@misc{Uciński_Dariusz_Sensor, author={Uciński, Dariusz}, howpublished={online}, publisher={Zielona Góra: Uniwersytet Zielonogórski}, language={eng}, abstract={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}, abstract={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.}, abstract={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.}, type={artykuł}, title={Sensor network scheduling for identification of spatially distributed processes}, keywords={sensor network, parameter estimation, distributed parameter system, optimum experimental design, Fisher information matrix}, }