Statistical Process Control and Projection Techniques for Structural Health Monitoring

This paper focuses on applying statistical process control techniques to vibration-based damage diagnosis. First, an auto-regressive (AR) model is fit to the measured acceleration-time histories from an undamaged structure. Coefficients of the AR model are selected as the damage-sensitive features for the subsequent control chart analysis. Finally, the AR coefficients of the models fit to subsequent new data are monitored relative to the control limits. A unique aspect of this study is the coupling of various projection techniques such as principal component analysis, linear and quadratic discriminant operators with the statistical process control in an effort to enhance the discrimination between features from the undamaged and damaged structures. This combined statistical procedure is applied to vibration test data acquired from a concrete bridge column as the column is progressively damaged. The coupled approach captures a clearer distinction between undamaged and damaged vibration responses.