Binary-Encoded Transformable Modular Component Method for Structural Crack Identification

Accurate identification of complex crack networks with branching and intersecting topologies remains a challenge in aerospace and civil engineering. Conventional non-destructive testing techniques are constrained by limited coverage and equipment access requirements, while model-based inverse methods face the curse of dimensionality and high computational cost when characterizing intricate crack morphologies. To address these limitations, a Binary-encoded Transformable Modular Component (BTMC) method is proposed, which abstracts complex crack morphologies into combinations of modular components representing elementary crack topological operations and encodes their parameters into a unified binary genotype. This representation converts the high-dimensional continuous inverse problem into a discrete combinatorial optimization task over a bounded search space, and the extended finite element method is coupled with a genetic algorithm for forward analysis and parameter optimization. Numerical simulations covering non-intersecting cracks, intersecting networks, and irregular morphologies beyond the component library demonstrate that the method maintains stable identification accuracy under measurement noise up to 10%. Experimental verification on a metal tensile plate and a wing surface curved-shell structure confirms that the identified configurations are mechanically consistent with the measurements, with the strain-response error on the wing surface reduced from 8.67% for the traditional genetic algorithm to 2.27% for BTMC. Across all test cases, the BTMC method converges in fewer generations with a total identification time of approximately 16 min on average, which provides a computationally efficient framework for online structural health monitoring of aircraft structures.