Artificial Intelligence
Algorithms for automatic sensor placement to acquire complete and accurate information
Algorithms for automatic sensor placement to acquire complete and accurate information
Automatic sensor placement for accurate dimensional inspection
Computer Vision and Image Understanding
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Configuring and enhancing measurement systems for damage identification
Advanced Engineering Informatics
Data mining techniques for improving the reliability of system identification
Advanced Engineering Informatics
A model for data fusion in civil engineering
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Finite Elements in Analysis and Design
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This paper presents a generic methodology for measurement system configuration when the goal is to identify the behaviour models that reasonably explain observations. For such tasks, the best measurement system provides maximum separation between candidate models. In this work, the degree of separation between models is measured using Shannon's Entropy Function. The location and type of measurement devices are chosen such that the entropy of candidate models is greatest. This methodology has been tested on a laboratory structure and, to demonstrate generality, an existing fresh water supply network in a town in Switzerland. In both cases, the methodology suggests an appropriate set of sensors for identifying the state of the system.