Title :
The fusion of redundant SEVA measurements
Author :
Duta, Mihaela ; Henry, Manus
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, UK
fDate :
3/1/2005 12:00:00 AM
Abstract :
The self-validating (SEVA) sensor carries out an internal quality assessment, and generates, for each measurement, standard metrics for its quality, including online uncertainty. This paper discusses consistency checking and data fusion between several SEVA sensors observing the same measurand. Consistency checking is shown to be equivalent to the maximum clique problem, which is NP-hard, but a linear approximation is described. A technique called uncertainty extension is proposed which causes a smooth reduction in the influence of outliers as they become increasingly inconsistent with the majority.
Keywords :
computational complexity; condition monitoring; intelligent sensors; optimisation; redundancy; sensor fusion; NP-hard problem; consistency checking; internal quality assessment; linear approximation; maximum clique problem; online uncertainty; redundant SEVA measurement fusion; self-validating sensor; smooth reduction; standard quality metrics; uncertainty extension; Current measurement; Fusion power generation; Measurement standards; Measurement uncertainty; Monitoring; Noise measurement; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Transducers; Maximum clique problem; self-validating (SEVA) sensors; sensor fusion;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2004.840448