Prof. Ruqiang Yan is Director of International Machinery Center, iHarbour Academy of Frontier Equipment, Xi'an Jiaotong University. He received his PhD degree in Mechanical Engineering from the University of Massachusetts Amherst, USA, in 2007. He is a Fellow of American Society of Mechanical Engineers (ASME) and received the IEEE Instrumentation and Measurement Society Technical Award in 2019. His research interests include data analytics, artificial intelligence, and energy-efficient sensing and sensor networks for the condition monitoring and fault diagnosis of complex engineering systems.
Artificial Intelligence Enabled Diagnosis and Prognosis in Manufacturing
The new generation AI technology, especially deep learning, has shown a great advantage in feature learning and knowledge mining, which provides a new way for intelligent diagnosis and prognosis in manufacturing. This talk first provides a brief overview of deep learning. Then applications of some typical deep network models in intelligent diagnosis and prognosis are discussed, followed by a new trend of deep learning theory and development.