Method for measuring space charge accumulation distribution condition of solid cable insulation layer

Abstract

The invention discloses a method for measuring the space charge accumulation distribution condition of an insulating layer of a solid cable. The method comprises the following steps: S1, stripping an armored part of the solid cable; s2, detecting an insulating layer space charge signal of the entity cable through a pulse electro-acoustic method, and performing mean filtering to obtain a pulse electro-acoustic response signal v0 (t) of the insulating layer without space charge accumulation at an initial moment and a pulse electro-acoustic response signal vt (t) at a t moment; s3, performing baseline correction on the signal v0 (t) and the signal vt (t) to remove a linear trend so as to respectively obtain a signal v0-1 (t) and a signal vt-1 (t), performing wavelet denoising on the signal v0-1 (t) and the signal vt-1 (t) so as to respectively obtain a signal v0-2 (t) and a signal vt-2 (t), and finally performing frequency domain transformation on the signal v0-2 (t) and the signal vt-2 (t) so as to respectively obtain a frequency domain signal V0-2 (f) and a frequency domain signal Vt-2 (f); according to the method, the space charge distribution of the entity cable is obtained by performing mean filtering on the space charge signals of the insulating layer and combining signal processing methods such as baseline correction, wavelet denoising and deconvolution, and the method has the characteristics of rapid measurement and good universality.

Description

Technical Field

[0001] This invention relates to the field of high voltage and insulation technology, and in particular to a method for measuring the distribution of space charge accumulation in the insulation layer of a solid cable. Background Technology

[0002] The distribution of space charge in the insulation layer of a solid cable has a significant impact on its performance. Among existing space charge measurement methods, the pulsed electroacoustic (PEA) method has advantages such as high sensitivity and high resolution, and is now widely used in the measurement of space charge in thin sheet insulation materials. The PEA method obtains information about the space charge within the insulation layer by superimposing a narrow pulse voltage onto the insulation layer subjected to DC high voltage to generate and capture the sound pressure wave. However, when the object of space charge measurement changes from a thin sheet to a thicker solid cable insulation layer, the characteristic intensity of the captured signal is greatly reduced, while the noise level increases, and the signal length also increases significantly, which may lead to signal baseline tilting. Summary of the Invention

[0003] The purpose of this invention is to provide a method for measuring the space charge accumulation distribution in the insulation layer of a solid cable. This invention obtains the space charge distribution of the solid cable by performing mean filtering on the space charge signal of the insulation layer, combined with signal processing methods such as baseline correction, wavelet denoising, and deconvolution. This method features rapid measurement and good universality.

[0004] The technical solution of the present invention: A method for measuring the distribution of space charge accumulation in the insulation layer of a solid cable, comprising the following steps: Step S1: Strip the armored portion of the solid cable; Step S2: Apply voltage to the physical cable, detect the space charge signal of the insulation layer of the physical cable using the pulse electroacoustic method, and perform mean filtering to obtain the pulse electroacoustic response signal v0(t) at the initial moment when there is no space charge accumulation in the insulation layer and the pulse electroacoustic response signal v at time t. t (t); Step S3: For signals v0(t) and v t (t) After baseline correction to remove the linear trend, the signals v are obtained respectively. 0-1 (t) and v t-1 (t), then for the signal v 0-1 (t) and v t-1 (t) Perform wavelet denoising to obtain the signal v 0-2 (t) and v t-2 (t), finally for signal v 0-2 (t) and v t-2 (t) Perform frequency domain transformation to obtain the frequency domain signal V. 0-2 (f) and Vt-2 (f); Step S4: For the frequency domain signal V 0-2 (f) and V t-2 (f) Perform deconvolution to obtain the signal. U ( f ), for signals U ( f Gaussian filtering is performed to obtain the signal. U g ( f ); Step S5: For the signal U g ( f Inverse transform yields the time-domain signal u g (t), then the time-domain signal u g (t) The charge density distribution curve ρ(z) along the thickness of the insulating layer is obtained by reconstructing.

[0005] In the above-mentioned method for measuring the space charge accumulation distribution in the insulation layer of a solid cable, the mean filtering of the pulse electroacoustic method has n iterations, and the applied voltage to the solid cable is V; the pulse electroacoustic response signal v0(t) at the initial moment when there is no space charge accumulation in the insulation layer is obtained by the following formula: ; In the formula, S ( f ) represents the system functions of the system instruments; u 0 ( t The voltage signal consists of the surface charge σ(0) on the grounding side electrode of the physical cable; The pulse electroacoustic response signal v at time t t (t) is obtained through the following formula: ; In the formula, u t ( t ) represents the voltage signal of the cumulative charge distribution at time t.

[0006] In the aforementioned method for measuring the spatial charge accumulation distribution in the insulation layer of a solid cable, the mean number n is 1000-3000.

[0007] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a solid cable, the baseline correction process in step S3 is shown in the following formula: ; In the formula, k 0 The best-fit straight line for the signal v0(t) data.k t For signal v t (t) The best-fit line for the data.

[0008] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a physical cable, the threshold for wavelet denoising in step S3 is: ; in, N For signal length, The standard deviation of noise; The threshold type is soft threshold; the threshold scaling criterion is based on noise estimation scaling of the first-level coefficients; the wavelet decomposition level is 8; and the wavelet basis is db4 type.

[0009] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a physical cable, the frequency domain transformation in step S3 is a Laplace transform, as shown in the following equation: ; In the formula, d To restore the insulation thickness of the physical cable; tau is the time constant.

[0010] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a solid cable, the deconvolution process in step S4 is shown in the following formula: ; In the formula, U 0 ( t ) is the pulse function of the charge on the electrode surface.

[0011] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a solid cable, the Gaussian filtering process in step S4 is shown in the following formula: ; In the formula, G ( f ) is the frequency domain transfer function of the Gaussian filter, used for high-frequency cutoff filtering.

[0012] In the aforementioned method for measuring the space charge accumulation distribution in the insulation layer of a solid cable, the restoration process in step S5 is to... U g ( f Perform an inverse Laplace transform to obtain the time-domain signal. u g (t), then for u g (t) at z=v saThe charge density distribution curve ρ(z), v along the thickness of the insulating layer is obtained by transforming the position t. sa This represents the speed at which sound waves propagate through the insulation layer of a solid cable at room temperature.

[0013] Compared with existing technologies, this invention targets solid cable insulation layers with a thickness much greater than that of thin sheets. By combining the aforementioned mean filtering with signal processing methods such as baseline correction, wavelet denoising, and deconvolution, it effectively overcomes the limitations of traditional methods in thick media, such as rapid signal attenuation and feature blurring, and accurately captures spatial charge accumulation information along the thickness direction of the insulation layer. Furthermore, setting the mean number in the relatively high range of 1000-3000 avoids both the signal characteristics being submerged in noise and the inability to distinguish the difference between initial no charge and charge accumulation after voltage application due to excessively low numbers, and the reduced acquisition efficiency caused by excessively high numbers, thus ensuring that the mean-filtered v0(t) and v t The charge response characteristics of (t) are more prominent, providing high-quality raw data for subsequent signal processing; baseline correction, by removing the linear trend, can completely eliminate the interference of baseline tilt on the signal reference, making the corrected v 0-1 (t) and v t-1 (t) A flat baseline avoids charge distribution calculation errors caused by tilting, ensuring that subsequent wavelet denoising, deconvolution, and other processing are based on a stable signal reference; wavelet denoising significantly reduces noise while preserving the detailed features of the charge distribution to the greatest extent, effectively preventing noise from masking the true charge response, and making the denoised v 0-2 (t) and v t-2 (t) more closely resembles the real charge distribution characteristics, providing a clean input for subsequent deconvolution processing; finally, by combining deconvolution, Gaussian filtering and inverse transform, the charge density distribution curve along the thickness of the insulating layer is accurately restored, clearly showing the charge density variation pattern at different locations. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 This is a signal diagram before wavelet denoising in an embodiment of the present invention; Figure 3 This is a signal image after wavelet denoising according to an embodiment of the present invention; Figure 4 This is a charge density distribution curve of an embodiment of the present invention. Detailed Implementation

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0016] Example: A method for measuring the distribution of space charge accumulation in the insulation layer of a solid cable, as shown in the attached figure. Figure 1 As shown, proceed with the following steps: Step S1: Select a 110kV cross-linked polyethylene (XLPE) solid cable with an insulation layer thickness of 34mm. The speed of sound propagation in the insulation layer at room temperature is v. sa The speed is 2000 m / s. Use wire strippers to remove the outer armor and shielding of the solid cable to expose the insulation layer. Lightly sand the insulation layer surface with sandpaper until smooth to remove residual metal debris. Clean the surface with anhydrous ethanol to avoid impurities affecting the charge measurement. Check the insulation layer for damage and ensure there are no scratches or breaks. Then, fix the cable in the electrode clamp of the PEA measurement system to ensure that the high-voltage electrode is in close contact with the insulation layer surface. Step S2: Start the PEA system, set the pulse width to 5ns, the sampling frequency to 100MHz, and continuously acquire 2000 space charge signals. Process the signals using the system's built-in mean filtering function to obtain the initial response signal v0(t) without charge accumulation. Apply a 220kV DC voltage and maintain the voltage stability. Similarly, acquire 2000 signals and perform mean filtering to obtain the pulse electroacoustic response signal v at time t. t (t); Taking the Laplace deconvolution method as an example, the space charge in the pulse electroacoustic data processing is calculated. The relationship between the space charge distribution signal and the pulse response signal in the pulse electroacoustic method is as follows: (1); In the formula, S ( f ) represents the system functions of the system instruments; u 0 ( t The voltage signal is composed of the surface charge σ(0) on the grounding side electrode of the physical cable, eliminating the surface charge signal on the high-voltage side of the physical cable; After applying pressure for a period of time, the pulse electroacoustic response signal after mean filtering at time t is obtained: (2); In the formula, u t ( t ) represents the voltage signal of the cumulative charge distribution at time t.

[0017] Step S3: Import v0(t) and v into MATLAB t (t) data, using the polyfit function to perform linear fitting on the signal, and obtaining the best-fit line respectively. k 0 and k t For signals v0(t) and v t (t) After baseline correction to remove the linear trend, the signals v are obtained respectively. 0-1 (t) and v t-1(t), the processing procedure is shown in the following formula: ; In the formula, k 0 The best-fit straight line for the signal v0(t) data. k t For signal v t (t) The best-fit line for the data; if the baseline is flat and requires no correction, baseline correction can be skipped, as shown in the appendix. Figure 2 As shown, the horizontal axis represents the location of the insulating layer (0-34mm), and the vertical axis represents the signal voltage (-0.006V-0.008V). There is obvious high-frequency noise in the signal, the baseline is slightly tilted, which masks the initial rising edge, and the local charge characteristic peak is masked by noise.

[0018] Then call the wavelet function, setting the parameters: wavelet basis to db4, decomposition level to 8 (too high a level will lose too much low-frequency information, too low a level will result in insufficient denoising effect), threshold type to soft threshold, and wavelet denoising threshold selection rule to general threshold. ; in, N For signal length, The standard deviation of noise; For signal v 0-1 (t) and v t-1 (t) Perform wavelet denoising to obtain the signal v 0-2 (t) and v t-2 (t), the results are attached. Figure 3 As shown, noise is significantly attenuated, signal smoothness is significantly improved, and the baseline tends to be horizontal, while key features of charge distribution (such as local peaks) and attached... Figure 2 The corresponding information is accurately preserved.

[0019] Finally, regarding signal v 0-2 (t) and v t-2 (t) Perform frequency domain transformation to obtain the frequency domain signal V. 0-2 (f) and V t-2 (f) The frequency domain transform is the Laplace transform, as shown in the following equation: (3); In the formula, d To restore the insulation thickness of the physical cable; tau The time constant is set to 400μs, which can avoid the baseline tilt problem after deconvolution and solve the problem of non-convergence at the end of the signal.

[0020] Step S4: Combining formulas (1), (2), and (3), the relationship between the space charge distribution signal and the pulse response signal in the pulse electroacoustic method after frequency domain transformation can be obtained: ; ; From the above formula, we can derive: ; In the formula, U 0 ( t Let be the pulse function of the electrode surface charge. It is a pulse with a distribution area of ​​"1" and no width. Since such a pulse has a constant spectrum across the entire frequency range, its pulse function in the frequency domain is: U 0( f ) = 1; for the signal U ( f Gaussian filtering is performed to obtain the signal. U g ( f The Gaussian filtering process is shown in the following formula: ; In the formula, G ( f ) is the frequency domain transfer function of the Gaussian filter, used for high-frequency cutoff filtering.

[0021] Step S5: For U g ( f Performing an inverse Laplace transform yields the time-domain signal u. g (t), then for u g (t) at z=v sa The time signal is transformed by changing the position t, converting it into a spatial distribution along the thickness of the insulating layer, resulting in the charge density distribution curve ρ(z) along the thickness of the insulating layer, as shown in the attached figure. Figure 4 As shown in the figure, the curves clearly show the change in charge density along the thickness of the insulation layer, with a clear peak-valley distribution (such as the peak value of positive charge and the valley value of negative charge at a specific location). Moreover, the curve changes continuously without abnormal jumps, which is consistent with the physical law that the charge in the insulation layer of a solid cable accumulates at different depths due to the difference in electric field gradient. This verifies the effectiveness of the entire signal processing flow (deconvolution, Gaussian filtering, inverse transform, etc.) and shows that the final charge density distribution can accurately reflect the real spatial charge accumulation state.

[0022] In summary, this invention targets solid cable insulation layers with thicknesses much greater than those of thin sheets. By employing the aforementioned mean filtering combined with signal processing methods such as baseline correction, wavelet denoising, and deconvolution, it effectively overcomes the limitations of traditional methods, which suffer from rapid signal attenuation and feature blurring in thick media. This allows for the accurate capture of spatial charge accumulation information along the insulation layer thickness direction. Furthermore, setting the mean iteration count to a high value of 2000 avoids both the signal characteristics being submerged in noise and the inability to distinguish between initial no charge and charge accumulation after voltage application due to excessively low counts, and the reduced acquisition efficiency caused by excessively high counts. This ensures that the mean-filtered v0(t) and v... t The charge response characteristics of (t) are more prominent, providing high-quality raw data for subsequent signal processing; baseline correction, by removing the linear trend, can completely eliminate the interference of baseline tilt on the signal reference, making the corrected v 0-1 (t) and v t-1 (t) A flat baseline avoids calculation errors in charge distribution caused by tilting, ensuring that subsequent wavelet denoising, deconvolution, and other processing are based on a stable signal reference; wavelet denoising significantly reduces noise while preserving the detailed features of charge distribution (such as abrupt changes in local charge accumulation), effectively preventing noise from masking the true charge response, and making the denoised v 0-2 (t) and v t-2 (t) more closely resembles the real charge distribution characteristics, providing a clean input for subsequent deconvolution processing; finally, by combining deconvolution, Gaussian filtering and inverse transform, the charge density distribution curve along the thickness of the insulating layer is accurately restored, clearly showing the charge density variation pattern at different locations.

Claims

1. A method for measuring the distribution of space charge accumulation in the insulation layer of a solid cable, characterized in that: Follow these steps: Step S1: Strip the armored portion of the solid cable; Step S2: Apply voltage to the physical cable, detect the space charge signal of the insulation layer of the physical cable using the pulse electroacoustic method, and perform mean filtering to obtain the pulse electroacoustic response signal v0(t) at the initial moment when there is no space charge accumulation in the insulation layer and the pulse electroacoustic response signal v at time t. t (t); Step S3: For signals v0(t) and v t (t) After baseline correction to remove the linear trend, the signals v are obtained respectively. 0-1 (t) and v t-1 (t), then for the signal v 0-1 (t) and v t-1 (t) Perform wavelet denoising to obtain the signal v 0-2 (t) and v t-2 (t), finally for signal v 0-2 (t) and v t-2 (t) Perform frequency domain transformation to obtain the frequency domain signal V. 0-2 (f) and V t-2 (f); Step S4: For the frequency domain signal V 0-2 (f) and V t-2 (f) Perform deconvolution processing to obtain the signal. U ( f ), for signals U ( f Gaussian filtering is performed to obtain the signal. U g ( f ); Step S5: For the signal U g ( f Inverse transform yields the time-domain signal u g (t), then the time-domain signal u g (t) The charge density distribution curve ρ(z) along the thickness of the insulating layer is obtained by reconstructing.

2. The method for measuring the spatial charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The mean filtering in the pulse electroacoustic method has n iterations, and the applied voltage to the physical cable is V. The pulse electroacoustic response signal v0(t) with no space charge accumulation in the insulation layer at the initial moment is obtained by the following formula: ； In the formula, S ( f ) represents the system functions of the system instruments; u 0 ( t The voltage signal consists of the surface charge σ(0) on the grounding side electrode of the physical cable; The pulse electroacoustic response signal v at time t t (t) is obtained through the following formula: ； In the formula, u t ( t ) represents the voltage signal of the cumulative charge distribution at time t.

3. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 2, characterized in that: The mean number n ranges from 1000 to 3000.

4. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The baseline correction process in step S3 is shown in the following formula: ； In the formula, k 0 The best-fit straight line for the signal v0(t) data. k t For signal v t (t) The best-fit line for the data.

5. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The threshold for wavelet denoising in step S3 is: ； in, N For signal length, The standard deviation of noise; The threshold type is soft threshold; the threshold scaling criterion is based on noise estimation scaling of the first-level coefficients; the wavelet decomposition level is 8; and the wavelet basis is db4 type.

6. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The frequency domain transform in step S3 is a Laplace transform, as shown in the following equation: ； In the formula, d To restore the insulation thickness of the physical cable; tau is the time constant.

7. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The deconvolution process in step S4 is shown in the following formula: ； In the formula, U 0 ( t ) is the pulse function of the charge on the electrode surface.

8. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The Gaussian filtering process in step S4 is shown in the following formula: ； In the formula, G ( f ) is the frequency domain transfer function of the Gaussian filter, used for high-frequency cutoff filtering.

9. The method for measuring the space charge accumulation distribution in the insulation layer of a solid cable according to claim 1, characterized in that: The restoration process in step S5 is to... U g ( f Performing an inverse Laplace transform yields the time-domain signal. u g (t), then for u g (t) at z=v sa The charge density distribution curve ρ(z), v along the thickness of the insulating layer is obtained by transforming the position t. sa This represents the speed at which sound waves propagate through the insulation layer of a solid cable at room temperature.

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