Key dates and participating speakers
Tuesday 18 to Thursday 20 June 2024
Milton Hill House, Oxford, UK
| Key dates | |||
| Submission of proposals for structured sessions | 5 January 2024 | ||
| Deadline for structured session abstract submission | 2 February 2024 | ||
| Deadline for general abstract submission (not more than 200 words) | Still accepting (subject to availability) | ||
| Notification of abstract acceptance (not later than) | 29 March 2024 | ||
| Deadline for submission of full-length papers (to ensure publication of your paper you must adhere to this date; any papers submitted after this date will not be included) | 12 April 2024 | ||
| Notification of full-length paper acceptance (not later than) | 26 April 2024 | ||
| Early registration | 17 May 2024 | ||
| Speaker registration | 17 May 2024 | ||
| Plenary speakers |
| Speakers | Title | ||
| Dr S Babu | Enhancing asset integrity in the oil & gas industry through condition monitoring of storage infrastructures: a sensor-based approach | ||
| Professor I Baillie | Condition monitoring of aero engines: big data challenges and a comparison to NDT | ||
| M Behzad | Vibration feature selection for machinery condition monitoring | ||
| Dr J Griffaton | Health monitoring with vibrations at Safran Aircraft Engines: an overview of the ‘doing well’ and the ‘I would like’ | ||
| Dr M Khan | Non-contact-based sensing: fundamentals, impact and challenges | ||
| Professor Z Su | Ultra-fast laser ultrasonics-enabled multi-scale material characterisation | ||
| Distinguished Overview Speakers |
| Speakers | Title | ||
| M Behzad | Challenges in condition monitoring for industry, academics and standardisation organisations | ||
| Professor R Burdzik | Quantum physics and AI: current challenges and opportunities in technical diagnostics and condition monitoring | ||
| D Hickey and B Simmonds | Assessing the success or failure of a reliability engineering program in the wind industry | ||
| Professor J Lacaille | Automated defect detection in aeronautic materials using machine-learning and neural networks | ||
| Professor D Wang | Difference mode decomposition: the uniqueness of classical Fourier transform for machine condition monitoring | ||
| Structured session organisers |
| Speakers | Title | ||
| Professor L Gelman | Condition monitoring for renewable energy assets | ||
| General condition monitoring | |||
| S Greenfield | General condition monitoring | ||
| Dr J Griffaton | AI in condition monitoring | ||
| NDT and SHM | |||
| Professor A Hope | Vibration monitoring and analysis | ||
| General condition monitoring | |||
| Dr E Juuso | Advanced signal processing and diagnostics in condition monitoring | ||
| D Manning-Ohren | AI in condition monitoring | ||
| S Mills | Condition monitoring management, training and certification | ||
| Professor S Noroozi | Human dynamics and health related condition monitoring | ||
| Professor F Pellicano and Dr A Zippo | Innovations in signal processing and modelling for complex industrial systems | ||
| Dr A Rahbarimanesh | Data-driven and physics-based modelling for condition monitoring of industrial assets | ||
| Professor M Shafiee | Computer vision and deep learning for structural health monitoring of renewable energy | ||
| Professor D Wang | Advances in interpretable condition monitoring and diagnostic methods | ||
| D Whittle | Condition monitoring methods and technologies | ||
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
