Predictive algorithms for determining blowing pressure in a pipe organ

Abstract

The reconstruction of a pipe organ involves determining the blowing pressure. The lack of information about the pressure value significantly prolongs the process of instrument restoration. In addition, it may even result in irreversible damage to the pipes, as the adjustment of the sound parameters that depend on the pressure requires changing the physical structure of the pipes. In this paper, we provide a methodology for determining the blowing pressure in a pipe organ. We also present a formula describing the air pressure in the pipe foot, depending only on the height of the pipe’s cut-up and the fundamental frequency. We apply machine learning to determine the blowing pressure, based on the parameters of only a percentage of pipes. Moreover, we use generative artificial intelligence, which achieves outstanding prediction accuracy. We conclude that the height of the cut-up and the fundamental frequency allow determining the blowing pressure. The more pipes, the higher the accuracy, but even 10% of pipes can be sufficient.