A hierarchy of sources of errors influencing the quality of identification of unknown parameters using a meta-heuristic algorithm

• We developed a method in order to perform an identification of parameters.
• We carried out this method on several structures to identify parameters.
• We identified sources of errors during identification process.
• Localization of the sensors is the most important source of errors.

The aim of structural monitoring is to get mechanical and valuable information concerning structural parameters. A generic frame was developed in order to identify unknown parameters thanks to an iterative process using a meta-heuristic algorithm. It combines data obtained through structural monitoring, a mechanical model and an optimization algorithm. The quality of identification depends on the quality of the data set, on that of the mechanical model and on the algorithm efficiency. It is shown through several tests on two case studies how uncertainty or errors arising from various sources can impact the accuracy of predicted values.