Fault diagnosis of WSNs node based on wavelet neural network

Autor:	Lei Lin, De‐kai Xu, Hou‐jun Wang
Rok vydání:	2010
Předmět:	Engineering Wavelet neural network Computational Theory and Mathematics business.industry Applied Mathematics Node (networking) Real-time computing Electrical and Electronic Engineering Fault model Fault (power engineering) business Wireless sensor network Computer Science Applications
Zdroj:	COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. 29:563-570
ISSN:	0332-1649
DOI:	10.1108/03321641011015020
Popis:	PurposeThe 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/approachThe approach uses WNN to diagnose the sensor module of the node.FindingsThe method based on WNN sensing parts of the WSN nodes in additional fault location is accurate feasible.Research limitations/implicationsThe fault of WSNs node protean, it is necessary to establish even more fault model for the training of WNN.Practical implicationsThe simulation results provide useful guidelines for the engineers faced with the detection the fault of the WSN node.Originality/valueThe WNN is well‐known. The innovation here is applying this method in order to diagnose the fault of WSNs node.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b52e858f79f652b6084a3018828e77b0 https://doi.org/10.1108/03321641011015020 Zobrazit plný text záznamu