Programme

Tuesday 18 to Thursday 20 June 2024
Milton Hill House, Oxford, UK 



  Sponsorsored by



Reliability Maintenance Solutions
Sensonics LtdSpectraQuest Inc
   
Monday 17 June 2024
16.00-19.00
RegistrationRoom A: Wisteria
19.00-21.00Welcome Buffet – Room: Pergola
Tea and Coffee – Room: Pergola


Tuesday 18 June 2024
08.00
RegistrationRoom A: Wisteria
Tea and CoffeeRoom: Pergola
Exhbition – Room A: Wisteria
09.00-09.20Opening Ceremony – Welcome and introduction
Professor L Gelman, UK, D Gilbert, UK, and Dr S Baboo, Singapore

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria
09.20-09.50Plenary Keynote Lecture [1A0]: Health monitoring with vibrations at Safran Aircraft Engines: an overview of the ‘doing well’ and the ‘I would like’
J Griffaton, France

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria
09.50-10.20Exhibitor Spotlight Session
09.50-09.55 – JME Ltd
09.55-10.00 – Oceanscan Ltd
10.00-10.05 – SpectrumCBM Ltd
10.05-10.10 – RMS Ltd
10.10-10.15 – Yateks Co Ltd
10.15-10.20 – BINDT

Chair: Professor A Hope
Room A: Wisteria
10.20-11.00Tea and CoffeeRoom: Pergola
Exhibition – Room A: Wisteria

Session A – Data-driven and physics-based modelling for condition monitoring of industrial assets

Chair: Dr A Rahbarimanesh
Room A: Wisteria
Session B – Innovations in signal processing and modelling for complex industrial systems

Chairs: Professor F Pellicano and Dr A Zippo
Room B: Crimson Birch
11.00-11.20[1A1] Application of machine learning in computational fluid dynamics-based design and optimisation of turboexpanders used in natural gas pressure reduction stations

S Rahbarimanesh¹, A Nejat², A Rahbarimanesh³ and S Mousavi²
¹University of British Columbia, Canada
²University of Tehran, Iran
³University of Manchester, UK
[1B1] Lateral bearing stiffness effect on the spiral bevel gear non-linear vibration response

F Samani¹,², M Molaie², S Rakhshani¹, M Asadi¹, R Ebrahimnejad², A Zippo², G Iarriccio² and F Pellicano²
¹Shahid Bahonar University of Kerman, Iran
²University of Modena and Reggio Emilia, Italy
11.20-11.40[1A2] Machine learning-enabled decision support system (ML-DSS) for asset condition monitoring

A Rahbarimanesh¹, M Burrows² and S Rahbarimanesh³
¹University of Manchester, UK
²RS Group plc, UK
³University of British Columbia, Canada
[1B2] Dynamical response of electrical transmission system

R Ebrahimnejad, M Molaei, G Iarriccio, A Zippo and F Pellicano
University of Modena and Reggio Emilia, Italy
11.40-12.00[1A3] Project nautilUS +: a fully autonomous robotic technology for smart floor thickness monitoring of hazardous liquid storage tanks

A Rahbarimanesh¹ and M Burrows²
¹University of Manchester, UK
²RS Group plc, UK
[2B2] Matsuoka nonlinear oscillator integration for investigating Parkinsonian tremor dynamics through multibody simulation

A Zippo and F Pellicano
University of Modena and Reggio Emilia, Italy
12.00-12.20[1A4] Extending B-COSFIRE for automatic extraction of craquelure

M Fernandes¹,², R Araújo¹, G Almeida¹ and S Paredes²
¹JTA – The Data Scientists, Portugal
²Polytechnic Institute of Coimbra, Portugal

[1B3] Fault diagnosis for rotating machine based on Mel spectrogram and residual neural network

F Tu, S Yang and J Yang
Sichuan University, China
12.20-13.30Lunch – Room: Hotel Restaurant
Exhibition – Room A: Wisteria
12.30-13.30International Scientific Advisory Committee Meeting (working lunch by invitation only)
Room A: Wisteria
13.30-14.00Plenary Keynote Lecture [2A0]: Enhancing asset integrity in the oil & gas industry through condition monitoring of storage infrastructures: a sensor-based approach
Dr S Babu, Singapore

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria

14.00-14.10CM Book Update
Professor A Hope, UK

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria


Session A – Advances in interpretable condition monitoring and diagnostic methods

Chair: Professor D Wang

Room A: Wisteria
Session B – Induction and PM motor condition monitoring and diagnostics

Chairs: Dr S Ganeriwala

Room B: Crimson Birch
14.10-14.30[2A1] Interpretable fusion methodology of health indices and multi-dimensional analogue on complex industrial turbine cavitation condition monitoring

Y Fu¹, D Wang¹ and Z Peng¹,²
¹Shanghai Jiao Tong University, China
²Ningxia University, China

[1B4] Distinguished Overview Lecture: Difference mode decomposition: the uniqueness of classical Fourier transform for machine condition monitoring

D Wang
Shanghai Jiao Tong University, China
14.30-14.50[2A2] Composite health index construction for online monitoring based on control chart performance optimisation

Y Wang, D Wang and B Hou
Shanghai Jiao Tong University, China

[2B1] Application of minimum entropy decomposition rolling element bearing fault analysis in a permanent magnet motor

S Ganeriwala
SpectraQuest Inc, USA

14.50-15.10[2A3] Aeroengine remaining life prediction based on grey similarity multi-scale matching

S Sun¹,², H Huang¹, J Ding¹, W Lu¹,² and D Wang³
¹Harbin Institute of Technology, China
²Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, China
³Shanghai Jiao Tong University, China

[2B3] Developing a digital twin model for a centrifugal pump opportunity and challenges

S Ganeriwala
SpectraQuest Inc, USA

15.10-15.30[2A4] Gaussian assumptions free interpretable linear discriminant analysis for machine condition monitoring

Y Chen and D Wang
Shanghai Jiao Tong University, China

[2B4] Failure mode and slip frequency analysis in induction motors

S Ganeriwala
SpectraQuest Inc, USA

15.30-15.50Tea and CoffeeRoom: Pergola
Exhibition – Room A: Wisteria

Session A – Computer vision and deep learning for structural health monitoring of renewable energy

Chair: Professor M Shafiee

Room A: Wisteria
Session B – Condition monitoring methods and technologies

Chair: D Whittle

Room B: Crimson Birch
15.50-16.10[3A1] Computer vision and deep learning for structural health monitoring of wind turbines

M Shafiee
University of Surrey, UK

[3B1] A concise review of transfer learning and generative learning for autonomous and robotic systems fault detection and diagnosis

C Li and L Zhang
University of Manchester, UK

16.10-16.30[3A2] Monitoring mooring lines of floating offshore wind turbines: autoregressive coefficients and stacked auto-associative deep neural networks

S Sharma¹ and V Nava¹,²
¹Basque Center for Applied Mathematics, Spain
²Tecnalia, Spain

[3B2] Gearbox fault detection method under unseen working conditions and damage

S Wang, Y Vidal and F Pozo
Universitat Politècnica de Catalunya, Spain

16.30-16.50[3A3] The application of the process capability index (PCI) in a fatigue test of a tidal turbine blade using historic and real-time load data

M Munko, K Connolly, F Cuthill, M Valdivia Camacho,
E McCarthy and S Lopez Dubon
University of Edinburgh, UK

[3B3] Gas path analysis of a two-shaft gas turbine engine by utilising multi-operating point conditions and bank of Kalman filters

S Abyaneh
Mapna Group, Iran

16.50-17.10[3A4]

THIS SLOT IS AVAILABLE FOR A LATE SUBMISSION
[3B4] The monitoring of exhaust particulate from a marine diesel engine

J Harris
Defence Science and Technology Group, Australia

17.10

17.15
Conference close for the day

Evening event – Walking tour of Oxford City Centre and a meal at the Côte Restaurant. This is a ticketed event. If you wish to attend but do not have a ticket, please contact the BINDT registration desk. This is subject to availability, as places are limited. Please assemble at the main entrance to Milton Hill House to leave at approximately 17.15.


Wednesday 19 June 2024
08.00
RegistrationRoom A: Wisteria
Tea and CoffeeRoom: Pergola
Exhbition – Room A: Wisteria
09.00-09.30Plenary Keynote Lecture [4A0]: Artificial intelligence (AI) and its applications: a future perspective
W Mansoor, UAE

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria

Session A – Condition monitoring management, training and certification

Chair: S Mills
Room A: Wisteria
Session B – AI in condition monitoring


Chair: D Manning-Ohren
Room B: Crimson Birch
09.30-09.50[4A1] Condition monitoring and failure analysis of a liquefied natural gas plant cryogenic heavies removal column reflux pump

E Pereira
Glasgow Caledonian University, UK
[4B1] Alleviating limited dataset in inter-shaft bearing fault diagnosis based on multi-source information with information discriminator

Y Yu and H R Karimi
Politecnio di Milano, Italy
09.50-10.10[4A2] Title to be confirmed

G Walker
Faraday Predictive Ltd, UK
[4B2] A post-hoc analysis of deep learning approach for cracks identification in concrete structures

M Sohaib¹, M Junayed Hasan² and Z Zheng¹
¹Zhejiang Normal University, China
²Robert Gordon University, UK
10.10-10.30[4A3] Effective conference presenting

S Mills
SpectrumCBM Ltd, UK
[4B3] Enhancing gas pipeline monitoring with graph neural networks: a new approach for acoustic emission analysis under variable pressure conditions

M Junayed Hasan¹, M Arifeen¹, M Sohaib², A Rohan¹
and S Kannan¹
¹Robert Gordon University, UK
²Zhejiang Normal University, China
10.30-11.10Tea and Coffee – Room: Pergola
Exhibition – Room A: Wisteria

Session A – General condition monitoring

Chair: Professor A Hope
Room A: Wisteria
Session B – AI in condition monitoring

Chair: Dr J Griffaton
Room B: Crimson Birch 
11.10-11.30[5A1] Visualising vibration: a ‘gamechanger’ for troubleshooting, diagnostics and root cause analysis

D Whittle
RMS Ltd, UK

[5B1] Modelling of the vibratory response of an aircraft engine using AI

J Gomez and J Griffaton
Safran Aircraft Engines, France
11.30-11.50[5A2] Update on ISO standards in condition monitoring

S Mills
SpectrumCBM Ltd, UK

[5B2] Anomaly detection for complex equipment monitoring

J Becu, C Thirard, B Wascat and T Mazoyer
Acoem, France

Session A – Vibration monitoring and analysis


Chair: Professor A Hope
Room A: Wisteria
Session B – Human dynamics and health-related condition monitoring

Chair: Professor S Noroozi
Room B: Crimson Birch 
11.50-12.10[5A3] Mind the gap

D Manning-Ohren
Eriks, UK

[5B3] Cadaveric testing of a novel sensor for non-destructive load balancing in total knee replacements (TKRs)

S Al-Nasser, S Noroozi and A Harvey
Bournemouth University, UK

12.10-12.30[5A4] Instrumentation condition monitoring vibration and failure analysis of screw air compressor package in liquefied natural gas plant

E Pereira
Glasgow Caledonian University, UK

[5B4] The need for monitoring deltoid tension and shoulder kinematics during a total reverse shoulder arthroplasty (RSA)

S Noroozi, N Aslani, S Al-Nasser and R Hartley
Bournemouth University, UK

12.20-13.30Lunch – Room: Hotel Restaurant
Exhibition – Room A: Wisteria
13.30-14.00Plenary Keynote Lecture [6A0]: Ultra-fast laser-enabled ultrasonic material characterisation and AI-facilitated quality monitoring in additive manufacturing
Professor Z Su, China

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria


Session A – General condition monitoring


Chair: S Greenfield

Room A: Wisteria
Session B – Advanced signal processing and diagnostics in condition monitoring

Chair: Dr E Juuso

Room B: Crimson Birch
14.00-14.20[6A1] Criticality, risk assessment and cost-effective condition monitoring examples

S Greenfield
Anokhi Consulting Engineers, UK

[6B1] Natural language-based information in intelligent condition monitoring and control

E Juuso
University of Oulu, Finland

14.20-14.40[6A2] Varnish in oil: the true amount

R Cutler
Oil Analysis Laboratories, UK

[6B2] Estimation of remaining useful life (RUL) of rolling element bearings based on the adaptive kernel Kalman filter

Z Li, R Zhu, T Verwimp, H Wen and K Gryllias
KU Leuven, Belgium


Session A – General condition monitoring continued

Chair: S Greenfield

Room A: Wisteria
Session B – Title to be confirmed

Chair: to be confirmed

Room B: Crimson Birch
14.40-15.00[6A3] Monitoring energy recovery in a full-scale fatigue test

M Munko¹, S Lopez Dubon¹, F Cuthill¹, W Rampen¹
and C Ó Brádaigh²
¹University of Edinburgh, UK
²University of Sheffield, UK

[6B3] Condition monitoring of aero engines: big data challenges and a comparison to NDT

I Baillie
Rolls-Royce plc, UK

15.00-15.20[6A4] Impulsive mode decomposition and its four application cases to impulsive signal extraction

B Hou and D Wang
Shanghai Jiao Tong University, China

[6B4] Long-term ferritic steel pipeline monitoring at 500°C: ultrasonic sensors (EMATs) for accurate thickness monitoring

N Lunn¹, M Potter¹ and S Dixon²
¹Sonemat Ltd, UK
²University of Warwick, UK

15.20-15.40Tea and CoffeeRoom: Pergola
Exhibition – Room A: Wisteria

Session A – Title to be confirmed

Chair: to be confirmed

Room A: Wisteria

15.40-16.20Workshop – An introduction to oil debris monitoring technologies

S Greenfield
Anokhi Consulting Engineers, UK

16.20-17.10Workshop – Vibration analysis diagnostics and case study challenge

D Whittle
RMS Ltd, UK

17.10


19.30
20.00
Conference close for the day

Evening event:
Pre-dinner drinks
– Room B: Crimson Birch
Conference Dinner – Room B: Crimson Birch

Thursday 20 June 2024
08.00
RegistrationRoom A: Wisteria
Tea and CoffeeRoom: Pergola
09.00-09.30Plenary Keynote Lecture [7A0]: Non-contact-based sensing: fundamentals, impact and challenges
Dr M Khan, UK

Chair: Professor A Hope, UK
Room A: Wisteria

Session A – General condition monitoring

Chair: to be confirmed
Room A: Wisteria
Session B – NDT and SHM

Chair: Dr J Griffaton
Room B: Crimson Birch
09.30-09.50[7A1] Distinguished Overview Lecture: Deep information fusion for mechanical fault diagnosis

H R Karimi
Politecnico di Milano, Italy
[7B1] Non-destructive evaluation of debonding in composites using air-coupled coda wave analysis and local defect resonance techniques

Z Li and J Jiao
Beijing University of Technology, China
09.50-10.10[7A2] Artificial intelligence on wind turbines

T Lau
Sensonics Ltd, UK
[7B2] Construction of tensile curves via conformal prediction

D Razafindrakoto¹,², A Celisse¹, J Lacaille², L Sadeg Martelet² and F Corpace²
¹Université Paris 1 Panthéon-Sorbonne, France
²Safran Aircraft Engines, France
10.10-10.30[7A3] Distinguished Overview Lecture: Challenges in condition monitoring for industry, academics and standardisation organisations

M Behzad¹ and L Gelman²
¹Sharif University of Technology, Iran
²University of Huddersfield, UK

[7B3] Distinguished Overview Lecture: Automated defect detection in aeronautic materials using machine learning and neural networks

J Lacaille
Safran Aircraft Engines, France

10.30-11.00Tea and Coffee – Room: Pergola

Session A – General condition monitoring

Chair: Professor L Gelman
Room A: Wisteria
Session B – Maintenance

Chair: to be confirmed
Room B: Crimson Birch
11.00-11.20[8A1] Distinguished Overview Lecture: Quantum physics and artificial intelligence: current challenges and opportunities in technical diagnostics and condition monitoring

R Burdzik
Silesian University of Technology, Poland

[8B1] An individual report reviewing the current maintenance effectiveness of a safety-critical site (ABC Chemical Manufacturers)

J Watkinson, A Ompusunggu and J Orson
Cranfield University, UK
11.20-11.40[8A2] Novel condition monitoring technologies via motor current signature analysis

L Gelman
University of Huddersfield, UK

[8B2]

THIS SLOT IS AVAILABLE FOR A LATE SUBMISSION
11.40-12.00[8A3] Distinguished Overview Lecture: Assessing the success or failure of a reliability engineering programme in the wind industry

D Hickey and B Simmonds
Natural Power, UK

[8B3]

THIS SLOT IS AVAILABLE FOR A LATE SUBMISSION
12.00-12.30Plenary Keynote Lecture [9A0]: Condition monitoring of aero engines: big data challenges and a comparison to NDT
Professor I Baillie, UK

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria

12.30-13.30Panel session: future directions in condition monitoring
Speaker(s) to be confirmed

Chair: Professor L Gelman, University of Huddersfield, UK
Room A: Wisteria

13.30-13.35Conference closing ceremony and The Len Gelman Best Paper Award ceremony
Room A: Wisteria
13.35-14.30Lunch – Room: Hotel Restaurant

For further information contact: Events and Awards Department, The British Institute of Non-Destructive Testing,
Midsummer House, Riverside Way, Bedford Road, Northampton NN1 5NX, UK.
Tel: +44 (0)1604 438300; Email: cm_mfpt@bindt.org; Web: www.cm-mfpt.org