A topological-based method for allocating sensors by using CSP techniques

Authors:
R. Ceballos;V. Cejudo;R. M. Gasca;C. Del Valle
Affiliations:
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Spain;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla, Spain
Venue:
CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
Year:
2005

Citing 4
Cited 1

A theory of diagnosis from first principles

Artificial Intelligence
Characterizing diagnoses and systems

Artificial Intelligence
Unveiling the ISCAS-85 Benchmarks: A Case Study in Reverse Engineering

IEEE Design & Test
Limited discrepancy search

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1

Minimizing test-point allocation to improve diagnosability in business process models

Journal of Systems and Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

Model-based diagnosis enables isolation of faults of a system. The diagnosis process uses a set of sensors (observations) and a model of the system in order to explain a wrong behaviour. In this work, a new approach is proposed with the aim of improving the computational complexity for isolating faults in a system. The key idea is the addition of a set of new sensors which allows the improvement of the diagnosability of the system. The methodology is based on constraint programming and a greedy method for improving the computational complexity of the CSP resolution. Our approach maintains the requirements of the user (detectability, diagnosability,...).