Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm | Zendy

TingHua Yi | Zendy; HongNan Li | Zendy; Ming Gu | Zendy

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Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm

Author(s) -

TingHua Yi,

HongNan Li,

Ming Gu

Publication year - 2011

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2011/395101

Subject(s) - crossover , coding (social sciences) , algorithm , modal , structural health monitoring , genetic algorithm , mathematical optimization , binary number , convergence (economics) , computer science , mathematics , engineering , structural engineering , artificial intelligence , statistics , materials science , arithmetic , polymer chemistry , economics , economic growth

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale structures. Based on the criterion of the OSP for the modal test, an improved genetic algorithm, called “generalized genetic algorithm (GGA)”, is adopted to find the optimal placement of sensors. The dual-structure coding method instead of binary coding method is proposed to code the solution. Accordingly, the dual-structure coding-based selection scheme, crossover strategy and mutation mechanism are given in detail. The tallest building in the north of China is implemented to demonstrate the feasibility and effectiveness of the GGA. The sensor placements obtained by the GGA are compared with those by exiting genetic algorithm, which shows that the GGA can improve the convergence of the algorithm and get the better placement scheme

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