Slender structure sensor optimization: A genetic algorithm approach
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Copyright 2015 by the International Society of Offshore and Polar Engineers (ISOPE). Extracting the desired modal information from an instrumented slender structure, while minimizing the number of sensors, is a challenging problem requiring well-defined objectives that can be used in an optimization process. In this study the use of a Genetic Algorithm approach that incorporates active recovery mode shape information was investigated. Data recorded from an experiment investigating the flow-induced vibration of a smooth horizontally towed cylinder was used in the optimization process. In addition to the smooth cylinder case, the data of a cylinder covered with buoyancy elements and helical strakes was also investigated to extend the approach to more complicated scenarios. The large number of fiber optic strain gage sensors used in measuring the motion response provided the opportunity to explore the recovery of mode shape information using single and multiple objective scenarios by varying the active sensor locations. The single objective examples illustrated the situations where only a specified number of sensors were available, and/or there were restrictions in placing the sensors. A two objective optimization case was also investigated that illustrates use of the Pareto Front Method.