Multicopters Workshop 2020: Book Your Place Now!
Registration is now open for the Workshop on Multicopters for Inspection, taking place on Wednesday 1 July 2020 at the Park Inn by Radisson Hotel and Conference Centre, London Heathrow, UK. This event is organised by the British Institute of Non-Destructive Testing (BINDT) and will run alongside the Seventeenth International Conference on Condition Monitoring and Asset Management (CM 2020) taking place from Tuesday 30 June to Thursday 2 July 2020.
This event follows on from the successful 2018 workshop and will present delegates with information about the current progress of developments for multicopters, commonly known as drones, for carrying out aerial inspections of industrial and other assets.
Multicopters are increasingly being used to conduct inspections of locations that are difficult to access or hostile to human inspectors. Great cost savings have been made through the use of multicopters when compared to traditional inspection methods that often require scaffolding to be erected.
Drones can carry high-resolution cameras, thermal imaging equipment or light detection and ranging (LIDAR) equipment. Recent developments include the deployment of ultrasonic sensors to take thickness measurements of remote components.
The aim of the workshop is to inform delegates of the legal, safety and training requirements, supported by case studies of a variety of applications, including oil & gas, wind turbines, rail, power generation and distribution.
The fee of £80.00 + VAT (BINDT Member rate) or £90.00 + VAT (non-member rate) covers attendance at the one-day workshop, including tea/coffee breaks and lunch. For further information or to download a booking form visit: https://www.bindt.org/events/Seminars-and-Workshops/workshop-on-multicopters-for-inspection/
For information about the CM 2020 conference visit: https://www.cm-mfpt.org
The British Institute of Non-Destructive Testing (BINDT) is a UK-based professional engineering institution working to promote the advancement of the science and practice of non-destructive testing (NDT), condition monitoring (CM), diagnostic engineering and all other materials and quality testing disciplines. Internationally recognised, it is concerned with the education, training and certification of its members and all those engaged in NDT and CM and through its publications and annual conferences and events it disseminates news of the latest advances in the science and practice of the subjects. For further information about the Institute and its activities, visit http://www.bindt.org
What are NDT and CM?
Non-destructive testing is the branch of engineering concerned with all methods of detecting and evaluating flaws in materials. Flaws can affect the serviceability of a material or structure, so NDT is important in guaranteeing safe operation as well as in quality control and assessing plant life. The flaws may be cracks or inclusions in welds and castings or variations in structural properties, which can lead to a loss of strength or failure in service. The essential feature of NDT is that the test process itself produces no deleterious effects on the material or structure under test. The subject of NDT has no clearly defined boundaries; it ranges from simple techniques such as the visual examination of surfaces, through the well-established methods of radiography, ultrasonic testing and magnetic particle crack detection, to new and very specialised methods such as the measurement of Barkhausen noise and positron annihilation spectroscopy.
Condition monitoring (CM) aims to ensure plant efficiency, productivity and reliability by monitoring and analysing the wear of operating machinery and components to provide an early warning of impending failure, thereby reducing costly plant shutdown. Condition monitoring originally used mainly vibration and tribology analysis techniques but now encompasses new fields such as thermal imaging, acoustic emission and other non-destructive techniques. The diagnostic and prognostic elements, in addition to increasingly sophisticated signal processing, is using trends from repeated measurements in time intervals of days and weeks.