A high-static--low-dynamic stiffness (HSLDS) vibration isolator based on a tunable nesting-type electromagnetic negative stiffness (NS) mechanism is presented. The stiffness characteristics of the HSLDS system can be tuned by regulating the current in the coil. When the current is zero, the HSLDS system may degenerate into a passive isolator. The distinctive features of this proposed isolation system are demonstrated from two aspects: (1) in contrast to passive isolators, the proposed isolator can further widen the bandwidth of vibration isolation and improve the isolation performance near the natural frequency of the passive system; (2) compared with certain other electromagnetic isolation systems, the proposed system has a more compact structure, heavier load capacity, and higher NS-generating efficiency. The proposed electromagnetic NS mechanism consists of four permanent magnets and four coil windings. Analytical models of the electromagnetic force and the displacement transmissibility are established. To select an appropriate structural parameter for the prototype, the effects of geometric parameters on transmissibility are discussed from a theoretical viewpoint. The vibration isolation performance of the proposed isolator system is verified, and a tuning strategy is investigated through experiments.

This study presents a novel electromagnetic variable stiffness isolator that achieves bidirectional stiffness regulation, which means that the isolator experiences a reduced stiffness when the applied current is positive and an increased stiffness when the opposite current is applied. In addition, the stiffness variations are equal for two currents with the same magnitude but opposite polarities. The proposed isolator can not only ensure the vibration isolation performance in working frequency zone that is relatively far from the natural frequency, but also can realize high-damping-like effect for shock response attenuation, without introducing any additional damping components that may complicate the system. The bidirectional stiffness regulation was realized by combining mechanical springs with hybrid magnets (permanent magnets and coil windings). Variation in the overall stiffness of the proposed isolator occurred when the current was continuously adjusted. A prototype of the isolator was designed, fabricated and then tested with a round displacement step shock at the base. The theoretical analysis revealed that this device could be utilized as an active vibration isolator through certain control strategies. The experimental results proved the effectiveness of the proposed mechanism in shock isolation and revealed that it outperforms the conventional isolator in suppressing the residual vibration.

Recent methods that project images into deep feature spaces to evaluate quality degradation have produced inefficient results due to biased mappings; i.e., these projections are not aligned with the perceptions of humans. In this paper, we develop a hyperdebiasing framework to address such bias in full-reference image quality assessment. First, we perform orthogonal Tucker decomposition on the top of feature tensors extracted by a feature extraction network to project features into a robust content-agnostic space and effectively eliminate the bias caused by subtle image perturbations. Second, we propose a hypernetwork in which the content-aware parameters are produced for reprojecting features in a deep subspace for quality prediction. By leveraging the content diversity of large-scale blind-reference datasets, the perception rule between image content and image quality is established. Third, a quality prediction network is proposed by combining debiased content-aware and content-agnostic features to predict the final image quality score. To demonstrate the efficacy of our proposed method, we conducted numerous experiments on comprehensive databases. The experimental results validate that our method achieves state-of-the-art performance in predicting image quality.