SUMMARYIn this paper, a Bayesian sequential sensor placement algorithm, based on the robust information entropy, is proposed for multi-type of sensors. The presented methodology has two salient features. It is a holistic approach such that the overall performance of various types of sensors at different locations is assessed. Therefore, it provides a rational and effective strategy to design the sensor configuration, which optimizes the use of various available resources. This sequential algorithm is very efficient due to its Bayesian nature, in which prior distribution can be incorporated. Therefore, it avoids the possible unidentifiability problem encountered in a sequential process, which starts with small number of sensors. The proposed algorithm is demonstrated using a shear building and a lattice tower with consideration of up to four types of sensors.

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Model updating of dynamical systems has been attracting much attention because it has a very wide range of applications in aerospace, civil, and mechanical engineering, etc. Many methods were developed and there has been substantial development in Bayesian methods for this purpose in the recent decade. This article introduces some state-of-the-art work. It consists of two main streams of model updating, namely model updating using response time history and model updating using modal measurements. The former one utilizes directly response time histories for the identification of uncertain parameters. In particular, the Bayesian time-domain approach, Bayesian spectral density approach and Bayesian fast Fourier transform approach will be introduced. The latter stream utilizes modal measurements of a dynamical system. The method introduced here does not require a mode matching process that is common in other existing methods. Afterwards, discussion will be given about the relationship among model complexity, data fitting capability and robustness. An application of a 22-story building will be presented. Its acceleration response time histories were recorded during a severe typhoon and they are utilized to identify the fundamental frequency of the building. Furthermore, three methods are used for analysis on this same set of measurements and comparison will be made.