Techniques

Diagnosis of Active Systems: Principles and Techniques by Gianfranco Lamperti, Marina Zanella (auth.)

By Gianfranco Lamperti, Marina Zanella (auth.)

This booklet is ready model-based prognosis of a category of discrete-event platforms referred to as lively platforms. approximately, model-based analysis is the duty of checking out the defective parts of a actual procedure in response to the saw habit and the process version. An lively method is the abstraction of a actual artefact that's modeled as a community of com­ municating automata. for instance, the security equipment of an influence transmission community may be comfortably modeled as an lively method, the place breakers, safeguard units, and contours are evidently defined by way of finite kingdom machines. The asynchronous prevalence of a brief circuit on a line or a bus-bar reasons the response of the safety units, which goals to isolate the shorted line. This response should be defective and several other strains could be ultimately remoted, instead of the shorted line basically. The diagnostic challenge to be solved is uncovering the defective units established the seen a part of the response. as soon as the prognosis activity has been on finished, the produced effects are exploited to mend the equipment (and additionally to localize the fast circuit, during this pattern case). apparently, the learn provided during this booklet used to be brought on a decade in the past by way of a undertaking 011 brief circuit localization, performed through ENEL, the Italian electrical energy board, in addition to different business and educational eu partners.

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Extra resources for Diagnosis of Active Systems: Principles and Techniques

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In the system model, which is a nondeterministic automaton, unobservable events are either failures or events that cause changes in the system state which are not recorded by sensors. The system model is both assumed not to incorporate unobservable cycles and to generate a live language. These two assumptions together guarantee that a failure event is, sooner or later, followed by an observable event. 1. 1 displays the behavioral models (observable events are in bold) of the two components A (left) and B (right) of the system we consider in this example.

However, models differ from the real systems they represent as every model depends on its own set of simplifying assumptions and approximations. M odel- Based Diagnosis 13 A model is good to a diagnostic purpose if such simplifications and approximations are acceptable in the case at hand. For example, the adopted models may feature too coarse a granularity for the current purpose. Such a modeling problem can be solved by providing more detailed models, which lead to a better approximation of the real system.

The teleological model specifies the purpose of the system at hand by describing its goals and the relationships alllong them. The junctional model links the teleological primitives with the behavioral ones, which are more detailed. The advantage is that the diagnostic proce:::;s, starting from the teleological model, who:::;e search space is smaller, and then passing through the functional model, can at the end focus attention on those parts only of the behavioral model that are responsible for the faulty behavior.

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