Fault diagnosis of WSNs node based on wavelet neural network

Abstract

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.

Citation

Lin, L., Xu, D. and Wang, H. (2010), "Fault diagnosis of WSNs node based on wavelet neural network", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 29 No. 2, pp. 563-570. https://doi.org/10.1108/03321641011015020