Damage Classification in CFRP Laminates Using Principal Component Analysis (PCA) Approach
Signal processing is an important element used for identifying damage in any SHM-related application. The method here is used to extract features from the use of different types of sensors, of which there are many. The responses from the sensors are also interpreted to classify the location and severity of the damage. This paper describes the signal processing approaches used for detecting the impact locations and monitoring the responses of impact damage. Further explanations are also given on the most widely-used software tools for damage detection and identification implemented throughout this research work. A brief introduction to these signal processing tools, together with some previous work related to impact damage detection, are presented and discussed in this paper.
R. Varatharajoo, E. J. Abdullah, D. L. Majid, F. I. Romli, A. S. Mohd Rafie and K. A. Ahmad
M. T. H. Sultan et al., "Damage Classification in CFRP Laminates Using Principal Component Analysis (PCA) Approach", Applied Mechanics and Materials, Vol. 225, pp. 189-194, 2012