Structural Damage Detection Based on a Fiber Bragg Grating Sensing Array and a Back Propagation Neural Network: An Experimental Study

摘要

This study presents an experimental verification of a structural damage recognition technique based on a fiber Bragg grating array and a back propagation neural network. A flat plate was designed and fabricated for these experiments. The plate structure was loaded using a lever and a weight, and damage was introduced by putting a hole in the plate. Data was collected for the healthy and damaged cases when the load was applied at different positions on the plate. The neural network was able to identify damage to the plate. This approach for damage detection is useful when a static load can be applied at multiple points on a structure.