Active fault diagnosis for stochastic large scale systems under non-separable costs

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43969687" target="_blank" >RIV/49777513:23520/24:43969687 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.automatica.2023.111348" target="_blank" >https://doi.org/10.1016/j.automatica.2023.111348</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.automatica.2023.111348" target="_blank" >10.1016/j.automatica.2023.111348</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Active fault diagnosis for stochastic large scale systems under non-separable costs

Popis výsledku v původním jazyce

The paper focuses on active fault diagnosis of stochastic large-scale systems decomposed into several coupled subsystems, where the subsystem fault-free and faulty behavior is described in the multiple-model framework. In the active approach, the detector generates optimal excitation input to improve the diagnosis. This paper proposes a solution to the problems with cost functions in a generally non-separable form. Unlike the separable form, the generally non-separable form facilitates penalizing missed detections, false alerts, and incorrect, false identifications involving several subsystems simultaneously. Three approaches are proposed to treat such cost functions in the offline stage of the active fault diagnosis algorithm. Their performance is illustrated using a simple example and an elaborate example involving a power network system.

Název v anglickém jazyce

Active fault diagnosis for stochastic large scale systems under non-separable costs

Popis výsledku anglicky

The paper focuses on active fault diagnosis of stochastic large-scale systems decomposed into several coupled subsystems, where the subsystem fault-free and faulty behavior is described in the multiple-model framework. In the active approach, the detector generates optimal excitation input to improve the diagnosis. This paper proposes a solution to the problems with cost functions in a generally non-separable form. Unlike the separable form, the generally non-separable form facilitates penalizing missed detections, false alerts, and incorrect, false identifications involving several subsystems simultaneously. Three approaches are proposed to treat such cost functions in the offline stage of the active fault diagnosis algorithm. Their performance is illustrated using a simple example and an elaborate example involving a power network system.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA22-11101S" target="_blank" >GA22-11101S: Tenzorový rozklad v aktivní diagnostice poruch pro stochastické rozlehlé systémy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Automatica

ISSN

0005-1098

e-ISSN

1873-2836

Svazek periodika

159

Číslo periodika v rámci svazku

JAN 2024

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

001102728500001

EID výsledku v databázi Scopus

2-s2.0-85175268259