The intense electromagnetic environments (EMEs), such as the intentional electromagnetic interference and electromagnetic pulse, pose severe threats to the normal functions of electric and electronic systems. A system is usually composed of numbers of interdependently linked subsystems or equipments. The interactions of the system and the high-power EME involve large quantities of parameters and scenarios, so the complete tests or computations are usually difficult to fulfill, which leads to a hard mission to assess the system-level electromagnetic vulnerability. This paper provides the thought of divide-and-rule to cope with this problem. First, it divides the system into relatively independent and manageable subsystems, and after respective tests and computations, the subsets of data are fused to characterize the whole system. The key point for this assessment methodology is to set up one model or framework to unify all the activities, which is completed here by the causal Bayesian networks (BNs). The system-level effects and the environment threats are characterized with the probability theory. The modeling and parameter determining techniques are presented. Since fault tree analysis (FTA) is also utilized in the electromagnetic risk assessment, the assessment procedures based on relatively BN and FTA are compared. The final results indicate that BN is capable of extending the modeling and analysis power of FTA.

System-Level Vulnerability Assessment for EME: From Fault Tree Analysis to Bayesian Networks—Part I: Methodology Framework / Mao, Congguang; Canavero, Flavio. - In: IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY. - ISSN 0018-9375. - STAMPA. - 58:1(2016), pp. 180-187. [10.1109/TEMC.2015.2484067]

System-Level Vulnerability Assessment for EME: From Fault Tree Analysis to Bayesian Networks—Part I: Methodology Framework

CANAVERO, Flavio
2016

Abstract

The intense electromagnetic environments (EMEs), such as the intentional electromagnetic interference and electromagnetic pulse, pose severe threats to the normal functions of electric and electronic systems. A system is usually composed of numbers of interdependently linked subsystems or equipments. The interactions of the system and the high-power EME involve large quantities of parameters and scenarios, so the complete tests or computations are usually difficult to fulfill, which leads to a hard mission to assess the system-level electromagnetic vulnerability. This paper provides the thought of divide-and-rule to cope with this problem. First, it divides the system into relatively independent and manageable subsystems, and after respective tests and computations, the subsets of data are fused to characterize the whole system. The key point for this assessment methodology is to set up one model or framework to unify all the activities, which is completed here by the causal Bayesian networks (BNs). The system-level effects and the environment threats are characterized with the probability theory. The modeling and parameter determining techniques are presented. Since fault tree analysis (FTA) is also utilized in the electromagnetic risk assessment, the assessment procedures based on relatively BN and FTA are compared. The final results indicate that BN is capable of extending the modeling and analysis power of FTA.
File in questo prodotto:
File Dimensione Formato  
jnl-2016-TEMC_Vulnerability-I_cm+fc.pdf

non disponibili

Descrizione: jnl-2016-TEMC_Vulnerability-I_cm+fc.pdf
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 504.91 kB
Formato Adobe PDF
504.91 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
jnl-2016-TEMC_Vulnerability-I_cm+fc_OA.pdf

accesso aperto

Descrizione: jnl-2016-TEMC_Vulnerability-I_cm+fc_OA
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 521.25 kB
Formato Adobe PDF
521.25 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2646717
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo