News

2020/6/3

NEW PUBLICATION

Title: A Feature Selection-Based Approach for the Identification of Critical Components in Complex Technical Infrastructures: Application to the CERN Large Hadron Collider

Journal: Reliability Engineering and System Safety

Authors: Piero Baraldi, Andrea Castellano, Ahmed Shokry, Ugo Gentile, Luigi Serio, Enrico Zio

Free download until July 15th , 2020: https://authors.elsevier.com/c/1b7ig3OQ~fLcRF

Abstract: Complex Technical Infrastructures (CTIs) are large-scale systems made of tens of thousands of interdependent components organized in complex hierarchical architectures. They evolve in time in a way that at one point their functional logic may be more complex than originally designed, and, therefore, traditional reliability/risk importance measures cannot be used for identifying the critical components on which the protection and recovery efforts should be primarily allocated. We propose an approach for identifying the most critical components based on the large amount of operational data collected from the CTI monitoring systems over long time periods and under different operational settings. The underlying idea is to develop binary classifiers to associate different combinations of measured signals to the CTI operating or failed state. The critical CTI components are those whose condition monitoring signals allow optimally classifying the CTI state. To identify the signals and to build the classifier, we consider a feature selection wrapper approach based on the combined use of Support Vector Machine classifiers and the Binary Differential Evolution algorithm for optimization. The approach is successfully applied to a real dataset collected from the CERN (European Centre for Nuclear Research) Large Hadron Collider, a CTI for experiments of physics.

Presentation


2020/4/9

CALL FOR A POSTDOC POSITION AT LASAR

STEP FOR REGISTRATION AND APPLICATION 


Congratulations to Mingjing Xu! He won the best student poster award at the “European Safety and Reliability Conference (ESREL 2019)”

The work has been done during his PhD in the Laboratory of Signal and Risk Analysis of Politecnico di Milano (LASAR).

Poster

Paper


Congratulation to Riccardo Borghi! He won the best presentation award at the “Offshore Mediterranean Conference”

The work has been done during his master thesis within a collaboration between the Laboratory of Signal and Risk Analysis of Politecnico di Milano (LASAR) and ENI S.p.A.

Riccardo Borghi CV

Master Thesis Abstract


Congratulation to Dr. Francesco Cannarile! He has been awarded a PhD title in “mathematical models and methods in engineering from Politecnico di Milano”

finto_serio

Short Bio

Defense Presentation

Thesis Abstract

List of Publications


The website of the project

Manutenzione intelligente (smart maintenance) di impianti industriali e opere civili mediante tecnologie di monitoraggio 4.0 e approcci prognostici (MAC4PRO, progetto BRIC 2018 INAIL)

funded by INAIL has been launched. Lasar is a member of the project consortium. More information at: https://site.unibo.it/mac4pro/it


CALL FOR A POSTDOC POSITION AT POLIMI


CONGRATULATIONS TO FRANCESCO DI MAIO FOR THE PROMOTION TO ASSOCIATE PROFESSOR

Presentazione attività di ricerca

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