Resumen de Fault diagnosis of WSNs node based on wavelet neural network

Lei Lin, De-kai Xu, Hou-jun Wang

• 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.