Open AccessImproved multi-objective sensor optimization method for structural damage identification based on genetic algorithm
Author(s) -
Jun Zhang,
Kun Zhang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/780/3/032022
Subject(s) - genetic algorithm , sensitivity (control systems) , identification (biology) , algorithm , computer science , modal , mathematical optimization , meta optimization , structural health monitoring , noise (video) , inverse problem , bridge (graph theory) , optimization problem , mathematics , engineering , structural engineering , artificial intelligence , mathematical analysis , chemistry , electronic engineering , polymer chemistry , image (mathematics) , biology , medicine , botany
An improved multi-objective sensor location optimization method based on genetic algorithm is proposed. According to the analytic relationship between structural response, mode shapes and damage quantities, the sensitivity matrix of structural dynamic response containing both structural modal information and damage information is firstly constructed, and then the objective function of multi-objective sensor location optimization method is established according to the minimum identification error criterion and the principle of ill- posedness in the inverse problem. In addition, a multi-objective genetic algorithm, NSGA-II, is used to solve the optimal location of measurement points. Finally, a simply supported box girder bridge is studied for validating the proposed method. Numerical simulations show that the improved optimization method based on genetic algorithm can achieve the optimization goal better, and the measurement points optimized by the improved method can get better damage identification results at the same level of measurement noise.