A rubber plate insulation performance detection method and system based on power parameter characteristics
Patent Information
- Application Number
- CN202611543715.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-10-08
- Publication Date
- 2026-11-03
AI Technical Summary
Existing testing technologies for the insulation performance of rubber sheets mainly rely on single-frequency testing, which cannot capture the relaxation behavior and interface polarization characteristics of insulation materials in a wide frequency range. This leads to missed or misjudged defects in the early stages of aging or in localized areas. Furthermore, multi-frequency test analysis is easily affected by interface polarization within the dielectric, space charge effects, and measurement noise, making it difficult to accurately obtain DC insulation resistance and low-frequency dielectric loss tangent values.
By acquiring the power parameter signals of the multi-band test response, performing adaptive modulation decomposition, constructing the impedance-frequency response surface, and using the extrapolation method to calculate the equivalent insulation resistance and dielectric loss tangent of the rubber sheet at zero frequency, the insulation performance level is determined by combining the preset threshold table.
It enables reliable determination of the insulation performance of rubber sheets, improves the accuracy and repeatability of testing, reduces the risk of misjudgment based on a single indicator, requires no manual intervention in the testing process, and yields good consistency of results.
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Figure CN123029427A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of rubber sheet insulation performance testing technology, specifically to a method and system for testing rubber sheet insulation performance based on electrical parameter characteristics. Background Technology
[0002] As a commonly used insulating material in electrical equipment, the accurate testing of the insulation performance of rubber sheets is crucial for ensuring the safe operation of equipment. Existing rubber sheet insulation performance testing technologies mainly rely on insulation resistance measurements and dielectric loss factor tests at power frequency or a single frequency. These methods obtain the steady-state insulation resistance value and the power frequency dielectric loss tangent by applying a DC voltage or a single-frequency AC voltage across the rubber sheet, and then assess the insulation status based on empirical thresholds. However, insulation degradation in rubber sheets is often accompanied by changes in their dielectric response frequency characteristics. Single-frequency testing cannot capture the relaxation behavior and interface polarization characteristics of insulating materials across a wide frequency range, providing only partial information about the insulation status and easily leading to missed or misjudged early-stage aging or localized defects. Furthermore, rubber sheets in actual operation are subjected to electric field stresses from multiple frequency components, such as harmonics and transient overvoltages, making it difficult for power frequency insulation parameters to fully reflect their true insulation capacity under multi-frequency stress. To overcome the limitations of single-frequency testing, multi-frequency dielectric response testing technology has been introduced into the field of insulation assessment. This technology obtains wide-band dielectric response data by applying test voltages containing multiple frequency components to the insulating medium. However, in existing multi-frequency test analysis, swept-frequency impedance analysis or Fourier transform is typically used to directly obtain the impedance amplitude and phase at each frequency, and then the data points are fitted into an equivalent circuit model. This approach is susceptible to interference from interface polarization, space charge effects, and measurement noise when dealing with non-homogeneous and lossy media such as rubber sheets. Energy leakage between adjacent frequency components in the frequency domain response also reduces the accuracy of feature extraction at each frequency band, thus affecting the reliability of subsequent insulation parameter estimation. Meanwhile, the practical need in high-voltage insulation is to obtain DC insulation resistance and low-frequency dielectric loss tangent values that directly reflect the intrinsic insulation state of the rubber sheet. However, deterministic methods that directly extrapolate from multi-frequency AC responses to zero frequency are still imperfect, lacking robust modeling methods for the asymptotic behavior of the impedance surface as the frequency approaches zero, making it difficult to accurately provide DC insulation performance parameters from wide-band data.
[0003] Based on the above problems, it is necessary to adaptively separate the characteristic signal components of different frequency bands from the multi-band power parameter response, and use the frequency division characteristics to construct an impedance-frequency response surface. In this way, the equivalent insulation resistance and equivalent dielectric loss tangent of the rubber sheet at zero frequency can be stably obtained by extrapolating the surface, thereby improving the accuracy and repeatability of insulation performance determination. Summary of the Invention
[0004] The purpose of this invention is to provide a method and system for testing the insulation performance of rubber sheets based on electrical parameter characteristics. This method accurately extracts the electrical parameter characteristics of each frequency band from the multi-frequency test response and extrapolates the DC equivalent insulation resistance and equivalent dielectric loss tangent of the rubber sheet from the frequency response surface, thereby achieving a reliable determination of the insulation performance level of the rubber sheet.
[0005] To achieve the above objectives, the present invention provides the following technical solution: The present invention provides a method for testing the insulation performance of a rubber sheet based on electrical parameter characteristics, comprising: acquiring the electrical parameter response signal of the rubber sheet under test under applied multi-frequency test voltage, wherein the electrical parameter response signal includes current harmonic components and voltage harmonic components; performing an adaptive modulation decomposition operation based on multi-frequency carrier signals on the electrical parameter response signal to obtain multiple sub-signal components characterizing the electrical parameter characteristics of different frequency bands; constructing an impedance-frequency response surface of the rubber sheet insulation medium based on the phase difference sequence of the sub-signal components; calculating the equivalent insulation resistance and equivalent dielectric loss tangent of the rubber sheet at zero frequency using an extrapolation method based on the impedance-frequency response surface; and generating an insulation performance level determination result of the rubber sheet based on the equivalent insulation resistance and the equivalent dielectric loss tangent combined with a preset insulation performance threshold table.
[0006] By applying test voltages covering multiple frequency bands to the test sheet and obtaining wide-band electrical parameter responses, the problem of incomplete insulation condition reflection by single-frequency testing can be avoided. As a technical solution of this invention, when acquiring the electrical parameter response signal, a signal generator applies a set of AC test voltages with a logarithmic frequency distribution to the test sheet. A data acquisition card simultaneously acquires current and voltage signals, and a discrete Fourier transform is performed on the acquired signals to extract current and voltage harmonic components. The logarithmically distributed test frequencies allow for denser measurement information in the low-frequency region, providing a reliable data foundation for subsequent low-frequency extrapolation.
[0007] During adaptive modulation decomposition, a set of carrier signals with different center frequencies covering the frequency range of the multi-band test voltage is constructed. Each carrier signal is multiplied point-by-point with the power parameter response signal to obtain a modulated mixed signal sequence. Then, a sliding window integral filter is applied to each mixed signal sequence to extract the envelope signal corresponding to each carrier frequency as a sub-signal component. Preferably, the length of the sliding window is set to half the period of the carrier signal. The window is moved point-by-point along the mixed signal sequence, and the arithmetic mean of the data points within the window is calculated. The time series formed by this average value is used as the envelope signal. This method can effectively separate the response characteristics of different frequency bands and suppress noise and carrier residual components, so that the sub-signal components more accurately reflect the dielectric response of the adhesive board in each frequency band.
[0008] When constructing the impedance-frequency response surface, the instantaneous phase of each sub-signal component is extracted, and the difference between each sub-signal component and the corresponding frequency band phase of the applied multi-band test voltage is calculated to obtain a phase difference sequence. A discrete point set in three-dimensional space is constructed using the phase difference sequence as the ordinate, the amplitude ratio of the sub-signal components as the abscissa, and the center frequency of the sub-signal components as the depth coordinate. Bicubic spline interpolation is then performed on this discrete point set to generate a continuous impedance-frequency response surface. This surface integrates information from the three dimensions of amplitude, phase, and frequency, and can intuitively and completely characterize the impedance variation of the insulating medium in the rubber sheet over a wide frequency range.
[0009] When calculating the equivalent insulation resistance and the equivalent dielectric loss tangent, multiple discrete data points in the lower asymptote region with frequencies approaching zero are extracted from the impedance-frequency response surface. Linear regression analysis is performed on these discrete data points to obtain a linear regression equation, and the extrapolation constant term of this linear regression equation is set as the equivalent insulation resistance. Simultaneously, the convergence value of the phase difference sequence at frequencies approaching zero is extracted from the impedance-frequency response surface, and this convergence value is set as the equivalent dielectric loss tangent. Preferably, the linear regression analysis employs a weighted least squares method, where the weights are proportional to the reciprocal of the frequency values of the discrete data points. This enhances the influence of extremely low-frequency data on the extrapolation results, improving the accuracy and stability of insulation parameter estimation at zero frequency. Furthermore, when performing linear regression analysis on the discrete data points, the covariance matrix of the discrete data points in the impedance-frequency coordinate plane is calculated. The slope and intercept of the linear regression equation are determined based on the eigenvalue decomposition results of the covariance matrix, and the intercept is used as the extrapolation constant term, making the determination of the regression coefficients more robust.
[0010] When generating insulation performance level determination results, a preset insulation performance threshold table includes normal thresholds, warning thresholds, and alarm thresholds. The equivalent insulation resistance is compared piecewise with the normal, warning, and alarm thresholds to obtain the first-level insulation resistance determination number. The equivalent dielectric loss tangent is also compared piecewise with the normal, warning, and alarm thresholds to obtain the second-level dielectric loss determination number. The first-level insulation resistance determination number and the second-level dielectric loss determination number are combined and coded, and the combined code corresponds to the insulation performance level determination result. This dual-parameter cross-evaluation method integrates insulation status information from both resistive leakage and dielectric loss perspectives, reducing the risk of misjudgment based on a single indicator and improving the reliability of the insulation performance level determination for the rubber sheet.
[0011] This invention also provides a system for testing the insulation performance of rubber sheets based on electrical parameter characteristics, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the aforementioned method for testing the insulation performance of rubber sheets based on electrical parameter characteristics. This system can be integrated into portable or online testing equipment, automatically completing multi-frequency excitation, signal decomposition, surface construction, extrapolation calculation, and grade determination. The testing process requires no manual intervention, and the results are highly consistent.
[0012] The technical effects and advantages provided by the present invention in the above technical solution are as follows: By constructing a set of carrier signals with center frequencies covering the frequency range of multi-band test voltages, the power parameter response signal is multiplied point-by-point with each carrier signal to obtain a modulated mixed signal sequence. A sliding window integral filter is then applied to the mixed signal sequence to extract the envelope signal corresponding to each carrier frequency as a sub-signal component, thus achieving adaptive modulation decomposition of the multi-band mixed response signal. This decomposition method utilizes carrier modulation to shift the response components of different frequency bands to the baseband, and then uses sliding window integral filtering to complete low-pass extraction. The separation of sub-signal components in each frequency band does not depend on a predetermined filter bandwidth and fixed center frequency configuration, and can adaptively lock the instantaneous amplitude and phase information of the frequency band of interest according to the actual carrier frequency. Compared with methods that directly perform Fourier transform or bandpass filtering on the full-band response signal, this decomposition process effectively suppresses the influence of energy leakage and noise interference between adjacent frequency components on feature extraction, making the sub-signal components more accurately characterize the true power parameter features of the insulating medium within the corresponding frequency band, providing reliable input data for subsequent construction of high-precision impedance-frequency response surfaces. A discrete point set of a three-dimensional impedance-frequency response surface is constructed using the phase difference sequence and amplitude ratio of each sub-signal component. A continuous surface is then generated through bicubic spline interpolation. Based on this, multiple discrete data points are extracted from the lower asymptote region where the surface frequency approaches zero. Weighted least-squares linear regression is then performed, where the weights are proportional to the reciprocal of the frequency values of the discrete data points. The intercept of the regression equation is used as the equivalent insulation resistance. Simultaneously, the convergence value of the phase difference sequence at the frequency approaching zero is extracted as the equivalent dielectric loss tangent. This processing method integrates the frequency dependence characteristics of phase difference and amplitude ratio under multi-frequency response into a continuous surface, intuitively reflecting the continuous change of the impedance of the rubber sheet insulation medium with frequency. Using inverse frequency-weighted regression in the low-frequency asymptote region of the surface effectively highlights the dominant role of low-frequency data in the extrapolation results, suppresses the influence of high-frequency measurement disturbances on DC parameter estimation, and makes the extrapolated equivalent insulation resistance and equivalent dielectric loss tangent values closer to the intrinsic insulation behavior of the rubber sheet under a DC electric field. Compared with directly using measured values at low frequencies or conventional equal-weighted extrapolation methods, this method improves the stability and accuracy of zero-frequency insulation parameter estimation, thereby giving the final insulation performance level determination result generated based on this parameter and a threshold table a higher degree of confidence. Attached Figure Description
[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.
[0014] Figure 1This is a flowchart of a method for testing the insulation performance of rubber sheets based on electrical parameter characteristics; Figure 2 This is a flowchart of adaptive modulation decomposition based on multi-frequency carrier signals; Figure 3 These are curves showing the change in phase difference of the insulating dielectric impedance of the rubber sheet as a function of frequency under different amplitude ratios. Figure 4 This is a schematic diagram of extrapolating the equivalent insulation resistance in the zero-frequency range of the impedance-frequency response surface; Figure 5 It is the time-domain waveform of the voltage and current signals of the rubber sheet under the application of multi-band test voltage. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0016] See Figure 1This invention provides a method for testing the insulation performance of a rubber sheet based on electrical parameter characteristics. The method includes the following steps: First, acquiring the electrical parameter response signal of the rubber sheet under test under multi-frequency test voltages. The electrical parameter response signal includes current harmonic components and voltage harmonic components. The acquisition method involves: a signal generator applying a set of logarithmically distributed AC test voltages to the rubber sheet under test; a data acquisition card simultaneously acquiring the current signal flowing through the rubber sheet and the voltage signals across the rubber sheet; performing a discrete Fourier transform on the current and voltage signals to extract the current and voltage harmonic components; performing an adaptive modulation decomposition operation based on multi-frequency carrier signals on the electrical parameter response signal to obtain multiple sub-signal components characterizing the electrical parameter characteristics of different frequency bands; constructing an impedance-frequency response surface of the rubber sheet insulation medium based on the phase difference sequence of the sub-signal components; calculating the equivalent insulation resistance and equivalent dielectric loss tangent of the rubber sheet at zero frequency using an extrapolation method based on the impedance-frequency response surface; and generating an insulation performance level determination result for the rubber sheet based on the equivalent insulation resistance and equivalent dielectric loss tangent combined with a preset insulation performance threshold table. The preset insulation performance threshold table includes normal threshold, warning threshold, and alarm threshold. The method for generating the insulation performance level determination result is as follows: the equivalent insulation resistance is compared with the normal threshold, warning threshold, and alarm threshold in segments to obtain the first-level insulation resistance value determination number; the equivalent dielectric loss tangent is compared with the normal threshold, warning threshold, and alarm threshold in segments to obtain the second-level dielectric loss determination number; the first-level insulation resistance value determination number and the second-level dielectric loss determination number are combined and coded, and the combined code corresponds to the insulation performance level determination result.
[0017] Example 1: In specific implementation, please refer to Figure 2 The process involves performing an adaptive modulation decomposition operation based on a multi-frequency carrier signal on the power parameter response signal to obtain multiple sub-signal components that characterize the power parameter features in different frequency bands. This includes constructing a carrier signal, generating a mixed signal sequence, sliding window integral filtering, and extracting the envelope signal as a sub-signal component.
[0018] A set of carrier signals with different center frequencies is constructed, with the frequency range of all carrier signals covering the frequency range of the multi-band test voltage. The multi-band test voltage contains several AC voltage components with logarithmically distributed frequencies, and the center frequency of each carrier signal corresponds one-to-one with each frequency component in the multi-band test voltage. Each carrier signal is a cosine signal, and its discrete expression is as follows: ,in Indicates the first The center frequency of each carrier signal This indicates a discrete sampling time point. The power parameter response signal is a discrete-time sequence, containing a real-value sequence formed by the combination of current harmonic components and voltage harmonic components, which are synchronously acquired with multi-band test voltages.
[0019] After obtaining the carrier signal and the power parameter response signal, each carrier signal and the power parameter response signal are multiplied point by point. Specifically, for the first... One carrier signal, the carrier signal The discrete sampled values are multiplied by the corresponding sampled point values of the power parameter response signal to obtain the modulated mixed signal sequence. , The sampling point number, Let n be the total number of sampling points for the power parameter response signal, n = 0, 1, 2, ... Mixed signal sequences Each element is composed of Give, The power parameter response signal is in the first... The amplitude of each sampling point.
[0020] After performing multiplication operations for all carrier frequencies, a sliding window integral filter is applied to each mixed signal sequence to extract the envelope signal corresponding to each carrier frequency. The sliding window length used in the sliding window integral filter is set to half the carrier signal period. (Carrier signal period) From the carrier center frequency Decision, that is Sliding window length The calculation method is as follows ,in, The sampling frequency of the power parameter response signal. The sliding window is moved along the mixed signal sequence. Moving point by point, the starting position of the sliding window changes from 0 to... The movement step is 1 sampling point. At each window position, the arithmetic mean of all data points within the window is calculated. This arithmetic mean is calculated using the following formula: in, Indicates the first The arithmetic mean of a mixed signal sequence at the m-th window position, where m is the starting index of the sliding window, ranging from m = 0, 1, 2, ... , The length of the sliding window. Let be the value of the nth sampling point in the kth mixed signal sequence. By traversing all feasible window positions of the mixed signal sequence, a series of arithmetic averages are obtained, forming a time series, which is the carrier signal. The corresponding envelope signal.
[0021] Each carrier frequency generates a corresponding envelope signal, and all obtained envelope signals are used as sub-signal components characterizing the electrical parameter characteristics of different frequency bands. The final output number of sub-signal components is the same as the number of frequency components contained in the multi-band test voltage. Each sub-signal component corresponds to a modulation envelope of a center frequency, reflecting the electrical parameter response characteristics of the test sheet in that frequency band.
[0022] Example 2: In practice, the impedance-frequency response surface of the insulating medium of the adhesive sheet is constructed based on the phase difference sequence of the sub-signal components. This process includes three steps: extraction of the phase difference sequence, construction of the discrete point set, and generation of a continuous surface by bicubic spline interpolation.
[0023] When extracting the phase difference sequence, the instantaneous phase of each sub-signal component is obtained. The instantaneous phase is obtained by performing a Hilbert transform on the sub-signal component. The analytic signal of each sub-signal component is calculated; the real part of the analytic signal is the sub-signal component itself, and the imaginary part is the result of the Hilbert transform. The argument of the analytic signal is the instantaneous phase sequence of the sub-signal component. In the applied multi-band test voltage, the phase of the frequency band corresponding to the sub-signal component is the known initial phase of the excitation source. For each sub-signal component, the difference between the instantaneous phase of the sub-signal component and the phase of the corresponding frequency band of the applied multi-band test voltage is calculated; this difference sequence constitutes the phase difference sequence. Each element in the phase difference sequence reflects the phase shift between the voltage and current of the tested adhesive plate at that frequency band at the corresponding sampling time.
[0024] After obtaining the phase difference sequence, the amplitude ratio of the sub-signal components also needs to be acquired. The amplitude ratio is defined as the ratio of the envelope amplitude of the sub-signal component to the amplitude of the corresponding frequency component in the applied multi-band test voltage. The envelope amplitude of the sub-signal component is extracted from the envelope signal, and the amplitude of the corresponding frequency component is a known test voltage setpoint. Using the phase difference sequence as the ordinate, the amplitude ratio of the sub-signal components as the abscissa, and the center frequency of the sub-signal components as the depth coordinate, a discrete point set in three-dimensional space is constructed. Each sub-signal component generates a discrete point at each sampling time. The coordinates of the discrete point are determined by the amplitude ratio, phase difference, and center frequency corresponding to the sub-signal component at that time. The discrete points generated by all sub-signal components at all sampling times constitute the discrete point set in three-dimensional space.
[0025] Bicubic spline interpolation is performed on a discrete point set to generate a continuous impedance-frequency response surface. Bicubic spline interpolation is based on a two-dimensional parameter domain formed by the amplitude ratio dimension and the center frequency dimension of the discrete point set, using the phase difference as the function value to construct a smooth surface function. The interpolation process employs cubic spline basis functions in both the amplitude ratio and center frequency directions. The amplitude ratio range and the center frequency range of the discrete point set are equally divided into several grid intervals, forming a regular rectangular grid. For each grid node, the phase difference surface value at that node is determined by solving the bicubic spline coefficient equations using the phase difference values of several discrete points in its neighborhood. The surface expression defined by bicubic spline interpolation within each grid cell is as follows: in, This represents the phase difference between the amplitude ratio coordinate u and the center frequency coordinate v on a continuous surface. This represents the magnitude ratio coordinate value of the bottom left node of the current grid cell; This represents the center frequency coordinates of the bottom left node of the current grid cell; These are bicubic spline coefficients, where the subscripts r and s represent the polynomial power indices in the amplitude ratio direction and the center frequency direction, respectively. The values of r and s are both in the range of 0, 1, 2, and 3. Each grid cell contains 16 coefficients. These coefficients are determined by constraints imposed on the phase difference at the four corner points of the grid cell, the first partial derivative of the phase difference with respect to the amplitude ratio, the first partial derivative of the phase difference with respect to the center frequency, and the mixed second partial derivative of the phase difference with respect to the amplitude ratio and the center frequency. The first and mixed second partial derivatives are obtained by numerical difference calculations on adjacent discrete points in the discrete point set. After traversing all grid cells and calculating the coefficients, the surface patches on all grid cells are combined to form a continuous impedance-frequency response surface.
[0026] See Figure 3 The horizontal axis of the graph represents the center frequency, using a logarithmic scale, with a frequency range from 0.5 Hz to 1000 Hz. The vertical axis represents the phase difference, in degrees. The graph shows the curves of phase difference as a function of center frequency for the insulating medium of the rubber sheet under different amplitude ratios: 0.2, 0.4, 0.6, 0.8, and 1.0, corresponding to five curves of different colors and marking styles. All curves exhibit a clear frequency-dependent characteristic.
[0027] In the low-frequency range (approximately 0.5 Hz to 10 Hz), regardless of the amplitude ratio, the phase difference remains at a low level, close to zero degrees, and the five curves overlap, indicating that different amplitude ratios have little impact on the phase difference. This suggests that the voltage and current phases of the adhesive sheet are nearly synchronized in this frequency range, and the insulation performance is stable.
[0028] As the frequency gradually increases from 10 Hz to approximately 100 Hz, the phase difference begins to rise significantly, with the curve showing a clear inflection point and a rapid growth trend. During this stage, the phase difference curves corresponding to different amplitude ratios separate; the larger the amplitude ratio, the higher the phase difference, reflecting that the polarization and loss characteristics of the insulating medium in the rubber sheet are enhanced at larger amplitude ratios, leading to a greater phase shift.
[0029] In the high-frequency range (100 Hz to 1000 Hz), the phase difference curve tends to flatten out and reach a certain stable value. The stable phase difference values corresponding to each amplitude ratio increase sequentially from low to high. The phase difference is largest when the amplitude ratio is 1.0, at about 85 degrees, and smallest when the amplitude ratio is 0.2, at about 65 degrees. This reflects that the dielectric loss of the rubber sheet tends to saturate in the high-frequency range and is significantly affected by the amplitude ratio.
[0030] Example 3: In practice, the process of calculating the equivalent insulation resistance and equivalent dielectric loss tangent of the rubber sheet at zero frequency based on the impedance-frequency response surface using extrapolation includes extracting discrete data points, calculating the equivalent insulation resistance using weighted linear regression analysis, and extracting the phase difference convergence value to calculate the equivalent dielectric loss tangent.
[0031] Multiple discrete data points are extracted from the lower asymptote region where the frequency approaches zero from the impedance-frequency response surface. Along the center frequency dimension of the impedance-frequency response surface, a range where the frequency value is closest to zero is selected. Within this range, the impedance amplitude at which the amplitude ratio dimension is zero is extracted from the impedance-frequency response surface at uniform frequency intervals, resulting in discrete data points. Each discrete data point contains a frequency value and an impedance amplitude; the frequency value of the q-th discrete data point is denoted as... The impedance amplitude is , where q = 0, 1, 2, ..., Q, and Q is the total number of extracted discrete data points.
[0032] Linear regression analysis is performed on multiple discrete data points using the weighted least squares method, where the weights are proportional to the reciprocal of the frequency values of the discrete data points. The weight of the q-th discrete data point is defined. This allows discrete data points with lower frequencies to have greater weight in regression analysis. The weighted frequency mean is calculated for the weighted discrete data points. and weighted impedance amplitude mean The calculation method is as follows , In the impedance-frequency coordinate plane, a weighted covariance matrix is constructed. The expression for the weighted covariance matrix is: Where C represents the weighted covariance matrix, which is a 2×2 real symmetric matrix; The weight of the q-th discrete data point; Let q be the frequency value of the q-th discrete data point; Let q be the impedance magnitude of the qth discrete data point; The weighted average frequency of all discrete data points; Let C be the weighted average impedance magnitude of all discrete data points; Q is the total number of discrete data points. Eigenvalue decomposition is performed on the weighted covariance matrix C, yielding two eigenvalues and two corresponding eigenvectors. The eigenvector corresponding to the larger eigenvalue indicates the principal direction of the discrete data points' distribution in the impedance-frequency coordinate plane. The slope of the linear regression equation is determined by the ratio of the second component to the first component of the eigenvector corresponding to the larger eigenvalue, and the intercept is determined by both the weighted average and the slope. The intercept is used as an extrapolation constant term in the linear regression equation.
[0033] The extrapolation constant term of the linear regression equation is set to the equivalent insulation resistance. The value of the equivalent insulation resistance is equal to the impedance amplitude of the linear regression equation at zero frequency.
[0034] The convergence value of the phase difference sequence as the frequency approaches zero is extracted from the impedance-frequency response surface. On the impedance-frequency response surface, the phase difference value at the center frequency with the lowest center frequency dimension is read, or the arithmetic mean of the phase difference values at several center frequency values with the smallest center frequency dimension is taken; the resulting value is the convergence value. The convergence value is set as the tangent of the equivalent dielectric loss angle.
[0035] See Figure 4 In the graph, the horizontal axis represents frequency in Hertz, ranging from 0 to 0.1 Hertz, and the vertical axis represents impedance amplitude in Ohms, ranging from approximately 400 to 650 Ohms. The scatter plot represents multiple discrete data points extracted from the impedance-frequency response surface. These data points lie within the lower asymptote region where the frequency approaches zero, with the amplitude ratio set to zero. The solid orange line represents the weighted linear regression fitting curve based on weighted least squares, with weights proportional to the reciprocal of the frequency to ensure that low-frequency data points have a greater impact on the fitting results. The dashed red line represents the constant impedance amplitude corresponding to the equivalent insulation resistance, with a value of 498.2 Ohms.
[0036] As shown in the figure, the discrete data points exhibit a relatively dispersed distribution trend within the impedance-frequency plane, but the impedance amplitude shows an overall linear upward trend with increasing frequency. The weighted linear regression curve effectively reflects the main trend of the discrete data points, and the intercept of the regression line at zero frequency represents the equivalent insulation resistance, corresponding to the red dashed line of 498.2 ohms. This regression value, calculated using extrapolation, reflects the static insulation resistance characteristics of the rubber sheet insulation medium.
[0037] Example 4: In practice, the electrical parameter response signals of the test sheet under test are acquired when multi-frequency test voltages are applied. These signals include current harmonic components and voltage harmonic components. A signal generator applies a set of AC test voltages with a logarithmic frequency distribution to the test sheet. Logarithmic distribution means that the ratio of the frequency values of adjacent frequency components is constant, and the frequency range covers 0.01 Hz to 1000 Hz. The signal generator outputs multiple sinusoidal voltage signals sequentially or simultaneously, with the amplitude of each sinusoidal voltage signal set to a fixed value of 10 volts.
[0038] The data acquisition card synchronously acquires the current signal flowing through the test plate and the voltage signal across the test plate. The sampling frequency of the data acquisition card is set to 10 times the highest frequency component of the applied AC test voltage. Synchronous acquisition means that the current signal acquisition channel and the voltage signal acquisition channel sample under the same clock trigger. The acquired current and voltage signals are both discrete-time sequences.
[0039] Discrete Fourier Transform (DFT) is performed on both the current and voltage signals to extract current and voltage harmonic components. The DFT converts the time-domain signal to the frequency domain. Complex values are extracted at each frequency point corresponding to the applied AC test voltage. The complex values of the current signal at these frequency points constitute the current harmonic components, and the complex values of the voltage signal at these frequency points constitute the voltage harmonic components. The current and voltage harmonic components together form the power parameter response signal.
[0040] In practical implementation, the preset insulation performance threshold table includes normal thresholds, caution thresholds, and alarm thresholds. These thresholds are preset judgment limits for equivalent insulation resistance and equivalent dielectric loss tangent, respectively. For equivalent insulation resistance, the normal threshold is set to 100 megohms, the caution threshold to 10 megohms, and the alarm threshold to 1 megohm. For equivalent dielectric loss tangent, the normal threshold is set to 0.02, the caution threshold to 0.05, and the alarm threshold to 0.10.
[0041] The insulation performance level of the adhesive sheet is determined based on the equivalent insulation resistance and the equivalent dielectric loss tangent, combined with a preset insulation performance threshold table. The equivalent insulation resistance is compared segmentally with the normal threshold, the warning threshold, and the alarm threshold. When the equivalent insulation resistance is greater than or equal to the normal threshold, the first-level insulation resistance determination number is 1; when the equivalent insulation resistance is less than the normal threshold but greater than or equal to the warning threshold, the first-level insulation resistance determination number is 2; when the equivalent insulation resistance is less than the warning threshold but greater than or equal to the alarm threshold, the first-level insulation resistance determination number is 3; and when the equivalent insulation resistance is less than the alarm threshold, the first-level insulation resistance determination number is 4. The equivalent dielectric loss tangent is then compared segmentally with the normal threshold, the warning threshold, and the alarm threshold. When the equivalent dielectric loss tangent is less than or equal to the normal threshold, the second-level dielectric loss determination number is 1; when the equivalent dielectric loss tangent is greater than the normal threshold and less than or equal to the attention threshold, the second-level dielectric loss determination number is 2; when the equivalent dielectric loss tangent is greater than the attention threshold and less than or equal to the alarm threshold, the second-level dielectric loss determination number is 3; when the equivalent dielectric loss tangent is greater than the alarm threshold, the second-level dielectric loss determination number is 4.
[0042] The first-level insulation resistance determination number and the second-level dielectric loss determination number are combined and coded. The combined code is formed by concatenating the values of the first-level insulation resistance determination number and the second-level dielectric loss determination number in sequential order to create a two-digit code. The first digit of the two-digit code is the first-level insulation resistance determination number, which can be 1, 2, 3, or 4; the second digit is the second-level dielectric loss determination number, which can also be 1, 2, 3, or 4. There are 16 possible values for the combined code, each corresponding to a different insulation performance level determination result.
[0043] When the combined code is 11, the insulation performance level is determined to be good. When the combined code is 12, 21, or 22, the insulation performance level is determined to be normal but requires attention. When any digit in the combined code is 3 and the other digit is not 4, the insulation performance level is determined to be degraded and requires maintenance. When any digit in the combined code is 4, the insulation performance level is determined to be severely deteriorated and requires immediate replacement.
[0044] See Figure 5 The horizontal axis of the graph represents time in seconds, ranging from 0 to 0.5 seconds; the vertical axis represents amplitude in volts (V) or amperes (A), ranging from approximately -75 to 110. The graph contains two curves: the blue curve represents the voltage signal, and the red curve represents the current signal. The legend clearly indicates the correspondence between the two signals.
[0045] The voltage signal curve exhibits high-amplitude fluctuations, starting at approximately 50V and then fluctuating significantly within a time interval of 0 to 0.5 seconds. The waveform contains obvious harmonic oscillation characteristics, and the overall fluctuation range is approximately -50V to 100V, reflecting the complex amplitude response of the multi-band test voltage applied to both ends of the test plate. The voltage signal waveform exhibits periodic superposition characteristics, consistent with the logarithmic distribution of the frequency of the multi-band AC test voltage applied by the signal generator described in Example 4.
[0046] The amplitude of the current signal curve is significantly low, concentrated between -1A and 1A, and the waveform is relatively stable. The slight fluctuations reflect the harmonic response components of the current flowing through the tested rubber sheet. The amplitude and waveform characteristics of the current signal contrast sharply with the voltage signal, indicating that the harmonic response of the current in the rubber sheet is relatively weak, which is consistent with the characteristics of the current signal data synchronously acquired in Example 4.
[0047] Example 5: In practical implementation, a rubber sheet insulation performance testing system based on electrical parameter characteristics includes a signal generator, a data acquisition card, a processor, and a memory. The output terminal of the signal generator is electrically connected to both ends of the rubber sheet to be tested. The analog input channel of the data acquisition card is electrically connected to the current detection terminal and voltage detection terminal of the rubber sheet to be tested, respectively. The digital output interface of the data acquisition card is electrically connected to the data input interface of the processor. The processor and the memory are electrically connected via a bus. The memory stores a computer program. When the processor calls and executes the computer program in the memory, the insulation performance testing steps are implemented.
[0048] The processor controls the signal generator to apply a set of AC test voltages with a logarithmic frequency distribution to the substrate under test. This set of AC test voltages contains 20 sinusoidal voltage components, with the lowest frequency component at 0.01 Hz and the highest frequency component at 1000 Hz. The frequency ratio of adjacent frequency components is 1.5. The amplitude of each sinusoidal voltage component is 10 volts. The signal generator outputs all frequency components simultaneously in a superposition manner to form a multi-band test voltage.
[0049] The processor controls the data acquisition card to synchronously acquire the current signal flowing through the test plate and the voltage signal across the test plate. The sampling frequency of the data acquisition card is set to 10 kHz, and the sampling duration covers 10 complete cycles of the lowest frequency component in the multi-band test voltage. The data acquisition card converts the acquired current and voltage signals into digital quantities and transmits them to the processor.
[0050] The processor performs Discrete Fourier Transform (DFT) on the current and voltage signals respectively, extracting the current harmonic components and voltage harmonic components. The DFT has 65,536 points and a frequency resolution of approximately 0.15 Hz. The processor locates the frequency points corresponding to the frequencies of the applied 20 sinusoidal voltage components in the frequency domain, reads the complex values of the current signal at each corresponding frequency point to form the current harmonic components, and reads the complex values of the voltage signal at each corresponding frequency point to form the voltage harmonic components. The current and voltage harmonic components together constitute the power parameter response signal.
[0051] The processor performs an adaptive modulation decomposition operation based on multi-frequency carrier signals on the power parameter response signal, obtaining multiple sub-signal components characterizing the power parameters in different frequency bands. The processor constructs a set of carrier signals with different center frequencies, where the center frequency of each carrier signal corresponds one-to-one with the frequency of each sinusoidal voltage component in the multi-band test voltage. The number of center frequencies for the carrier signals is 20. Each carrier signal is a cosine signal, with the discrete expression as follows: .in, This represents the center frequency of the k-th carrier signal. This represents the m-th sampling time. The power parameter response signal is a real-value sequence. Where n is the sampling point number. The processor performs point-by-point multiplication on each carrier signal and the power parameter response signal. For the k-th carrier signal, a modulated mixed signal sequence is generated. The processor performs sliding window integral filtering on each mixed signal sequence to extract the envelope signal corresponding to each carrier frequency. The sliding window length is set to half the carrier signal period, expressed as the number of sampling points. For the k-th carrier signal, the sliding window length is... The calculation formula is: ,in, The sampling frequency of the data acquisition card. The center frequency of the carrier. The processor slides the window along the mixed signal sequence. Moving point by point, at each window position, the arithmetic mean of all data points within the window is calculated, and so on. ,in, This represents the arithmetic mean of the k-th mixed signal sequence at the m-th window position, where m is the starting index of the window. The sequence formed by all arithmetic means is used as the envelope signal corresponding to the k-th carrier signal. The 20 envelope signals are used as 20 sub-signal components.
[0052] The processor constructs an impedance-frequency response surface for the insulating medium of the adhesive sheet based on the phase difference sequence of the sub-signal components. The processor performs a Hilbert transform on each sub-signal component to obtain its analytic signal, and extracts the instantaneous phase sequence from the analytic signal. For each sub-signal component, the difference between the instantaneous phase and the initial phase of the corresponding frequency component in the applied multi-band test voltage is calculated to obtain the phase difference sequence. The processor obtains the amplitude ratio of each sub-signal component, which is the ratio of the envelope amplitude of the sub-signal component to the amplitude of the corresponding frequency test voltage. The processor uses the phase difference sequence as the ordinate, the amplitude ratio of the sub-signal components as the abscissa, and the center frequency of the sub-signal components as the depth coordinate to construct a discrete point set in three-dimensional space. Each sampling moment corresponds to a discrete point, and the discrete points generated by all sub-signal components at all sampling moments constitute the discrete point set. The processor performs bicubic spline interpolation on the discrete point set to generate a continuous impedance-frequency response surface. The interpolation grid is divided into 100 nodes in the amplitude ratio direction and 20 nodes in the center frequency direction. The phase difference at each grid node is solved using the bicubic spline coefficient equation system to obtain the surface.
[0053] The processor calculates the equivalent insulation resistance and equivalent dielectric loss tangent of the adhesive sheet at zero frequency using extrapolation based on the impedance-frequency response surface. The processor extracts discrete data points from the lower asymptote region where the frequency approaches zero from the impedance-frequency response surface. Along the center frequency dimension, points on the surface corresponding to the five lowest center frequency values are selected, and a frequency value is assigned to each point. and an impedance magnitude q=1, 2, 3, 4, 5. The processor performs weighted least squares linear regression analysis on the 5 discrete data points, with weights... The processor calculates the weighted frequency average. and weighted impedance mean After constructing the weighted covariance matrix, eigenvalue decomposition is performed. The slope of the linear regression equation is determined by the eigenvector corresponding to the largest eigenvalue, and the intercept is obtained by combining the weighted mean points. The intercept of the linear regression equation is the impedance amplitude at zero frequency, and the processor sets this intercept as the equivalent insulation resistance. The processor reads the phase difference value at the node with the lowest center frequency from the impedance-frequency response surface, and uses this phase difference value as the convergence value of the phase difference sequence when the frequency approaches zero, setting it as the equivalent dielectric loss tangent.
[0054] The processor generates the insulation performance level determination result of the adhesive sheet based on the equivalent insulation resistance and equivalent dielectric loss tangent, combined with a preset insulation performance threshold table. The preset insulation performance threshold table is stored in memory and includes the normal insulation resistance threshold, the insulation resistance warning threshold, the insulation resistance alarm threshold, the normal dielectric loss threshold, the dielectric loss warning threshold, and the dielectric loss alarm threshold. The normal insulation resistance threshold is set to 100 megohms, the insulation resistance warning threshold is set to 10 megohms, and the insulation resistance alarm threshold is set to 1 megohm. The normal dielectric loss threshold is set to 0.02, the dielectric loss warning threshold is set to 0.05, and the dielectric loss alarm threshold is set to 0.10. The processor compares the equivalent insulation resistance with the normal insulation resistance threshold, the insulation resistance attention threshold, and the insulation resistance alarm threshold in segments: when the equivalent insulation resistance is greater than or equal to the normal insulation resistance threshold, the first-level insulation resistance value judgment number 1 is obtained; when the equivalent insulation resistance is less than the normal insulation resistance threshold but greater than or equal to the insulation resistance attention threshold, the first-level insulation resistance value judgment number 2 is obtained; when the equivalent insulation resistance is less than the insulation resistance attention threshold but greater than or equal to the insulation resistance alarm threshold, the first-level insulation resistance value judgment number 3 is obtained; when the equivalent insulation resistance is less than the insulation resistance alarm threshold, the first-level insulation resistance value judgment number 4 is obtained. The processor compares the equivalent dielectric loss tangent with the normal dielectric loss threshold, the dielectric loss warning threshold, and the dielectric loss alarm threshold in segments: when the equivalent dielectric loss tangent is less than or equal to the normal dielectric loss threshold, a second-level dielectric loss determination number 1 is obtained; when the equivalent dielectric loss tangent is greater than the normal dielectric loss threshold and less than or equal to the dielectric loss warning threshold, a second-level dielectric loss determination number 2 is obtained; when the equivalent dielectric loss tangent is greater than the dielectric loss warning threshold and less than or equal to the dielectric loss alarm threshold, a second-level dielectric loss determination number 3 is obtained; and when the equivalent dielectric loss tangent is greater than the dielectric loss alarm threshold, a second-level dielectric loss determination number 4 is obtained. The processor concatenates the first-level insulation resistance determination number and the second-level dielectric loss determination number in sequence to form a combined code. The correspondence between the combined code and the insulation performance level determination result is as follows: combined code 11 corresponds to good insulation performance; combined codes 12, 21, and 22 correspond to normal insulation performance requiring attention; combined codes containing the digit 3 but not the digit 4 correspond to decreased insulation performance requiring repair; combined codes containing the digit 4 correspond to severely deteriorated insulation performance requiring immediate replacement. The processor outputs the final insulation performance level determination result to the display device or stores it in the memory.
[0055] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.
Claims
1. A method for testing the insulation performance of rubber sheets based on electrical parameter characteristics, characterized in that, Includes the following steps: The electrical parameter response signal of the test sheet is obtained under the application of multi-frequency test voltage, and the electrical parameter response signal includes current harmonic components and voltage harmonic components; An adaptive modulation decomposition operation based on a multi-frequency carrier signal is performed on the power parameter response signal to obtain multiple sub-signal components that characterize the power parameter features in different frequency bands. The impedance-frequency response surface of the insulating medium of the adhesive sheet is constructed based on the phase difference sequence of the sub-signal components. Based on the impedance-frequency response surface, the equivalent insulation resistance and equivalent dielectric loss tangent of the adhesive sheet at zero frequency are calculated by extrapolation. The insulation performance level of the adhesive sheet is determined by combining the equivalent insulation resistance and the equivalent dielectric loss tangent with a preset insulation performance threshold table.
2. The method for testing the insulation performance of adhesive sheets based on electrical parameter characteristics according to claim 1, characterized in that, The process of performing an adaptive modulation decomposition operation based on a multi-frequency carrier signal on the power parameter response signal yields multiple sub-signal components characterizing the power parameter features at different frequency bands, specifically: Construct a set of carrier signals with different center frequencies, wherein the frequency range of the carrier signals covers the frequency range of the multi-band test voltage; Each carrier signal is multiplied point-by-point with the power parameter response signal to obtain a modulated mixed signal sequence. Perform sliding window integral filtering on each of the mixed signal sequences to extract the envelope signal corresponding to each carrier frequency; The envelope signal is used as the sub-signal component.
3. The method for testing the insulation performance of adhesive sheets based on electrical parameter characteristics according to claim 1, characterized in that, The construction of the impedance-frequency response surface of the adhesive sheet insulation medium based on the phase difference sequence of the sub-signal components is specifically as follows: Extract the instantaneous phase of each of the sub-signal components, calculate the difference between the sub-signal component and the phase of the corresponding frequency band of the applied multi-band test voltage, and obtain the phase difference sequence; Using the phase difference sequence as the vertical axis, the amplitude ratio of the sub-signal components as the horizontal axis, and the center frequency of the sub-signal components as the depth coordinate, a discrete point set in three-dimensional space is constructed. Bicubic spline interpolation is performed on the discrete point set to generate the continuous impedance-frequency response surface.
4. The method for testing the insulation performance of rubber sheet based on electrical parameter characteristics according to claim 1, characterized in that, The equivalent insulation resistance and equivalent dielectric loss tangent of the adhesive sheet at zero frequency are calculated by extrapolation based on the impedance-frequency response surface, specifically as follows: Multiple discrete data points in the lower asymptote region with frequencies approaching zero are extracted from the impedance-frequency response surface; Linear regression analysis was performed on the multiple discrete data points to obtain the linear regression equation; The extrapolation constant term of the linear regression equation is set to the equivalent insulation resistance; The convergence value of the phase difference sequence when the frequency approaches zero is extracted from the impedance-frequency response surface, and the convergence value is set as the equivalent dielectric loss tangent.
5. The method for testing the insulation performance of adhesive sheet based on electrical parameter characteristics according to claim 1, characterized in that, The preset insulation performance threshold table includes normal threshold, attention threshold and alarm threshold; The process of generating the insulation performance level determination result of the adhesive board based on the equivalent insulation resistance and the equivalent dielectric loss tangent, combined with a preset insulation performance threshold table, specifically involves: The equivalent insulation resistance is compared with the normal threshold, the attention threshold and the alarm threshold in segments to obtain the first-level insulation resistance value determination number. The equivalent dielectric loss tangent is compared with the normal threshold, the attention threshold and the alarm threshold in segments to obtain the second-level dielectric loss determination number. The first-level insulation resistance determination number and the second-level dielectric loss determination number are combined and coded, and the combined code corresponds to the insulation performance level determination result.
6. The method for testing the insulation performance of adhesive sheet based on electrical parameter characteristics according to claim 4, characterized in that, The linear regression analysis performed on the multiple discrete data points yields the linear regression equation, specifically as follows: Calculate the covariance matrix of the plurality of discrete data points in the impedance-frequency coordinate plane; The slope and intercept of the linear regression equation are determined based on the eigenvalue decomposition results of the covariance matrix. The intercept is used as an extrapolation constant term of the linear regression equation.
7. The method for testing the insulation performance of adhesive sheet based on electrical parameter characteristics according to claim 1, characterized in that, The acquisition of the electrical parameter response signal of the adhesive sheet under test under the applied multi-frequency test voltage specifically involves: A set of AC test voltages with a logarithmic frequency distribution is applied to the test sheet using a signal generator; The current signal flowing through the test plate and the voltage signal across the test plate are simultaneously acquired by the data acquisition card. Perform Discrete Fourier Transform on the current signal and the voltage signal to extract the current harmonic components and the voltage harmonic components.
8. The method for testing the insulation performance of adhesive sheet based on electrical parameter characteristics according to claim 2, characterized in that, The step of performing sliding window integral filtering on each of the mixed signal sequences to extract the envelope signal corresponding to each carrier frequency is specifically as follows: The length of the sliding window is set to half the period of the carrier signal; The sliding window is moved point by point along the mixed signal sequence, and the arithmetic mean of all data points in the window is calculated at each window position; The time series formed by the arithmetic mean is used as the envelope signal.
9. The method for testing the insulation performance of rubber sheet based on electrical parameter characteristics according to claim 4, characterized in that, The linear regression analysis employs the weighted least squares method, where the weights are proportional to the reciprocal of the frequency values of the discrete data points.
10. A system for testing the insulation performance of rubber sheets based on electrical parameter characteristics, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for detecting the insulation performance of a rubber sheet based on electrical parameter characteristics as described in any one of claims 1 to 9.