Model-based diagnosis of systems emphasizing a holistic approach

Diagnosis of technical systems is very important both from the technical an d economic point of view. Monitoring and diagnosis start with the observati on of symptoms, which depend on the fast time dynamics and on the system's evolution based on the slow time coordinate. Model-based diagnosis can be p erformed by symptoms directly and by a holistic mathematical model of the e ntire system decomposed into subsystems, whereas the submodels of the relat ed subsystems can be of different accuracies dependent on their goals. If t hese models are adjusted at every lifetime required for condition assessmen t of the operating system/system in service, and if the models are verified and validated, then they represent the best knowledge base available for d iagnosis. Adaptation of mathematical models uses system identification tool s which can produce verified, validated and usable mathematical models. The se models serve for fault detection, localization, assessment and cause fin ding, for trend prediction and decisionmaking for further use of the system . Consequently, the procedure described combined with an extended knowledge base of the limit states etc. of the system can be seen as an intelligent diagnostic method.