The structural health monitoring (SHM) benchmark study on optimal sensorplacement for the Canton Tower, sponsored by the Asia-Pacific Network of Centersfor Research in Smart Structures Technology (ANCRiSST), is first detailed in thispaper. Then a two-step information entropy-based algorithm for sensor placementoptimization is performed on the benchmark model. In the first step, mode shapechange due to damage is extracted through modal analysis on the benchmark structure.In the second step, information entropy index is introduced to measure theuncertainties over the damage detection for each mode shape change, and then a multiobjectiveminimization problem in terms of different sensor placements is constructed.The optimal solution is determined as the one that provides almost equally informativedata for all objectives. To validate the effectiveness of the determined optimal sensorplacement, damage detection is performed on damage scenarios of the benchmarkmodel using pre- and post-damage mode shapes obtained from the selected sensorplacement. The results show that the obtained sensor configuration is able to provideinformation sensitive to damage.
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