Korbicz, Józef - red. ; Uciński, Dariusz - red.
Sensor network scheduling for identification of spatially distributed processes
Group publication title:
Subject and Keywords:
sensor network ; parameter estimation ; distributed parameter system ; optimum experimental design ; Fisher information matrix
The work treats the problem of fault detection for processes described by partial differential equations as that of maximizing the power of a parametric hypothesis test which checks whether or not system parameters have nominal values. A simple node activation strategy is discussed for the design of a sensor network deployed in a spatial domain that is supposed to be used while detecting changes in the underlying parameters which govern the process evolution ; The setting considered relates to a situation where from among a finite set of potential sensor locations only a subset of them can be selected because of the cost constraints. As a suitable performance measure, the Ds-optimality criterion defined on the Fisher information matrix for the estimated parameters is applied. ; The problem is then formulated as the determination of the density of gauged sites so as to maximize the adopted design criterion, subject to inequality constraints incorporating a maximum allowable sensor density in a given spatial domain. The search for the optimal solution is performed using a simplicial decomposition algorithm. The use of the proposed approach is illustrated by a numerical example involving sensor selection for a two-dimensional diffusion process.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, Volume 22, Number 1 (2012) ; click here to follow the link