A Novel Non-Probabilistic Sensor Placement Method for Structural Health Monitoring Using an Iterative Multiobjective Optimization Algorithm

A novel non-probabilistic sensor placement method for structural health monitoring is proposed with interval numbers based on the relationship of interval for sensor number (RISEN) index, and an iterative multiobjective optimization algorithm is constituted to optimize sensor placement. To avoid the limitation of scarce statistical information, the interval objectives of effective independence and eigenvalue vector product methods are derived. To overcome the inaccuracy of sensor number decisions using the determinate methods in uncertain cases, the novel RISEN index is defined to ascertain the best sensor number. Considering the number and locations of sensors as two types of design variables, two methods are regarded as optimization objectives, which are composed of the multiobjective optimal sensor placement methods. Based on the modified hypervolume evaluation index, an iterative multiobjective optimization algorithm is investigated using the updating process to improve the efficiency of the sensor placement. The validity of the method is proven using four examples.