Title :
`NEURAL-MAINE´: intelligent on-line multiple sensor diagnostics for steam turbines in power generation
Author :
Harris, T. ; Gamlyn, L. ; Smith, P. ; MacIntyre, J. ; Brason, A. ; Palmer, R. ; Smith, H. ; Slater, A.
Author_Institution :
Neural Applications Group, Brunel Univ., Uxbridge, UK
Abstract :
Neural-Maine is a project under the European EUREKA-Maine (Maintaining Availability in Europe) initiative. The project is in its first of four years and has begun to develop a system for performing plant diagnosis for complex rotating machines such as steam turbines. The key advance involves the use of artificial neural networks for local sensory fusion of multiple transducers reporting to a committee network structure for interpretation and whole plant condition modelling. The work is being carried out by a consortia from the UK and Holland. The paper presents results from the feasibility study and the preliminary work in the development phase
Keywords :
fault diagnosis; machine testing; maintenance engineering; neural nets; sensor fusion; steam turbines; European EUREKA-Maine initiative; Holland; Neural-Maine; UK; artificial neural networks; committee network structure; complex rotating machines; intelligent on-line multiple sensor diagnostics; local sensory fusion; multiple transducers; plant diagnosis; power generation; steam turbines; whole plant condition modelling; Costs; Electric breakdown; Intelligent sensors; Machinery; Power generation; Predictive maintenance; Preventive maintenance; Production; Testing; Turbines;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487499
