Learning-Based Solutions for Active Monitoring and Anomaly Detection in Advanced Industrial Applications
Presenter: Sabrina Milani
DEIB - Conference Room "E. Gatti" (Bld. 20)
March 18th, 2025 | 11.45 am
Contact: Prof. Simone Formentin
DEIB - Conference Room "E. Gatti" (Bld. 20)
March 18th, 2025 | 11.45 am
Contact: Prof. Simone Formentin
Sommario
On March 18th, 2025 at 11.45 am Sabrina Milani, PHD Student in Information Technology, will hold a seminar on "Learning-Based Solutions for Active Monitoring and Anomaly Detection in Advanced Industrial Applications" at DEIB Conference Room "Emilio Gatti" (Building 20).
The integration of physics-based models with machine learning techniques enhances anomaly detection and classification in complex systems. While physics-based models face high computational costs and limitations in capturing intricate dynamics, machine learning models often lack interpretability and physical constraints. The seminar focuses on the application of these approaches in wind turbine monitoring, where distinguishing among different anomalies is particularly challenging, and in road-friction classification for automotive safety. By integrating physics-informed models with data-driven learning, the proposed approach enhances diagnostic accuracy and real-time performance across various industrial applications.
The integration of physics-based models with machine learning techniques enhances anomaly detection and classification in complex systems. While physics-based models face high computational costs and limitations in capturing intricate dynamics, machine learning models often lack interpretability and physical constraints. The seminar focuses on the application of these approaches in wind turbine monitoring, where distinguishing among different anomalies is particularly challenging, and in road-friction classification for automotive safety. By integrating physics-informed models with data-driven learning, the proposed approach enhances diagnostic accuracy and real-time performance across various industrial applications.
