CN113702754A - Distribution cable defect positioning algorithm adopting windowed Fourier transform - Google Patents
Distribution cable defect positioning algorithm adopting windowed Fourier transform Download PDFInfo
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Abstract
The invention provides a distribution cable defect positioning algorithm adopting windowed Fourier transform, which comprises the following steps: step 1, testing cable data; and 2, inputting an impedance spectrum to the head end of the cable to position the local defect/intermediate joint of the cable. The invention has the beneficial effects that: and applying windowed Fourier transform, analyzing and comparing different window function performances, and selecting an optimal window function to improve the identification sensitivity and the positioning precision of the cable local defect/intermediate joint.
Description
Technical Field
The invention relates to the field of locating distribution cable local defects/intermediate joint defects, in particular to a distribution cable defect locating algorithm adopting windowed Fourier transform.
Background
In order to ensure the safe operation of the distribution cable and improve the power supply reliability of the distribution cable, the distribution cable needs to be periodically detected, and a corresponding field processing scheme is formulated according to the insulation state of the detected cable. For diagnosing the cable moisture severity, the commonly used test diagnosis method includes: insulation resistance test method and dielectric loss factor test method. Although the three methods can diagnose the local cable moisture defect, the three methods all belong to an overall insulation evaluation method, and only can diagnose the overall insulation performance of the cable, and the local cable moisture defect cannot be accurately positioned.
However, in the actual field test, if the position of the local damp defect of the cable can be quickly and accurately determined, the field maintenance efficiency is greatly improved, and the maintenance cost is saved. The cable positioning detection methods commonly used in actual sites include a Partial Discharge (PD) method, a Time Domain Reflectometry (TDR) method, and a frequency domain reflectometry.
Although a great deal of related research is carried out on the cable local defect positioning technology in the prior art, and the traditional cable positioning technology is improved based on the FDR method, so as to promote the further development of the cable local defect positioning technology, at present, research is not carried out at home and abroad on the aspects of positioning and diagnosing the damp defects of the distribution cable body and the intermediate joint. Aiming at the aspect of positioning and diagnosing the damp defect of the distribution cable line, the key problems to be solved are as follows:
at present, based on the FDR method, Inverse Fast Fourier Transform (IFFT) and Integral Transform (IT) algorithms are used to locate the local damp defect, but these two algorithms do not consider the problems of spectrum leakage and fence effect when Discrete Fourier Transform (DFT) analysis is used in the data processing process, which will cause the great reduction of defect identification sensitivity and location accuracy when locating the local defect of the cable. Therefore, how to effectively suppress the spectrum leakage and the barrier effect and improve the accuracy of spectrum analysis is a key problem for improving the local defect positioning algorithm of the distribution cable.
Disclosure of Invention
The invention overcomes the defects in the prior art, provides a positioning algorithm for the defects of a distribution cable by adopting windowed Fourier transform, and aims to realize the positioning of the local defects and the intermediate joints of a cable body by utilizing the input impedance spectrum of the head end of the cable.
The purpose of the invention is realized by the following technical scheme.
The distribution cable defect positioning algorithm adopting windowed Fourier transform comprises the following steps:
and 2, inputting an impedance spectrum to the head end of the cable to position the local defect/intermediate joint of the cable.
Preferably, step 2, the specific method for locating the cable local defect/intermediate joint by the cable head end input impedance spectrum includes the following steps:
s1, determining the position of the tail end l of the cable by finding the position of the frequency maximum value under the fundamental frequency, thereby realizing the positioning of the two ends of the head and the tail end of the cable and the local defect;
and S2, the accuracy of the frequency spectrum analysis is improved by improving the upper limit of the test frequency/adopting a windowed Fourier transform analysis algorithm to inhibit the frequency spectrum leakage and the fence effect.
Preferably, in the foregoing scheme, the formula for calculating the maximum frequency value in step S1 is:
f|Z|max1at maximum frequency, v is the wave velocity and l is the length of the cable.
Preferably, in the step S2, the windowed fourier transform analysis algorithm is one or two of a Hamming window, a Blackman window, a four-term third-order Nuttall window, and a second-order Nuttall self-convolution window.
Preferably, in the step S2, four third-order Nuttall windows are selected for the cable positioning spectrogram with the body affected with moisture defect, and are subjected to windowing processing.
Preferably, in the step S2, a second-order Nuttall self-convolution window is selected for the cable positioning spectrogram with the damp defect of the intermediate connector, and the windowing is performed on the cable positioning spectrogram.
The invention has the beneficial effects that:
if there is a local defect/intermediate joint (i.e. impedance discontinuity) in the cable line, the transmission characteristics in the cable line will change, and the resonance law of the input impedance spectrum at the head end of the cable changes to be characterized. Therefore, the cable head end input impedance spectrum can be utilized to locate the cable partial defect/intermediate joint to realize the diagnosis of the cable partial defect/intermediate joint.
The positioning of the cable local defect/intermediate joint can be realized by utilizing the amplitude spectrum of the input impedance of the head end of the cable and DFT analysis, and meanwhile, in order to improve the accuracy of the frequency spectrum analysis, the WFT algorithm can be utilized to inhibit the frequency spectrum leakage and the fence effect brought by the DFT algorithm, so that the identification sensitivity and the positioning accuracy of the cable local defect/intermediate joint are improved.
Compared with the traditional classical window functions (Hamming window and Blackman window), the window function performance of the four-term third-order Nuttall window and the second-order Nuttall self-convolution window can better inhibit the spectrum leakage and the barrier effect due to the traditional classical window functions, and the accuracy of spectrum analysis is improved.
In the aspect of improving the identification sensitivity of the body affected moisture defect and the middle joint affected moisture defect, four third-order Nuttall windows are selected to process the body affected moisture defect cable positioning spectrogram, and a second-order Nuttall self-convolution window is selected to process the middle joint affected moisture defect cable positioning spectrogram.
Drawings
FIG. 1 is a cable distribution parameter equivalent model;
FIG. 2 is a signal transmission schematic of a live cable;
FIG. 3 is a signal transmission schematic of a defective cable;
FIG. 4 is a simulated cable headend input impedance magnitude spectrum;
FIG. 5 is a simulated 500m cable positioning spectrogram;
FIG. 6-1 is a time-frequency domain characteristic curve of (a) a Hamming window, a Blackman window, a four-term third-order Nuttall window, and a second-order Nuttall self-convolution window of a time-domain waveform;
FIG. 6-2 is (b) a time-frequency domain characteristic curve of a Hamming window, a Blackman window, a four-term third-order Nuttall window, and a second-order Nuttall self-convolution window of a time-domain waveform;
fig. 7 is a view showing the positioning effect of the intermediate joint cable after the windowing process.
Detailed Description
The technical solution of the present invention is further illustrated by the following specific examples.
1.1 Cable Transmission characteristics and input impedance Spectroscopy
The transmission characteristics of a signal (or energy) in a cable can be described in terms of transmission line theory. Under high frequency conditions, as the frequency increases, the radiation loss, conductor loss, and dielectric loss of the circuit element increase, and the parameters in the circuit element change accordingly, so that the circuit cannot be regarded as a lumped parameter circuit. When the length of the cable is far longer than the wavelength of the signal, the cable can be equivalent to a distributed parameter circuit, and the transmission characteristic of the line is mainly related to the electrical performance of the cable, namely the input impedance and the reflection coefficient in the cable line are used as characteristics. The equivalent model of the distribution parameters of the cable can be represented by FIG. 1, wherein R0、 L0、G0、C0Respectively the resistance, inductance, conductance and capacitance of the cable per unit length.
The equivalent model is composed of a series circuit element and a parallel circuit element, wherein the series element is a resistor R0Δ x and inductance L0Δ x, the parallel element being conductance G0Δ x and capacitance C0Δx。
As the frequency f increases, the distributed resistance of the cable increases and the distributed inductance decreases due to skin and proximity effects. Resistance R of cable per unit length0And an inductance L0Can be separatedThe other approximation is represented as:
in the formula: ω is angular frequency, ω ═ 2 π f; r isc、rsThe radius of the cable core and the radius of the shielding layer are included; rhoc、ρsThe resistivity of the cable core and the shielding layer; mu.s0Is a vacuum magnetic permeability.
Capacitance per unit length of cable C0And conductance G0Can be respectively expressed as:
in the formula: epsilon and sigma are respectively the dielectric constant and the conductivity of the dielectric medium of the cable.
For a cable with total length l, the voltage u (x) and current i (x) at any position x from the head end of the cable are:
U(x)＝Ui2eγ(l-x)+Ur2e-γ(l-x) (2-5)
in the formula: u shapei2、Ur2An incident voltage wave and a reflected voltage wave at the end of the cable (i.e., the load side); gamma is the propagation constant in the cable run; z0Is the characteristic impedance of the cable.
The characteristic impedance and the propagation constant of the cable are characteristic parameters of signal transmission in the cable line and are determined by distribution parameters in the cable line.
Characteristic impedance Z0Is composed of
Under high frequency conditions, there is ω L0>>R0，ωC0>>G0When the resistance R in the formula (2-7) is present0And conductance G0Negligible, the formula (2-7) can be abbreviated
Propagation constant gamma of
In the formula: v is the wave velocity of the electromagnetic waves in the cable; alpha is a decay constant; beta is a phase constant. The attenuation constant and the phase constant respectively represent amplitude attenuation characteristics and phase lag characteristics of signals in the cable transmission process.
Combining the equations (2-5) and (2-6), it can be derived that the input impedance at any x from the head end of the cable is
Wherein the reflection coefficient of the cable end is gammaLIs composed of
In the formula: zLIs the load impedance at the end of the cable (i.e., when x ═ l). If the cable end is open, there is ZLInfinity, whenL＝1。
At the cable head (i.e. when x is 0), the cable head input impedance z (f) is
For a cable of a given length, the transmission characteristics of the cable line are determined by the distribution parameters of the cable, which are in turn frequency-dependent, so that the cable head-end input impedance z (f) is a frequency-dependent function and has a frequency dependence. Characteristic impedance Z of cable under high frequency condition0The load impedance Z of the end of the cableLThe influence of frequency change is small, so that the change of the input impedance Z (f) at the head end of the cable is mainly influenced by the propagation constant gamma, if the distribution parameter at a certain local position in the cable line is slightly changed, the transmission characteristic in the cable line is also changed, and further the input impedance Z (f) at the head end of the cable is changed, so that the transmission characteristic of signals in the cable line can be described by using a cable input impedance frequency spectrum, and the insulation state of the cable can be diagnosed.
1.2 Cable input impedance characterization
According to the above section, the cable head end input impedance can characterize the electrical information state of the cable, and its frequency spectrum (i.e., the cable head end input impedance spectrum) can very sensitively reflect the signal transmission characteristics of the cable. When the cable has a local defect, the propagation constant at the local position of the cable is changed, so that the signal transmission characteristic of the cable is changed, and the characteristic is changed to be represented in a curve resonance rule in an input impedance spectrum. Therefore, the signal transmission characteristics of the intact cable and the defective cable need to be analyzed in detail to obtain the difference between the signal transmission characteristics of the intact cable and the defective cable, on the basis, a mathematical model formula of the input impedance of the head ends of the intact cable and the defective cable is deduced based on the input impedance spectrum, and the local defect of the cable is positioned and diagnosed according to the characteristic difference of the input impedance of the intact cable and the defective cable.
1.2.1 Signal Transmission characteristics and head-end input impedance Spectrum of intact Cable
For a perfect cable with the length of l and an open circuit at the tail end of the cable, a cable line does not contain a defect point (namely an impedance discontinuous point), one end of the cable is selected as a head end, and a one-dimensional coordinate system is established by taking the head end (x ═ 0) of the cable as an origin to point to the tail end (x ═ l) of the cable. The incident wave is injected from the head end of the cable, and the incident wave is totally reflected only when propagating to the tail end of the cable, and the perfect cable model and the signal transmission schematic diagram are shown in fig. 2. The characteristic impedance and propagation constant of a perfect cable are respectively Z0hAnd gammah。
According to equation (2-12), the head end (x ═ 0) input impedance Z of the intact cableh(f) Is composed of
Wherein Z is0h、γhCharacteristic impedance, propagation constant, f, of the intact cable, respectivelyLhThe reflection coefficient at the end of a perfect cable (x ═ l) is measured.
2.2.1 Signal Transmission characteristics and head-end input impedance Spectrum for defective Cable
If there is a defect (such as damage, insulation degradation, moisture, etc.) at the local position of the cable or an intermediate joint is made, the distribution parameters at the local position of the cable are changed, and an impedance discontinuity is formed, so that the transmission characteristics of signals in the cable are changed. In order to compare the signal transmission difference between a perfect cable and a defective cable, the section analyzes the influence of the existence of the local defect on the cable signal transmission characteristic according to a defective cable model containing the local defect, and realizes the positioning of the local defect according to the difference between the signal transmission characteristic and the signal transmission characteristic of the perfect cable.
For a defective cable with the length of l and an open circuit at the tail end of the cable, a cable line contains a local defect with a certain length (namely an impedance discontinuous point), one end of the cable is selected as a head end, and the head end (x ═ of the impedance discontinuous point) of the cable is used as the head end0) Establishing a one-dimensional coordinate system for the origin point, pointing to the cable end (x ═ l), at a distance l from the cable head enda、lbA (l)a<lb) Has a length of (l)b-la) Local defects (i.e., impedance discontinuities). The incident wave is injected from the head end of the cable, and the incident wave is propagated to the head end of the local defect (x ═ l)a) Local defect end (x ═ l)b) When the cable is used, once refraction and reflection respectively occur, the signal can be subjected to dispersion and attenuation after passing through a local defect section, and then the signal is continuously transmitted to the tail end of the cable to be subjected to total reflection. A model of a defective cable with localized defects and a signal transmission scheme are shown in fig. 3. The characteristic impedance and propagation constant of a good cable section are respectively Z0hAnd gammahThe characteristic impedance and propagation constant of the defective cable section are respectively Z0dAnd gammad。
According to the formula (2-12), the defective cable having the local defect has a head end (x ═ 0) input impedance Zd(f) Is composed of
Wherein Z is0d、γdCharacteristic impedance and propagation constant of the defective cable, respectively. Zla(f)、Zlb(f)、Гla、ГlbRespectively a defective cable la、lbThe input impedance and the reflection coefficient.
According to the signal transmission characteristic analysis and the mathematical model formula derivation of the head end input impedance aiming at the intact cable and the defective cable, the method can find that the signal transmission characteristic of the defective cable at the local position is changed due to the existence of the local defect in the signal transmission compared with the intact cable, and the characteristics of refraction and reflection and dispersion attenuation of incident waves at the local defective section are taken as the characteristics; compared with the intact cable, on the mathematical model formula of the head end input impedance, the defective cable has local defects, so that the head end input impedance Z of the defective cable is ensuredd(f) Z different from intact cableh(f) In that respect Therefore, the difference of the intact cable and the defective cable in signal transmission can be utilized, modeling simulation analysis is carried out on the intact cable and the defective cable according to the mathematical model formulas of the head end input impedance of the intact cable and the head end input impedance of the defective cable, and the positioning of the local defect/intermediate joint of the cable is realized by using a corresponding cable defect positioning algorithm.
1.3 Cable Defect location principle and location Algorithm improvement
1.3.1 Cable Defect location principle analysis
In order to realize the positioning of the local defects of the cable, a Discrete Fourier Transform (DFT) is used to perform corresponding processing on the input impedance spectrum at the head end of the cable, so as to realize the positioning of the local defects of the cable, and the positioning results of the local defects at the head end and the tail end of the cable are presented in the form of a cable positioning spectrogram. Because the input impedance spectrum at the head end of the cable contains a plurality of characteristic quantities capable of representing the characteristics of the cable line, only the amplitude of the input impedance is selected for analysis and discussion.
Combining formula (2-9), simplifying formula (2-12) to obtain the cable head end input impedance Z (f)
Expanding the formula (2-20) by using an Euler formula to obtain
The amplitude value | Z (f) | of the input impedance at the head end of the cable is obtained
When cos (-2 β l) ═ 1, the amplitude of the input impedance at the head end of the cable takes the maximum value | Z (f) andmaxat this time
-2 β l ═ 2k pi, k ═ 1,2, 3. (k is a positive integer) (2-24)
Combining formula (2-9), the formula (2-24) can be rewritten as
According to the derivation result, the maximum frequency f corresponding to the maximum amplitude point of the input impedance of the head end of the cable can be obtained|Z|maxIs composed of
Since the cable head input impedance z (f) is a function of frequency, it can also be considered as a function of f as a time variable. At fundamental frequency, k is 1, and the maximum frequency f corresponding to the maximum amplitude point of the input impedance at the head end of the cable at this time|Z|max1Is composed of
At high frequencies, the wave velocity v in the cable approaches a constant, and the length l of the cable is fixed, then fZmax1Also approaching a constant. Thus, the frequency maximum f at the fundamental frequency can be foundZmax1The position of the cable tail end is determined, so that the two ends of the cable head end and the two ends of the cable tail end and the local defect position are positioned.
Using a 500m long 10kV XLPE cable as a modeling object, according to the head-end input impedance Z of the intact cable and the defective cable mentioned in section 2.2 of the texth(f)、Zd(f) The mathematical formula models of (1) respectively carry out modeling and positioning analysis on the intact cable and the defective cable. Fig. 4 shows the input impedance amplitude spectra at the head end of a cable for a 500m intact cable, a 500m cable with an intermediate joint at 250m, respectively. As can be seen from the input impedance amplitude spectrum at the head end of the cable in fig. 4, there is a periodic resonance law in the input impedance amplitude spectrum, and there is a maximum value in the input impedance amplitude in each resonance period, and these resonance points (the maximum value points of the input impedance) gradually start to attenuate with the increase of frequency, and the attenuation is very severe especially at high frequency. In addition, compared with a perfect cable, the cable has an intermediate joint, so that impedance discontinuity points appear on the cable, the transmission characteristic in a cable line is changed, and the resonance rule of the input impedance amplitude spectrum at the head end of the cable is changed into representation. Thus, this feature can be used to locate and diagnose discontinuities in cable impedance (intermediate junctions/local defects) in comparison to a perfect cable.
The positioning method described above is used to process the input impedance amplitude spectrum at the head end of the cable in fig. 4, and the obtained cable positioning result is shown in fig. 5.
As can be seen from the simulation positioning result of fig. 5, the positioning of the first end and the last end of the cable can be realized by using the positioning algorithm provided herein, that is, the overall length of the cable is determined, and after the position of the tail end of the cable is determined, the position of the middle joint of the cable can also be determined. However, after the DFT algorithm is used to process the input impedance amplitude spectrum, the period of data is truncated, which may cause spectrum leakage and fence effect, and bring errors to the accuracy of spectrum analysis, thus making the identification effect of the cable intermediate connector less than ideal. However, in actual field, most of the cable lines contain a plurality of intermediate joints, and the positioning effect is reduced due to the increase of the number of the joints. Although the identification sensitivity and the test accuracy of the cable intermediate joint/local defect can be improved by the method of increasing the upper limit of the test frequency, the method cannot fundamentally solve the fundamental problem that the positioning identification sensitivity is reduced due to the DFT algorithm.
1.3.2 windowed Fourier transform and windowed function Performance analysis
In order to effectively suppress the spectrum leakage and the fence effect existing when DFT is adopted to process the input impedance spectrum of the cable head end, the invention provides a method for improving the positioning of local defects/intermediate joints of a distribution cable. A Windowed Fourier Transform (WFT) analysis algorithm is adopted to inhibit the spectrum leakage and the fence effect caused by DFT, and improve the accuracy of spectrum analysis to a certain extent.
The performance of the window function can directly affect the effect of suppressing the frequency spectrum leakage and the barrier effect. Therefore, 4 window functions (Hamming window, Blackman window, four-term third-order Nuttall window and second-order Nuttall self-convolution window) are selected as analysis discussion objects, the performances of the 4 window functions are compared and analyzed, the optimal window function is selected according to the identification and positioning effects of the optimal window function on the intermediate joint/local defect, and the identification sensitivity and the positioning accuracy on the intermediate joint/local defect of the cable are improved.
1. Time-frequency domain characteristics and performance analysis of window functions
(1) Four-term third-order Nuttall window
The Nuttall window is a cosine combination window with a time domain expression of
In the formula: m, N are the number of terms of the window function and the window length, respectively; bmIs a cosine combination term coefficient; n is 0, 1, …, N-1.
Four third-order Nuttall windows are selected as discussion objects, and the coefficients of the other chord combination terms of the window function are respectively set as b0＝0.338 946、b1＝0.481 973、b2＝0.161 054、b3＝0.018 027。
(2) Nuttall self-convolution window function
The p-order Nuttall self-convolution window is formed by carrying out convolution operation on p same Nuttall window functions, namely
In the formula: w is aNUTTALL-pThe window length of (N ') is N' ═ pN. When the window length N is fixed, the larger the convolution order p is, the larger the window length of the Nuttall self-convolution window is, and the wider the main lobe of the Nuttall self-convolution window is.
(3) Discussion of Window function Performance
The four-term third-order Nuttall window and the second-order Nuttall self-convolution window have better spectrum leakage suppression effect. Therefore, four items of third-order Nuttall window functions and second-order Nuttall self-convolution windows with good performance are selected as research and discussion objects, the performance of the research and discussion objects is compared with that of classical window functions (Hamming windows and Blackman windows), the performance of the research and discussion objects is compared through analysis, and the optimal window function is selected. It should be added that, because the form of the classical window function Kaiser window is too complex, the specific gravity between the main lobe width and the side lobe height needs to be selected by itself, which is not suitable for simplifying programming and field application, and is not discussed herein.
In order to better compare the performances of the 4 window functions, simulations are used herein to analyze the time domain characteristics and the frequency domain characteristics of the 4 window functions at the same window length (N ═ 64).
FIG. 6-1 and FIG. 6-2 are time-frequency domain characteristic curves of Hamming window, Blackman window, four-term third-order Nuttall window and second-order Nuttall self-convolution window.
By comparing the performances of the 4 window functions, the method can obtain that the sidelobe attenuation of the four-term third-order Nuttall window is fastest, the Blackman window is second, the second-order Nuttall is slower from the convolution window, and the Hamming window is slowest in terms of the sidelobe attenuation rate under the same window length; in terms of the peak level of the side lobe, the side lobe of a Hamming window is maximum, the Blackman window is second, a four-term third-order Nuttall window is smaller, and a second-order Nuttall self-convolution window is minimum. Therefore, on the aspect of improving the accuracy of spectral analysis, the window function performance of the four-term third-order Nuttall window and the second-order Nuttall self-convolution window is better inhibited from spectrum leakage and barrier effect due to the traditional classical window function.
2. Comparison of positioning effect before and after windowing
After analyzing the performance of the 4 window functions, performing WFT analysis on the cable positioning spectrogram of the middle joint in the graph 5 by using a Hamming window, a Blackman window, a four-term third-order Nuttall window and a second-order Nuttall self-convolution window respectively. The positioning result after the windowing process is shown in fig. 7.
According to the positioning results of the cable of the intermediate joint before and after the windowing process in fig. 7, the positioning accuracy of the intermediate joint is measured by the relative positioning error, and the positioning results of the intermediate joint are shown in table 1.
TABLE 1 results of positioning of intermediate joints after processing with different window functions
Table.2-1 Location results of the intermediate joint after different window functions processing
From the positioning result of the intermediate joint after windowing, compared with the condition that the intermediate joint is not windowed, the identification and positioning sensitivity of the intermediate joint is improved to a certain extent by a Hamming window, a Blackman window, a four-term third-order Nuttall window and a second-order Nuttall self-convolution window after WFT. In the identification of the intermediate joint, the Hamming window and the Blackman window which are used as classical window functions have poor window function performance, so that the identification effect of the intermediate joint is not ideal; the four-term third-order Nuttall window has better window function performance, and the identification capability of the four-term third-order Nuttall window to the intermediate joint is better than that of a Hamming window and a Blackman window, but is still not as good as that of a second-order Nuttall self-convolution window. In the positioning of the intermediate joint, because the second-order Nuttall self-convolution window has more excellent window function performance, compared with the processing without the window and the other three window functions, the positioning precision is higher, and the positioning error is within 0.076%.
Therefore, the second-order Nuttall self-convolution window has the best effect on improving the identification and positioning sensitivity of the intermediate joint, and the second-order Nuttall self-convolution window is selected as the optimal window function.
In summary, in order to ensure that the cable positioning spectrogram has higher frequency resolution and can better inhibit frequency spectrum leakage during frequency spectrum analysis, four third-order Nuttall windows are selected for windowing the cable positioning spectrogram with the damp defect of the body; and aiming at the positioning spectrogram of the cable with the damp defect of the intermediate joint, selecting a second-order Nuttall self-convolution window to perform windowing treatment on the cable. The reason is that the reflection intensity of the local damp defect of the body is often weaker than that of the middle joint, if a second-order Nuttall self-convolution window with a wider main lobe is selected to process a cable positioning spectrogram of the damp defect of the body, the reflection of the damp defect is probably mistaken for a side lobe to suppress the side lobe, so that the reflection of the defect cannot be presented on the positioning spectrogram, and therefore four third-order Nuttall windows with narrower main lobes are selected to perform windowing processing on the damp defect.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (6)
1. The distribution cable defect positioning algorithm adopting windowed Fourier transform is characterized in that: the method comprises the following steps:
step 1, testing cable data;
and 2, inputting an impedance spectrum to the head end of the cable to position the local defect/intermediate joint of the cable.
2. The algorithm for locating defects in a power distribution cable using windowed fourier transform as claimed in claim 1, wherein: step 2, the specific method for positioning the local defect/intermediate joint of the cable by inputting the impedance spectrum at the head end of the cable comprises the following steps:
s1, determining the position of the tail end l of the cable by finding the position of the frequency maximum value under the fundamental frequency, thereby realizing the positioning of the two ends of the head and the tail end of the cable and the local defect;
and S2, the accuracy of the frequency spectrum analysis is improved by improving the upper limit of the test frequency/adopting a windowed Fourier transform analysis algorithm to inhibit the frequency spectrum leakage and the fence effect.
3. The algorithm for locating defects in a power distribution cable using windowed fourier transform as claimed in claim 2, wherein: the calculation formula of the maximum frequency value in step S1 is:
f|Z|max1at maximum frequency, v is the wave velocity and l is the length of the cable.
4. The algorithm for locating defects in a power distribution cable using windowed fourier transform as claimed in claim 2, wherein: the windowed Fourier transform analysis algorithm added in the step S2 is any one or any two of a Hamming window, a Blackman window, a four-term third-order Nuttall window and a second-order Nuttall self-convolution window.
5. The algorithm for locating defects in a power distribution cable using windowed fourier transform as claimed in claim 4, wherein: in the step S2, four third-order Nuttall windows are selected for the cable positioning spectrogram of the body affected with damp defects to perform windowing processing on the cable positioning spectrogram.
6. The algorithm for locating defects in a power distribution cable using windowed fourier transform as claimed in claim 4, wherein: in the step S2, a second-order Nuttall self-convolution window is selected for the cable positioning spectrogram of the damp defect of the intermediate joint, and windowing is performed on the cable positioning spectrogram.
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