Synthetic data derived from a digital twin for an error compensation algorithm of hydrogen tube fitting assembly

Abstract

The importance of renewable energy sources and storage media is steadily increasing. The use of hydrogen is one of the solutions intended to meet this challenge. Thus, production systems of hydrogen-producing electrolyzers have to be further developed and made more efficient. Consequently, this paper demonstrates the generation of synthetic data in a simulative environment for an error compensation algorithm to improve positioning accuracy using an image-based approach in the assembly process of hydrogen tube fittings as well as the enhancement of the system to a digital twin.