Title :
Optimization based fault detection for nonlinear systems
Author :
Retheim, T. ; Vincent, Tyrone L. ; Shoureshi, Rahmat
Author_Institution :
Center for Adv. Control of Energy & Power Syst., Colorado Sch. of Mines, Golden, CO, USA
Abstract :
As systems become more complex and interconnected, it becomes more difficult to monitor and maintain them. Components wear or fail, or operating conditions change, causing a degradation of performance. To meet this challenge, a theory of fault detection and isolation has been developed to enable automatic detection of faulty conditions. The focus of the paper is on a general, practical method of nonlinear fault detection which is easily implemented on input/output models that are generated by modern nonlinear system identification methods. The method proposed is different in that a neural network is used to model the process dynamics, while a dead-beat observer is implemented by solving a set of coupled nonlinear equations. This allows us to introduce constraints into the problem that can improve the power of the fault detection test
Keywords :
fault diagnosis; neural nets; nonlinear systems; observers; optimisation; power transformers; automatic detection; coupled nonlinear equations; dead-beat observer; fault detection and isolation; faulty conditions; input/output models; modern nonlinear system identification methods; neural network; nonlinear fault detection; nonlinear systems; optimization based fault detection; performance degradation; process dynamics; Condition monitoring; Couplings; Degradation; Fault detection; Fault diagnosis; Neural networks; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Power system modeling;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.945984
