Investivation of the effect of damping on structure-borne sound by using vibration damping material on galvanized low carbon steel plates

The application of damping coatings to metal sheets is a commonly used method to suppress undesirable vibration and noise levels in various industries. As numerical simulations play a vital role in designing a high-quality product with fewer cost, an accurate and practical way of modelling such type of structures is necessary. It is aimed to develop a methodology that helps to define the damping parameters of such viscoelastic coating layers through Rayleigh damping coefficients. An estimation formula that gives Rayleigh damping coefficients based on thicknesses was obtained with machine learning tools. For this purpose, several tests were performed with different coating thicknesses on steel plates. In parallel, a great number of simulations were performed not only to compare with the reference values from the tests, but also to create a data set and feed the learning algorithms. Test results were compared with simulation and Oberst method results. It has been observed that Oberst method has limitation problems. Therefore, it has been determined that the results of machine learning algorithms perform significantly better results when compared to the test results. Vibro-acoustic analysis models have been created with the determined material properties and these generated numerical models have been validated with tests. Then, both the test results and the numerical model results obtained from have been examined. The effects of free layer damping applications have been researched on vibration and noise control. The most effective parameters on vibration damping, noise reduction and sound radiation have been determined as the coating thickness, the frequency range, and the mode shape of the plate.