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Indexed by:期刊论文

Date of Publication:2015-04-01

Journal:STRUCTURAL ENGINEERING AND MECHANICS

Included Journals:SCIE、EI、Scopus

Volume:54

Issue:2

Page Number:305-317

ISSN No.:1225-4568

Key Words:optimal sensor placement; monkey algorithm; artificial fish swarm algorithm; collaborative-climb; modal assurance criterion

Abstract:Optimal sensor placement (OSP) is an integral component in the design of an effective structural health monitoring (SHM) system. This paper describes the implementation of a novel collaborative-climb monkey algorithm (CMA), which combines the artificial fish swarm algorithm (AFSA) with the monkey algorithm (MA), as a strategy for the optimal placement of a predefined number of sensors. Different from the original MA, the dual-structure coding method is adopted for the representation of design variables. The collaborative-climb process that can make the full use of the monkeys' experiences to guide the movement is proposed and incorporated in the CMA to speed up the search efficiency of the algorithm. The effectiveness of the proposed algorithm is demonstrated by a numerical example with a high-rise structure. The results show that the proposed CMA algorithm can provide a robust design for sensor networks, which exhibits superior convergence characteristics when compared to the original MA using the dual-structure coding method.