Structural Health Monitoring Using Genetic Fuzzy Systems

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.

Inhaltsverzeichnis

Introduction.- Genetic Fuzzy Systems.- SHM of Beams.- SHM of Composite Beams.- SHM of Helicopter Rotors.

Zusammenfassung

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.

Produktdetails

• Autoren: Ranjan Ganguli, Prashant Pawar, Prashant M Pawar, Prashant M. Pawar
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Taschenbuch
• Erschienen: 01.01.2014
• EAN: 9781447159681
• ISBN: 978-1-4471-5968-1
• Seiten: 132
• Abmessung: 158 mm x 235 mm x 9 mm
• Gewicht: 225 g
• Illustration: VIII, 132 p.
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Technik > Maschinenbau, Fertigungstechnik; B, astronautics, engineering, Civil Engineering, Signal, Image and Speech Processing, Mathematical and Computational Engineering, Solid Mechanics, Signal Processing, Mechanics, Mechanics, Applied, Engineering mathematics, Applied mathematics, Mathematical and Computational Engineering Applications, Maths for engineers, Aerospace engineering, Aerospace Technology and Astronautics, Aerospace & aviation technology, Civil engineering, surveying & building, Speech processing systems, Digital and Analog Signal Processing, Imaging systems & technology, Image processing, Building repair, Conservation of buildings & building materials, Building Repair and Maintenance, Buildings—Repair and reconstruction