Keynote

Speech Title:

Intelligent PHM in the Big Data Era: A Collaborative Paradigm of Deep Learning and Physics

Speaker:

Ruqiang Yan, Xi’an Jiaotong University

Abstract:

The emergence of Prognostics and Health Management (PHM) systems is reshaping how we manage complex, high-end equipment across its entire lifecycle, driving the shift toward intelligent operation and maintenance in the Industry 4.0 era. At the heart of PHM lies fault diagnosis—a critical capability now undergoing rapid transformation. Fueled by advances in deep learning, data-driven approaches have surpassed traditional physics-based models in managing massive volumes of measurement data. Yet, despite their success, these black-box models often fall short in interpretability and trustworthiness, especially in safety-critical applications. This keynote explores a new frontier in intelligent fault diagnosis: the convergence of data science and physics through physics-informed deep learning. By embedding physical laws into neural networks, this collaborative approach bridges the gap between empirical insights and theoretical understanding. It enhances transparency, improves controllability, and unlocks new pathways for knowledge discovery. As we move deeper into the big data era, such hybrid models offer a promising route to more reliable, explainable, and robust PHM systems—ushering in a new generation of smart diagnostics for complex physical systems.

Bio:

Ruqiang Yan is a Full Professor and Director of International Machinery Center at the School of Mechanical Engineering, Xi’an Jiaotong University, China. His research interests include data analytics, AI, and energy-efficient sensing and sensor networks for the condition monitoring and health diagnosis of large-scale, complex, dynamical systems. Dr. Yan is a Fellow of IEEE (2022) and ASME (2019). He is the recipient of several prestigious awards including the First Prize for Technological Invention in Shaanxi Province in 2020, the First Prize for Natural Science from the Ministry of Education in 2020, and the 2019 IEEE Instrumentation and Measurement Society Technical Award. He has led the development of one IEEE standard and published over one hundred papers in IEEE and ASME journals, and other publications. He was the Editor-in-Chief of the IEEE Transactions on Instrumentation and Measurement, currently serves as an IEEE Instrumentation and Measurement Society Distinguished Lecturer and Associate Editor-in-Chief of Chinese Journal of Mechanical.