On-line fault diagnosis technique of the magnetic Levitation vehicle system

The supervision of technical processes is the subject of increased development because of the reliability and safety. The
use of process computers and microcomputers permits the application of methods, which result in an earlier detection of
process faults than is possible by conventional limit and trend checks. With the aid of process models, estimation and
decision methods it is possible to also monitor non-measurable variables like process states, process estimation and
characteristic quantities. This paper describes how recursive identification techniques can be used in order to detect the
faults of the dynamic continuous systems. This approach employs a combination of operators, the system dynamic
being expressed in terms of the incremental difference delta that serves to some theoretical advantages and the time
delays expressed using the z operator. So, estimation of parameters of diagnose model, and the faults detection who
makes to the aide of statistical methods based on the interval of confidence (χ2 distribution, Fisher distribution and
Student distribution). This technique is validated in simulation by the application on a magnetic levitation vehicle
system MLV.

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