A workshop called by Lincoln City Council convened today at the University of Lincoln to discuss the road map toward a Combined Heat and Power plant for Lincoln. Stakeholders including the University of Lincoln, Siemens and Lincolnshire County Council were in attendance, and will be moving forward to form a steering group to develop the […]
Professor Paul Stewart
CHP and Distributed Generation – the Lincoln Perspective
On Thursday this week I will be giving a short presentation at a workshop convened by the City of Lincoln council.The workshop title is A Decentralised Energy Solution for Lincoln. I will be placing activities in the School of Engineering with both Siemens and the City Council into context for the proposed project, and also […]
Decentralised Energy for Lincoln – Workshop Thursday 14th March
A growing number of areas in the UK have implemented decentralised energy to ensure a reliable and sustainable solution for future energy supply. With this in mind, and following an initial meeting in November 2012 hosted by Siemens, City of Lincoln Council is hosting a workshop to discuss decentralised energy options for Lincoln. We currently […]
Sensor Validation Research Publications on Siemens sponsored research
We run Remote Monitoring and Sensing (RMS) and Sensor Validation projects with Siemens Industrial Turbomachinery as part of our remit as Preferred University Partner. The Remote Monitoring and Sensing project is a rolling work-programme which focuses on the research, development and application of data-analysis tools for the on-line determination of a wide-range of unit failure […]
Applied sensor fault detection and identification using hierarchical clustering and SOMNNs, with faulted-signal reconstruction
Yu Zhang; Bingham, C.; Zhijing Yang; Gallimore, M.; Stewart, P., “Applied sensor fault detection and identification using hierarchical clustering and SOMNNs, with faulted-signal reconstruction,” MECHATRONIKA, 2012 15th International Symposium , vol., no., pp.1,7, 5-7 Dec. 2012 keywords: {computerised instrumentation;fault diagnosis;neural nets;numerical analysis;pattern clustering;sensors;signal classification;signal reconstruction;SFD-I graphical interpretation;SOMNN;applied sensor fault detection;applied sensor fault identification;classification map fingerprint;dendrograms;faulted-signal […]