Genetic Algorithm Based Sensor Placement Optimization and Modal identification for Truss Structure Satellite

In this paper, the energy signals received by sensors are used as the sensor placement optimization principle, and the genetic algorithm (GA) is used to optimize the placement of sensors installed on the truss structure. In order to achieve better optimization results and avoid the same variable values in the individual after genetic evolution, compared with the traditional constraints imposed on genetic algorithm, this paper uses the degree of information redundancy between each installation point as the constraint condition. After the sensor placement is optimized, the sensors output the deformation information of the truss structure as the outputs of the system, and the modal identification of the satellite truss structure is carried out by using observer Kalman filter identification (OKID) and eigensystem realization algorithm (ERA) methods. Finally, the sensor placement is optimized, which can meet the identification accuracy requirements.