs).

[0070] TVFEMD is used to decompose the reflected wave signal when phase A is grounded to obtain IMF. The implementation process is:

[0071] 1) Determine the instantaneous amplitude A(t) and instantaneous phase of the original low-voltage pulse reflected wave signal x(t)

[0072]

[0073] In the formula, is the Hilbert transform of x(t).

[0074] 2) According to the local maximum sequence of amplitude A(t) {t max} and the local minimum sequence {t min}, the corresponding analytical signal is defined as:

[0075]

[0076] In the formula, a1 and a2 are constants.

[0077] From the above formula we can infer:

[0078]

[0079] In the formula, is the instantaneous phase at different times.

[0080] 3) Calculation and Find the local cutoff frequency

[0081]

[0082]

[0083] Where η1(t) and η2(t) are obtained by interpolation.

[0084] 4) Use a time-varying filter to filter the unevaluated signal to obtain the local mean, calculate the signal h(t), and stop the boundary condition θ(t).

[0085]

[0086] In the formula, B Loughlin (t) is the Loughlin instantaneous bandwidth; is the weighted mean instantaneous frequency.

[0087] Continue to update x(t). If the signal satisfies θ(t)≤ξ, then x(t) is considered to be an IMF component. Otherwise, repeat the above steps until the decomposition is complete. ξ is the bandwidth threshold.

[0088] Step 3: Signal separation: Based on the screening effect of the correlation coefficient method and kurtosis analysis on the original signal, the N IMFs obtained in step 2 are separated to obtain the noisy modal component p(t) and the non-noisy modal component q(t).

[0089] The correlation coefficient method and kurtosis analysis are used to screen and separate the A-phase fault grounding reflected wave signal to obtain the noisy component and the non-noisy component. The calculation formula of the correlation coefficient method and kurtosis analysis is:

[0090] Correlation coefficient method:

[0091]

[0092] In the formula, r i is the correlation coefficient; x i are the eigenmode components, is the average value of each eigenmode component; y is the original low-pressure pulse reflection wave signal x(t), is the average value of the original low-pressure pulse reflected wave signal.

[0093] Kurtosis analysis method:

[0094]

[0095] Where, X rms is the standard deviation of the signal.

[0096] The IMF separation formula thus formed is:

[0097]

[0098] Where α and β are constants.

[0099] Step 4: Modal component denoising. Based on the advantages of combined morphological difference filtering (CEMDF) in suppressing noise and highlighting signal features, CEMDF is used to denoise the noisy modal component p(t) to obtain the denoised modal component s(t).

[0100] CEMDF is used to reduce the noise mode separated from the phase A fault grounding signal. The noise reduction formula is:

[0101] f CEDMF =f GCD (n)-f GOE (n)

[0102] In the formula, f GCD is a generalized closed-expansion operator, f GOE is a generalized opening-erosion operator, and its calculation formulas are:

[0103]

[0104] In the formula, g1 and g2 are different structural elements; the solid origin represents the closing operation, and the hollow origin represents the opening operation.

[0105] Step 5: Signal reconstruction. The denoised modal components in step 4 are combined with the non-noised modal components in step 3 to obtain the denoised signal f(t).

[0106] The signal is reconstructed by adjusting the proportion of the denoised modal component s(t) in the final signal. The calculation formula for signal reconstruction is:

[0107]

[0108] This completes the complete noise reduction process of the A-phase fault grounding reflected wave signal.

[0109] An embodiment of the present invention further provides another computer device, including a processor and a memory configured to store a computer program that can be run on the processor; wherein, when the processor is configured to run the computer program, the method steps in the aforementioned embodiment are executed.

[0110] In practical applications, the processor includes a field programmable gate array (FPGA), and the processor may be a central processing unit (CPU) or a digital signal processor (DSP). It is understandable that for different devices, the electronic device used to implement the function of the processor may be other, and the embodiment of the present invention does not specifically limit it.

[0111] The above-mentioned memory can be a volatile memory (volatile memory), such as a random access memory (RAM); or a non-volatile memory (non-volatile memory), such as a read-only memory (ROM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD); or a combination of the above-mentioned types of memory, and provide instructions and data to the processor.

[0112] In an exemplary embodiment, an embodiment of the present invention further provides a computer-readable storage medium for storing a computer program.

[0113] Optionally, the computer-readable storage medium can be applied to any one of the methods in the embodiments of the present invention, and the computer program enables the computer to execute the corresponding processes implemented by the processor in each method in the embodiments of the present invention. For the sake of brevity, they are not described here.

[0114] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0115] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0116] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0118] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0119] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0120] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A joint denoising method for cable fault location signal based on improved TVFEMD-CEMDF, characterized in that The steps include: Step 1: inject a low-pressure pulse at the detection point to obtain the original low-pressure pulse reflected wave signal x(t); Step 2, performing time-varying filtering empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components; Step 3, separating the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t); Step 4: Use the combined morphological difference filter CEMDF to perform denoising on the noisy modal component p(t) to obtain the denoised modal component s(t); Step 5: Reconstruct the denoised modal component s(t) and the unnoised modal component q(t) to obtain the denoised signal f(t).

2. The method according to claim 1, characterized in that: The specific process of step 2 is: Step 21, determine the instantaneous amplitude A(t) and instantaneous phase of the original low-pressure pulse reflected wave signal x(t) Step 22, determine the analytical signal of the original low-pressure pulse reflected wave signal x(t) as: In the formula, a1, a2 are constants; It can be inferred that: Step 23, find the local cutoff frequency Step 24, filtering the uncalculated signal using a time-varying filter to obtain a local mean and calculating a stop boundary condition θ(t); Step 25, determine if θ(t)≤ξ of the original low-voltage pulse reflected wave signal x(t), where ξ is the bandwidth threshold, and then consider x(t) to be an intrinsic mode component at this time; otherwise, update x(t) and repeat steps 21-25 until the decomposition is completed.

3. The method according to claim 2, characterized in that: In step 23, the calculation formula is as follows: In the formula, is the instantaneous phase at different times; η1(t) and η2(t) are obtained by interpolation.

4. The method according to claim 2, characterized in that: In step 25, the stop boundary condition θ(t) is calculated according to the following formula: In the formula, B Loughlin (t) is the Loughlin instantaneous bandwidth; is the weighted mean instantaneous frequency.

5. The method according to claim 1, characterized in that: In step 3, the eigenmode components are separated using the correlation coefficient method and kurtosis analysis, and the calculation formula is: In the formula, α and β are constants; r i is the correlation coefficient, k i is the kurtosis; x i is the i-th eigenmode component; is the average value of the signal; y is the original reflected wave signal, is the original reflected wave signal mean; X rms is the standard deviation of the signal.

6. The method according to claim 1, characterized in that: In step 4, CEMDF is used to perform denoising on the noisy modal component p(t), and the denoising formula is: f CEDMF =f GCD (n)-f GOE (n) In the formula, f GCD is a generalized closed-expansion operator, f GOE is the generalized opening-erosion operator, and its calculation formulas are: In the formula, g1 and g2 are different structural elements; the solid origin represents the closing operation, and the hollow origin represents the opening operation.

7. The method according to claim 1, characterized in that: In step 5, the denoised modal component s(t) and the non-noised modal component q(t) are combined and reconstructed using the following formula: Among them, f(t) is the denoised signal.

8. A cable fault location signal joint noise reduction system based on improved TVFEMD-CEMDF, characterized by: include, The original low-pressure pulse reflected wave signal acquisition module is configured to acquire the original low-pressure pulse reflected wave signal x(t) after the low-pressure pulse is injected into the detection point; A time-varying filter empirical mode decomposition module is configured to perform a time-varying filter empirical mode decomposition TVFEMD on the original low-voltage pulse reflection wave signal x(t) to obtain N intrinsic mode components; A separation module is configured to separate the N IMFs to obtain a noisy modal component p(t) and a non-noisy modal component q(t); A denoising module is configured to perform denoising on the noisy modal component p(t) by using a combined morphological difference filter CEMDF to obtain a denoised modal component s(t); as well as, The reconstruction module is configured to reconstruct the denoised modal component s(t) and the non-noised modal component q(t) to obtain the denoised signal f(t).

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that: When the processor executes the computer program, the steps of the cable fault location signal joint denoising method based on improved TVFEMD-CEMDF as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program; characterized in that: When the computer program is executed by a processor, the steps of the cable fault location signal joint noise reduction method based on improved TVFEMD-CEMDF as described in any one of claims 1 to 7 are implemented.

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