Identifying Damage Sensitive Features Using Nonlinear Time- Series and Bispectral Analysis

The process of implementing a damage detection strategy for aerospace, civil, and mechanical engineering systems is called structural health monitoring. Vibration-based damage detection is receiving considerable attention from the research community for such monitoring. Recent research has recognized that the process of vibration-based structural health monitoring is fundamentally one of statistical pattern recognition. This process is composed of four steps: 1.) Operational evaluation; 2.) Data acquisition and cleansing; 3.) Feature selection and data compression, and 4.) Statistical model development. This paper focuses on the development of damage sensitive features in systems exhibiting nonlinear response. Two features extraction methods are emphasize; nonlinear time-series analysis and bispectral analysis. These techniques are applied to data from a concrete column that was progressively damaged by quasi-static cyclic loading.