Title :
On-line sensor fault detection, isolation, and accommodation in automotive engines
Author :
Capriglione, Domenico ; Liguori, Consolatina ; Pianese, Cesare ; Pietrosanto, Antonio
Author_Institution :
DAEIMI, Univ. of Cassino, Italy
fDate :
6/24/1905 12:00:00 AM
Abstract :
The paper describes the hybrid solution, based on Artificial Neural Networks, ANNs, and production rule adopted in the realization of an Instrument Fault Detection, Isolation, and Accommodation scheme for automotive applications. Details on the ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.
Keywords :
automotive electronics; fault diagnosis; intelligent sensors; internal combustion engines; neural nets; IFDIA instrument; artificial neural network; automotive engine; fault accommodation; fault detection; fault isolation; on-line sensor; production rule; Actuators; Artificial neural networks; Automotive engineering; Control systems; Electronic mail; Engines; Fault detection; Pressure control; Sensor phenomena and characterization; Sensor systems;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2002. IMTC/2002. Proceedings of the 19th IEEE
Print_ISBN :
0-7803-7218-2
DOI :
10.1109/IMTC.2002.1007218
