logo-polimi
Loading...
Degree programme
Programme Structure
Show/Search Programme
Degree Programme
International context
Customized Schedule
Your customized time schedule has been disabled
Enable
Search
Search a Professor
Professor's activities
Search a Course
Search a Course (system prior D.M. n. 509)
Search Lessons taught in English
Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the professor, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information on professor
ProfessorBaraldi Piero
QualificationFull professor full time
Belonging DepartmentDipartimento di Energia
Scientific-Disciplinary SectorING-IND/19 - Nuclear Power Plants
Curriculum VitaeDownload CV (121.35Kb - 22/01/2018)
OrcIDhttps://orcid.org/0000-0003-4232-4161

Contacts
Professor's office hours
DepartmentFloorOfficeDayTimetableTelephoneFaxNotes
energia----MondayFrom 15:00
To 17:00
6345----
E-mailpiero.baraldi@polimi.it
Professor's personal websitewww.lasar.polimi.it

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2021 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Journal Articles
A method for fault diagnosis in evolving environment using unlabeled data (Show >>)
A multi-branch deep neural network model for failure prognostics based on multimodal data (Show >>)
A novel association rule mining method for the identification of rare functional dependencies in Complex Technical Infrastructures from alarm data (Show >>)
A semi-supervised method for the characterization of degradation of nuclear power plants steam generators (Show >>)
Association rules extraction for the identification of functional dependencies in complex technical infrastructures (Show >>)
Bootstrapped ensemble of artificial neural networks technique for quantifying uncertainty in prediction of wind energy production (Show >>)


List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A coevolutionary optimization approach with deep sparse autoencoder for the extraction of equipment degradation indicators (Show >>)
A method for inferring casual dependencies among abnormal behaviours of components in complex technical infrastructures (Show >>)
A methodology for the identification of the critical components of the electrical distribution network of cern’s large hadron collider (Show >>)
A novel degradation state indicator for steam generators of nuclear power plants (Show >>)
Agent-based modeling and reinforcement learning for optimizing energy systems operation and maintenance: the pathmind solution (Show >>)
An ensemble of echo state networks for predicting the energy production of wind plants (Show >>)
An unsupervised method for the reconstruction of maintenance intervention times (Show >>)
Data-driven extraction of association rules of dependent abnormal behaviour groups (Show >>)
Data-driven identification of critical components in complex technical infrastructures using Bayesian additive regression trees (Show >>)
Deep reinforcement learning for optimizing operation and maintenance of energy systems equipped with phm capabilities (Show >>)
Fault detection based on optimal transport theory (Show >>)
Fault diagnostics by conceptors-aided clustering (Show >>)
Fault prognostics in presence of event-based measurements (Show >>)
Multi-objective evolutionary algorithm for the identification of rare functional dependencies in complex technical infrastructures (Show >>)
Text mining for the automatic classification of road accident reports (Show >>)
The aramis data challenge: Prognostics and health management in evolving environments (Show >>)
Journal Articles
A Feature Selection-based Approach for the Identification of Critical Components in Complex Technical Infrastructures: Application to the CERN Large Hadron Collider (Show >>)
A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments (Show >>)
A data-driven framework for identifying important components in complex systems (Show >>)
A novel method for maintenance record clustering and its application to a case study of maintenance optimization (Show >>)
Challenges to IoT-Enabled Predictive Maintenance for Industry 4.0 (Show >>)
Dynamic Surrogate Modeling for Multistep-ahead Prediction of Multivariate Nonlinear Chemical Processes (Show >>)
Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants (Show >>)
Fault prognostics by an ensemble of Echo State Networks in presence of event based measurements (Show >>)
Industrial equipment reliability estimation: A Bayesian Weibull regression model with covariate selection (Show >>)
Partially observable Markov decision processes for optimal operations of gas transmission networks (Show >>)


List of publications and reserach products for the year 2019 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Scheda Bibliografica
An evidential similarity-based regression method for the prediction of equipment remaining useful life in presence of incomplete degradation trajectories (Show >>)
Conference proceedings
Automatic Extraction of a Health Indicator from Vibrational Data by Sparse Autoencoders (Show >>)
Journal Articles
An ensemble of models for integrating dependent sources of information for the prognosis of the remaining useful life of Proton Exchange Membrane Fuel Cells (Show >>)
Elastic net multinomial logistic regression for fault diagnostics of on-board aeronautical systems (Show >>)


List of publications and reserach products for the year 2018 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A heterogeneous ensemble approach for the prediction of the remaining useful life of packaging industry machinery (Show >>)
A smart framework for the availability and reliability assessment and management of accelerators technical facilities (Show >>)
Dealing with uncertainty in modelling of wastewater disinfection by peracetic acid (Show >>)
Journal Articles
A Markov decision process framework for optimal operation of monitored multi-state systems (Show >>)
A Novel Method for Sensor Data Validation based on the analysis of Wavelet Transform Scalograms (Show >>)
A framework for reconciliating data clusters from a fleet of nuclear power plants turbines for fault diagnosis (Show >>)
An Ensemble of Component-Based and Population-Based Self-Organizing Maps for the Identification of the Degradation State of Insulated-Gate Bipolar Transistors (Show >>)
Differential evolution-based multi-objective optimization for the definition of a health indicator for fault diagnostics and prognostics (Show >>)
Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components (Show >>)
Hybrid Probabilistic-Possibilistic Treatment of Uncertainty in Building Energy Models: A Case Study of Sizing Peak Cooling Loads (Show >>)


List of publications and reserach products for the year 2017 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A Dynamic Weighting Ensemble Approach for Wind Energy Production Prediction (Show >>)
A Hybrid Monte Carlo and Possibilistic Approach to Estimate Non-Suppression Probability in Fire Probabilistic Safety Analysis (Show >>)
A switching ensemble approach for remaining useful life estimation of electrolytic capacitors (Show >>)
An unsupervised clustering method for assessing the degradation state of cutting tools used in the packaging industry (Show >>)
Resistance-based probabilistic design by order statistics for an oil and gas deep-water well casing string affected by wear during kick load (Show >>)
Journal Articles
A Systematic Semi-Supervised Self-adaptable Fault Diagnostics approach in an evolving environment (Show >>)
A locally adaptive ensemble approach for data-driven prognostics of heterogeneous fleets (Show >>)
Development of a Bayesian multi-state degradation model for up-to-date reliability estimations of working industrial components (Show >>)
Ensemble of optimized echo state networks for remaining useful life prediction (Show >>)
Prediction of industrial equipment Remaining Useful Life by fuzzy similarity and belief function theory (Show >>)
manifesti v. 3.4.18 / 3.4.18
Area Servizi ICT
28/09/2021