This invention provides a method and
system for quantitatively detecting
material crack depth based on thermal gradient
vector field, belonging to the field of
nondestructive testing technology. The invention proposes a quantitative detection scheme of unilateral
heat flow excitation + orthogonal gradient scanning: First, a unilateral high-temperature boundary is constructed using a portable chemical self-heating pack and insulating material, forcing the
heat flow to transversely cross the crack, forming a significant temperature step; second,
infrared thermographic sequences of the cooling process are acquired to construct a two-dimensional thermal
potential energy field and calculate the global gradient
vector field; morphological algorithms are used to extract the crack topological skeleton, and virtual rays are emitted along the local orthogonal detection direction determined by the local thermal
gradient direction at the skeleton nodes. Adaptive orthogonal integration is performed to extract multidimensional spatial features under multiple
time series, which are then input into a
supervised learning regression model to invert the physical depth of the crack. This invention effectively eliminates the geometric projection error caused by crack curvature, and features high computational accuracy and strong anti-interference ability, making it suitable for large-scale
rapid detection in
engineering sites.