چكيده به لاتين
Abstract:
One of the most important topic in the maintenance filed of rail infrastructures is Condition monitoring. Condition monitoring is a process that it is used to provide information about condition of the system. In this thesis, identification methods in structural systems are considered as an important part of the condition monitoring procedure. These methods are used to estimate structural parameters such as stiffness, damping and etc. Also, these methods can be classified in two types based on the type of accessable data, output or input-output measurments. In this study, the methods based on output data are examined.
In general, the topics is presented in this thesis include:
• State-space Realization of dynamics equations to estimate unkown parameters of structural systems by using the Kalman filter (KF).
• Investigate ILS-UI and compare it with KF method
• Investigate ERA and Fast ERA methods
• introduce Modified ERA and Modified Fast ERA ERA to improve ERA and Fast ERA methods
The effectiveness of these methods have been examined by using experimental data and analyzing the simulation results.
Keywords: System identification, Least square estimation, Kalman filter, ERA method, ARMA method
