Fault diagnosis of WSNs node based on wavelet neural network

• Lei Lin ^[1] ; De-kai Xu ^[1] ; Hou-jun Wang ^[1]
  1. [1] University of Electronic Science Technology of China
• Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 29, Nº 2 (Special Issue: Selected papers from CAC 2008), 2010, págs. 563-570
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • Purpose – The purpose of this paper is to provide a new method of the fault diagnosis of wireless sensor networks (WSNs) node, which is based on wavelet neural network (WNN).

    Design/methodology/approach – The approach uses WNN to diagnose the sensor module of the node.

    Findings – The method based on WNN sensing parts of the WSN nodes in additional fault location is accurate feasible.

    Research limitations/implications – The fault of WSNs node protean, it is necessary to establish even more fault model for the training of WNN.

    Practical implications – The simulation results provide useful guidelines for the engineers faced with the detection the fault of the WSN node.

    Originality/value – The WNN is well‐known. The innovation here is applying this method in order to diagnose the fault of WSNs node.