The diagnostics of slight damage are extremely significant for providing the early warning
damage information for in-service structures. This thesis presents the development of a
systematic experimental method to identify structural damage by the experimental
techniques. Three carbon fabric squared composite p1ates were used as the research
objects. Two of them with light crack damage that can be classified as fiber breaking and
matrix cracking were supposed to be identified through the dynamic experimental
techniques. The tests of the frequency response functions (FRFs) of the investigated
objects were conducted first to provide a general understanding of the dynamic properties
of the material and the structures. Then the tests of the velocity fields at some specified
frequencies are performed to acquire dynamic response data of the objects for the study
purposes.
A systematic method to process the experimental data has been developed first in this
thesis. The best regressive mathematical models for the test velocity fields are built based
on the linear polynomial regression procedures and statistical analysis. To perform damage
identification, the correlation coefficient (CC) and spatial correlation coefficient (SCC)
techniques based on the best-fitted models and the curvature models were used. Finally,
the student t' statistical tests were applied to decide whether the two compared data sets
are significantly different in statistical sense.
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