Programme
Tuesday 18 to Thursday 20 June 2024
Milton Hill House, Oxford, UK
![](/admin/Images/CM2024/CM2024_WebpageHeader.jpg)
Sponsored by |
![]() | ![]() | ![]() | |
Reliability Maintenance Solutions | Sensonics Ltd | SpectraQuest Inc | |
Monday 17 June 2024 | |
16.00-19.00 | Registration – Room A: Wisteria |
19.00-21.00 | Welcome Buffet – Room: Pergola Tea and Coffee – Room: Pergola |
Tuesday 18 June 2024 | |||
08.00 | Registration – Room A: Wisteria Tea and Coffee – Room: Pergola Exhbition – Room A: Wisteria | ||
09.00-09.20 | Opening 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 | ||
09.20-09.50 | Plenary 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 | ||
09.50-10.20 | Exhibitor Spotlight Session 09.50-09.55 – SpectrumCBM Ltd 09.55-10.00 – RMS Ltd 10.00-10.05 – Yateks Co Ltd 10.05-10.10 – BINDT 10.10-10.15 – Faraday Predictive Ltd 10.15-10.20 – Sensonics Ltd Chair: Professor A Hope Room A: Wisteria | ||
10.20-11.00 | Tea and Coffee – Room: 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 non-linear oscillator integration for investigating Parkinsonian tremor dynamics through multi-body 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 | |
12.20-13.30 | Lunch – Room: Orchid Exhibition – Room A: Wisteria | ||
12.30-13.30 | International Scientific Advisory Committee Meeting (working lunch by invitation only) Room B: Crimson Birch | ||
13.30-14.00 | Plenary 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 | ||
14.00-14.10 | CM 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: D Whittle 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] Presentation cancelled due to ill health | |
14.50-15.10 | [2A3] Aero engine 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] Presentation cancelled due to ill health | |
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] Presentation cancelled due to ill health | |
15.30-15.50 | Tea and Coffee – Room: 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 | [3B4] The monitoring of exhaust particulate from a marine diesel engine J Harris Defence Science and Technology Group, Australia | |
16.50 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 | Registration – Room A: Wisteria Tea and Coffee – Room: Pergola Exhbition – Room A: Wisteria | ||
09.00-09.30 | Plenary Keynote Lecture [4A0]: Vibration feature selection for machinery condition monitoring Professor M Behzad, Iran 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] A case study in using motor current to diagnose a long-standing mystery in a seawater lift pump A Jones and A Bates 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 | |
10.30-11.10 | Tea 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] Presentation cancelled | |
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 | |
12.30-13.30 | Lunch – Room: Orchid Exhibition – Room A: Wisteria | ||
13.30-14.00 | Plenary Keynote Lecture [6A0]: Ultra-fast laser ultrasonics-enabled multi-scale material characterisation Professor Z Su, Hong Kong 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 – General condition monitoring 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 | ||
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 | |
15.20-15.40 | Tea and Coffee – Room: Pergola Exhibition – Room A: Wisteria | ||
Session A – Workshops Chair: S Greenfield Room A: Wisteria | |||
15.40-16.20 | Workshop – An introduction to oil debris monitoring technologies S Greenfield Anokhi Consulting Engineers, UK | ||
16.20-17.10 | Workshop – 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: Pergola Conference Dinner – Room A: Wisteria |
Thursday 20 June 2024 | |||
08.00 | Registration – Room A: Wisteria Tea and Coffee – Room: Pergola | ||
09.00-09.30 | Plenary 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: Professor L Gelman Room A: Wisteria | Session B – NDT and SHM Chair: Dr J Griffaton Room B: Crimson Birch | ||
09.30-09.50 | In search of information: application of vibroacoustic methods in transport engineering R Burdzik Silesian University of Technology, Poland | [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 | |
10.30-11.00 | Tea and Coffee – Room: Pergola | ||
Session A – General condition monitoring Chair: Professor L Gelman Room A: Wisteria | Session B – Maintenance Chair: D Whittle 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 | ||
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 | ||
12.00-12.30 | Plenary 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 | ||
12.30-13.30 | Panel Session: future directions in condition monitoring Chair: Professor L Gelman, University of Huddersfield, UK Room A: Wisteria | ||
13.30-13.35 | Conference Closing Ceremony and the Len Gelman Best Paper Award Ceremony Room A: Wisteria | ||
13.35-14.30 | Lunch – Room: Orchid |
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