Gallimore, Michael, Yang, Zhijing, Bingham, Chris , Stewart, Paul, James, N., Watson, S. and Latimer, A. (2011) Novelty detection for predictive maintenance scheduling for industrial gas turbines. In: International Conference on Mechanical Engineering and Technology (ICMET-London 2011), November 2011, London.
Full content URL: http://dx.doi.org/10.1115/1.859896.paper73
Full text not available from this repository.
| Item Type: | Conference or Workshop contribution (Presentation) |
|---|---|
| Item Status: | Live Archive |
Abstract
The paper presents results of an investigation to predict impending failure mechanisms of a gearbox drive train in the sub 15MW class of the Siemens gas turbine product range. Particular emphasis is given to the prediction of gearbox failures and inter-connected components. Experimental results from real-time data show that the application of SVM techniques provides an efficient basis for minimising the impact of unscheduled maintenance requirements, on product lifetime and cost for these units.
| Keywords: | Gas Turbine, Remote monitoring and sensing, predictive maintenance |
|---|---|
| Subjects: | H Engineering > H321 Turbine Technology |
| Divisions: | College of Science > School of Engineering |
| Related URLs: | |
| ID Code: | 6058 |
| Deposited On: | 18 Aug 2012 19:52 |
Repository Staff Only: item control page