Fault Detection of WSN Based on Spatial Correlation

Abstract

Regarding application with smooth variation of detection, spatial correlation of sensors’ data within a small field was applied to sensor nodes’ fault diagnosis. The data were sorted into several continuous sequences by sink node. Sequence with minimum variance was regarded as normal data to determine normal nodes. For undetermined nodes, it can be determined via calculation on deviation to normal nodes’ data of vicinity area. If deviation does not exceed the threshold, the node is normal; otherwise, it is regarded as a fault node. The research on WSN in a greenhouse shows that fault node can be effectively detected in time by this method.

Online data fault detection for wireless sensor networks - case study

“…Yuan [6] proposed an anomaly detection process that requires a powerful node to construct models for the aggregated data. Bing [7] applied the spatial correlation using a resource-plentiful node. In addition, some solutions [8,9] are costly in communication terms.…”

“…Besides the physical redundancy requirement, the efficiency of these solutions requires that the neighbors report correct readings which may not be always guaranteed. Other approaches [5][6][7] require resource-plentiful nodes to perform more complex computational tasks. Yao [5] identified anomalies by a local step on the nodes using temporal correlations then by an aggregation step using spatial correlations on more powerful node.…”

The Two-Scale Finite Element Estimates for Thermoelasticity in Perforated Structure with Boundary Layer

“…Up to now, the finite element estimates and algorithms for the thermoelastic problem in composites with small perforated structure with boundary layer have not been considered. In this paper, following the idea in [6], one higher order two-scale finite element (FE) method coupled with matched boundary layer is proposed and some finite errors are analyzed.…”