SPECIAL SESSION #2
Data Generation and Deep Learning Methods applied to Fault Diagnosis and Prognosis
ORGANIZED BY
Loredana Cristaldi
Loredana Cristaldi
Politecnico di Milano, Italy
Luca Martiri
Luca Martiri
Politecnico di Milano, Italy
ABSTRACT
Industrial systems are typical complex entities comprising various subsystems and diverse types of mechanical, power, information, and electronic systems, either independently or in combination. Given their increasingly pivotal role in the economy, it is imperative to transition traditional manufacturing processes into more intelligent and sustainable frameworks.
To advance further towards sustainability, the field of fault diagnosis and prognosis (FDP) assumes a great significance. FDP endeavors to identify and locate faults within captured sensory data while also forecasting their potential failures. Consequently, the capability to predict impending failures or anticipate when a mechanical component has reached the end of its operational life can significantly mitigate maintenance and replacement costs. Simultaneously, it ensures the reliability and efficiency of the system.
TOPICS
Topics of interest for this Special Session include but are not limited to:
- Sustainable manufacturing processes;
- Fault diagnosis and prognosis (FDP);
- Sensory data;
- Predictive maintenance;
- Replacement costs;
- Reliability;
- Efficiency;
- Operational life.
ABOUT THE ORGANIZERS
Loredana Cristaldi (S’91–M’01–SM’06) received the M.Sc. degree in electrical engineering from the University of Catania, Catania, in 1992, and the Ph.D. degree in electrical engineering from the Politecnico di Milano, Milan, Italy, in 1995. In 1999, she joined the Dipartimento di Elettrotecnica, Politecnico di Milano as an Assistant Professor of electrical and electronic measurements. She is a Full Professor with the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano.
Her current research interests include the measurements of electric quantities under nonsinusoidal conditions, virtual instruments, and measurement methods for reliability, monitoring, and fault diagnosis.
Prof. Cristaldi is a Counsellor of the IEEE Student Branch of the Politecnico di Milano and a member of the TC 315 CEI (WG6) and TC56 CEI.
Luca Martiri was born in Rho (MI), Italy on November 9, 1998. He received the MSc degree in Computer Science and Engineering, from Politecnico di Milano, Italy in 2023 and is currently a PhD student at the Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano.
His current research activities are in the field of anomaly detection in mechanical and temperature measurements, and data driven State of Health and End of Life prediction of Li-Ion batteries.
