Discrimination algorithm for aviation fault arc detection

A fault arc and discriminant algorithm technology, applied in the direction of calculation, testing of dielectric strength, computer components, etc., can solve the problem of not considering the influence of frequency domain characteristics on fault arc current and so on

Inactive Publication Date: 2017-08-18
BEIHANG UNIV
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Problems solved by technology

The above two patent applications only analyzed the fault arc current from the time domain characteristics, and did not consider the influence of the frequency domain characteristics on the fault arc current

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  • Discrimination algorithm for aviation fault arc detection
  • Discrimination algorithm for aviation fault arc detection
  • Discrimination algorithm for aviation fault arc detection

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Embodiment Construction

[0096] The specific implementation method of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0097] The invention discloses a discrimination algorithm for aviation fault arc detection, which adopts the combination of fast Fourier decomposition (FFT), wavelet transform (WT) and information entropy (IE) by collecting aviation series and parallel fault arc current signals under different loads The method and empirical mode decomposition method (EMD), through the wavelet transform and multiple sampling analysis of the current signal under different load conditions, extract the characteristics of the fault arc current signal with both time domain and frequency domain for analysis, and increase the fault discrimination The accuracy of the load, and the current of the start-stop process of the normal load is also compared with the arc current, so as to eliminate the misjudgment caused by the judgment of the fault current;

[00...

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Abstract

The invention discloses a discrimination algorithm for aviation fault arc detection and belongs to a field of aviation fault arc detection. The algorithm specifically includes collecting fault arc current signals in conditions with different loads on a test platform; judging whether the fault arc current signals are DC fault arc current or AC fault arc current and extracting characteristic quantities with both time domain and frequency domain; aiming at wavelet energy of DC fault arcs, information entropy and current change rate and wavelet energy of AC fault arcs, training a support vector machine predication model by taking the information entropy and a fourth eigenmode function value obtained through empirical mode decomposition; and distinguishing fault and normal states of arcs by utilizing two support vector machine predication models. According to the invention, a plurality of characteristic quantities are selected, fault characteristic contingency is reduced and discrimination accuracy is increased. Intelligent discrimination is performed on characteristics in a fault and normal critical range and randomness is reduced.

Description

technical field [0001] The invention relates to a discrimination algorithm for aviation fault arc detection, which belongs to the field of aviation fault arc detection. Background technique [0002] With the rapid development of my country's aviation industry, people pay more and more attention to aviation safety. The working environment of the aviation system is complex. For example, the vibration during the flight will lead to poor contact of the wire connection part, and the temperature change and radiation will cause the aging of the insulation surface of the transmission line, etc., and these problems may lead to the generation of arc faults. [0003] Fault arcs can be divided into series fault arcs and parallel fault arcs according to their generation methods; series fault arcs are caused by loose wire connections or poor contact; their fault currents are generally small. Parallel fault arc mostly occurs between the phase line and the neutral line or between the phase...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/12G06K9/62
CPCG01R31/1272G06F18/2411
Inventor 张俊民钟锋林浩
Owner BEIHANG UNIV
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