Structural Health Monitoring Using Genetic Fuzzy Systems

Pawar, Prashant M.; Ganguli, Ranjan

ISBN 10: 1447159683 / ISBN 13: 9781447159681

Editore: Springer London Ltd, 2014

The high profile of structural health monitoring (SHM) will add urgency to this detailed treatment of intelligent SHM development and implementation via the evolutionary system, which uses a genetic algorithm to automate the development of the fuzzy system. Num Pages: 140 pages, 25 black & white tables, biography. BIC Classification: TBJ; TGB; TNKX; TRP; TTBM. Category: (G) General (US: Trade). Dimension: 235 x 155 x 8. Weight in Grams: 226. . 2014. Paperback. . . . . Books ship from the US and Ireland. Codice articolo V9781447159681

Riassunto:

Structural 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 structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems.

Dalla quarta di copertina:

Structural 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.

Dati bibliografici

Titolo: Structural Health Monitoring Using Genetic ...
Casa editrice: Springer London Ltd
Data di pubblicazione: 2014
Legatura: Brossura
Condizione: New