A methology of alarm filtering using using, dynamic fault tree
Résumé
This article presents a new approach for filtering the faults thanks to the defined Dynamic Fault Tree (DFT). The proposed methodology includes the dependencies between fault events in the models. Two problems must thus be solved, they relate to the filtering of false alarms, and the reduction of the size of the ambiguity of fault isolation related to the occurrence of a failure. In response to the expressed needs for diagnosis, as well for the needs for filtering and localization of the failures, it is necessary to introduce new dynamic gates making it possible to translate new dependencies relationships. Based on previous techniques, the approach presented in this paper is based on four peculiar powerful features. First, the concept of the precedence between events is taken account in order to resort to an adapted configuration for the fault isolation. Secondly, another relevant data to establish a diagnosis is to take into account the concepts of redundancies between various sets. The appearance of the same phenomenon on various sets can make it possible to refine the fault isolation. The knowledge of the character of the failures is a third important information, indeed according to the character of the identified breakdowns, one will be able for example to refine the localization or to filter certain events considered as non-representative of the character of breakdown. Fourth, the time duration of the alarm is more interesting information to be exploited. The proposed DFT model can be modularized and each module translated into a High Level Petri Net (HLPN). Translation of DFT modules into HLPN has proved to be very flexible, and various kinds of new dependencies can be easily accommodated. In order to exploit this flexibility a new representation, called event diagram, is introduced.