Dr Graeme West

Senior Lecturer

Electronic and Electrical Engineering

Personal statement

I am a Senior Lecturer in the department of Electronic and Electrical Engineering, having been appointed through the Chancellor's Fellowship scheme.  My research interests lie in the area of intelligent decision support, primarily for applications in the Energy Industry, and with a particular focus on through lifetime management of nuclear power generation assets.  This covers a broad range of disciplines ranging from artificial intelligence, machine learning, & data analytics through to image and video processing.  Application areas include inspection, condition monitoring, diagnostics and prognostics of plant items, both from individual asset and fleet wide perspectives.  I am an academic lead in the University’s Advanced Nuclear Research Centre (ANRC).

My current projects at the University include improving understanding of the graphite reactor cores of Advanced Gas-cooled Reactors (AGR) through analysis of refuelling data (EDF Energy), Automated sizing and classification of defects in CANDU reactor pressure tubes (Bruce Power), improved visual inspection of AGR fuel channel bricks (EDF Energy) and visual inspection of steel pipe work in the nuclear industry (NNL, Sellafield, WideBlue, Inspecta-hire).

 

Expertise

Has expertise in:

    • Intelligent Systems and Artificial Intelligence
    • Data Analytics and Machine Learning
    • Condition Monitoring, Diagnostics and Prognostics
    • Nuclear power generation instrumentation and control

Publications

Improved online localisation of CANDU duel defects using ancillary data sources and neural networks
Wallace Christopher, McEwan Curtis, West Graeme, Aylward William, McArthur Stephen
Nuclear Technology Vol 206, pp. 697-705 (2020)
https://doi.org/10.1080/00295450.2019.1697174
A new approach for crack detection and sizing in nuclear reactor cores
Devereux Michael G, Murray Paul, West Graeme M
Nuclear Engineering and Design Vol 359 (2020)
https://doi.org/10.1016/j.nucengdes.2019.110464
A novel assessment of delayed neutron detector data in CANDU reactors
Aylward Will, Wallace Christopher, West Graeme, McEwan Curtis
Journal of Nuclear Engineering and Radiation Science (2020)
Error analysis and calibration for a novel pipe profiling tool
Jackson William, Dobie Gordon, MacLeod Charles, West Graeme, Mineo Carmelo, McDonald Liam
IEEE Sensors Journal (2019)
https://doi.org/10.1109/JSEN.2019.2960939
3-D visualization of AGR fuel channel bricks using Structure-from-Motion
Law Kristofer, West Graeme, Murray Paul, Lynch Chris
Nuclear Engineering and Design (2019)
Elasticity measurement of soft tissues using hybrid tactile and MARG based displacement sensor systems
Hampson Rory, Dobie Gordon, West Graeme
IEEE Sensors Journal Vol 19, pp. 10262-10270 (2019)
https://doi.org/10.1109/JSEN.2019.2930207

More publications

Teaching

I am 2nd Year Adviser of Studies for the BEng/MEng Electronic and Electrical Engineering undergraduate degree courses.

i am module registrar for EM501: Fifth Year Group Projects for the MEng Electrical and Mechanical Engineering Students.

I am responsible for the 2nd year EE/EM271 Sensor and Signal Processing Laboratory where the students design and build an instrument for measuring the thickness of steel using an ultrasonic transducer.

I am module registrar for the 3rd Year EM310: Signal and Systems course which covers the concepts and analysis of signals in both the time and frequency domains in the context of both analogue and discrete (digital) domains, baoth in terms of mathematical analysis and practical systems.

I teach a 5-week module on "Intelligent Condition Monitoring" as part of ME507 Machinery Diagnosis and Condition Monitoring.

Research interests

My research interests are in the design and application of artificial intelligence techniques to support the management of key engineering assets in a number of industries.  I have a particular focus in nuclear power generation applications and my research supports EDF Energy, who run and maintain the UK's Civil nuclear power stations, in analysing data that comes from their graphite reactor cores.  

Professional activities

Panel Session on PHM Applications in Power Generation
Speaker
30/7/2020
Artificial Intelligence in Nuclear Power Generation Applications
Speaker
13/7/2020
American Nuclear Society (ANS) Human Factors (External organisation)
Advisor
1/5/2020
Innovation in Automated Assessment of Pressure Tube Defects
Speaker
9/5/2019
The Advanced Nuclear Research Centre: Industrial informatics for supporting through-life nuclear asset management
Speaker
21/3/2019
Harnessing Data Science for Industrial Value: Successes, Experience and Lessons Learned from the Electrical Energy Sector
Speaker
15/5/2018

More professional activities

Projects

KTP - ICR Integrity
West, Graeme (Principal Investigator) McArthur, Stephen (Co-investigator)
27-Jan-2020 - 26-Jan-2022
Image Processing for Enhanced Visual Inspection of Nuclear Waste Packages GC142 Phase 2
Murray, Paul (Principal Investigator) Marshall, Stephen (Co-investigator) Ren, Jinchang (Co-investigator) West, Graeme (Co-investigator) Zabalza, Jaime (Research Co-investigator)
01-Jan-2020 - 31-Jan-2020
Doctoral Training Partnership 2018-19 University of Strathclyde | Fagan, Andrew
West, Graeme (Principal Investigator) McArthur, Stephen (Co-investigator) Fagan, Andrew (Research Co-investigator)
01-Jan-2019 - 01-Jan-2023
ANRC -04 Advanced Image Processing Techniques for In-core Inspections
West, Graeme (Principal Investigator) Murray, Paul (Co-investigator)
01-Jan-2018 - 31-Jan-2021
Insptectahire - OGIC
Dobie, Gordon (Principal Investigator) MacLeod, Charles Norman (Co-investigator) Rana, Shuvendu (Co-investigator) West, Graeme (Co-investigator)
03-Jan-2018 - 31-Jan-2020
ANRC 001 Ext Automated Classification and Sizing of Pressure Tube Defects Phase IV - GATED - YEAR 2
West, Graeme (Principal Investigator) Dobie, Gordon (Co-investigator) Gachagan, Anthony (Co-investigator)
During routine inspections of CANDU nuclear reactors a selected subset of the pressure tubes which house the nuclear fuel are inspected ultrasonically. This generates a large volume of data which has to be manually assessed. In this project, we are examining the applicability of automated intelligent analysis techniques to support the manual sizing and classification of any observed defects.
01-Jan-2017 - 30-Jan-2019

More projects

Address

Electronic and Electrical Engineering
Royal College Building

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