Identification of Sudden Stiffness Change in the Acceleration Response of a Nonlinear Hysteretic Structure

Abstract EN

The integration of discrete wavelet transform and independent component analysis (DWT-ICA) method can directly identify time-varying changes in linear structures.

However, better metrics of structural seismic damage and future performance after an event are related to structural permanent and total plastic deformations.

This study proposes a two-stage technique based on DWT-FastICA and improved multiparticle swarm coevolution optimization (IMPSCO) using a baseline nonlinear Bouc–Wen structural model to directly identify changes in stiffness caused by damage as well as plastic or permanent deflections.

In the first stage, the measured structural dynamic responses are preprocessed firstly by DWT, and then the Fast ICA is used to extract the feature components that contain the damage information for the purpose of initially locating damage.

In the second stage, the structural responses are divided at the identified damage instant into segments that are used to identify the time-varying physical parameters by using the IMPSCO, and the location and extent of damage can accordingly be identified accurately.

The efficiency of the proposed method in identifying stiffness changes is assessed under different ground motions using a suite of two different ground acceleration records.

Meanwhile, the effect of noise level and damage extent on the proposed method is also analyzed.

The results show that in a realistic scenario with fixed filter tuning parameters, the proposed approach identifies stiffness changes within 1.25% of true stiffness within 8.96 s; therefore, it can work in real time.

Parameters are identified within 14% of the actual as-modeled value using noisy simulation-derived structural responses.

This indicates that, in accordance with different demands, the proposed method can not only locate and quantify damage within a short time with a high precision but also has excellent noise tolerance, robustness, and practicality.