Detecting Faults: Virtual Experts Bridge Gap in Engineering Industry
Intelligent software that can automatically detect system faults in industrial machines is being developed by researchers in a bid to assist current support engineers and plug an expanding skills gap in the engineering industry. The EVES (Evolutionary Virtual Expert System) project will see the design and development of an automated fault diagnostic system integrated into […]
Intelligent software that can automatically detect system faults in industrial machines is being developed by researchers in a bid to assist current support engineers and plug an expanding skills gap in the engineering industry.
The EVES (Evolutionary Virtual Expert System) project will see the design and development of an automated fault diagnostic system integrated into an industrial data platform, assisting engineers by speeding up communication responses and feedback of incoming site data.
The system is being created by researchers at the University of Lincoln in partnership with Siemens Industrial Turbomachinery Ltd, thanks to a First Investigator Award of almost £100,000 from the Engineering and Physical Sciences Research Council (EPSRC).
Using data provided by the industrial partner, the team at Lincoln will develop software to detect failures in gas turbines, using a combination of expert systems which have the ability to acquire experience, and other artificial intelligence techniques.
The systems will begin as ‘virtual apprentices’ who will be trained by human engineers through coaching, examining and refining processes until they are ready to be promoted to the ‘virtual experts’.
The virtual experts will ‘learn’ to make sound judgements, integrating the strengths of precision, learning ability, adaptability and knowledge sharing with other systems, matching and even outperforming human experts working without such support.
The project will be led by Dr Yu Zhang, from the University’s School of Engineering who specialises in intelligent industrial systems.
Dr Zhang said: “There are many well-known fault diagnostic systems in the field, but often they operate at a less practical level and work more individually.
“This project represents a first attempt at delivering an integrated automated fault diagnostic system for industrial applications using information extracted from all available algorithms and models of the mechanical system, together with critiques from human engineers.”
While this project looks specifically at faults in the gas turbines, it is hoped the technology could be applied more widely to all fault diagnostic systems, including those found in power plants, military weapons, the health service, and natural disaster monitoring.
The research will have important implications for many UK industries which are facing future skills gaps.
When the project is complete the virtual experts will be able to provide critical support for human engineers and, with further development, could go on to act as trainers for younger workers entering the profession. This will become increasingly important as the uptake of more modern technologies in the workplace lead to longer learning curves for young engineers.
The project will begin in September 2018 and run for 12 months.