YAN

In our daily life, when we are sick, we usually go to the hospital and ask experienced doctors for diagnosis and treatment. The long-term operation of machines will also produce "disease", that is the so-called fault. We need to seek the help of "doctor" of the machine to diagnose the occurrence of the fault and predict its development trend, and then provide guidance for its operation and maintenance. The new generation of artificial intelligence technology represented by deep learning provides a new way of intelligent diagnosis for machine doctors. On the basis of introducing the development history of artificial neural network, this talk introduces the concept and characteristics of deep learning, and then discusses several typical deep network models and their application in intelligent diagnosis of machines, as well as the development trend of deep learning in the future.

 - Brief of the Lecture : 

Lecture By Dr Ruquiang Yan, Distinguished Lecturer of IEEE Instrumentation and Measurement  Society

During The ICBDS  2024 Conference at VIIT ( VIT Kondhwa Campus) on 19 October 2024 was held from 2 pm to 3 pm (IST) in online Mode. This was a part of Keynote addresses in the conference.

The Topic: Machine Doctor in the Era of Artificial Intelligence.

Topic Was explained lucidly by Dr Ruqiang Yan . He tried to explain Wavelet Transform method for analyzing machine defects, tooth breaking conditions, vibration of the machinery. He also gave a brief comparison with Fourier Transform. He mentioned about activities at  Xian Jiaotong University in China. He gave a illustrations of Research Background comparing Human Doctor and Machine Doctor.  He made a mention of GE Manufacturing Services integration. He explained predictive road map for maintenance and ten give some case studies using Artificial Intelligence. – DL ML and AI. Then explained in brief about ANN . Finally DL and ANN and Limitations of DL. Use of  WaveletKernelNet for diagnosis was also explained. It was very impressive lecture. Questions were raised by some participants to get more depth on the information shared by Dr Yan. Were replied very eloquently and convincing the participants. Amongst  the participant  1. Dr Octavian Postolache, DL of IMS, 2. Dr Rajesh Ingle,VC of the Symbiosis University, 3. Prof Khurjekar , Chair IMS Pune chapter  4.Dr. Amar Buchade, VC IEEE Pune Section,& 5. Dr Shilpa Sondkar, Vice Chair IMS Pune Chapter. All these took part in question and answer sessions. 

Biography:

Ruqiang Yan received the M.S. degree in precision instrument and machinery from the University of Science and Technology of China, Hefei, China, in 2002, and the Ph.D. degree in mechanical engineering from the University of Massachusetts at Amherst, Amherst, MA, USA, in 2007.

He was a Guest Researcher at the National Institute of Standards and Technology (NIST) in 2006-2008 and a Professor with the School of Instrument Science and Engineering, Southeast University, Nanjing, China from 2019 to 2018. He joined the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China, in 2018. His research interests include energy-efficient sensing, data analytics, and artificial intelligence for the condition monitoring, fault diagnosis and prognosis of large-scale, complex, dynamical systems.

Dr. Yan is a Fellow of IEEE (2022) and ASME (2019). His honors and awards include the IEEE Instrumentation and Measurement Society Distinguished Service Award in 2022, and Technical Award in 2019, and multiple best paper awards. Dr. Yan is the Editor-in-Chief of the IEEE Transactions on Instrumentation and Measurement, and Editorial Board Member of several other journals.

Affiliation:

Xi'an Jiaotong University, China, Country China     

Email:    yanruqiang@xjtu.edu.cn

Email:

Address: Xi'an Jiaotong University, , China