Fuzzy diagnostic reasoning that takes into account the uncertainty of the relation between faults and symptoms
International Journal of Applied Mathematics and Computer Science (2006)
- Volume: 16, Issue: 1, page 27-35
- ISSN: 1641-876X
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topKościelny, Jan, and Syfert, Michał. "Fuzzy diagnostic reasoning that takes into account the uncertainty of the relation between faults and symptoms." International Journal of Applied Mathematics and Computer Science 16.1 (2006): 27-35. <http://eudml.org/doc/207775>.
@article{Kościelny2006,
abstract = {Knowledge about the relation between faults and the observed symptoms is necessary for fault isolation. Such a relation can be expressed in various forms, including binary diagnostic matrices or information systems. The paper presents the use of fuzzy logic for diagnostic reasoning. This method enables us to take into account various kinds of uncertainties connected with diagnostic reasoning, including the uncertainty of the faults-symptoms relation. The presented methods allow us to determine the fault certainty factor as well as certainty factors of the normal and unknown process states. The unknown process state factor groups all the states with unknown and multiple faults with the states with improper residual values, while the normal state factor indicates similarity between the observed state and the pattern fault-free state.},
author = {Kościelny, Jan, Syfert, Michał},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {uncertainty; diagnostic relation; fuzzy logic; fault isolation},
language = {eng},
number = {1},
pages = {27-35},
title = {Fuzzy diagnostic reasoning that takes into account the uncertainty of the relation between faults and symptoms},
url = {http://eudml.org/doc/207775},
volume = {16},
year = {2006},
}
TY - JOUR
AU - Kościelny, Jan
AU - Syfert, Michał
TI - Fuzzy diagnostic reasoning that takes into account the uncertainty of the relation between faults and symptoms
JO - International Journal of Applied Mathematics and Computer Science
PY - 2006
VL - 16
IS - 1
SP - 27
EP - 35
AB - Knowledge about the relation between faults and the observed symptoms is necessary for fault isolation. Such a relation can be expressed in various forms, including binary diagnostic matrices or information systems. The paper presents the use of fuzzy logic for diagnostic reasoning. This method enables us to take into account various kinds of uncertainties connected with diagnostic reasoning, including the uncertainty of the faults-symptoms relation. The presented methods allow us to determine the fault certainty factor as well as certainty factors of the normal and unknown process states. The unknown process state factor groups all the states with unknown and multiple faults with the states with improper residual values, while the normal state factor indicates similarity between the observed state and the pattern fault-free state.
LA - eng
KW - uncertainty; diagnostic relation; fuzzy logic; fault isolation
UR - http://eudml.org/doc/207775
ER -
References
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- Kościelny J.M. and Syfert M. (2004): Fuzzy logic application for the description of diagnostic relation uncertainty. - Proc. 10-th IEEE Int. Conf. Methods and Models in Automation and Robotics, Międzyzdroje, Poland, pp. 757-762.
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