Application of artificial neural networks for indirect load measurements on bridges from vibration measurements

Abstract

The German Research Foundation (DFG) has launched in September 2022 the priority program SPP 2388 100+ to develop new methods for digital representation, SHM and lifetime management of complex structures, due to the continuously increasing amount of old infrastructure buildings. The present contribution is prepared within the LEMOTRA project as a part of SPP 2388 100+. The data assimilation techniques present a potential SHM approach and presume a permanent update of a computational model by use of continuous measurements. System changes resulting from damage or aging processes can be detected and localized, provided the measurement and model prediction share the same cause. Thus, the load identification is a necessary prerequisite for data assimilation methods. In this paper an approach using artificial neural networks is developed to determine the main parameters of the traffic load associated with vehicles crossing a bridge. Simple feed forward neural networks have already been used for predicting structural displacements or discovering system anomalies. However, a more sophisticated network structure is necessary for the purpose of extracting features from time history measurement data. Therefore, a cluster structure of convolutional neural networks (CNN) was developed to gain knowledge about load characteristics such as load magnitudes, load velocities or the number of vehicles on the bridge. The developed approach has been tested on a numerical example. For this purpose, a finite element model of a bridge is created and loaded by various moving loads with variable relevant parameters. Simulated acceleration data at multiple locations on the bridge are considered as artificial measurements and then used in the training process. The impact of different measurement noise levels on the quality of the CNNs is being investigated as well. The obtained results allow for some conclusions on advantages and drawbacks which should be a matter of discussion during the conference.