Date of this Version
Chongsheng Cheng, Ri Na, Zhigang Shen, Thermographic Laplacian-pyramid filtering to enhance delamination detection in concrete structure, Infrared Physics & Technology, Volume 97, 2019, Pages 162-176, ISSN 1350-4495, https://doi.org/10.1016/j.infrared.2018.12.039. (https://www.sciencedirect.com/science/article/pii/S1350449518307394)
Despite decades of efforts using thermography to detect delamination in concrete decks, challenges still exist in removing environmental noise from thermal images. The performance of conventional temperature-contrast approaches can be significantly limited by environment-induced non-uniform temperature distribution across imaging spaces. Time-series based methodologies were found robust to spatial temperature non-uniformity but requires extended period to collect data. A new empirical image filtering method is introduced in this paper to enhance the delamination detection using blob detection method that originated from computer vison. The proposed method employs a Laplacian of Gaussian filter to achieve multi-scale detection of abnormal thermal patterns by delaminated areas. Results were compared with the state-of-the-art methods and benchmarked with time-series methods in the case of handling non-uniform heat distribution issue. Tor further evaluate the performance of the method numerical simulations using transient heat transfer models were used to generate the ‘theoretical’ noise-free thermal images for comparison. Significant performance improvement was found compared to the conventional methods in both indoor and outdoor tests. This methodology proved to be capable to detect multi-size delamination using single thermal image. It is robust to non-uniform temperature distribution. The limitations were discussed to refine the applicability of the proposed procedure.