Title :
Aviation arc fault diagnosis based on weight direct determined neural network
Author :
Huang Yuanhang ; Wang Yongxing ; Dong Enyuan ; Zou Jiyan
Author_Institution :
Dalian Univ. of Technol., Dalian, China
Abstract :
A diagnosis method for the aviation fault arc is proposed in this paper, which is a multi-input weights direct determination (WDD) network. Characteristics of arc current are used for aviation arc fault detection. Arc fault samples are acquired with the help of a self-made arc generator. Feature vectors are obtained from the current of the samples with the wavelet transforming. After training, the fault diagnosis network is verified with the test samples. The result shows that the method has a better performance for aviation fault arc recognition with a simple algorithm.
Keywords :
air safety; aircraft; arcs (electric); electrical faults; electrical safety; fault diagnosis; neural nets; wavelet transforms; WDD; arc current; arc generator; aviation arc fault diagnosis; aviation fault arc recognition; multiinput weights direct determination; wavelet transform; weight direct determined neural network; Arc discharges; Biological neural networks; Circuit faults; Entropy; Fault diagnosis; Training;
Conference_Titel :
Electric Power Equipment - Switching Technology (ICEPE-ST), 2013 2nd International Conference on
Conference_Location :
Matsue
DOI :
10.1109/ICEPE-ST.2013.6804339
