MODELING OF FREQUENCY RESPONSE FUNCTION (FRF) MAGNITUDE FOR CANTILEVER BEAM AS A THREE-DEGREE-OF-FREEDOM VIBRATION SYSTEM

• Main Author: Farhan Husain, Muhammad
• Format: Final Project
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/77962
• Institution: Institut Teknologi Bandung

One of the causes of failure in industrial rotating machinery is the dynamic stiffness alteration of support structures. The prevention of these rotating machinery failures can be achieved through the implementation of structural support modifications. Prior to designing modifications for the support structure of rotating machinery, it is necessary to model the Frequency Response Function (FRF) magnitude to predict the post-modification FRF magnitude curve. Therefore, this study was conducted to model the FRF magnitude of a cantilever beam as three-degree-of-freedom vibration system using the finite element method to closely match experimental results. The study started with deflection and FRF tests to identify dynamic characteristics and properties of the test subject. Subsequently, the Rayleigh damping coefficients were calculated using least squares and traditional method based on damping ratio values obtained from tests. These the Rayleigh damping coefficients, mass density, and Young's modulus were employed for modeling the FRF magnitude using the Finite Element Method (FEM) in Ansys. The results of the FRF magnitude modeling were compared with theoretical calculations and experimental FRF tests. The study found that the FRF magnitude modelling for Sensor 1 closely resembled the FRF test results with an error range of 5.33% to 6.36%. However, there was a significant error in FRF magnitude modelling for Sensor 2, which ranges from 25.59% to 115.70%. This substantial error was attributed to inaccuracies in the Half-Power Point method when identifying damping ratios on the FRF magnitude curve without anti-resonance points. The smallest errors in FRF magnitude modelling for Sensor 1 and 2 were respectively obtained using the Pure Approach (PA) and Inverse Frequency Weighted Approach (IFWA) methods.