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.
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).
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.
Congratulation to Dr. Francesco Cannarile! He has been awarded a PhD title in “mathematical models and methods in engineering from Politecnico di Milano”
The website of the project
funded by INAIL has been launched. Lasar is a member of the project consortium. More information at: https://site.unibo.it/mac4pro/it
CONGRATULATIONS TO FRANCESCO DI MAIO FOR THE PROMOTION TO ASSOCIATE PROFESSOR