Passive dynamic vibration absorber (DVA) is widely used in structural vibration reduction, and the higher efficient DVA is always required for some special situations. This article aims to propose the novel inerter-based dynamic vibration absorbers (IDVAs) to enhance the performance of the passive DVA. Firstly, several novel IDVAs are presented by matching the inerter with DVA in different places. Then, the closed-form optimal parameters of six kinds of IDVAs are obtained based on the classical fixed-point theory. The obtained parameters demonstrates that all the inerters connected between the primary system and absorber system do not provide improvement for the performance of DVAs, while all the inerters connected to the earth can improve the performance of DVAs. Moreover, the comparisons among the IDVAs show that the inerter connected to the earth in the grounded DVA (IR2 in this paper) performs the best performance in vibration absorption. More than 30 % improvement can be obtained from IR2 as compared with other IDVAs. Finally, the further comparison among the IDVAs under white noise excitation also shows that IR2 is superior to other IDVAs. The results may provide theoretical basis for design of the optimal IDVA in engineering practice.

Bearing is a key component of satellite inertia actuators such as moment wheel assemblies (MWAs) and control moment gyros (CMGs), and its operating state is directly related to the performance and service life of satellites. However, because of the complexity of the vibration frequency components of satellite bearing assemblies and the small loading, normal running bearings normally present similar fault characteristics in long-term ground life experiments, which makes it difficult to judge the bearing fault status. This paper proposes an automatic fault diagnosis method for bearings based on a presented indicator called the characteristic frequency ratio. First, the vibration signals of various MWAs were picked up by the bearing vibration test. Then, the improved ensemble empirical mode decomposition (EEMD) method was introduced to demodulate the envelope of the bearing signals, and the fault characteristic frequencies of the vibration signals were acquired. Based on this, the characteristic frequency ratio for fault identification was defined, and a method for determining the threshold of fault judgment was further proposed. Finally, an automatic diagnosis process was proposed and verified by using different bearing fault data. The results show that the presented method is feasible and effective for automatic monitoring and diagnosis of bearing faults.