Novel Sensing Networks for Intelligent Monitoring (Newton)

Completed

Nuclear Fission and Fusion(Nuclear Fission, Other nuclear fission)
Not Energy Related

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials)
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering)

Not Cross-cutting

Professor GY Tian
Electrical, Electronic & Computer Eng
Newcastle University

Standard

EPSRC

01 July 2012

31 December 2016

54 months

£1,175,282

Mechanical engineering

North East

NC : Engineering

Professor GY Tian, Electrical, Electronic & Computer Eng, Newcastle University

Professor J Austin, Computer Science, University of York
Dr Z Ding, Electrical, Electronic & Computer Eng, Newcastle University
Dr TJ Dodd, Automatic Control and Systems Engineering, University of Sheffield
Dr Z Lang, Automatic Control and Systems Engineering, University of Sheffield
Mr JA Neasham, Electrical, Electronic & Computer Eng, Newcastle University

Project Contact, Cybula Ltd

This proposal seeks funding for a four-year research programme to develop an autonomous, intelligent system to obtain a revolutionary solution for condition/structural health intelligent monitoring, with specific applications in condition monitoring of railways and in-service Non-Destructive Evaluation (NDE) for nuclear applications. This project addresses important goals: low cost and low power consumption sensor networks, sensor exploration, software architectures, autonomous data fusion and intelligent system management, spectrally efficient and reliable communications with novel approaches of radio frequency identification (RFID) based passive sensing networks, non-linear feature extraction and model based fusion, compressed sensing, cloud-based computing and decision making. The research will extend our knowledge in several complementary areas: low cost sensor technologies, wireless sensor network (WSN) for NDE and structural health monitoring (SHM), feature extraction and fusion, robust communication, and software architectures. The work will be undertaken jointly by cross-disciplinary research teams from Newcastle, Sheffield and York Universities, in collaboration with industrial strategic partners

23/07/12