Abstract This paper introduces the design, fabrication, and dynamic modeling of a new linkage-based electromagnetic energy harvester for roadways. The system addresses key challenges often overlooked, including ensuring driver comfort, easy installation under a speed bump, low complexity, high power density, and high durability. It features a transmission module and an energy generation module. The transmission module utilizes mechanical linkages to amplify the input displacement by a factor of nine before transmitting motion to the generator. The energy generation module includes a pair of gearboxes, two generators, and energy storage circuits. The innovative system is optimized within operational space; its linkage-based transmission offers a simpler design, reduced transmission losses, durability, and quick response to vehicle loads. Additionally, the maximum vertical deflection is limited to 3 mm to consider driver comfort. Experiments were conducted at 0.5 Hz, 1 Hz, and 1.6 Hz. Experimental and simulation results closely align, except at low frequency (0.5 Hz). An average output power of 0.56 W and energy output of 0.35 J per cycle are achieved at 30% efficiency, with an input frequency of 1.6 Hz and an amplitude of 3 mm. Field tests show the maximum power ranges from 2.75 W to 4.5 W at lower vehicle speeds. The system’s power density reaches approximately 67 W m −3 at a displacement amplitude of 3 mm, which is a high value compared to other reports in the literature.

Abstract A concept for a 2-degree-of-freedom (DOF) mobile robot is proposed, and its design and experimental study are conducted. The robot achieves linear motion along the x -axis and rotational motion along the z -axis using only two serial inertial impact devices vibrators driven by inertial impact forces. Flexible hinge mechanisms of the 2-DOF piezoelectric robot are simulated using ANSYS Workbench by varying structural parameters. Dynamic equations are established, and a dynamic simulation model is built using MATLAB/Simulink to output performance simulations. A prototype is produced, and the drive waveform, voltage amplitude, and frequency are adjusted in experiments to study the linear movement speed, rotational movement speed, and displacement accuracy of the linear and rotational movements of the piezoelectric robot. Its 2-DOF motion performance was verified, and the results are compared with the dynamic simulation results to analyze the rationality of the model. Based on a more compact and sophisticated structural design, this concept enables the 2-DOF motion of a piezoelectric robot, providing a new technical path for the design of piezoelectric-driven multi-DOF robots and verifying the feasibility and effectiveness of the inertial configuration in terms of motion accuracy and mechanism simplification. Experimental results show that the device maintains stable performance under drive voltages ranging from 10 to 140 Vp–p. Under drive conditions of 10 V and 1 Hz, the maximum linear movement accuracy of the drive device is 0.26 μ m. At 100 V and within the test frequency range, the maximum movement speed is 16.223 mm s −1 . Under 9 Hz conditions, the maximum operating speed is 1.06 mm s −1 , demonstrating excellent motion speed performance. Under driving conditions of 100 V and 11 Hz, the maximum rotational movement speed of the drive device is 11.73 μ rad s −1 .

Abstract Bolt preload quantification using the electromechanical impedance (EMI) method fundamentally relies on a localized vibration mode to ensure a linear relationship between the peak admittance frequency and the preload. Conventionally, this condition is uniquely met at the bolt head, where the structural dynamics inherently localize vibration energy. Consequently, reliable quantification has not been achievable at arbitrary positions where multi-modal coupling prevails. This study introduces a new strategy of active vibration localization to break this spatial constraint. We develop an auxiliary smart structure that actively creates a localized, single-dominated vibration mode at any chosen measurement point, thereby ensuring the consistency between the peak admittance frequency and the structural natural frequency. Numerical simulations and experimental tests verify its capability to deliver accurate, position-independent quantification. This work breaks the spatial constraint and proposes a viable paradigm for EMI-based bolt preload monitoring, showing the potential for applications in complex mechanical connection systems.

Abstract Soft actuators have emerged as a promising solution for robotics, offering enhanced adaptability and safety compared to traditional rigid counterparts. However, achieving simultaneous high precision in motion control and tactile sensing remains a significant challenge. This study presents a novel soft actuator system, Tac-BAMG, combining bubble artificial muscle group (BAMG) with TacTip tactile sensing to achieve multi-degree-of-freedom motion and tactile sensing feedback. The work emphasizes the metrological evaluation of the actuator’s performance, including detailed assessments of contraction rates, pressure-bearing capabilities, and sensing accuracy. The Tac-BAMG design integrates a measurement-oriented approach, enabling precise characterization of tactile and kinematic properties critical for robotic applications. A soft gripper prototype composed of Tac-BAMG units demonstrated stable performance across diverse gripping tasks with minimal deformation. By employing advanced measurement techniques, the findings advance the metrological characterization of soft actuators, enabling their precise application in intelligent manufacturing and adaptive robotic systems.

Abstract High-static-low-dynamic-stiffness (HSLDS) vibration isolation systems, owing to their inherent nonlinearities, are prone to jump phenomena under high excitation amplitudes, leading to impaired low-frequency vibration isolation performance. To address this issue, this paper proposes a hybrid magnetic HSLDS isolator with an integrated electromagnetic shunt damper (EMSD), which is designed based on the principle of eddy current effects. This isolator can achieve superior low-frequency vibration isolation performance through active regulation of system stiffness and damping. First, the nonlinear magnetic force of the isolator and the electromagnetic coupling coefficient of the EMSD are derived. In addition, a negative resistance circuit based on an operational amplifier is designed to reduce the system impedance and enhance the damping force. Based on this, an electromechanically coupled, two-degree-of-freedom dynamic model of the isolator is developed to analyze its low-frequency vibration isolation performance. Experiments are performed to validate the effectiveness of the system in regulating both stiffness and damping. Additionally, an adaptive regulation strategy is proposed based on the experimental results; this strategy enables the system to adaptively adjust its stiffness and damping in response to variations in the vibration source frequency. Experimental results indicate that, compared to the passive state, the isolator employing the regulation strategy exhibits a 16.6% reduction in the initial isolation frequency and a 46.7% attenuation of the resonance peak. Optimal vibration suppression is achieved across the full frequency band.

Abstract The design and optimization of magnetorheological elastomer (MRE) isolators fundamentally dictate their ultimate performance and application potential. Current methods are limited by over-reliance on designer’s personal experience or inability to concurrently optimize structural configuration and performance parameters. To address these limitations, this study proposes a synergistic design method for MRE isolator, combining extended-variable tri-phase topology optimization and multi-objective parameter optimization. The tri-phase method expands design variables from [0, 1] to [−1, 1], enabling simultaneous optimization of the excitation coil, magnetic circuit and air region without increasing dimensionality, thus yielding a lightweight configuration of MRE isolator. It overcomes the drawback of traditional optimization methods that require predefined of structural configurations. Based on the topological results, a parametric model is constructed, and a multi-objective optimization method (coupling NSGA-II genetic algorithm with finite element simulation) is developed to derive the Pareto frontier. This frontier resolves design trade-offs among the ‘magnetic field–energy consumption–lightweighting’ of MRE isolator. An optimal design is selected from the feasible solution space, achieving minimal mass while maintaining an 89th-percentile magnetic energy ratio. Experimental validation confirms the design’s adaptive vibration mitigation performance and manufacturability. This work establishes a systematic and scalable methodology that bridges empirical design and data-driven optimization, applicable to MRE isolators and other electromagnetic smart devices.

Abstract This work investigates the reliability of dielectric elastomer actuators (DEAs) based on silicone elastomers and carbon nanotube (CNT) electrodes from two key perspectives: intrinsic dielectric breakdown and long-term reliability associated with CNT electrode stability, particularly under high-frequency actuation. Experimental results reveal that the breakdown behavior is strongly influenced by voltage polarity, waveform, frequency, and material thickness, while high-frequency bipolar voltages result in significant insulation degradation. To facilitate systematic testing, a multi-channel reliability testing platform was developed, enabling continuous monitoring of voltage, current, and breakdown events for multiple DEAs under various conditions. It is found that high-frequency mechanical vibrations can cause CNT detachment from the silicone surfaces, reducing the overlapping area of the top and bottom electrodes to nearly zero. Furthermore, it is demonstrated that actuation current plays a critical role in accelerating DEA performance decline through CNT degradation. Coating encapsulation layers and using relatively higher-areal-density CNT electrodes can substantially enhance long-term reliability. In addition, self-healing current waveforms in the milliamperes range were observed, regardless of whether the electrodes have coated layers or CNT areal densities. These insights offer fundamental guidance for the design and control of DEA systems under sustained high-frequency electrical stress.

Abstract Flying-vision-based calibration (FVC) guarantees the alignment accuracy of laser direct imaging for digital lithography. Unfortunately, disturbances to the flexible substrate via warping reduce the FVC accuracy. A pigeon-inspired bionic compliant mechanism (BioCM) is designed to develop a robust FVC system. Two differential lever amplifiers increase the magnification ratio within a compact design domain. A pair of pigeon-inspired multihinge S-type flexible beams reduces the stress during high-frequency focusing steps. The levers and beams are combined into the BioCM. A compliance analysis and structural optimisation approach optimises the BioCM. A flying controller is developed for the flying-photography BioCM. The test results demonstrate that the pigeon-inspired BioCM improves the FVC accuracy when disturbances occur.

Abstract To improve the wide-frequency vibration control capability of semi-active vibration isolators, the bidirectional variable modulus performance of hard magnetic magnetorheological elastomers (H-MRE) is crucial. To further enhance the characteristics of H-MRE, various technical solutions have been implemented in recent years, including filling H-MRE with pre-magnetized hard magnetic particles and doping soft magnetic particles into H-MRE. However, existing studies have faced issues such as particle agglomeration and complex preparation processes. In response to the contradiction between the complexity of the H-MRE preparation process and performance improvement in existing research, this study improves MRE performance by optimizing the hard magnetic particles and their distribution in H-MRE. By replacing traditional hard magnetic particles with magnetocrystalline anisotropic NdFeB particles, which exhibit better magnetic properties such as remanent magnetization, coercivity and saturation magnetization. The study systematically investigates the mechanism by which particle distribution influences H-MRE performance. Experimental results show that while enhancing the amplitude of positive modulus changes, the reverse modulus change amplitude of H-MRE is increased to 23.3%. This study lays an important foundation for the application of H-MRE in vibration control fields.

Abstract This study focuses on the force estimation of NiTi shape memory alloy (SMA) actuators, particularly addressing the challenges posed by material fatigue and force degradation over repeated actuation cycles. Traditional modeling approaches for SMAs, which typically include constitutive, phase transformation, and heat transfer sub-models, often fail to account for these degradation phenomena, leading to inaccuracies in long-term predictions. To overcome these limitations, we developed and implemented multivariate long short-term memory (LSTM) recurrent neural networks for accurate force estimation using measured parameters such as electrical power (current, voltage), strain, and temperature. An extensive experimental setup was designed to cyclically and electrothermally (Joule heating) activate the SMA actuators at varying strain levels, and the degradation in force production was quantified, with a reduction of up to 20.62% observed after 1000 cycles. The study introduced both single-stage and two-stage LSTM architectures, with the SLF model, which incorporates historical force data along with other measurements, achieving the highest accuracy (RMSE of 0.003 N). More sensor-limited and deployment-oriented variants also performed well: SLWF and SLWTF achieved RMSEs of 0.089 N and 0.110 N, respectively, and the two-stage MTSL (with learned temperature as a hidden state) achieved 0.096 N. The proposed LSTM-based models demonstrated their efficacy in providing reliable force estimations under conditions of actuator degradation, making them suitable for real-time applications where traditional analytical models fall short. These findings offer valuable insights for applications requiring stabilized forces and consistent actuation performance in the presence of material fatigue.