Data Aggregation Algorithm of Sensor Network Nodes for Health Monitoring Based on Fuzzy Clustering

2021 ◽  
Vol 52 (1) ◽  
pp. 20210459
Author(s):  
Shujun Liang ◽  
Jing Cheng ◽  
Jianwei Zhang
Keyword(s):  
Sensor Network ◽  
Fuzzy Clustering ◽  
Health Monitoring ◽  
Data Aggregation ◽  
Network Nodes

States analysis and Agent modeling for wireless sensor network nodes

2011 ◽  
Vol 30 (12) ◽  
pp. 3155-3157
Author(s):  
Zhi CHEN ◽  
Jie SHI ◽  
Ying KONG ◽  
Yun ZHANG
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Agent Modeling ◽  
Network Nodes

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

2021 ◽  
pp. 147592172110332
Author(s):  
Mehrdad Ghyabi ◽  
Hamidreza Nemati ◽  
Ehsan Dehghan-Niri
Keyword(s):  
Finite Element ◽  
Sensor Network ◽  
Health Monitoring ◽  
Surface Crack ◽  
Piezoelectric Sensor ◽  
Network Coverage ◽  
Coverage Area ◽  
Fem Simulations ◽  
Network Geometry ◽  
Critical Defect

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

Sensor network paradigms for structural health monitoring

2006 ◽  
Vol 13 (1) ◽  
pp. 210-225 ◽  
Author(s):  
Charles R. Farrar ◽  
Gyuhae Park ◽  
David W. Allen ◽  
Mike D. Todd
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Structural Health
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