# Configuring a sensor network for fault detection in distributed parameter systems

International Journal of Applied Mathematics and Computer Science (2008)

- Volume: 18, Issue: 4, page 513-524
- ISSN: 1641-876X

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topMaciej Patan, and Dariusz Uciński. "Configuring a sensor network for fault detection in distributed parameter systems." International Journal of Applied Mathematics and Computer Science 18.4 (2008): 513-524. <http://eudml.org/doc/207904>.

@article{MaciejPatan2008,

abstract = {The problem of fault detection in distributed parameter systems (DPSs) is formulated as that of maximizing the power of a parametric hypothesis test which checks whether or not system parameters have nominal values. A computational scheme is provided for the design of a network of observation locations in a spatial domain that are supposed to be used while detecting changes in the underlying parameters of a distributed parameter system. The setting considered relates to a situation where from among a finite set of potential sensor locations only a subset 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. Then, the solution of a resulting combinatorial problem is determined based on the branch-and-bound method. As its essential part, a relaxed problem is discussed in which the sensor locations are given a priori and the aim is to determine the associated weights, which quantify the contributions of individual gauged sites. The concavity and differentiability properties of the criterion are established and a gradient projection algorithm is proposed to perform the search for the optimal solution. The delineated approach is illustrated by a numerical example on a sensor network design for a two-dimensional convective diffusion process.},

author = {Maciej Patan, Dariusz Uciński},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {branch-and-bound; constrained experimental design; distributed parameter systems; fault detection; parameter estimation; sensor location},

language = {eng},

number = {4},

pages = {513-524},

title = {Configuring a sensor network for fault detection in distributed parameter systems},

url = {http://eudml.org/doc/207904},

volume = {18},

year = {2008},

}

TY - JOUR

AU - Maciej Patan

AU - Dariusz Uciński

TI - Configuring a sensor network for fault detection in distributed parameter systems

JO - International Journal of Applied Mathematics and Computer Science

PY - 2008

VL - 18

IS - 4

SP - 513

EP - 524

AB - The problem of fault detection in distributed parameter systems (DPSs) is formulated as that of maximizing the power of a parametric hypothesis test which checks whether or not system parameters have nominal values. A computational scheme is provided for the design of a network of observation locations in a spatial domain that are supposed to be used while detecting changes in the underlying parameters of a distributed parameter system. The setting considered relates to a situation where from among a finite set of potential sensor locations only a subset 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. Then, the solution of a resulting combinatorial problem is determined based on the branch-and-bound method. As its essential part, a relaxed problem is discussed in which the sensor locations are given a priori and the aim is to determine the associated weights, which quantify the contributions of individual gauged sites. The concavity and differentiability properties of the criterion are established and a gradient projection algorithm is proposed to perform the search for the optimal solution. The delineated approach is illustrated by a numerical example on a sensor network design for a two-dimensional convective diffusion process.

LA - eng

KW - branch-and-bound; constrained experimental design; distributed parameter systems; fault detection; parameter estimation; sensor location

UR - http://eudml.org/doc/207904

ER -

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