THE SYMPTOM OBSERVATION MATRIX FOR MONITORING AND DIAGNOSTICS

Monitoring of complex technical systems in operation/service is a task concerning safety, reliability and risk management. Additionally, the monitoring and diagnosis of such systems is also recommended for the reduction of costs, and to increase the life of systems under consideration. ndamental quantities for monitoring and diagnosis are symptoms contained in measured data of a time-variant system. Symptoms are observable and sensitive with respect to faults or damage. Questions such as how to find symptoms, how they should be evaluated for information condensation in order to detect, and if possible to localize, faults or damage, are discussed, and, additionally, the choice of the measuring matrix and the test forces are treated in the context of the state space formulation of time-variant models. e purpose of information condensation and the evaluation of symptoms, the symptom observation matrix is introduced and manipulated by the singular value decomposition. The properties of the observation matrix with its singular values and singular vectors show their applicability for monitoring and diagnosis.