Advances in predictive maintenance and fault detection for Industry 4.0


Morello Rosario Morello

Rosario Morello

University Mediterranea of Reggio Calabria, Italy

Liu Zheng Liu

Zheng Liu

Faculty of Applied Science, The University of British Columbia, Canada


This Special Session intends to encourage the submission of original research papers concerning predictive maintenance, non-invasive diagnostic techniques, and status monitoring applications. Nowadays, transducers and measurement instrumentation are widely used for monitoring the status and faults of components and systems. Fault detection and predictive maintenance represent exciting research fields in the Industry 4.0 context; nevertheless, several perspectives and open research problems have to be investigated, such as data processing, sensor failure and reliability, interface and signal treatment standards, fault-tolerance, maintenance, calibration and traceability issues.

Therefore, this Special Session aims to collect manuscripts that will make significant contributions in the field of instrumentation and systems maintenance, fault detection and data processing addressed to reliable and non-invasive diagnosis or monitoring applications. Further topics concern the definition of procedures for maintenance and calibration, reliability and failure assessment.


The main topics include:

  • Predictive maintenance;
  • Fault detection;
  • Non-invasive sensor-based diagnostic techniques;
  • Virtual twins for fault detection;
  • Non-invasive monitoring of system performances;
  • Sensor array for health status monitoring;
  • Sensor data fusion;
  • Fault tolerance and reliability;
  • Maintenance and calibration;
  • Failure assessment;
  • Virtual twins;
  • Standards for transducers and sensors.

The Special Session aims to provide an overview of advances and the latest novel and emergent technologies, implementations and applications concerning predictive maintenance and fault diagnosis by using transducers and sensors, sensor networks and sensing systems.


Rosario Morello, was born in Reggio Calabria, Italy, in 1978. He received the M.Sc. Degree (cum laude) in Electronic Engineering and the Ph.D. Degree in Electrical and Automation Engineering from the University Mediterranea of Reggio Calabria, Italy, in 2002 and 2006, respectively. Since 2005, he has been temporary Professor of Electrical and Electronic Measurements at the Department DIIES of the same University. At the moment, he is Associate Professor and Scientific Director of the Advanced Thermography Center at Dept. DIIES, University Mediterranea of Reggio Calabria, Italy. His main research interests include advanced thermography, the design and characterization of distributed and intelligent measurement systems, wireless sensor network, decision-making problems and measurement uncertainty, process quality assurance, instrumentation reliability and calibration, biomedical applications and statistical signal processing, non-invasive systems, diagnostic algorithms, measurement instrumentation and methodologies related to Industry 4.0. Prof. Morello is a member of the Italian Group of Electrical and Electronic Measurements (GMEE).

Zheng Liu received a Doctorate in engineering from Kyoto University, Kyoto, Japan, in 2000 and a Ph.D. degree from the University of Ottawa, Canada, in 2007. From 2000 to 2001, he was a Research Fellow at Nanyang Technological University, Singapore. He then joined the Institute for Aerospace Research (IAR), National Research Council Canada, Ottawa, ON, Canada, as a Governmental Laboratory Visiting Fellow nominated by NSERC. After being with IAR for 5years, he transferred to the NRC Institute for Research in Construction, where he was a Research Officer. From 2012 to 2015, he worked as a full Professor at Toyota Technological Institute, Nagoya, Japan. He is currently a full professor at the School of Engineering at the University of British Columbia, Okanagan. His research interests include image/data fusion, computer vision, pattern recognition, industrial Internet of Things, digital twin, predictive maintenance, and non-destructive inspection and evaluation. He is a fellow of SPIE and a senior member of IEEE. He holds a Professional Engineer license in British Columbia and Ontario. Dr. Liu serves on the editorial board for journals: IEEE Transactions on AgriFood Electronics, IEEE Journal of RFID, Information Fusion, Machine Vision and Applications, and Non-destructive Testing and Evaluation.