Micro Displacement and Strain Detection for Crack Prediction on Concrete Surface Using Optical Nondestructive Evaluation Methods

Abstract

Continuous inspection of the concrete structures is important for extending the operating life span of nuclear power plants. Restricted physical accessibility to the nuclear plant structures, due to concerns of radiation, presents a unique challenge to the conventional visual inspection and contact-type nondestructive evaluation (NDE) technologies. Digital image correlation (DIC) is an optical NDE method that can measure the structural parameters such as displacement and strain. However, it is highly challenging to accurately detect micro displacement on the concrete surface because of weathering and change in illumination conditions. Usually, an artificial speckle pattern with good contrast to the object surface is needed for calibration and tracking, but it is difficult to apply in the field. In order to be able to detect micro surface strain for crack prediction in outdoor environment, a DIC-based NDE technology is developed to significantly improve the measurement accuracy by incorporating the orientation code matching (OCM) technique, a robust and accurate template matching algorithm. Concrete specimens were built and tested under four-point bending. Using the remotely measured images, the OCM incorporated DIC method successfully predicted concrete cracks before they emerged on the surface. The experiments also demonstrated the robustness of the method against the optical noise including weathering and change in illumination conditions.