SS15- Big Data Opportunities: System Health Monitoring and Management

Special Session Organized by

Dong Wang, Shanghai Jiao Tong University, China; Weiwen Peng, Sun Yat-sen University, China; Changqing Shen, Soochow University, China; Yang Zhao, City University of Hong Kong, Hong Kong, China;

The concept of system is generally defined as ‘an organized set of detailed methods, procedures and routines that are created to carry out a specific activity or solve a specific problem’, and that has been successfully applied to many domains, ranging from mechanical systems to public health systems. System health monitoring and management (SHMM) refers to the framework of continuous surveillance, analysis and interpretation of related data for system maintenance, management and strategic planning. This framework is essential to ensure that an entire system is stable and in control. A fundamental problem in SHMM is to study how to take advantage of correlated active and passive data to help prediction and forecasting, monitoring and surveillance, fault detection and diagnostics, engineering management, supply chain management, and many more. This special session aims to provide a platform to report advances in system health monitoring and management, discuss its relationship with other disciplines, and present its several applications to complex systems.

Topics of interest include, but are not limited to

• Intelligent operation and maintenance and big data analysis
• Prognostics and health management
• Statistical learning, machine learning and data mining
• Condition monitoring and fault diagnosis
• Deep learning
• Non-destructive testing
• Signal processing
• Dynamics
• Engineering management
• Supply chain management

Submissions Procedure

All the instructions for paper submission are included in the conference website indin2020.com.

Deadlines

Download Call for Papers

Click here to download this special session call for papers