Study and Experiment for the Automatic Identification of Plate Vibration Frequencies Based on Chladni Patterns

This paper begins by analyzing several studies discussing the use of Chladni patterns in various contexts. Specifically, Chladni patterns are used to identify the arrangement of nodes associated with the mechanical vibrations of thin plates. Consequently, the utility of these patterns is linked to the spatial distribution of vibration nodes—relevant to applications such as mounting configurations and the accumulation of granular material on separation systems. The ability to rapidly identify node arrangements based on frequency is highly valuable. This paper aims to analyze the correlation between a Finite Element Method (FEM) simulation model and images obtained through the experimental generation of Chladni patterns in order to improve the parameter identification approach of vibrational devices. To this end, a system based on neural networks is proposed for the identification and correlation of these images. The goal of automated identification by use of neural networks is set in order to eliminate subjective identification by the human eye. A correspondence function is derived to relate the experimental Chladni patterns to the numerical FEM model of the thin plates’ natural vibrations. The present research addresses a subject that is not fully studied in the papers cited, namely, that of matching the parameters of numerical modeling with the experimental analysis and expressing them with a mathematical relation.