Title :
On-line sensor fault detection, isolation, and accommodation in automotive engines
Author :
Capriglione, Domenico ; Liguori, Consolatina ; Pianese, Cesare ; Pietrosanto, Antonio
Author_Institution :
Univ. of Cassino, Italy
Abstract :
This paper describes the hybrid solution, based on artificial neural networks (ANNs), and the production rule adopted in the realization of an instrument fault detection, isolation, and accommodation scheme for automotive applications. Details on ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.
Keywords :
automotive electronics; fault diagnosis; intelligent sensors; neural nets; IFDIA system; artificial neural networks; automotive engine; fault accommodation; fault isolation; instrument fault detection; on-line sensor; production rule; Artificial neural networks; Automotive engineering; Control systems; Engines; Fault detection; Instruments; Manifolds; Redundancy; Sensor phenomena and characterization; Sensor systems;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2003.815994
