000 02856nam a22003735i 4500
001 281300
003 MX-SnUAN
005 20160429154059.0
007 cr nn 008mamaa
008 150903s2011 xxk| o |||| 0|eng d
020 _a9780857299079
_99780857299079
024 7 _a10.1007/9780857299079
_2doi
035 _avtls000334024
039 9 _a201509030243
_bVLOAD
_c201404300253
_dVLOAD
_y201402041138
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTA349-359
100 1 _aPawar, Prashant M.
_eautor
_9306866
245 1 0 _aStructural Health Monitoring Using Genetic Fuzzy Systems /
_cby Prashant M. Pawar, Ranjan Ganguli.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2011.
300 _aviii, 130 páginas 39 ilustraciones, 1 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aIntroduction -- Genetic Fuzzy Systems -- SHM of Beams -- SHM of Composite Beams -- SHM of Helicopter Rotors.
520 _aStructural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: • SHM of beams; • SHM of composite tubes; and • SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structural components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aGanguli, Ranjan.
_eautor
_9306867
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780857299062
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-85729-907-9
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c281300
_d281300