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To improve the vibration isolation performance and bandwidth, loading capacity and supporting stability of passive vibration isolation system by utilizing nonlinearity, a bio-inspired embedded X-shaped vibration isolation (BIE-XVI) structure is proposed considering muscle/tendon contractile functions, joint rotational friction and connecting rod mass simultaneously. Furthermore, the dynamic model with pure linear elements and geometric relationship are established and the nonlinear variation properties are investigated. The effects of the key parameters of the BIE-XVI structure on frequency response characteristics and vibration isolation range are analyzed thoroughly by incremental harmonic balance method in various working conditions. From the parametric investigations, it can be found that the sensitivities of the nonlinear resonance properties are markedly different with respect to the different structure parameters. For longer rod length, larger assembly angle and higher stiffnesses, the hardening nonlinearity is weakened, but the resonance peak does not necessarily decrease. Besides, the softening nonlinearity and hardening nonlinearity can be interconverted with changing isolated mass and excitation amplitude. The BIE-XVI structure can widen the isolation frequency range and reduce the resonance peak to improve the vibration isolation properties by adjusting/designing the structural parameters, which could realize quasi-zero-stiffness property for vibration isolation.

Nonlinear energy sinks (NES) have been shown to have broadband absorption for multiple modes. Furthermore, linear dynamic absorbers (LDA) often only operate effectively within located frequency ranges and are unable to achieve broadband absorption. Therefore, this manuscript first proposed using a hybrid LDA and NES to design the circular ring absorption system. Compared with LDA, broadband absorption could be achieved through configuring and tuning linear stiffness. Both the linear and nonlinear stiffnesses are introduced by adding vertical and horizontal springs. The linear and nonlinear stiffness effects on the circular ring absorption system are investigated simultaneously. The dynamic model of the circular ring absorption system with hybrid LDA and NES is constructed, and the approximate analytical solution is obtained using the harmonic balance analysis. The expressions of frequency response and force transmissibility are given, and the analytical results are verified numerically. By comparing the amplitude-frequency response curves of the circular ring with LDA only, NES only, and a hybrid LDA and NES, it is confirmed that a hybrid LDA and NES can better control the forced vibration of the circular ring absorption system. Hybrid LDA and NES were shown to suppress main resonance peaks of the circular ring absorption system, making the device resistant to misalignments. In a linear system, this can only be achieved by resonance matching, so a hybrid LDA and NES have the same effect as adding multiple linear absorbers. Some properties of damping, nonlinear stiffness, and mass ratios in a hybrid LDA and NES are investigated. These parameters determine the specific shape of the force transmissibility curve of the ring absorption system. It is found that a proper increase in the mass ratio of the hybrid LDA and NES can obtain a better vibration reduction effect; adjusting the damping ratio and nonlinear stiffness ratio of the hybrid LDA and NES can improve the vibration reduction effect to a certain extent. Based on the analysis of the parameters effects of hybrid LDA and NES on vibration control, the parameters of hybrid LDA and NES are compared. The analysis of the results demonstrates that by selecting reasonable damping, nonlinear stiffness, and mass ratios, the frequency band of the circular ring absorption system can be broadened. Finally, an experiment is performed to validate the correctness of the proposed method.

The present paper discusses a new approach for the experimental determination of modal parameters (resonant frequencies, modal shapes and damping coefficients) based on measured displacement values, using the non-contact optical method of digital image correlation (DIC). The output is a newly developed application module that, based on a three-dimensional displacement matrix from the experimental measurement results, can construct a frequency response function (FRF) for the purpose of experimental and operational modal analysis. From this frequency response function, the modal parameters of interest are able to be determined. The application module has been designed for practical use in Scilab 6.1.0, and its code interfaces directly with the ISTRA4D high-speed camera software. The module was built on measurements of a steel plate excited by an impact hammer to simulate experimental modal analysis. Verification of the correctness of the computational algorithm or the obtained modal parameters of the excited sheet metal plate was performed by simulation in the numerical software Abaqus, whose modal shapes and resonant frequencies showed high agreement with the results of the newly developed application.

To ensure frequency stability in power systems with high wind penetration, the doubly-fed induction generator (DFIG) is often used with the frequency fast response control (FFRC) to participate in frequency response. However, a certain output power suppression amount (OPSA) is generated during frequency support, resulting in the frequency modulation (FM) capability of DFIG not being fully utilised, and the system’s unbalanced power will be increased during speed recovery, resulting in a second frequency drop (SFD) in the system. Firstly, the frequency response characteristics of the power system with DFIG containing FFRC are analysed. Then, based on the analysis of the generation mechanism of OPSA and SFD, a combined wind-storage FM control strategy is proposed to improve the system’s frequency response characteristics. This strategy reduces the effect of OPSA and improves the FM capability of DFIG by designing the fuzzy logic of the coefficients of FFRC according to the system frequency index in the frequency support stage. During the speed recovery stage, the energy storage (ES) active power reference value is calculated according to the change of DFIG rotor speed, and the ES output power is dynamically adjusted to reduce the SFD. Finally, taking the IEEE 39-bus test system as an example, real-time digital simulation verification was conducted based on the RTLAB OP5707 simulation platform. The simulation results show that the proposed method can improve the FM capability of DFIG, reduce the SFD under the premise of guaranteeing the rapid rotor speed recovery, and avoid the overshooting phenomenon so that the system frequency can be quickly restored to a stable state.

HighlightsA bio-inspired flexible strain sensor with hypersensitivity and highly selective frequency response is prepared by styrene–isoprene–styrene combined with monolayer graphene.Benefiting from the structural design inspired by nature and hysteresis of viscoelastic materials, bio-inspired structures, and original materials' properties complement each other.The frequency recognition resolution of bio-inspired flexible strain sensor reaches 0.2 Hz, making it ideal for human–computer interaction and mechanical equipment health inspection.Flexible strain sensors are promising in sensing minuscule mechanical signals, and thereby widely used in various advanced fields. However, the effective integration of hypersensitivity and highly selective response into one flexible strain sensor remains a huge challenge. Herein, inspired by the hysteresis strategy of the scorpion slit receptor, a bio-inspired flexible strain sensor (BFSS) with parallel through-slit arrays is designed and fabricated. Specifically, BFSS consists of conductive monolayer graphene and viscoelastic styrene–isoprene–styrene block copolymer. Under the synergistic effect of the bio-inspired slit structures and flexible viscoelastic materials, BFSS can achieve both hypersensitivity and highly selective frequency response. Remarkably, the BFSS exhibits a high gage factor of 657.36, and a precise identification of vibration frequencies at a resolution of 0.2 Hz through undergoing different morphological changes to high-frequency vibration and low-frequency vibration. Moreover, the BFSS possesses a wide frequency detection range (103 Hz) and stable durability (1000 cycles). It can sense and recognize vibration signals with different characteristics, including the frequency, amplitude, and waveform. This work, which turns the hysteresis effect into a \"treasure,\" can provide new design ideas for sensors for potential applications including human–computer interaction and health monitoring of mechanical equipment.

The vibrational characteristics of the Hybrid III and NOCSAE headforms are not well understood. It is hypothesized that they may perform differently in certain loading environments due to their structural differences; their frequency responses may differ depending on the impact characteristics. Short-duration impacts excite a wider range of headform frequencies than longer-duration (padded) impacts. While headforms generally perform similarly during padded head impacts where resonant frequencies are avoided, excitation of resonant frequencies during short-duration impacts can result in differences in kinematic measurements between headforms for the matched impacts. This study aimed to identify the natural frequencies of each headform through experimental modal analysis techniques. An impulse hammer was used to excite various locations on both the Hybrid III and NOCSAE headforms. The resulting frequency response functions were analyzed to determine the first natural frequencies. The average first natural frequency of the NOCSAE headform was 812 Hz. The Hybrid III headform did not exhibit any natural frequencies below 1000 Hz. Comparisons of our results with previous studies of the human head suggest that the NOCSAE headform’s vibrational response aligns more closely with that of the human head, as it exhibits lower natural frequencies. This insight is particularly relevant for assessing head injury risk in short-duration impact scenarios, where resonant frequencies can influence the injury outcome.

In this paper, we study the problem of recognizing communication scenes under open set protocols, i.e., making the extracted features of communication scenes sufficiently separable under a suitable metric space. To achieve it, we design a feature fusion model based on a convolutional neural network to extract the features of communication scenes, and we take the real and imaginary parts of the channel frequency response as model inputs to extract the scene features sufficiently. Furthermore, in order to optimize the distribution of scene features in angular space, a Linear-Softmax loss function is designed to restrict the inter-class angles of extracted features to be larger than the intra-class angles by two hyperparameters. Meanwhile, a cosine distance-based communication scene recognition algorithm is designed to complete the communication scene recognition by calculating the cosine distance between features. Finally, it is tested on actual measurement data sets, and the experimental results show that compared with the state-of-the-art loss functions, the proposed Linear-Softmax loss function enables the learning of the maximum angular margin. The Linear-Softmax loss function combined with the proposed communication scenes recognition algorithm can complete the recognition of both closed-set and open-set test data, with a recognition accuracy as high as 97.28% on the closed-set test set and 85.65% on the open-set test set.

In the quest of improving the frequency response capability of wind turbines, control solutions trying to emulate synchronous machines have been proposed. While their performance in terms of frequency support is relatively good, they may trigger torsional oscillations, cause fatigue and damage in the drivetrain, and reduce its lifetime. In this paper, the torsional oscillations caused by a virtual synchronous machine (VSM)‐based frequency controller are illustrated, and methods for damping them are introduced. Two torsional oscillation damping methods are compared and combined to derive an improved method. Dynamic simulation results show better damping performance from the combined damping method.

The reliability of cross-linked polyethylene (XLPE)-insulated power cables, mostly used for electricity distribution and transmission in urban areas, is often compromised due to the lack of effective condition-based monitoring systems. This leads to difficulties in early fault detection and increased risk of unscheduled outages, and failures, particularly in cable end terminations. This research aims to develop a robust and accurate methodology for estimating moisture content in XLPE cable end terminations to enhance condition-based monitoring and ensure reliable power delivery. The study employed frequency domain spectroscopy to examine the dielectric properties of XLPE cable samples with varying moisture content levels. A novel predictive formula was derived to estimate moisture content using dielectric frequency response (DFR) supported by validation through sweep frequency response analysis (SFRA) tests. We conduct an experiment to estimate the moisture content and observe satisfactory agreement between the experimental and theoretical values. The proposed method achieved a high accuracy of 96%; the percentage error variation was minimal in moisture estimation, outperforming existing techniques. This study provides a practical and reliable approach for monitoring XLPE cable condition, particularly at end terminations. The proposed methodology ensures accurate moisture content estimation, enabling early fault detection and reducing the risk of unscheduled outages. This advancement has major implications for enhancing the reliability and efficiency of urban power systems.

Optimal sensor placement (OSP) is one of the essential factors affecting the accuracy of health management, particularly in health monitoring driven by mode information. A novel OSP method based on active learning is proposed to effectively capture modal shapes for Structural Health Monitoring (SHM). First, the optimal Latin Hypercube Sampling is carried out to generate initial sensor positions, and the corresponding amplitudes of modal shapes at these positions are obtained by a frequency response function. Subsequently, data-driven models are built to be treated as virtual sensors to reconstruct the integrated modal shapes of the structure, and the accuracies of the results are calculated. Then, considering the distribution of the input sensor position, an improved reliability-based expectation improvement function (IREIF2) is applied to find the optimal sensor positions by optimizing the parameters of the probability density function in IREIF2. Finally, the position and response of the optimal sensor are used to update the data-driven models for more accurate modal shape reconstruction, and the accuracies are calculated to determine whether the OSP process continues. Once the accuracies meet the desired criteria, the optimal sensor positions are also obtained. The superiority of the proposed method is verified by the comparisons with other OSP methods, and different case studies are also used to prove the proposed method can realize OSP for SHM.