Optimal statistical damage detection and classification in an experimental wind turbine blade using minimum instrumentation
| dc.contributor.author | Hoell, Simon | |
| dc.contributor.author | Omenzetter, Piotr | |
| dc.contributor.editor | Meyendorf, Norbert G. | |
| dc.contributor.institution | University of Aberdeen.Engineering | en |
| dc.contributor.institution | University of Aberdeen.Energy | en |
| dc.date.accessioned | 2017-09-12T11:00:37Z | |
| dc.date.available | 2017-09-12T11:00:37Z | |
| dc.date.issued | 2017-04-19 | |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 12 | |
| dc.format.extent | 3802005 | |
| dc.identifier | 104835175 | |
| dc.identifier | 244de867-b5b9-47b4-9e6e-cf54bfded606 | |
| dc.identifier | 85021821176 | |
| dc.identifier.citation | Hoell, S & Omenzetter, P 2017, Optimal statistical damage detection and classification in an experimental wind turbine blade using minimum instrumentation. in N G Meyendorf (ed.), Smart Materials and Nondestructive Evaluation for Energy Systems 2017. vol. 10171, 101710D, SPIE, Smart Materials and Nondestructive Evaluation for Energy Systems 2017, Portland, United States, 27/03/17. https://doi.org/10.1117/12.2257228 | en |
| dc.identifier.citation | conference | en |
| dc.identifier.doi | 10.1117/12.2257228 | |
| dc.identifier.isbn | 9781510608276 | |
| dc.identifier.uri | http://hdl.handle.net/2164/9287 | |
| dc.identifier.url | https://www.scopus.com/pages/publications/85021821176 | en |
| dc.language.iso | eng | |
| dc.publisher | SPIE | |
| dc.relation.ispartof | Smart Materials and Nondestructive Evaluation for Energy Systems 2017 | en |
| dc.subject | Damage classification | en |
| dc.subject | Principal component analysis | en |
| dc.subject | Statistical classification | en |
| dc.subject | Time series methods | en |
| dc.subject | Vibration analysis | en |
| dc.subject | Wind turbines | en |
| dc.subject | TA Engineering (General). Civil engineering (General) | en |
| dc.subject | Electronic, Optical and Magnetic Materials | en |
| dc.subject | Condensed Matter Physics | en |
| dc.subject | Computer Science Applications | en |
| dc.subject | Applied Mathematics | en |
| dc.subject | Electrical and Electronic Engineering | en |
| dc.subject.lcc | TA | en |
| dc.title | Optimal statistical damage detection and classification in an experimental wind turbine blade using minimum instrumentation | en |
| dc.type | Book item | en |
