In spacecraft energy power system (EPS), the objective of fault protection is to detect and respond to spacecraft faults. Its purpose is to eliminate single point failures or their effects and to ensure the spacecraft system integrity under anomalous conditions. Also, it is important to keep the continuity of the power supply and at the same time increase the reliability of spacecraft Energy power system. One of most deadly faults is arcing faults, which are accompanied by very erratic waveform variations. The sustainable current level in the arc is not sufficient to be reliably detected by conventional means. Feeder current signal analysis provides a solution to this detection problem. A Fast Fourier Transform method is applied to decompose the monitored voltage and current signals into a series of detailed spectral components. The spectral energies are calculated and then employed to train a neural network to identify arcing faults accurately.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Aerospace DC Arcing Fault Detection Using Neural Network Techniques


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Power Systems Conference ; 2002



    Publication date :

    2002-10-29




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Neural Network Based Ball Bearing Fault Detection Using Vibration Features for Aerospace Applications

    Haddad, S. D. / Chatterji, G. B. / SAE | British Library Conference Proceedings | 1994


    Neural Network Based Ball Bearing Fault Detection Using Vibration Features for Aerospace Applications

    Chatterji, Gano B. / Haddad, Sam David | SAE Technical Papers | 1994


    High Impedance Fault Detection Using Artificial Neural Network Techniques

    Watson, Karan L. / Fernando, Susith R. | SAE Technical Papers | 1992