An adaptive and space-energy efficiency vibration absorber system using a self-sensing and tunable magnetorheological elastomer

Vibration monitoring and buffering is an important technical task in many industrial fields, such as bridges, machine tools and other specific applications. Recently, a magneto-rheological elastomer (MRE) has been utilized in an intelligent vibration absorber system with tunable stiffness, which can reversibly regulate its resonant frequency in real time to effectively prevent the resonance of the mechanical system. However, this MRE must be integrated with a vibrational sensor and equipped with an external magnetic field (e.g., electromagnetic coils or permanent magnets). Thus, the overall system is usually bulky and energy-intensive, which severely limits its broad application potential. In this work, we present an MRE-based tunable vibration absorber (MRE-TVA) with an elaborate 3-layered architecture integrated with a self-sensing triboelectric nanogenerator (TENG) sensor. The inner two-layer MRE structure exhibits variable stiffness, while the outer layer of the negative Poisson's ratio structure can confine the deformation of the inner MRE layers and form a contact-separation TENG sensor with the MRE, where the sensor can recognize external vibration information in a timely manner. In particular, the TENG sensor enables sensitive identification of the abnormal state of resonant excitation and other mechanical disturbances through dual logic judgment control based on vibration frequency and amplitude. For energy-space efficiency, a bistable permanent magnet controlled by a pulse current is integrated to generate a desirable magnetic field for modulation of the MRE stiffness. Compared with traditional electromagnetic coils, the energy and space utilization rates are increased by 94.25% and 75%, respectively. This combination of self-sensing and vibration damping systems achieves high energy-space efficiency, which will enable the intelligent health monitoring of bridges and other autonomous, smart, and long-term engineering tasks.