Damage Localisation Using Symbolic Time Series Approach

Abstract

The objective of this paper is to localise damage in a single or multiple state at early stages of development based on the principles of symbolic dynamics. Symbolic Time Series Analysis (STSA) of noise-contaminated responses is used for feature extraction to detect and localise a gradually evolving deterioration in the structure according to the changes in the statistical behaviour of symbol sequences. The method consists of four primary steps: (1) generating the time series data by a set of measurements over time at evenly spaced locations along the structure; (2) creating the symbol space to generate symbol sequences based on the wavelet transformed version of time series data; (3) developing the symbol probability vectors to achieve anomaly measures; (4) localising damage based on any sudden variation in anomaly measure of two adjacent locations. The method was applied to a clamped–clamped beam subjected to random excitation in presence of 5 % white noise to examine the efficiency and limitations of the method. Simulation results under various damage conditions confirmed the efficiency of the proposed approach for localisation of gradually evolving deterioration in the structure, however, for the future work the method needs to be verified by experimental data.