On Self-organising Diagnostics in Impact Sensing Networks

Autor:	Vadim Gerasimov, Don Price, Nigel Hoschke, Peter Wang, Mikhail Prokopenko, Andrew Scott
Rok vydání:	2005
Předmět:	Acoustic emission Artificial neural network Computer science business.industry Test vector Real-time computing Prognostics Structural health monitoring Artificial intelligence business Energy (signal processing)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783540288978 KES (4)
Popis:	Structural health management (SHM) of safety-critical structures requires multiple capabilities: sensing, assessment, diagnostics, prognostics, repair, etc. This paper presents a capability for self-organising diagnosis by a group of autonomous sensing agents in a distributed sensing and processing SHM network. The diagnostics involves acoustic emission waves emitted as a result of a sudden release of energy during impacts and detected by the multi-agent network. Several diagnostic techniques identifying the nature and severity of damage at multiple sites are investigated, and the self-organising maps (Kohonen neural networks) are shown to outperform the standard k-means algorithm in both time- and frequency domains.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2ccfcf9891480f8c5cb7045ad99dfcea https://doi.org/10.1007/11554028_25 Zobrazit plný text záznamu