Title :
Fault detection schemes for a diesel engine turbocharger
Author :
Ludwig, C. ; Ayoubi, M.
Author_Institution :
Inst. of Control Eng., Tech. Univ. Darmstadt, Germany
Abstract :
In this paper two model based methods for real time fault detection of Diesel engine turbochargers are presented and compared. Fault detection schemes which are based on residual generation between the measured and some estimated process states require precise mathematical models of the process. One approach is utilizing parametric nonlinear dynamic models, whereas the other method uses artificial neural networks with distributed dynamics for modeling
Keywords :
failure analysis; internal combustion engines; modelling; neural nets; nonlinear dynamical systems; artificial neural networks; diesel engine turbocharger; distributed dynamics; parametric nonlinear dynamic models; real-time fault detection; residual generation; Artificial neural networks; Control engineering; Diesel engines; Electronic mail; Fault detection; Mathematical model; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; State estimation;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.531272
