Multi-Level Interval Estimation for Locating damage in Structures by Using Artificial Neural Networks

Abstract

A new analysis technique, called multi‐level interval estimation method, is developed for locating damage in structures. In this method, the artificial neural networks (ANN) analysis method is combined with the statistics theory to estimate the range of damage location. The ANN is multilayer perceptron trained by back‐propagation. Natural frequencies and modal shape at a few selected points are used as input to identify the location and severity of damage. Considering the large‐scale structures which have lots of elements, multi‐level interval estimation method is developed to reduce the estimation range of damage location step‐by‐step. Every step, estimation range of damage location is obtained from the output of ANN by using the method of interval estimation. The next ANN training cases are selected from the estimation range after linear transform, and the output of new ANN estimation range of damage location will gained a reduced estimation range. Two numerical example analyses on 10‐bar truss and 100‐bar truss are presented to demonstrate the effectiveness of the proposed method.