On Multi-Criteria Optimization of DVAs in Vibration Control of ۲-DOF Systems

Dynamic Vibration Absorbers (DVAs) play a pivotal role in suppressing unwanted vibrations and enhancing the stability of engineering systems. Conventional single-objective optimization approaches fall short of addressing the intricate and diverse requirements characteristic of modern engineering challenges. In response, the authors have created and developed DeVana, an advanced Python-based optimization framework explicitly designed for the multi-criteria optimization of DVAs. By employing genetic algorithms, DeVana enables the simultaneous optimization of critical DVA parameters, stiffness, damping, and mass, across multiple performance metrics. A comprehensive case study involving a fully coupled ۲DOF system demonstrated notable reductions in vibration amplitudes, achieving a minimized peak value of ۰.۰۱۶۵, while ensuring optimal resonance alignment within the frequency range of ۸۵۰–۱۷۰۰. This development represents a meaningful advancement in the design and application of DVAs, offering a versatile and effective solution for addressing vibration control challenges in complex engineering environments, with potential applications spanning industries such as aerospace, automotive, and civil engineering.

کلیدواژه ها:

Dynamic Vibration Absorber ، Multi-Criteria Genetic Algorithms Optimization ، Frequency Response Function ، Multi-Degrees of Freedom ، DeVana