Novel Sensing Networks for Intelligent Monitoring (Newton)
Lead Research Organisation:
Newcastle University
Department Name: Electrical, Electronic & Computer Eng
Abstract
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.
Planned Impact
The project aims to provide a step change in condition, health and environmental monitoring by developing and applying novel intelligent autonomous technologies, in order to reduce the risk of structural failure and to achieve advanced Operation and Maintenance (O&M) strategies. The impacts of this project can be assessed in the four aspects of knowledge, economy, society, and people as outlined below.
Knowledge - The project will deliver new autonomous monitoring systems with intelligent information and infrastructure management. This will achieve scientific advances in a range of areas including sensor and WSNs, NDE and SHM, digital signal processing, and software architecture etc., which all fit in the new EPSRC's investment plan. The fundamental topics to be addressed by the project will be of interest to academics working in the priority areas of renewable energy (tidal/wave/wind), water management, and automotive/aerospace where reliability and fault diagnosis are of prime concerns.
Economy - The project addresses a number of fundamental technology development areas which are critical in the scenarios identified in the call. As a direct benefit, a demonstration system for condition monitoring of railway or nuclear plants will be established near the end of project. The research outcomes will yield knowledge transfer into other scenarios and sectors. These include, for example, the use of 'sensor-on-board' to monitor fatigue cracks, stress, and hidden corrosion in aircrafts for BAE systems and the condition monitoring of offshore wind farms. Based on the results achieved in this project, the consortium will seek further funding from TSB, ETI, and EU for further demonstration projects. Structural system developers will benefit from the project when determining their preventative and predictive O&M strategies. This is very important for the UK to lead in high value service and manufacturing in the world.
Society - The safety and reliability of industrial plants and processes will improve as the result of the introduction of SHM. Long term deployment strategies for O&M will benefit from the application of intelligent condition & health monitoring techniques developed in this project. This will lead to a safe and healthy environment so as to bring benefits to society. The improved O&M strategies also have an impact on sustainability.
People - The PDRAs and academic investigators will benefit from the research studies, obtaining new experience and knowledge, as will the industrial collaborators who will have the opportunity to become closely involved in world leading research studies. Researchers outside the consortium will also benefit from the outcomes through the project's dissemination activities. This is essentially a 'Shaping Capability' project with defined research scenarios and in close collaboration with industrial partners. Through the project and associated industrial collaborations, research 'leaders' will be 'sharper' in focus. Many emerging areas such as cloud computing and Internet of Things (IoT) will reach to a better developed states. Some PDRAs in this project may work as academics after the project finishes. This will enhance the UK academic capacity in these areas.
Knowledge - The project will deliver new autonomous monitoring systems with intelligent information and infrastructure management. This will achieve scientific advances in a range of areas including sensor and WSNs, NDE and SHM, digital signal processing, and software architecture etc., which all fit in the new EPSRC's investment plan. The fundamental topics to be addressed by the project will be of interest to academics working in the priority areas of renewable energy (tidal/wave/wind), water management, and automotive/aerospace where reliability and fault diagnosis are of prime concerns.
Economy - The project addresses a number of fundamental technology development areas which are critical in the scenarios identified in the call. As a direct benefit, a demonstration system for condition monitoring of railway or nuclear plants will be established near the end of project. The research outcomes will yield knowledge transfer into other scenarios and sectors. These include, for example, the use of 'sensor-on-board' to monitor fatigue cracks, stress, and hidden corrosion in aircrafts for BAE systems and the condition monitoring of offshore wind farms. Based on the results achieved in this project, the consortium will seek further funding from TSB, ETI, and EU for further demonstration projects. Structural system developers will benefit from the project when determining their preventative and predictive O&M strategies. This is very important for the UK to lead in high value service and manufacturing in the world.
Society - The safety and reliability of industrial plants and processes will improve as the result of the introduction of SHM. Long term deployment strategies for O&M will benefit from the application of intelligent condition & health monitoring techniques developed in this project. This will lead to a safe and healthy environment so as to bring benefits to society. The improved O&M strategies also have an impact on sustainability.
People - The PDRAs and academic investigators will benefit from the research studies, obtaining new experience and knowledge, as will the industrial collaborators who will have the opportunity to become closely involved in world leading research studies. Researchers outside the consortium will also benefit from the outcomes through the project's dissemination activities. This is essentially a 'Shaping Capability' project with defined research scenarios and in close collaboration with industrial partners. Through the project and associated industrial collaborations, research 'leaders' will be 'sharper' in focus. Many emerging areas such as cloud computing and Internet of Things (IoT) will reach to a better developed states. Some PDRAs in this project may work as academics after the project finishes. This will enhance the UK academic capacity in these areas.
Organisations
- Newcastle University (Lead Research Organisation)
- Sellafield (United Kingdom) (Co-funder)
- Schlumberger (United Kingdom) (Co-funder)
- Defence Science and Technology Laboratory (Co-funder)
- United Kingdom Space Agency (Co-funder)
- Network Rail (Co-funder, Collaboration)
- BAE Systems (United Kingdom) (Co-funder)
- National Nuclear Laboratory (Collaboration)
- Rolls Royce Group Plc (Collaboration)
- ZONARE Medical Systems, Inc. (Collaboration)
- University of Sheffield (Collaboration)
- UNIVERSITY OF YORK (Collaboration)
- Cybula (United Kingdom) (Project Partner)
Publications
Sophian A
(2017)
Pulsed Eddy Current Non-destructive Testing and Evaluation: A Review
in Chinese Journal of Mechanical Engineering
Chen H
(2020)
Intelligent early structural health prognosis with nonlinear system identification for RFID signal analysis
in Computer Communications
Ge L
(2020)
Electrodes Optimization of an Annular Flow Electromagnetic Measurement System for Drilling Engineering
in IEEE Access
Ge L
(2020)
Electromagnetic Flow Detection Technology Based on Correlation Theory
in IEEE Access
Arcadius Tokognon C
(2017)
Structural Health Monitoring Framework Based on Internet of Things: A Survey
in IEEE Internet of Things Journal
Gao S
(2020)
A B-Spline Method With AIS Optimization for 2-D IoT-Based Overpressure Reconstruction
in IEEE Internet of Things Journal
Gao S
(2019)
A Novel Distributed Linear-Spatial-Array Sensing System Based on Multichannel LPWAN for Large-Scale Blast Wave Monitoring
in IEEE Internet of Things Journal
Zhang J
(2018)
Feature Extraction for Robust Crack Monitoring Using Passive Wireless RFID Antenna Sensors
in IEEE Sensors Journal
Sunny A
(2019)
Temperature Independent Defect Monitoring Using Passive Wireless RFID Sensing System
in IEEE Sensors Journal
Wen D
(2019)
Extraction of LOI Features From Spectral Pulsed Eddy Current Signals for Evaluation of Ferromagnetic Samples
in IEEE Sensors Journal
Ona D
(2020)
Investigation of Signal Conditioning for Tx-Rx PEC Probe at High Lift-Off Using a Modified Maxwell's Bridge
in IEEE Sensors Journal
Yan Y
(2020)
A Deep Learning-Based Ultrasonic Pattern Recognition Method for Inspecting Girth Weld Cracking of Gas Pipeline
in IEEE Sensors Journal
Omer M
(2018)
Passive UHF RFID Tag as a Sensor for Crack Depths
in IEEE Sensors Journal
Hu P
(2019)
Wireless Localization of Spallings in Switch-Rails With Guided Waves Based on a Time-Frequency Method
in IEEE Sensors Journal
Daura L
(2019)
Wireless Power Transfer Based Non-Destructive Evaluation of Cracks in Aluminum Material
in IEEE Sensors Journal
Yuan F
(2021)
Investigation of DC Electromagnetic-Based Motion Induced Eddy Current on NDT for Crack Detection
in IEEE Sensors Journal
Buhari M
(2019)
Microwave-Based SAR Technique for Pipeline Inspection Using Autofocus Range-Doppler Algorithm
in IEEE Sensors Journal
Zhao A
(2017)
Miniaturization of UHF RFID Tag Antenna Sensors for Corrosion Characterization
in IEEE Sensors Journal
Cao B
(2020)
Noncontact Thickness Measurement of Multilayer Coatings on Metallic Substrate Using Pulsed Terahertz Technology
in IEEE Sensors Journal
Chen X
(2019)
Investigation of Skewness Feature for Evaluation of Defects Using Eddy Current Pulsed Thermography
in IEEE Sensors Journal
Alamin M
(2012)
Principal Component Analysis of Pulsed Eddy Current Response From Corrosion in Mild Steel
in IEEE Sensors Journal
Wu Y
(2020)
Research on Moisture Content Detection of Wood Components Through Wi-Fi Channel State Information and Deep Extreme Learning Machine
in IEEE Sensors Journal
Du C
(2020)
A High-Accuracy Least-Time-Domain Mixture Features Machine-Fault Diagnosis Based on Wireless Sensor Network
in IEEE Systems Journal
Zhang J
(2016)
UHF RFID Tag Antenna-Based Sensing for Corrosion Detection & Characterization Using Principal Component Analysis
in IEEE Transactions on Antennas and Propagation
Chen L
(2014)
Iterative Detection-Decoding of Interleaved Hermitian Codes for High Density Storage Devices
in IEEE Transactions on Communications
Gao B
(2018)
Physics-Based Image Segmentation Using First Order Statistical Properties and Genetic Algorithm for Inductive Thermography Imaging.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Tang C
(2017)
Smart Compressed Sensing for Online Evaluation of CFRP Structure Integrity
in IEEE Transactions on Industrial Electronics
Li K
(2019)
AR-Aided Smart Sensing for In-Line Condition Monitoring of IGBT Wafer
in IEEE Transactions on Industrial Electronics
Zhu J
(2018)
Probability of Detection for Eddy Current Pulsed Thermography of Angular Defect Quantification
in IEEE Transactions on Industrial Informatics
Zhang X
(2019)
CFRP Impact Damage Inspection Based on Manifold Learning Using Ultrasonic Induced Thermography
in IEEE Transactions on Industrial Informatics
Zhu J
(2021)
Characterization of Rolling Contact Fatigue Cracks in Rails by Eddy Current Pulsed Thermography
in IEEE Transactions on Industrial Informatics
Wang Y
(2018)
Thermal Pattern Contrast Diagnostic of Microcracks With Induction Thermography for Aircraft Braking Components
in IEEE Transactions on Industrial Informatics
Zhu J
(2019)
Comparison Study of Different Features for Pocket Length Quantification of Angular Defects Using Eddy Current Pulsed Thermography
in IEEE Transactions on Instrumentation and Measurement
Tang C
(2020)
Feature-Supervised Compressed Sensing for Microwave Imaging Systems
in IEEE Transactions on Instrumentation and Measurement
Hodge V
(2015)
Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey
in IEEE Transactions on Intelligent Transportation Systems
Adewale I
(2013)
Decoupling the Influence of Permeability and Conductivity in Pulsed Eddy-Current Measurements
in IEEE Transactions on Magnetics
Yuan F
(2020)
Investigation on Velocity Effect in Pulsed Eddy Current Technique for Detection Cracks in Ferromagnetic Material
in IEEE Transactions on Magnetics
Marindra A
(2018)
Chipless RFID Sensor Tag for Metal Crack Detection and Characterization
in IEEE Transactions on Microwave Theory and Techniques
Ran Y
(2019)
Physical layer authentication scheme with channel based tag padding sequence
in IET Communications
Liu F
(2019)
Investigations for inclination angle characterization of angular defects using eddy current pulsed thermography
in Infrared Physics & Technology
Gao S
(2016)
High-Performance Wireless Piezoelectric Sensor Network for Distributed Structural Health Monitoring
in International Journal of Distributed Sensor Networks
Qiu F
(2021)
Correlation of magnetic field and stress-induced magnetic domain reorientation with Barkhausen Noise
in Journal of Magnetism and Magnetic Materials
Liu J
(2019)
Domain wall characterization inside grain and around grain boundary under tensile stress
in Journal of Magnetism and Magnetic Materials
Li P
(2018)
System identification-based frequency domain feature extraction for defect detection and characterization
in NDT & E International
Si D
(2019)
Variational mode decomposition linked wavelet method for EMAT denoise with large lift-off effect
in NDT & E International
Fan M
(2017)
Pulsed eddy current thickness measurement using phase features immune to liftoff effect
in NDT & E International
Yi Q
(2019)
New features for delamination depth evaluation in carbon fiber reinforced plastic materials using eddy current pulse-compression thermography
in NDT & E International
Peng J
(2015)
Investigation into eddy current pulsed thermography for rolling contact fatigue detection and characterization
in NDT & E International
Zhang J
(2017)
Passive RFID sensor systems for crack detection & characterization
in NDT & E International
Hodge VJ
(2016)
Hadoop neural network for parallel and distributed feature selection.
in Neural networks : the official journal of the International Neural Network Society
Description | RFID sensors and Communication, LF, HF and UHF RFIDs have been investigated; RFID sensor network and demonstration are developed in conjunction with industries. Chipless RFID sensors have been demonstrated for crack and corrosion sensing and monitoring in the first time. Nonlinear signal processing for pulsed eddy current and UT signal feature extraction and identification More applications link to Big data management and ICT infrastructure e.g. IOTs are investigated. More applications for running gears have been granted |
Exploitation Route | Further research and demonstration link to industries e.g. Network Rail, National Nuclear Lab, British Steel, CRRC (for Chinese railway). It has been proposed for security application including e-passport. More research initiatives such as Engineering Grand Challenges, Robotics and Autonomous Systems, H2020 should be explored. Further international funded projects have been funded e.g. NSFC and Chinese industries in oil and gas pipelines and running gears for high speed railways. |
Sectors | Aerospace, Defence and Marine,Agriculture, Food and Drink,Construction,Digital/Communication/Information Technologies (including Software),Electronics,Energy,Healthcare,Government, Democracy and Justice,Manufacturing, including Industrial Biotechology,Retail,Security and Diplomacy,Transport,Other |
URL | http://research.ncl.ac.uk/newton/ |
Description | RFID sensors have been applied for nuclear plant monitoring, design and development of innovative wagons through shift2rail. Through our publication, British Steel has approached us for integration of RFID and sensing together for rail track asset management for HS2. More publications and research projects are prepared. RFID sensors have been applied for oil and gas pipeline industry. RFID sensors have been applied for running gears. |
Sector | Aerospace, Defence and Marine,Agriculture, Food and Drink,Construction,Digital/Communication/Information Technologies (including Software),Electronics,Energy,Healthcare,Manufacturing, including Industrial Biotechology,Retail,Transport,Other |
Impact Types | Societal,Economic |
Description | Commission of the European Communities |
Amount | £425,000 (GBP) |
Funding ID | CONHEALTH 2576737 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 04/2012 |
End | 04/2016 |
Description | EMAT based Pipeline integrity |
Amount | £62,000 (GBP) |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 09/2016 |
End | 03/2017 |
Description | EPSRC IAA 3D eddy current thermography |
Amount | £58,835 (GBP) |
Funding ID | EP/K503885/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2016 |
End | 03/2017 |
Description | Game changer Proposal and Poster |
Amount | £5,000 (GBP) |
Organisation | National Nuclear Laboratory |
Sector | Public |
Country | United Kingdom |
Start | 10/2016 |
End | 03/2017 |
Description | NDTonAIR: Training Network in Non-Destructive Testing and Structural Health Monitoring of Aircraft structures |
Amount | £189,034 (GBP) |
Funding ID | 722134 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 05/2017 |
End | 04/2020 |
Description | NSFC Key International Project (2020-2024): Intelligent Sensing & Monitoring of Running Gears |
Amount | ¥2,540,000 (CNY) |
Funding ID | 61960206010 |
Organisation | National Science Foundation China |
Sector | Public |
Country | China |
Start | 01/2020 |
End | 12/2024 |
Description | The British Council grant for the UK-China-BRI Countries Education Partnership Initiative |
Amount | £160,000 (GBP) |
Funding ID | CN_BJS-1_PartnershipFund |
Organisation | British Council |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2020 |
End | 12/2024 |
Description | USMART - smart dust for large scale underwater wireless sensing |
Amount | £400,000 (GBP) |
Funding ID | EP/P017975/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 02/2017 |
End | 01/2020 |
Description | GE PII |
Organisation | ZONARE Medical Systems, Inc. |
Country | United States |
Sector | Private |
PI Contribution | Knowledge transfer through KTP |
Collaborator Contribution | KTP |
Impact | Ongoing |
Start Year | 2016 |
Description | NNL |
Organisation | National Nuclear Laboratory |
Country | United Kingdom |
Sector | Public |
PI Contribution | Win gamechanger proposal and partnership for Robotics and Autonomous Systems |
Collaborator Contribution | partnership for Robotics and Autonomous Systems |
Impact | Develop poster and a proposal |
Start Year | 2010 |
Description | Network Rail |
Organisation | Network Rail Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Joint tests and case studies |
Collaborator Contribution | Industrial problems, samples |
Impact | Joint studies |
Start Year | 2012 |
Description | Rolls-Royce plc |
Organisation | Rolls Royce Group Plc |
Country | United Kingdom |
Sector | Private |
Start Year | 2008 |
Description | University of Sheffield |
Organisation | University of Sheffield |
Department | Automatic Control and Systems Engineering |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Feature extraction and signal processing |
Collaborator Contribution | Part of Newton project |
Impact | Multi-disciplinary and complementary |
Start Year | 2013 |
Description | University of York |
Organisation | University of York |
Country | United Kingdom |
Sector | Academic/University |
Start Year | 2007 |
Description | Panellist in ENDE 2015 |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The 20th International Workshop on Electromagnetic NonDestructive Evaluation, ENDE2015, was successfully held at the Katahira Sakura Hall, Tohoku University, Sendai, Japan, 21-23, September. A keynote lecture by Professor Gerd Dobmann titled 'Global trend of ENDE studies' was held on 22nd to review the development of studies of electromagnetic non-destructive evaluations in the last couple of decades. The recent trends of the studies were then discussed in a subsequent panel session titled 'ET&ENDE - Where we are and where we want to go?' where three distinguished professors, Professor Antonello Tamburrino, Professor Gui Yui Tian, and Professor Lalita Udpa, were invited as panelists. |
Year(s) Of Engagement Activity | 2015 |