Universitätsbibliothek
Weimar Open Access

Mohamed Said Helmy Alabassy

• As machine vision-based inspection methods in the field of Structural Health Monitoring (SHM) continue to advance, the need for integrating resulting inspection and maintenance data into a centralised building information model for structures notably grows. Consequently, the modelling of found damages based on those images in a streamlined automated manner becomes increasingly important, not justAs machine vision-based inspection methods in the field of Structural Health Monitoring (SHM) continue to advance, the need for integrating resulting inspection and maintenance data into a centralised building information model for structures notably grows. Consequently, the modelling of found damages based on those images in a streamlined automated manner becomes increasingly important, not just for saving time and money spent on updating the model to include the latest information gathered through each inspection, but also to easily visualise them, provide all stakeholders involved with a comprehensive digital representation containing all the necessary information to fully understand the structure’s current condition, keep track of any progressing deterioration, estimate the reduced load bearing capacity of the damaged element in the model or simulate the propagation of cracks to make well-informed decisions interactively and facilitate maintenance actions that optimally extend the service life of the structure. Though significant progress has been recently made in information modelling of damages, the current devised methods for the geometrical modelling approach are cumbersome and time consuming to implement in a full-scale model. For crack damages, an approach for a feasible automated image-based modelling is proposed utilising neural networks, classical computer vision and computational geometry techniques with the aim of creating valid shapes to be introduced into the information model, including related semantic properties and attributes from inspection data (e.g., width, depth, length, date, etc.). The creation of such models opens the door for further possible uses ranging from more accurate structural analysis possibilities to simulation of damage propagation in model elements, estimating deterioration rates and allows for better documentation, data sharing, and realistic visualisation of damages in a 3D model.…