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 […]

Siemens collaboration with School of Engineering recognised in THE Award #THEAwards

The Siemens collaboration with the University of Lincoln School of Engineering was recognised last night with the Times Higher Education award for Outstanding Employer Engagement. The collaboration with Siemens Industrial Turbomachinery Lincoln kicked off in 2009 with the founding of the first new School of Engineering in the UK for more than 20 years. The […]