Undesired oscillations commonly encountered in engineering practice can be harmful to structures and machinery. Vibration isolation systems are used to attenuate undesired oscillations. Recently, there has been growing interest in nonlinear approaches towards vibration isolation systems design. This work is focused on investigating the effect of nonlinear cubic viscous damping in a vibration isolation system consisting of a magnetic spring with a positive nonlinear stiffness, and a mechanical oblique spring with geometric nonlinear negative stiffness. Dynamic model of the vibration isolation system is obtained and the harmonic balance method (HBM) is used to solve the governing dynamic equation. Additionally, fourth order Runge–Kutta numerical simulation is used to obtain displacement transmissibility of the system under investigation. Results obtained from numerical simulation are in good agreement with those obtained using HBM. Results show that introducing nonlinear damping improves the performance of the vibration isolation system. Nonlinear damping purposefully introduced into the described vibration isolation system appears to eliminate undesired frequency jump phenomena traditionally encountered in quasi-zero-stiffness vibration isolation systems. Compared to its rival linear vibration isolation system, the described nonlinear system transmits less vibrations around resonant peak. At lower frequencies, both nonlinear and linear isolation systems show comparable transmissibility characteristics.

Modern 3D printed components are finding applications in dynamic structures. These structures are often subject to dynamic loadings. To date, research has mostly focused on investigating the mechanical properties of these 3D printed structures with minimum attention paid to their modal analysis. This work is focused on performing experimental modal analysis of 3D printed structures. The results show that the adhesion type has the most significant impact on the vibration response and parameters obtained from the modal analysis. The average dynamic modulus, natural frequency, and damping coefficient increased by approximately 12.5%, 5.5%, and 36%, respectively, for the specimens printed using skirt adhesion compared to those printed using raft adhesion. SEM analysis suggests that the 3D printed specimens with skirt adhesion yielded flattened layers, while raft adhesion resulted in rounded layers. The flattened layers of the specimens with skirt adhesion are likely an indication of an enhanced heat transfer between the 3D printer bed and the specimen. The printed specimens with skirt adhesion are in direct contact with the printer bed during the printing process. This enhances the heat transfer between the specimen and the printer bed, causing the layers to flatten out. The enhanced heat transfer yields a better inter-layer diffusion, resulting in improved physical bonding at the layers’ interface. The improved bonding yields higher stiffnesses and natural frequencies. For the specimens with skirt adhesion, the improved heat transfer process is also likely responsible for the enhanced damping properties. The strengthened inter-layer bonding at the layer–layer interface provides better energy dissipation along the contact lines between the layers.

This work examines the use of accelerometers to identify vibrational patterns that can effectively predict the state of a 3D printer, which could be useful for predictive maintenance. Prototypes using both a simple rectangular shape and a more complex Octopus shape were fabricated and evaluated. Fast Fourier Transform, Spectrogram, and machine learning models, such as Principal Component Analysis and Support Vector Machine, were employed for data analysis. The results indicate that vibrational signals can be used to predict the state of a 3D printer. However, the position of the accelerometers is crucial for vibration-based fault detection. Specifically, the sensor closest to the nozzle could predict the state of the 3D printer faster at a 71% greater sensitivity compared to sensors mounted on the frame and print bed. Therefore, the model presented in this study is appropriate for vibrational fault detection in 3D printers.

Control of total wall shear stress in ann-generation microfluidic network.