Methodology for Optimum Sensor Locations for Parameter Identification in Dynamic Systems

This paper provides a methodology for optimally locating sensors in a dynamic system so that data acquired from those locations will yield the best identification of the parameters to be identified. It addresses the following questions: (1) Given m sensors, where should they be placed in a spatially distributed dynamic system so that data from those locations will yield best estimates of the parameters that need to be identified?; and (2) given that we have already installed p sensors in a dynamic system, where should the next s be located? The methodology is rigorously founded on the Fisher information matrix and is applicable to both linear and nonlinear systems. A rapid algorithm is provided for use in large multi‐degree‐of‐freedom systems. After developing the general methodology, the paper goes on to develop the method in detail for a linear N‐degree‐of‐freedom, classically damped, system. Numerical examples are provided and it is verified that the optimal placement of sensors, as dictated by the met...