The main purpose of the current research is to pilot study the impact damage detection in a beam structure using infrared thermography. In this study, a beam structure, made of polyvinyl alcohol fiber reinforced engineering cementitious composite (PVA-ECC) was subjected to multiple low-velocity impacts at a constant energy level. After each impact, the structure was heated by means of halogen lamp, and acquisition of thermal images was conducted simultaneously. Sequences of thermal images were acquired with starting and ending time sets so as to include the entire evolution of thermal phenomenon, during both heating to cooling processes. Based on the relationship between the damage and the temperature variation under the thermal excitation, different damages in the impacted structures were analyzed in the thermographs. Through experimental investigation, the results demonstrated that different degrees of damage correspond to different infrared thermal characteristics. The generation and evolution of thermal signatures revealed the initiation and propagation of impact damages. It further illustrated that the proposed method is an innovative and effective approach to detect impact damage.

This study investigates the feasibility of identifying the axial position of circumferential defects in laminated pipeline structures based on damage indices. Wavelet packet decomposition is combined with damage indices, and the effects of dual defects with the same circumferential position but different axial positions, as well as dual defects with different circumferential and axial positions, on damage indices are separately studied. Our aim was to determine the potential to use damage indices to identify the axial position of circumferential defects in laminated pipeline structures. ABAQUS finite element analysis software was used to establish models of laminated pipeline structures with single defects and dual defects (with the same circumferential position but different axial positions, and with different circumferential and axial positions). The laminated pipeline structure was composed of a steel pipe (structural layer), a rigid polyurethane foam (insulation layer), and a high-density polyethylene (anticorrosion layer). The received sensing signals were averaged, and subjected to 5-level wavelet packet decomposition, to calculate the damage index values, which were then organized into a damage index matrix. Based on the trend of changes in the damage index matrix, the effects of variations in the number and circumferential position of the defects on the identification of the axial position of the damage were analyzed. The results indicate that the trend in damage index changes is influenced by the number of defects, and the increase in the circumferential distance between the second and the piezoelectric element sensor. This study found that when $1.7\lambda \le PD\le 3.4\lambda$, $I_{\mathrm{double}\mathrm{defect}90°}<I_{\mathrm{single}\mathrm{defect}}<I_{\mathrm{double}\mathrm{defect}0°}$; when $3.7\lambda \le PD\le 4\lambda$, $I_{\mathrm{double}\mathrm{defect}90°}<0.3<I_{\mathrm{double}\mathrm{defect}0°}<I_{\mathrm{single}\mathrm{defect}}$. This article demonstrates that the identification of the axial position of damage in laminated pipeline structures can be achieved using the damage index values in the damage index matrix. Additionally, this damage identification method overcomes the limitation of the wavelet packet’s inability to identify dual defects with relatively small relative axial distances. This provides new ideas and methods for finite element analysis in identifying the axial position of damage in laminated pipeline structures.