AU2020103078A4 - High-sensitivity diagnostic method for local defects of power cable - Google Patents
High-sensitivity diagnostic method for local defects of power cable Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/11—Locating faults in cables, transmission lines, or networks using pulse reflection methods
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
- G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
- G01R27/04—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant in circuits having distributed constants, e.g. having very long conductors or involving high frequencies
- G01R27/06—Measuring reflection coefficients; Measuring standing-wave ratio
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/083—Locating faults in cables, transmission lines, or networks according to type of conductors in cables, e.g. underground
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The disclosure discloses a high-sensitivity diagnostic method for local defects of
a power cable. This method realizes the positioning of the local defects of the power
cable by measuring and analyzing the reflection coefficient spectrum of the power
cable in combination with a strobing gate technology and a modem digital
processing technology based on a frequency-domain power cable reflection
coefficient spectrum, then the wave velocity of the tested cable obtained by a real
part or an imaginary part of the transformed reflection coefficient spectrum is
compared with the wave velocity of a new cable, and meanwhile the severity of the
local defect is estimated in combination with a difference between a transformed
reflection coefficient spectrum amplitude and a corresponding model fitting curve.
Compared with the prior art, the disclosure can not only realize location and
multi-defect identification of local defects with weak change degree but also assess
the severity of the local defects of the power cable.
Description
[0001] The disclosure relates to the technical field of electrical engineering, and
particularly to a high-sensitivity diagnostic method for local defects of a power cable.
[0002] The cross-linked polyethylene (XLPE) power cable has been widely used in
China's power industry because of its reliable electrical and mechanical properties
now. A large number of urban grid transformation work was performed in the early
1990s, and a large number of cables began to be applied to urban power grids.
However, due to fabricating processes and influences under long-term operation
conditions, the cable often generates local defects such as water trees, insulating
medium deformation and copper shielding layer loosening for the reasons of
moisture, overheating, extrusion, excessive bending and the like. If the local defects
of the cable are not treated, the local defects of the cable will be rapidly developed
under the action of a strong electric field to finally lead to the failure of cable
insulation, thereby bringing a lot of work for maintenance and replacement of the
cable and resulting in a lot of manpower andfinancial wastes. In addition, because
the cable is buried underground and concentrated in the central urban area, it is
difficult to replace the whole cable. From the point of view of cost saving, if the local
defects of the power cable can be diagnosed, a lot of manpower and financial
resources can be saved.
[0003] The existing matured time domain reflection (TDR) method can utilize a
pulse signal to diagnose the fault of the power cable. The Chinese patent
201310063871.3 "time domain reflection system and method" provides a method and system for determining conductor anomalies using a time domain reflection method. However, this method has not been able to diagnose the defects with weak change degree, and TDR has insufficiently high resolution ratio in multiple defect identification and near-end defect identification. Local discharge diagnosis of cables is a method to detect the local defects of the cables. However, due to small local discharge signal amplitude, serious attenuation, difficult signal separation and difficult multi-fault identification and other reasons, it is difficult to diagnose local defects in actual measurement. Meanwhile, a local discharge off-line test is often a destructive experiment which can affect the structure of the cable to a certain extent. The existing power cable detection and diagnosis technology still stays in the aspect of fault diagnosis, is in lack of diagnosing local defects with a weak cable structural parameter change degree, and can not check the early defects of the cable. Therefore, it is of great significance to develop a new local cable defect diagnosis technology.
[0004] The objective of the disclosure is to provide a high-sensitivity diagnostic method for local defects of a power cable based on a power cable reflection coefficient spectrum to realize the precise positioning and state assessment of local defects of the cable and meanwhile well distinguish the middle joint of the power cable. The high-sensitivity diagnostic method for local defects of the power cable of the disclosure has the advantages of advanced technology, easy operation, low cost and high sensitivity.
[0005] Provided is a high-sensitivity diagnostic method for local defects of a power cable, comprising the following steps:
[0006] 1. Data measurement of to-be-detected cable
[0007] A low-voltage linear frequency modulation signal, a pseudo random signal or a high-frequency narrow pulse V is transmitted to a tested power cable, a
reflection signal , reflected back from the tail end of the power cable is measured, and the amplitude Jd of the reflection coefficient spectrum of the cable and the real part Re al(F,() of the reflection coefficient spectrum and the imaginary part
Imag(F(f)) of the reflection coefficient spectrum are obtained through d- V
whereinf is a signal frequency, I is the length of the cable, v is the velocity of light in
vacuum, and the value v = 3 x 108 m/s.
[0008] 2. Data processing of to-be-detected cable
[0009] A to-be-tested frequency domain signal is transferred into a t'domain signal
by utilizing a transfer function -' , Fast Fourier Transformation (FFT) or
Discrete Fourier transformation (DFT) is performed on the transferred Re al(Fd(t'))
or Imag(Fd(t')) , and a frequency point fo is recorded, wherein the energy is
maximum; the transferred Re al(Fd(t')) or Imag(Fd(t')) is multiplied by a kaiser window and the multiplied result is subjected to Fast Fourier Transformation (FFT)
or Discrete Fourier transformation (DFT) into initially processed data KFd, and the
value in the kaiser window meets:
0.1102(a -8.7), a >50
[0010] #= 0.5842(a - 21)O^+ 0.07886(a - 21), 50 > a 21 0 a <21
[0011] wherein a is sidelobe attenuation multiple, and P initial value is 6. DFT
transformation from 0Hz to o is performed on Kd , the transformed result is mapped into an original distance diagnosis spectrum Do, wherein the transformed result is mapped into 0 m at0Hz, and the transformed result is mapped into the
length I of the cable at 0 .
[0012] The obtained original distance diagnosis spectrum is subjected to distance windowing, and the processing manner is as follows:
D(i)= Do (j) - min(DO)
[0013] Di max(DO) - min(DO)
[0014] wherein s is the length of the window whose value is not larger than the spatial resolution in the distance diagnosis spectrum Do, and D is the distance diagnosis spectrum obtained after processing.
[0015] 3. Data measurement and processing of reference cable
[0016] Since distortion points occur at the middle joint position of the cable in the process of measurement so as to affect the judgment of defect positions, a reference cable needs to be introduced for comparison in order to assess the influence of the middle joint of the power cable on defect positions. A non-tested phase cable in a three-phase system is used as the reference cable, then the amplitude Fd1 of the reflection coefficient spectrum of the reference power cable and the real part Real(FdIf of the reflection coefficient spectrum and imaginary part Imag(Fd() of the reflection coefficient spectrum are obtained by utilizing the
same manner in step (1), processing is conducted under the same condition in step (2) to obtain the processed distance diagnosis spectrum E.
[0017] The middle joint of each phase of the cable is generally made at the same position, in order to eliminate the influence on judgment of the middle joint on the local defect position of the cable, the distance diagnosis spectrum D is compared with the distance diagnosis spectrum E, distortion points, whose positions are the same those in the distance diagnosis spectrum E, in the distance diagnosis spectrum D are eliminated by utilizing the strobing gate technology to obtain the local defect distance diagnosis spectrum F, and the distortion points found in the local defect distance diagnosis spectrum F are local defect positions.
[0018] 4. Assessment of severity of local defects of cable
[0019] The obtained local defect distance diagnosis spectrum is subjected to Inverse Discrete Fourier Transformation (IDFT) or Inverse Fast Fourier Transformation (IFFT) to obtain the transformed t' domain reflection coefficient spectrum curve, the transformed t' domain reflection coefficient spectrum curve is transformed into Real(Fd2 (f)) or Imag(Fd 2 (f)) byutilizing t' -> f . Then the frequencyfkcorresponding to each maximum value point or minimum value point in Real(Fd2 (f)) or Imag( 2 (f)) is found, the average wave velocity of the power
N-1
cable is obtained by utilizing the formula v, =I2l(fk - fk)/(N- 1) vC is k=1 , and
compared with the wave velocity Vo of the new cable, wherein N is the number of
maximum value points or minimum value points in Real(Fd 2 (f)) or
Imag(Fd2 (f)) . If the difference between Ve and Vo is more than 2%, the local
defects of the tested cable are serious, for example the damage of cable copper shield is serious, and even the cable is failed.
[0020] In order to further assess the severity of local defects of the tested power cable, the mathematical model of the cable reflection coefficient spectrum mold value is established:
[0021] abs(Fd2 (f))=aehf+c df
[0022] By using the established mathematical model, the reflection coefficient spectrum obtained by measuring the tested power cable is subjected to data fitting by using the modulus value after the gate technology to obtain the fitting value corresponding to a higher frequency extreme pointfk the standard deviation between
d2 and the relative difference value of thefitting curve is obtained by utilizing
the thefrmulerror= std(11Fd 2 (1k)- abs(Fd2 (1k))/Iabs(Fdd22 (1k)))X 10000weent formula err=sdId2k2 , wherein std
is is standard deviation, and the severity of the local defects of the tested power cable assessed according to the obtained standard deviation. When error <5%, the local defects of the cable are relatively light, at this moment, a small amount of copper shielding layer loose defects are possibly present in the tested power cable or defects such as tool marks and scratching are present in an insulating medium, when 5%< error <10 % , the defect severity of the cable is moderate, at this moment, defects, such as damped insulating medium or large-area copper shielding layer damage, are possibly present in the tested power cable; when error >10%, the defects of the cable are very serious, at this moment, defects, such as the seriously deformed insulating medium, are possibly present in the tested power cable.
[0023] Further, in step (1), for a long cable, the signal attenuation is serious and the required signal frequency band is narrow; for a short cable, the signal attenuation is small and the required signal frequency band is wide. Meanwhile, when the signal is not attenuated to zero, the wider the signal frequency band is, the higher the positioning accuracy and sensitivity are.
[0024] Further, the wave velocity vo of the new cable in step (4) can be obtained by measuring the new cable, or the inductance L and capacitance C per unit length can be obtained through calculating the geometric size of the cable and the characteristics of the cable core and insulating material, or the inductance L and capacitance C per unit length of the new cable of the same type and same batch can be measured by an 1 RLC digital bridge and calculated through the formula
[0025] The disclosure has the following advantages:
[0026] 1. Using low-voltage measurement method instead of a destructive test measurement method not only does not damage cable insulation, but also reduces the weight and volume of measuring equipment.
[0027] 2. By processing frequency domain information, the local defects of the cable can be displayed more easily. On this basis, the sensitivity of locations of local defects of the cable is greatly improved by combining with a kaiser window function.
[0028] 3. Compared with TDR, the disclosure has higher identification ability for local defects with weak change degree, identification precision and identification sensitivity for multiple defects, and meanwhile has stronger identification ability for near-end defects.
[0029] 4. By adding a distance window to the distance diagnosis spectrum, the distortion points can be displayed more easily, thereby greatly improving the positioning accuracy.
[0030] 5. By comparing the distance diagnosis spectrums of the to-be-tested cable and the reference cable and through the strobling gate technology, the distortion points at the same position are found and eliminated, so as to eliminate the influence of the middle joint of the cable on the judgment of the local defect position of the cable.
[0031] 6. Through the calculation of the wave velocity of the cable, the severity of the local defect of the cable is preliminarily assessed. On this basis, the severity of the local defect is further assessed by combining with the reflection coefficient spectrum module value fitting curve after gating.
[0032] 7. The measurement method is not limited to the voltage level of the to-be-tested cable, and the traditional cable defect diagnosis method needs to select different test equipment according to different voltage levels.
[0033] Fig. 1 is a flowchart of a method of the disclosure.
[0034] Fig. 2 is a comparison distance diagnosis spectrum of a tested power cable
and a reference power cable plotted in example 1 of the disclosure. Wherein, a full
line represents the distance diagnosis spectrum of the tested power cable, and a
dotted line represents the distance diagnosis spectrum of the reference power cable.
[0035] Fig. 3 is a comparison graph of reflection coefficient amplitude spectrums
subjected to strobing gate plotted in example 1 of the disclosure. Wherein, a dotted
line represents the reflection coefficient amplitude spectrum of the tested power
cable after strobing gate technology is used, and a full line represents a curve fitted
according to a mathematic model of a module value of a reflection coefficient
spectrum.
[0036] Fig. 4 is a distance diagnosis spectrum of local defects plotted in example 2
of the disclosure.
[0037] Next, the disclosure will be particularly described through examples: it is
necessary to note that these examples are only for further describing the disclosure
and cannot be understood as limiting the protection scope of the disclosure. Those
skilled in the art can make nonessential modifications and regulations according to
the above contents of the disclosure.
[0038] Example 1
[0039] As shown in Fig. 2 and Fig.3, local defect diagnosis was performed on 100
m ZR-YJV22-8.7/15 power cable, the defect type was copper shielding layer loose defect, and the following steps were included:
[0040] (1) Data measurement of to-be-detected cable data measurement
[0041] A low-voltage pseudo random signal V was transmitted to a tested power
cable, a reflection signal reflected back from the tail end of the cable was
measured, and the amplitude 1dff of the reflection coefficient spectrum of the
cable and the real part Re al(Fd) of the reflection coefficient spectrum and the
imaginary part Imag(F(f)) of the reflection coefficient spectrum were obtained
through d V
[0042] (2) Data processing of to-be-detected cable
[0043] A to-be-tested frequency domain signal was transferred into a t' domain
signal by utilizing a transfer function , Fast Fourier Transformation (FFT) or
Discrete Fourier transformation (DFT) was performed on transferred Re(al(F(t'))
or Imag(F,(t')), and a frequency point ° was recorded; then the transferred Real(Fd(t')) or Imag(F,(t')) was multiplied by a kaiser window and Fast Fourier
Transformation (FFT) or Discrete Fourier transformation (DFT) was performed to
initially processed data Kd, and the 8 value in the kaiser window was 6;
[0044] DFT transformation from 0Hz to ° was performed on KYd , the transformed result was mapped into an original distance diagnosis spectrum Do, wherein the transformed result was mapped into Om at the 0Hz, and the transformed
result was mapped into the length 100 of the cable at f' .
[0045] The obtained original distance diagnosis spectrum was windowed, the distance windowing length s was 5 m, and the processing manner was as follows:
Do (j) - min(D)
[0046] max(DO) - min(DO)
[0047] (3) Data measurement and processing of reference cable
[0048] A non-tested phase cable in a three-phase system was used as the reference cable, then the amplitude Fd1(f) of the reflection coefficient spectrum of the
reference power cable and the real part Real(F, () of the reflection coefficient
spectrum and imaginary part Imag(F,(f)) of the reflection coefficient spectrum were obtained by utilizing the same manner in step (1), processing was conducted under the same condition in step (2) to obtain the processed distance diagnosis spectrum E.
[0049] Comparison between distance diagnosis spectrum D and the distance diagnosis spectrum E is shown in Fig. 2. Distortion points, whose positions are the same those in the distance diagnosis spectrum E, in the distance diagnosis spectrum D were eliminated by utilizing the strobing gate technology to obtain the local defect distance diagnosis spectrum F. It can be seen from Fig.2 that there is an obvious distortion point at the position of 70 m, and this position is the set local defect point.
[0050] (4) Assessment of severity of local defects of cable
[0051] The obtained local defect distance diagnosis spectrum was subjected to
Inverse Discrete Fourier Transformation (IDFT) or Inverse Fast Fourier
Transformation (IFFT) to obtain the transformed t' domain reflection coefficient
spectrum curve, the transformed t'domain reflection coefficient spectrum curve was
transferred into Real(Fd2 (f)) or Tmag(F 2 (f)) by utilizing the transfer function
t' ->f . Then the frequency fk corresponding to each maximum value point or
minimum value point in Real(Fd 2 (f)) or Imag(Fd2 (f)) is found, the average
wave velocity of the tested power cable was obtained by utilizing the formula N-1 v, = 2l(f, - fk) /(N-1) ,, v 1.7247 x 108m/s, and the wave velocity of k-1 ,namely,
the new cable was measured as vo=1.7261 x 10 8 m/s, wherein N was the number of
maximum value points or minimum value points in Real(Fd 2 (f)) or
Imag(F 2 (f)). The difference between ve and was 0.81%<2%, indicating the VO local defects of the tested cable were light.
[0052] In order to assess the severity of the local defects of the tested cable, the mathematic model of the reflection coefficient spectrum module value was established:
[0053] abs(Fd2 (f))=aehf+c d.
[0054] By using the established mathematical model, the reflection coefficient spectrum obtained by measuring the tested power cable was subjected to data fitting
by using the module value |Fd2(f) after the strobling gate technology was used, the
hitting result was abs(Fd 2(f))=0.137. e-1.23xo-7/,+0.80 95 - e-5474x 1 if fitig, as shown in Fig. 3, the fitting value corresponding to a higher frequency extreme pointfkwas
obtained, and the standard deviation error--1.16%<5% between 1d2(f and the relative difference value of the fitting curve was obtained by utilizing the formula
error=std(Fd 2 (1k b d 2 (1k))b d 2 (1k, indicating that the local
defect of the tested power cable was minor, and proving that the copper shielding layer loose defect was present in the tested power cable at this moment.
[0055] Example 2
[0056] As shown in Fig.4, local defect diagnosis was performed on 1500 m 10kV XLPE power cable, the defect type is serious deformation defect of insulating medium, and the following steps are included:
[0057] (1) Data measurement of to-be-detected cable data measurement
[0058] A low-voltage high-frequency narrow-pulse V was transmitted to a tested
1500m10I kV XLPE power cable, a reflection signal Vr reflected back from the tail
end of the cable was measured, and the amplitude 17d MI of the reflection
coefficient spectrum of the cable and the real part Real(Fd() of the reflection
coefficient spectrum and the imaginary part Imag(Fd() of the reflection
V through d coefficient spectrum were obtained tru
[0059] (2) Data processing of to-be-detected cable
[0060] A to-be-tested frequency domain signal was transferred into a t' domain
signal by utilizing a transfer function , Fast Fourier Transformation (FFT) or
Discrete Fourier transformation (DFT) was performed on transferred Re al(Fd(t'))
or Imag(Fd(t')) , and a frequency point f was recorded; then the transformed Real(Fd(t')) or Imag(Fd(t')) was multiplied with a kaiser window and the
transformed result was subjected to Fast Fourier Transformation (FFT) or Discrete
Fourier transformation (DFT) into initially processed data Kd, the 8 value in the kaiser window was 8;
[0061] DFT transformation from 0Hz to f was performed on d , the transformed result was mapped into an original distance diagnosis spectrum Do, wherein the transformed result was mapped into Om at the 0Hz, and the transformed
result was mapped into the length 1500 of the cable at f .
[0062] The obtained original distance diagnosis spectrum was windowed, the distance windowing length s was 30 m, and the processing manner was as follows:
rnn) Do (j) - min(D)
[0063] Di max(DO) - min(DO)
[0064] (3) Reference cable data measurement and processing
[0065] A non-tested phase cable in a three-phase system was used as the reference cable, then the amplitude lEdl of the reflection coefficient spectrum of the
reference power cable and the real part Real(Fd.U) of the reflection coefficient
spectrum and imaginary part Imag(F(f)) of the reflection coefficient spectrum were obtained by utilizing the same manner in step (1), and processing was conducted under the same condition in step (2) to obtain the processed distance diagnosis spectrum E.
[0066] Comparison between distance diagnosis spectrum D and the distance diagnosis spectrum E is shown in Fig. 3. Distortion points, whose positions are the same those in the distance diagnosis spectrum E, in the distance diagnosis spectrum D are eliminated by utilizing the strobing gate technology to obtain the local defect distance diagnosis spectrum F. It can be seen from Fig.3 that there is an obvious distortion point at the positions of 500 m and 1200m. These positions were the set local defect points.
[0067] (4) Assessment of severity of local defects of cable
[0068] The obtained local defect distance diagnosis spectrum was subjected to Inverse Discrete Fourier Transformation (IDFT) or Inverse Fast Fourier Transformation (IFFT) to obtain the transformed t' domain reflection coefficient spectrum curve, the transformed t'domain reflection coefficient spectrum curve was
transferred into Real(Fd 2 (f)) or Imag(F 2 (f)) by utilizing transfer function
t' - f . Then the frequency fk corresponding to each maximum value point or
minimum value point in Re al(Fd 2 (f)) or Imag(F 2 (f)) was found, the average
wave velocity of the tested power cable was obtained by utilizing the formula N-1 v, = 2l(f, - fk) /(N-1) ,, ve1.7217 x 10 8 m/s, and the wave velocity of k-1 ,namely,
the new cable was measured as vo=1.7261 x 108 m/s, wherein N is the number of
maximum value points or minimum value points in Real(Fd 2 (f)) or
Imag(F 2 (f)) . The difference between ve and VO was 2.55%>2%, indicating the
local defects of the tested cable were serious.
[0069] In order to assess the severity of the local defects of the tested cable, the mathematic model of the reflection coefficient spectrum module value was established:
[0070] abs(d2 (f))=aehf+c df
[0071] By using the established mathematical model, the reflection coefficient spectrum obtained by measuring the tested power cable was subjected to data fitting by using the module value jEd2(f) after the strobling gate technology was used, the fitting result was abs(Fd2 (f))=.3406e'-9.535x10-7+.28 30 -2. 2 x10-' the fitting value corresponding to a higher frequency extreme pointfi was obtained, and the standard deviation error=16.14%%>10% between j'd2(f) and the relative difference value of the fitting curve was obtained by utilizing the formula error= std(lFd2(k)- abs(Fd2 (1k))/abs(Fd (1k)))X100 , indicating that the local 2 defect of the tested power cable was serious, and proving that the insulating medium serious deformation defect was present in the tested power cable at this moment.
Editorial Note 2020103078 There is 4 pages of Claims only.
Claims (3)
1. A high-sensitivity diagnostic method for local defects of a power cable, comprising the following steps:
(1) Data measurement of to-be-detected cable
A low-voltage linear frequency modulation signal, a pseudo random signal or a high-frequency narrow pulse Vi is transmitted to a tested power cable, a reflection
signal , reflected back from the tail end of the power cable is measured, and the
amplitude 1df of the reflection coefficient spectrum of the cable and the real
part Real(fd)) of the reflection coefficient spectrum and the imaginary part
Imag(F(f)) of the reflection coefficient spectrum are obtained through d- V
whereinf is a signal frequency, I is the length of the cable, v is the velocity of light in
vacuum, and the value v = 3 x 108 m/s.
(2) Data processing of to-be-detected cable
A tested frequency domain signal is transferred into a t' domain signal by
utilizing a transfer function -' , Fast Fourier Transformation (FFT) or Discrete
Fourier transformation (DFT) is performed on the transferred Real(Fd(t')) or
Imag(F(t')) , and a frequency point f is recorded, wherein the energy is
maximum; the transferred Re al(Fd(t')) or Imag(F,(t')) is multiplied by a kaiser window and the multiplied result is subjected to Fast Fourier Transformation (FFT)
or Discrete Fourier transformation (DFT) into initially processed data KFd, and the
value in the kaiser window meets:
0..1102(a -8.7), a >50
#=8 0.5842(a -21) 0 4 +0.07886(a -21), 50 >a >21 0, a <21 wherein a is sidelobe attenuation multiple, and P initial value is 6. DFT transformation from 0Hz to o is performed on K d, and the transformed result is mapped into an original distance diagnosis spectrum Do, wherein the transformed result is mapped as 0 m at0Hz, and the transformed result is mapped into the length I of the cable at 0' .
The obtained original distance diagnosis spectrum is subjected to distance windowing, and the processing manner is as follows:
D(i)= Do (j) - min(D) J, max(DO) - min(DO)
wherein s is the length of the window whose value is not larger than the spatial resolution in the distance diagnosis spectrum Do, and D is the distance diagnosis spectrum obtained after processing.
(3) Data measurement and processing of reference cable
Since distortion points occur at the middle joint position of the cable in the process of measurement so as to affect the judgment of defect positions, a reference cable needs to be introduced for comparison in order to eliminate the influence of the middle joint of the power cable on defect positions. A non-tested phase cable in a
three-phase system is used as the reference cable, then the amplitude If'dl of the reflection coefficient spectrum of the reference power cable and the real part Real(Fdl(f)) of the reflection coefficient spectrum and imaginary part
Imag(Fd(f)) of the reflection coefficient spectrum are obtained by utilizing the
same manner in step (1), and processing is conducted under the same condition in step (2) to obtain the processed distance diagnosis spectrum E.
The middle joint of each phase of the cable is generally made at the same position, so in order to eliminate the influence on judgment of the middle joint on the local defect position of the cable, the distance diagnosis spectrum D is compared with the distance diagnosis spectrum E, distortion points, whose positions are the same those in the distance diagnosis spectrum E, in the distance diagnosis spectrum D are eliminated by utilizing the strobing gate technology to obtain the local defect distance diagnosis spectrum F, and the distortion points found in the local defect distance diagnosis spectrum F are local defect positions.
(4) Assessment of severity of local defects of cable
The obtained local defect distance diagnosis spectrum is subjected to Inverse Discrete Fourier Transformation (IDFT) or Inverse Fast Fourier Transformation (IFFT) to obtain the transformed t'domain reflection coefficient spectrum curve, the transformed t' domain reflection coefficient spectrum curve is transferred into Real(Fd2 (f)) or Imag(F 2 (f)) by utilizing transfer function t' - f . Then the
frequencyfkcorresponding to each maximum value point or minimum value point in Re al(Fd2 (f)) or Imag( 2(f))is found, the average wave velocity of the power N-1
cable is obtained by utilizing the formula v I = 2l(fk,, fk)/(N-1) v, is
compared with the wave velocity V0 of the new cable, wherein N is the number of
maximum value points or minimum value points in Real(Fd2 (f)) or
Imag(F 2 (f)) . If the difference between Ve and V0 is more than 2%, the local
defects of the tested cable are serious, for example the damage of cable copper shield is serious, and even the cable is failed.
In order to further assess the severity of local defects of the tested power cable, the mathematical model of the cable reflection coefficient spectrum mold value is established:
abs(d2 (f))=aehf+c d.f
By using the established mathematical model, the reflection coefficient spectrum obtained by measuring the tested power cable is subjected to data fitting by using the modulus value after the gate technology to obtain the fitting value corresponding to a higher frequency extreme pointfk the standard deviation between
d2 and the relative difference value of thefitting curve is obtained by utilizing
the theformulerror =std(lFd 2 (1k) - abs(Fd2(1k))/ abs(Fdd22 (1k)))X 1000%hrent formula err=sdId2k2 , wherein std
is standard deviation, and the severity of the local defects of the tested power cable is assessed according to the obtained standard deviation. When error <5%, the local defects of the cable are relatively light, at this moment, a small amount of copper shielding layer loose defects are possibly present in the tested power cable or defects such as tool marks and scratching are present in an insulating medium, when 5% <error <10 % , the defect severity of the cable is moderate, at this moment, defects, such as the damped insulating medium or large-area copper shielding layer damage, are possibly present in the tested power cable; when error >10%, the defects of the cable are very serious, at this moment, defects, such as the seriously deformed insulating medium, are possibly present in the tested power cable.
2. The high-sensitivity diagnostic method for local defects of a power cable according to claim 1, wherein in step (1), for a long cable, the signal attenuation is serious and the required signal frequency band is narrow; for a short cable, the signal attenuation is small and the required signal frequency band is wide; meanwhile, when the signal is not attenuated to zero, the wider the signal frequency band is, the higher the positioning accuracy and sensitivity are.
3. The high-sensitivity diagnostic method for local defects of a power cable according to claim 1, wherein the wave velocity vo of the new cable in step (4) can be obtained by measuring the new cable, or the inductance L and capacitance C per unit length can be obtained through calculating the geometric size of the cable and the characteristics of the cable core and insulating material, or the inductance L and capacitance C per unit length of the new cable of the same type and same batch can 1 be measured by an RLC digital bridge and calculated through the formula _1LC
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