Strategy for sensor number determination and placement optimization with incomplete information based on interval possibility model and clustering avoidance distribution index

Abstract A strategy for sensor number determination and placement optimization for structural health monitoring is proposed based on an interval possibility model and clustering avoidance distribution index. The performance of sensor configuration with optimum sensor number and less redundant information is primarily improved by considering two types of incomplete information simultaneously, namely uncertainty and redundancy. This study regards uncertainty as a non-probabilistic interval number to avoid the deficiency caused by the insufficient statistical distribution of uncertain structural parameters. As long as the bound of uncertainty is obtained, then a strategy for the sensor number can be determined using the interval possibility model and effective independence method. A novel redundant information elimination model is defined to reduce the redundant information caused by sensor clustering configuration, which considers the near neighbor distance, sensor configuration region and sensor number synchronously. Based on these two methods to address incomplete information in the sensor configuration field, the strategy for sensor placement optimization constitutes a novel combined fitness function, which comprises the effective independence method and clustering avoidance distribution index. Using the normalization and weighting factor, the combined fitness function is made more competitive by eliminating the order difference between the two objectives. Therefore, the best sensor number is suggested and the corresponding optimum sensor locations are achieved simultaneously using the genetic algorithm and the proposed strategy for sensor number and placement. The performance of sensor configuration and redundant information with incomplete information is balanced by the proposed strategy. Finally, the effectiveness of the proposed strategy and method is verified through three engineering numerical examples.