To detect micro defects in thick-section carbon fiber reinforced composite (CFRP), the recurrence analysis method was used to analyze ultrasonic signals of tested CFRP. First, small holes were made to simulate micro defects, and an ultrasonic pulse echo method was adopted to test these simulated defects of different sizes. Then, the signal segments around the defect position were selected, and recurrence analysis was performed after proper parameters like embedding dimension(m), time delay(τ), and threshold(ε) were chosen. The recurrence plots (RPs) of defect-free signals were compared with those of defective ones and, according to the physical meanings of recurrence quantification analysis (RQA) variables, the changes that appeared in RPs were explained. Finally, ultrasonic transducers with different frequencies were evaluated to determine which one has the best performance. The results show that a 7.5 MHz resolution series transducer is the best choice in our experiment, and while m=7, τ=2, and ε=2 , the defects may cause dark areas, white bands, and longer diagnosis structure in RPs and correspondingly larger RQA variables. More concretely, the ultrasonic signal of defect-free thick-section CFRP appears in a chaotic state, while defects may break this state and lead to another one. The results will lay a foundation for the quantitative identification and classification of real micro defects.