System identification by methods from the statistical signal theory, history and state of the art

Condition monitoring is an important area in which the OECD Halden Reactor Project has developed several tools. This paper presents a general overview of methods utilised in diagnosis systems, signal validation systems and process optimisation systems such as EFD, Mocom, Aladdin and PEANO. An overview of lessons learned on diagnosis of technical systems with special reference to system identification is reported. The analysis of input-output behaviour by special, suitable methods may be used as a tool for diagnosis. An overview of methods for empirical modelling and data analysis and their major differences is presented. It is explained how system identification methods and transforms may be used to build models based on observed data from a system. According to the Webster dictionary diagnosis is 'Investigation or analysis of the cause or nature of a condition, situation or a problem.' By examining data collected from a process the aim is to detect abnormal conditions and if possible understand what has been the cause of the observed problem. Section 1 gives a retrospective view at the development in the field of system identification. Section 2 presents a classification of the methods, while section 3 provides some practical advice on how diagnosis can be carried out by means of system identification methods (author) (ml)