Optimal sensor placement in structural health monitoring using discrete optimization

• Published in: Smart materials and structures Vol. 24; no. 12; pp. 125034 - 16
• Main Authors: Sun, Hao, Büyüköztürk, Oral
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.12.2015
• Subjects: Algorithms; discrete optimization; Dynamical systems; Health monitoring (engineering); iterated improved reduced system; Mathematical models; modal assurance criterion; optimal sensor placement; Optimization; Reduced order models; Sensors; Structural health monitoring
• ISSN: 0964-1726; 1361-665X
• DOI: 10.1088/0964-1726/24/12/125034

The objective of optimal sensor placement (OSP) is to obtain a sensor layout that gives as much information of the dynamic system as possible in structural health monitoring (SHM). The process of OSP can be formulated as a discrete minimization (or maximization) problem with the sensor locations as the design variables, conditional on the constraint of a given sensor number. In this paper, we propose a discrete optimization scheme based on the artificial bee colony algorithm to solve the OSP problem after first transforming it into an integer optimization problem. A modal assurance criterion-oriented objective function is investigated to measure the utility of a sensor configuration in the optimization process based on the modal characteristics of a reduced order model. The reduced order model is obtained using an iterated improved reduced system technique. The constraint is handled by a penalty term added to the objective function. Three examples, including a 27 bar truss bridge, a 21-storey building at the MIT campus and the 610 m high Canton Tower, are investigated to test the applicability of the proposed algorithm to OSP. In addition, the proposed OSP algorithm is experimentally validated on a physical laboratory structure which is a three-story two-bay steel frame instrumented with triaxial accelerometers. Results indicate that the proposed method is efficient and can be potentially used in OSP in practical SHM.