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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.

To study sweep frequency impedance (SFI) features of short-circuit (SC) faults easily, this paper proposes a broadband electric circuit model of a transformer winding and solves its three key problems. The first problem is the calculation of lumped-circuit parameters considering frequency-dependent complex anisotropic permeabilities (FDCAPs), which are caused by the physical characteristics, such as skin, proximity, and geometrical effects and anisotropic properties, of the transformer core and winding materials. The other issue is the establishment of the electric circuit model based on the SFI measurement connection mode, the transformer winding parameters, and a double-ladder network (DLN). Another issue is the construction of the state-space model of the electric circuit toward different SFI values to obtain all network branch voltages and currents. The accuracy of the proposed model is assessed by comparing its SFI signatures with those of the simulation model, without considering FDCAPs under healthy winding, and the corresponding physical transformer model during healthy winding and SC faults. It is observed that the SFI results of the proposed model are closer to the experimental measurements, and the model can be effectively used to study the SFI features of SC faults. Moreover, the impacts of different types of SC faults on the SFI data are concluded in this paper.

Declining proprioceptive function is associated with problems such as lower back pain and falls. Therefore, we developed a vibration device using sweep frequency to evaluate several proprioceptors with different response frequency ranges. This study aimed to elucidate the biological responses of healthy individuals to vibratory stimulation at different sites and frequency ranges and to propose cutoff values to determine the decline in proprioceptive function. Mechanical vibration was separately applied to the lower legs and lower back, and proprioceptive function was evaluated by defining the ratio of the center of pressure (CoP) in the anteroposterior direction during mechanical vibration to that during no vibration in the three frequency ranges. The cut-off value was defined as the mean value, with the standard deviation subtracted for each indicator. The cut-off values were higher in the lower legs than in the lower back at all frequency ranges and in the 30–53 Hz and 56–100 Hz frequency ranges for both the lower legs and lower back. In healthy individuals, 9.9% and 8.6% were below the cut-off values in the 30–53 Hz and 56–100 Hz frequency ranges for the lower legs, respectively.

From the perspective of green chemistry, it is of great significance to produce cellulose nanofibers (CNFs) with more environmentally friendly and sustainable materials. This study investigated the efficient cleavage of strong hydrogen bonds occurred in sugarcane bagasse (SCB), ultrafast fabrication of CNFs through a 20 min microwave-assisted ternary carboxylic acid deep eutectic solvent (Mw-TCADES) deconstruction and sweep frequency ultrasonic (SFU) separation pretreatment. It also investigated the subsequent high-intensity ultrasonication (HIU) fibrillation process. After pretreating SCB with two different TCADES (choline chloride: oxalic acid: AlCl3·6H2O, and choline chloride: lactic acid: AlCl3·6H2O, molar ratio 1:1:0.2), the cellulose content of the SCB was 56.2 and 62.6%, respectively. The CNFs obtained after the two Mw-TCADES treatments contained 0.74 and 0.84 mmol/g carboxylic acid groups, and the crystallinity was 58.05 and 60.71%, respectively. Meanwhile, the CNFs obtained under the optimum treatment conditions (Mw-TCADES, 100 °C, 20 min and HIU) showed high thermal stability, which exhibited promising potential for further applications. Under the optimum conditions, the CNFs had a length of about 400–600 nm, width of around 15–17 nm, and a height of about 6–7 nm. The results showed that the TCADES can be used effectively as an alternative to the traditional acid–base pretreatment method and provide a green and efficient method for the utilization of lignocellulosic materials and the separation of CNFs.Graphic abstract

Glass Fiber Reinforced Polymer (GFRP) is a kind of raw material used in the manufacture of composite insulator mandrels. If crack defects occur in the composite insulator mandrel, it will eventually lead to brittle fractures, which will cause extremely serious accidents. Aiming at detecting the internal defects of GFRP materials by the microwave reflection method, we carried out a numerical modeling analysis adopting the electromagnetic simulation method. Samples with different depths of defects are used for sweep frequency calculation, and the frequency range is from 18 to 26.5 GHz. A simple method for judging defective GFRP boards and non-defective GFRP boards is obtained. In addition, as the depth of the defect increases, the valley value of the S11 signal increases, and at the same time, the absolute value of the phase change of the signal decreases. The simulation results show that the microwave reflection method is feasible for detecting the defects of composite insulator materials.

Bistable system exhibiting complex dynamic behavior has been viewed as an efficient method to overcome the issue of linear energy harvester only performing well near the resonant frequency. Moreover, performance enhancement strategies of bistable energy harvesters have been extensively discussed mainly for systems with perfectly symmetric potentials. Due to the presence of imperfections as a result of non-uniform manufacturing of the harvesters, eccentricity of the buckling or magnetic force and uneven gravity, the dynamic characteristics and performance enhancement of asymmetric potential energy harvesting remain an open issue. Therefore, this paper investigates the influence mechanism and performance enhancement of a cantilever-based bistable energy harvesting system with asymmetric potentials. Bifurcation diagrams of the dimensionless electromechanical equations are employed to discover the effect of asymmetric potentials on the output response. Based on the numerical results, a performance enhancement method is proposed by compensating the asymmetric potentials with an appropriate bias of the system to decrease the negative impact of asymmetric potentials on bistable energy harvesting. The optimum bias angle is derived and numerical simulations under constant and sweep frequency excitations demonstrate that the performance of the asymmetric potential bistable energy harvesters is enhanced in a certain bias angle range around the optimum value. Two bistable energy harvesters with different asymmetric potential energy functions are investigated in the experiments and results verify the effectiveness of the proposed method for improving the energy harvesting performance.

Leveraging the superior vibration isolation performance of nonlinear stiffness, this paper proposes a magnetic-curved-spring isolator (MCSI) with quasi-zero stiffness property. The positive stiffness of this isolator is composed of repulsive magnets, while the negative stiffness is composed of a cam-roller-spring mechanism. The vibration isolation mechanism formed by the parallel connection of the two can adapt well to the isolation under different loads. To gain an in-depth understanding and verify the performance of the dual-nonlinear stiffness vibration isolator, its static restoring force is analyzed and its dynamic response is acquired via harmonic balance method, then the stability analysis is conducted. The obtained displacement transmissibility reflects its low resonance frequency and wide isolation frequency band. By constructing an experimental platform and applying sweep frequency-, periodic- and random excitations, the experiments show that the MCSI can achieve low-frequency isolation from 3 Hz. Compared with linear isolation, it demonstrates the superiority of the developed nonlinear isolator for supporting uncertain loads. Our proposed MCSI features adjustable positive and negative stiffness, being adaptable to various working environments, thus offering a novel approach to the design of vibration isolators.

In practical applications, precise tuning of current controllers is essential for achieving desirable dynamic performance and stability margins. Traditional tuning techniques rely heavily on accurate plant parameter identification. However, this process is often challenged by inherent nonlinearities and unmodeled dynamics in motor systems. To address this issue, this paper proposes a current loop parameter tuning algorithm based on open-loop frequency sweeping. As the swept Bode diagram reveals nonlinear factors typically neglected during modeling, it provides a basis for control parameter correction. A pulse-sine voltage injection method is first introduced to identify motor parameters, serving as initial values for the controller. By analyzing the magnitude and phase characteristics of the open-loop transfer function, the delay time constant in the high-frequency range can be accurately identified, and mismatched parameters in the low-to-mid frequency range can be corrected. This method does not rely on complex model structures or extensive online adaptation mechanisms. Experimental results on a mechanical test platform demonstrate that the proposed tuning strategy significantly enhances the current loop’s closed-loop bandwidth and dynamic performance.

The meniscus is crucial in maintaining the knee function and protecting the joint from secondary pathologies, including osteoarthritis. Although most of the mechanical properties of human menisci have been characterized, to our knowledge, its dynamic shear properties have never been reported. Moreover, little is known about meniscal shear properties in relation to tissue structure and composition. This is crucial to understand mechanisms of meniscal injury, as well as, in regenerative medicine, for the design and development of tissue engineered scaffolds mimicking the native tissue. Hence, the objective of this study was to characterize the dynamic and equilibrium shear properties of human meniscus in relation to its anisotropy and composition. Specimens were prepared from the axial and the circumferential anatomical planes of medial and lateral menisci. Frequency sweeps and stress relaxation tests yielded storage (G′) and loss moduli (G″), and equilibrium shear modulus (G). Correlations of moduli with water, glycosaminoglycans (GAGs), and collagen content were investigated. The meniscus exhibited viscoelastic behavior. Dynamic shear properties were related to tissue composition: negative correlations were found between G′, G″ and G, and meniscal water content; positive correlations were found for G′ and G″ with GAG and collagen (only in circumferential samples). Circumferential samples, with collagen fibers orthogonal to the shear plane, exhibited superior dynamic mechanical properties, with G′ ~70 kPa and G″ ~10 kPa, compared to those of the axial plane ~15 kPa and ~1 kPa, respectively. Fiber orientation did not affect the values of G, which ranged from ~50 to ~100 kPa.

During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied in a range of different applications and mainly using the frequency sweep-technique. Traditionally the tissue under study is considered to be timeinvariant and dynamic changes of tissue activity are ignored and instead treated as a noise source. This assumption has not been adequately tested and could have a negative impact and limit the accuracy for impedance monitoring systems. In order to successfully use frequency-sweeping EBIS for monitoring time-variant systems, it is paramount to study the effect of frequency-sweep delay on Cole Model-based analysis. In this work, we present a software tool that can be used to simulate the influence of respiration activity in frequency-sweep EBIS measurements of the human thorax and analyse the effects of the different error sources. Preliminary results indicate that the deviation on the EBIS measurement might be significant at any frequency, and especially in the impedance plane. Therefore the impact on Cole-model analysis might be different depending on method applied for Cole parameter estimation.