Search Results (247)

Regenerative vibrations are a major hindrance to flexible cantilever structures during milling, resulting in a reduced tool life and diminished surface finish. In this research, two actively controlled methods are directly compared: a genetic algorithm (GA)-optimized classical proportional-integral-derivative (PID) controller and a GA-optimized fractional-order PID (FOPID) controller for a milling-dependent regenerative force on a flexible cantilever beam via numerical modeling, using piezoelectric actuator/sensor patches. The original aspect lies in synergistically combining fractional-order control with genetic algorithm-based optimization to actively reduce chatter and increase the machining stability of flexible milling systems. The simulation results from the GA-FOPID controller exhibited a reduction in vibration of approximately 92.70% compared with the open-loop system by reducing the RMS value from 1.5058 × 10⁻⁴ m to 1.0996 × 10⁻⁵ m. By reducing the vibration level and enlarging the predicted stable machining region, these improvements could potentially contribute to longer tool life, improved surface finish, and reduced post-processing requirements, although these technological benefits were not directly modeled in the present study. The main innovation of this work involves a unique combination of fractional-order control, PZT actuation, and genetic algorithm optimization in a regenerative milling delay architecture. To the best of the authors’ knowledge, based on the literature surveyed in this work, this combination of techniques has not previously been reported for active chatter suppression. The stability lobe diagram (SLD) analysis, conducted under the single-mode approximation that serves as the reference framework for the like-for-like comparison of the five investigated configurations, shows that the critical axial depth of cut at the representative spindle speed increases from a_p,crit(1500) = 0.061 mm for the uncontrolled system to 0.52 mm under GA-FOPID control. This enlargement of the predicted stable machining region was further confirmed, at a comparable order of magnitude, when the structural model was extended to include the two next bending modes, indicating that the trend is not an artifact of the single-mode simplification. Therefore, although the results were obtained exclusively from numerical simulation and have not yet been experimentally validated, they support the use of optimization-based methods to implement FOPID strategies as a means to increase both reliability and performance of flexible milling configurations. Full article

Cantilever roadheaders are widely used in medium-soft rock tunneling. However, conventional pick cutters suffer from high rock-breaking load, excessive energy consumption, and severe abrasion, which restrict the performance of roadheader vehicle-end intelligent control systems. Existing ultrasonic rock-breaking studies mainly focus on drilling and polycrystalline diamond compact (PDC) cutters, while calibrated EDEM simulation and experimental studies of synchronous ultrasonic-vibration-assisted pick cutter cutting remain limited. This study investigates the rock-breaking behavior of synchronous ultrasonic vibration coupled with pick cutter cutting using 21 MPa artificial rock-like specimens. A calibrated EDEM simulation model was developed based on the Hertz–Mindlin with Bonding contact model and validated by uniaxial compression and Brazilian splitting tests. Meta-particle technology was applied to analyze fragmentation characteristics. The effects of ultrasonic frequency, cutting angle, and cone angle on rock-breaking load, debris production, and specific energy consumption were investigated through simulations and experiments. An ultrasonic-assisted cutting test system equipped with force sensors was established for validation. Results show that 30 kHz ultrasonic vibration effectively reduces rock-breaking load under the investigated operating conditions. A relatively favorable parameter combination obtained from the numerical simulations consists of an ultrasonic frequency of 30 kHz, a cutting angle of 40°, and a cone angle of 60°. Compared with conventional cutting, the optimized scheme reduces average cutting load by 74.69%, increases debris yield by 54.71%, and decreases mass-specific mechanical cutting energy consumption by 83.63%. This study provides quantitative data support for roadheader vehicle-end intelligent control systems. Full article

To address the demand for early hydrogen monitoring in power equipment insulation systems, a fiber-optic Fabry–Perot (F-P) hydrogen sensor based on a Pd–Cu alloy microcantilever is proposed. The microcantilever serves as the force-sensitive structure, with a Pd–Cu alloy film deposited as the hydrogen-sensitive layer and an Au reflective layer introduced to enhance optical reflection and suppress thermal drift. Hydrogen absorption induces volume expansion of the Pd–Cu film, causing cantilever bending and a consequent variation in the F-P cavity length, which leads to a shift in the characteristic wavelength of the reflected spectrum and enables wavelength-demodulated hydrogen detection. Finite element analysis was conducted to investigate the stress distribution and displacement response, confirming the effective amplification effect of the microcantilever structure. Sensor fabrication, packaging, and hydrogen response experiments were subsequently carried out. The results show a good linear response in the hydrogen concentration range of 0–300 ppm, with a wavelength sensitivity of approximately 20.8 pm/ppm and a limit of detection of 3.24 ppm. In a 24 h stability test, the baseline fluctuation standard deviation was 22.46 pm, indicating good stability and repeatable sensing performance. Temperature variation produced a wavelength sensitivity of approximately 0.2734 nm/°C, and environmental condition tests further demonstrated stable operation under temperature, humidity, vibration, and electromagnetic disturbances. The proposed sensor exhibits immunity to electromagnetic interference, intrinsic safety, and compatibility with miniaturized integration, showing promising potential for low-concentration hydrogen monitoring in power equipment. Full article

To meet the demand for high-range and high-frequency impact acceleration measurements, a fiber Bragg grating (FBG) accelerometer with a double-sided symmetrical inclined cantilever beam structure is proposed. The sensing principle is analyzed based on inertial and FBG sensing theories, and theoretical models for sensitivity and resonant frequency are derived. Using PPA-CF material and parameter optimization, the structural dimensions of the cantilever beam, effective fiber length, and proof mass are determined through numerical simulation. Finite element modal analysis shows a first-order natural frequency of 1284 Hz, with the dominant mode being axial translation of the mass block, ensuring pure axial strain on the FBG. A drop-weight impact calibration system is established for experimental testing. Results demonstrate that the sensor achieves a resonant frequency exceeding 1333 Hz, a measurement range above 500 g, and a practical sensitivity of approximately 1.183 pm/g. The linear response exhibits a coefficient of determination, R², of 0.9875, confirming excellent linearity. The proposed accelerometer effectively balances high-frequency response and measurement accuracy, providing a reliable solution for high-frequency impact monitoring in aerospace and impact dynamics applications. Full article

As the core sensor of inertial measurement units, the reliability of Micro-Electro-Mechanical Systems (MEMS) gyroscopes is critical for long-term navigation and motion control applications. To bridge the mechanism-data gap in MEMS multi-mechanism degradation modeling, this paper proposes a physics-informed dual-indicator reliability assessment framework based on Wiener processes. Two degradation indicators under consideration are frequency-related degradation caused by stiffness degradation and Q-factor degradation caused by damping degradation, for which corresponding physics-embedded stochastic degradation models are formulated. The two indicators are normalized and fused through a generalized weighted limit state function, where failure is defined as gyroscope-level performance failure. Closed-form reliability expressions are derived for linear limit states, while Monte Carlo simulation is used for nonlinear cases. Reduced-order multiphysics simulation cases, including a double-ended fixed beam and a cantilevered MEMS mass block, are used to demonstrate the mechanism-to-indicator-to-reliability modeling procedure. The results show that the proposed dual-indicator framework provides more balanced reliability assessment than single-indicator analysis under the simulation setting. The proposed method offers an alternative mechanism-informed approach for reliability analysis and lifetime prediction of other MEMS devices. Full article

Soft robots have attracted extensive attention owing to their high flexibility. Inflatable membrane tubes offer lightweight and safe environmental interaction, and external shaping actuators have further expanded their applicability. However, modeling such rigid-flexible gas coupled systems remains challenging due to the internal pressure, external loads, and complex deformations including bending, indentation, and wrinkling. To address curvature variation caused by tube deformation hysteresis, this study presents a static model based on virtual work and a segmented approach for inflatable robots. In the actuator unit, the irregular curvature variation and centerline deviation are quantified. In the cantilever unit, the effective bending moment, as well as the wrinkling and failure criteria are derived. The post-buckling deflection equation characterizes the abrupt curvature variation at the tube root caused by the local wrinkling and collapse. A multi-sensor experimental platform is conducted. The experimental results show that the proposed models achieve superior performance in static parameter identification and kinematic prediction. The bending torque error is below 7%, and the tip position error is less than 5% within the bending angle range of 0° to 100°, which confirm that the proposed models accurately predict the coupled deformation and provide a theoretical basis for the precise control of rigid–flexible gas coupled systems. Full article

Vibration energy harvesting has emerged as a sustainable solution for powering low-energy devices such as wireless sensors and wearable electronics. However, conventional vibration energy harvesters often suffer from narrow operational bandwidth and limited output performance under ultra-low excitation conditions. To overcome these limitations, this study proposes an asymmetric tristable vibration energy harvester integrated with an elastic magnifier (EM), hereafter referred to as the asymmetric TVEH with EM, to enhance energy conversion efficiency under weak excitation. A nonlinear two-degree-of-freedom electromechanical model is developed to describe the coupled dynamics between the cantilever beam and the EM, incorporating nonlinear restoring forces and electromechanical coupling effects. The system performance is investigated using the harmonic balance method (HBM) and time-domain numerical simulations. In addition, parametric studies are conducted to examine the influence of the EM mass and stiffness ratios on the dynamic response and energy harvesting performance. The numerical results demonstrate that the inclusion of the EM significantly amplifies the system response under ultra-low excitation $(f=0.055)$, enabling improved inter-well motion and enhancing energy conversion efficiency by up to 45%. To validate the analytical and numerical findings, an experimental prototype is fabricated and tested. The experimental results confirm the effectiveness of the proposed design, achieving a root mean square voltage of $V_{\mathrm{rms}}=5\mathrm{V}$ across a load resistance of $R_L=100\mathrm{k}\mathrm{\Omega }$ under a base acceleration of $1.4{\mathrm{m}/\mathrm{s}}^2$ at 14 Hz, measured over a 30 s window with a low-pass filter cut-off frequency of 100 Hz. The proposed asymmetric TVEH with EM consistently outperforms both the symmetric TVEH with EM and the asymmetric configuration without EM. Overall, the results highlight the pivotal role of the elastic magnifier in enhancing the dynamic response and harvesting performance under weak excitations, demonstrating strong potential for powering low-power electronic devices in practical applications. Furthermore, this work supports the United Nations Sustainable Development Goal SDG 7 (Affordable and Clean Energy) by promoting decentralized and renewable vibration-based energy harvesting technologies. Full article

In early-warning scenarios for thermal runaway in energy storage batteries, carbon monoxide (CO) may interfere with hydrogen detection and reduce the reliability of signal interpretation. To mitigate CO cross-interference under representative mixed-gas conditions and improve sensing stability, a fiber-optic microelectromechanical systems (MEMS) hydrogen sensor based on a Pd–Cu alloy-sensitive layer was developed. The sensor employs a single-cantilever structure and a reflective Fabry–Pérot (F–P) interferometer for optical readout. Comparative experiments were carried out using sensors coated with pure Pd and Pd–Cu-sensitive layers under pure H₂, CO background interference, and temperature-fluctuation conditions. The Pd–Cu sensor exhibited a good linear response over 0–500 ppm H₂, with a sensitivity of 0.0845 nm/ppm. Under a mixed atmosphere of 200 ppm H₂ and 500 ppm CO, the Pd–Cu sensor measured 198 ppm, whereas the pure Pd sensor measured 176 ppm, corresponding to relative errors of approximately 1% and 12%, respectively. In addition, the Pd–Cu sensor showed faster response/recovery behavior and better output stability after temperature compensation. These results indicate that, under the investigated conditions, the selected Pd–Cu-sensitive layer can effectively reduce CO-induced interference and improve the accuracy and stability of fiber-optic MEMS hydrogen sensing, supporting its feasibility for representative early-warning-related monitoring scenarios in energy storage batteries. Full article

The increasing demand for autonomous wireless sensors in Internet of Things (IoT) applications has intensified research on vibration energy harvesting, particularly in the low-frequency range where ambient vibrations are most prevalent. However, most vibration energy harvesters operate efficiently only at a single resonance mode, resulting in a narrow operational bandwidth and pronounced performance degradation under frequency detuning. To address this limitation, this paper proposes a multimodal hybrid piezoelectric–electromagnetic vibration energy harvester that exploits both the first and second resonance modes of a cantilever-based structure to achieve broadband low-frequency operation. The design is guided by the complementary utilization of strain-dominated and velocity-dominated regions associated with different vibration modes. Numerical modeling and finite element simulations are employed to investigate the influence of mass distribution, deformation characteristics, and relative velocity on energy conversion performance. A secondary cantilever carrying the electromagnetic coil is introduced to enhance the relative motion between the coil and the magnetic field, thereby extending the effective operational bandwidth. The experimental results demonstrate increased harvested power, improved energy conversion efficiency, and a significantly broadened effective frequency range compared to conventional single-mode piezoelectric and electromagnetic energy harvesters. Full article

This paper presents a yarn tension sensor based on Surface Acoustic Waves (SAW). To enhance the detection accuracy of the sensor, an improved beam structure is designed for tension measurement, along with intelligent algorithms for temperature compensation. Firstly, regarding the sensor structure, a simply supported beam with a hyperbolic surface is designed to achieve stress concentration by reducing the section modulus at the beam’s midpoint. Secondly, by incorporating an unbalanced split-electrode Interdigital Transducer (IDT) design, the sensor effectively suppresses signal sidelobe interference and significantly improves the structure’s tension sensitivity. Finally, in terms of signal processing, to eliminate the influence of environmental temperature fluctuations on measurements, a temperature-compensation algorithm based on Bayesian Optimization Least Squares Support Vector Machine (BO-LSSVM) with Gaussian Process regression is proposed. Experimental results show that the tension sensitivity of the improved structure was 8.2% higher than that of the doubly clamped beam and 12.7% higher than that of the cantilever beam. For temperature compensation, the BO-LSSVM model reduced the Mean Relative Error (MRE) by 5.67 percentage points relative to raw data and by 2.04 percentage points relative to the fixed-parameter LSSVM model, lowering the temperature sensitivity coefficient from 4.09 $(\times {10}^{-3}/°\mathrm{C})$ to 0.41 $({10}^{-3}/°\mathrm{C})$. Full article

The ability to assess molecular binding kinetics in real time is critical for advancing our understanding of molecular interactions in biochemical and biotechnological systems. This work presents a novel optical tweezer (OT)-based method to monitor molecular affinity in real time, focusing on the high-affinity streptavidin–biotin system as a model. Transparent poly(methyl methacrylate) (PMMA) microparticles functionalized with streptavidin were trapped before, during, and after binding with biotinylated bovine serum albumin (biotin–BSA), enabling the analysis of forward-scattered signals to detect nanoscale changes in particle size. By applying the Power Spectral Density method, the friction coefficient of individual particles was calculated, allowing for real-time tracking of binding dynamics and the estimation of the association rate constant ($k_{\mathrm{on}}\approx {10}^6{\mathrm{M}}^{-1}{\mathrm{s}}^{-1}$). These results are consistent with literature values and demonstrate the potential of this OT-based approach for non-invasive, label-free detection of molecular interactions. Compared to existing techniques, such as atomic force microscopy and cantilever-based sensors, this method offers significant advantages, including real-time monitoring, adaptability to different bioaffinity systems, and compatibility with miniaturized setups. This work establishes a foundation for using OT-based tools to monitor high-affinity molecular interactions in real time. While demonstrated here using biotinylated BSA as a model ligand, future studies will explore the method’s applicability to smaller ligands and more subtle surface modifications. Full article

Flow sensing is essential in biomedical engineering, industrial process control, and environmental monitoring. Conventional sensors, while accurate, are often constrained by high fabrication costs, complex processes, and limited design flexibility, restricting their use in disposable or rapidly customizable applications. This paper presents a novel ultra-low-cost airflow sensor fabricated entirely through fused deposition modeling 3D printing. The device employs a cantilever-based structure printed with PETg filament, followed by the deposition of a conductive ABS piezoresistive layer in a two-step process requiring no curing or post-processing. Experimental characterization reveals that the sensor operates in an ultra-low pressure range of 0.88–26.68 Pa, corresponding to flow velocities of 1.2–6.6 m/s. The sensor achieves a sensitivity of 967 Ω/Pa, a resolution of 9.27 Pa, and a detection limit of 83.27 Pa, with a total resistance change of approximately 51.5 kΩ. This kilo-ohm-scale response enables direct readout via a digital multimeter without requiring Wheatstone bridges or instrumentation amplifiers. The minimalist design, combined with sub-5 min fabrication time and material cost below $0.05, positions this sensor as an accessible platform for disposable, scalable, and resource-constrained flow monitoring applications in both biomedical and industrial contexts. Full article

This study aims to demonstrate the feasibility of a hybrid measurement system that combines Laser Doppler Vibrometry (LDV) and conventional accelerometers for operational modal analysis (OMA) of civil engineering structures. The proposed approach addresses the limitations of traditional accelerometer-based systems, particularly for large-scale or inaccessible structures, by integrating non-contact LDV measurements with conventional sensor data. Experimental tests were conducted on a cantilever beam and a pedestrian laboratory footbridge to validate the hybrid system. The LDV was used to measure velocity at key points, while accelerometers provided complementary reference acceleration measurements. Reflective targets were employed to facilitate non-contact data collection, allowing for the subsequent reuse of these targets for repeated measurements. The velocity data from the LDV were differentiated to obtain acceleration and integrated to estimate displacement, enabling a direct combination with accelerometer data. ARTeMIS Modal software was utilized to process and analyze the collected data, successfully identifying the natural frequencies and vibration modes of both structures. The results demonstrate that the LDV–accelerometer hybrid system effectively captures the dynamic behavior of structures, offering a comprehensive solution for modal analysis without extensive sensor deployment. This approach provides significant advantages in scenarios where traditional methods are impractical, positioning the hybrid system as a promising tool for dynamic analysis and infrastructure monitoring of complex structures. Full article

With the rapid development of high-voltage DC (HVDC) power systems, accurate measurement of surface electrostatic potential on insulating components has become critical for electric field assessment and insulation reliability. This paper proposes an electrostatic potential sensor based on cantilever micro-vibration modulation, which employs piezoelectric actuators to drive high-frequency micro-vibration of cantilever-type shielding electrodes, converting the static electrostatic potential into an alternating induced charge signal. An electrostatic induction model is established to describe the sensing principle, and the influence of structural and operating parameters on sensitivity is analyzed. Multi-physics coupled simulations are conducted to optimize the cantilever geometry and modulation frequency, aiming to enhance modulation efficiency while maintaining a compact sensor structure. To validate the effectiveness of the proposed sensor, an electrostatic potential measurement platform for insulating components is constructed, obtaining response curves of the sensor at different potentials and establishing a compensation model for the working distance correction coefficient. The experimental results demonstrate that the sensor achieves a maximum measurement error of 0.92% and a linearity of 0.47% within the 1–10 kV range. Surface potential distribution measurements of a post insulator under DC voltage agreed well with simulation results, demonstrating the effectiveness and applicability of the proposed sensor for HVDC insulation monitoring. Full article

To address the issue of low efficiency in recovering low-frequency vibration energy during vehicle operation, this paper proposes a piezoelectric energy capture harvester based on wheel vibration. The device employs a parallel configuration of dual cantilever beam piezoelectric transducers in its mechanical structure, with additional mass blocks to optimize its resonant characteristics in the low-frequency range. A synchronous switch energy harvesting circuit was designed. By actively synchronizing the switch with the peak output voltage of the piezoelectric element, it effectively circumvents the turn-on voltage threshold limitations of diodes in bridge rectifier circuits, thereby enhancing energy conversion efficiency. A dynamic model of this device was established, and multiphysics simulation analysis was conducted using COMSOL-Multiphysics to investigate the modal characteristics, stress distribution, and output performance of the energy harvester. This revealed the influence of the piezoelectric vibrator’s thickness ratio and the mass block’s weight on its power generation capabilities. Experimental results indicate that under 20 Hz, 12 V sinusoidal excitation, the system achieves an average output power of 3.019 mW with an average open-circuit voltage reaching 16.70 V. Under simulated road test conditions at 70 km/h, the output voltage remained stable at 6.86 V, validating its feasibility in real-world applications. This study presents an efficient and reliable solution for self-powering in-vehicle wireless sensors and low-power electronic devices through mechatronic co-design. Full article