XLPE (Cross Linked Polyethylene) cable partial discharging signal estimation method based on statistical learning theory

A statistical learning theory and discharge signal technology, applied in the field of XLPE cable partial discharge signal estimation based on statistical learning theory, can solve the problems of low signal-to-noise ratio, limited effect, and inability to restore the real signal well.

Inactive Publication Date: 2015-07-29
STATE GRID CORP OF CHINA +1
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Problems solved by technology

When the sampling length is insufficient or the sampling rate is too low, the effect of the traditional XLPE cable partial disch

Method used

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  • XLPE (Cross Linked Polyethylene) cable partial discharging signal estimation method based on statistical learning theory
  • XLPE (Cross Linked Polyethylene) cable partial discharging signal estimation method based on statistical learning theory
  • XLPE (Cross Linked Polyethylene) cable partial discharging signal estimation method based on statistical learning theory

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Embodiment Construction

[0044] Below in conjunction with accompanying drawing and embodiment the present invention will be further described:

[0045] A kind of XLPE cable partial discharge signal estimation method based on statistical learning theory, comprises the following steps:

[0046] Step 1, input the partial discharge signal of the XLPE cable collected;

[0047] Step 2, perform wavelet decomposition on the XLPE cable partial discharge signal, and calculate each decomposition coefficient w jk The corresponding decomposition coefficient energy W jk , the sequence of decomposition coefficients according to the order of decomposition coefficient energy from large to small; represented by the linear combination of basis functions

[0048] f m ( x , w ) = Σ i = 1 m w ...

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Abstract

The invention discloses an XLPE (Cross Linked Polyethylene) cable partial discharging signal estimation method based on a statistical learning theory. The XLPE cable partial discharging signal estimation method comprises the following steps: inputting an acquired XLPE cable partial discharging signal; representing the XLPE cable partial discharging signal by linear combination of a primary function; carrying out wavelet decomposition on the XLPE cable partial discharging signal to obtain a new wavelet coefficient sequence from big to small according to decomposition coefficient energy; enabling VCdimensionh to be equal to 1, 2,...L in sequence, and keeping former (h-1) wavelet decomposition coefficients from the new wavelet decomposition wavelet decomposition; zeroing residual decomposition coefficients and calculating corresponding structure risks; finding out a VCdimensionh0 which enables {Rstr(h)} to be minimum; and outputting an optimal estimated signal of XLPE cable partial discharging. The XLPE cable partial discharging signal estimation method based on the statistical learning theory has the beneficial effects that the matching degree of a treated signal waveform and a real signal waveform is high, a discharging signal component can be kept better, and the smooth effect on background noises is very remarkable.

Description

technical field [0001] The invention relates to the field of partial discharge detection of XLPE cables, in particular to a method for estimating partial discharge signals of XLPE cables based on statistical learning theory. Background technique [0002] XLPE (Cross-linked Polyethylene, XLPE) cable is a power cable with XLPE as the main insulation and PVC as the outer sheath. It has excellent electrical properties and heat resistance, large transmission capacity, simple process, and convenient installation. It has been widely used in transmission and distribution networks of various voltage levels in the power system. [0003] With the widespread application of XLPE cables in power transmission and distribution networks, power failures caused by XLPE cable insulation damage are also increasing. According to statistics from relevant departments, cable accidents account for more than 60% of all power equipment accidents. Under on-site detection conditions, partial discharge d...

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Application Information

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IPC IPC(8): G01R31/12G06F19/00
Inventor 段玉兵胡晓黎雍军杨波张皓孙晓斌孟海磊
Owner STATE GRID CORP OF CHINA
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