Search Results (99)

Resonant mass sensors based on micro/nanoelectromechanical systems (MEMS/NEMS) offer a promising approach for label-free gravimetric detection. However, practical applications often require not only high sensitivity but also improved loading repeatability and reduced dependence on mass loading position. In this work, a suspended resonant mass sensor based on a 10 nm-thick Hf_0.5Zr_0.5O₂ (HZO) piezoelectric film is proposed. A central silicon loading platform is introduced to provide a mechanically robust and spatially uniform sensing region. A Kirchhoff plate model incorporating residual stress is established to analyze the effects of residual stress and platform geometry on the resonant characteristics. The device is fabricated by combining SOI micromachining with wet transfer of the ultrathin HZO film. Laser Doppler vibrometry measurements show a first-order resonant frequency of 1.303 MHz and a quality factor of 342, corresponding to an extracted residual stress of approximately 1.319 GPa. Finite element simulations calibrated by experimental parameters indicate a uniform first-mode displacement distribution and a linear frequency response to added mass from 0 to 1 ng. The obtained mass sensitivities are 150.7 Hz/pg and 166.8 Hz/pg from finite element and analytical models, respectively. The proposed structure provides a feasible route toward repeatable pg-level resonant mass sensing based on ultrathin piezoelectric films. Full article

Passaggio is a natural physiological phenomenon during vocal register transitions in singing, with its pitch location varying across individuals. Conventional identification methods rely on auditory judgment or voice type classification, which may be limited in accuracy due to individual differences. This study proposes a method for estimating individual passaggio intervals based on laryngeal surface vibration measured by a laser Doppler vibrometer (LDV). In this study, laryngeal surface vibration signals and singing voice signals were synchronously recorded from 20 trained singers using an LDV and a microphone. The results indicate that passaggio intervals can be estimated from the variation in the ratio between the first two dominant low-order peaks (L₀/L₁) in the laryngeal vibration spectrum. In blind perceptual validation, 71.67% of expert judgments fell within the estimated intervals and 96.67% within ±2 semitones. Comparison with reported pedagogical passaggio ranges (e.g., Miller) showed a 75% overlap, reaching 90% in male singers. These findings suggest that the LDV-based method for passaggio identification may provide a promising non-invasive approach for estimating individual passaggio intervals. However, as an exploratory study, further validation is required. Full article

Magnetostrictive patch transducers (MPTs) are highly efficient for generating and detecting ultrasonic waves for non-destructive evaluation (NDE), though their use on cementitious media and fibre-reinforced concrete has not yet been investigated. In this study, a COMSOL simulation, validated with laser-Doppler vibrometry, was first used to quantify patch deformation for use in subsequent simulation of wave propagation in samples. The MPT system was then validated on thin glass plates, producing tunable A₀, S₀, and SH₀ modes through frequency-wavelength matching. In cementitious mortar plates, SH₀ and SH₁ modes were demonstrated experimentally for the first time using MPTs. The validated COMSOL model was then used to interpret complex signals in quasi-plate and half-space cementitious mortar prisms, showing that MPTs generate Rayleigh, bulk SH, and surface-skimming SH modes. In steel fibre-reinforced concrete, surface-skimming SH wave speed correlated with increases in breaking strength even in the presence of surface features such as notches. Notably, Rayleigh wave speeds could not be measured in the presence of surface features, and the Rayleigh velocities measured in the same sample, but not in the local tested area did not correlate with SH speed. This behaviour is likely due to the non-uniform distribution of material constituents, including fibre-reinforcement and coarse aggregate, combined with the different propagation paths and depth sensitivities of the reported wave modes. Overall, racetrack-coil MPTs enable multimodal inspection of cementitious media, providing information on the presence of geometric features and material properties. Full article

Local impedance variations in structural waveguides partially reflect and absorb incident flexural waves, motivating wave-based strategies for passive vibration control. This study develops and experimentally validates a wave-energy framework to quantify and optimize flexural wave absorption by Kelvin–Voigt attachments on a finite Timoshenko beam. A finite element model is validated against Scanning Laser Doppler Vibrometry measurements from a clamped–clamped aluminum beam with a passive damper mounted near one end, with dashpot parameters identified through two independent approaches and the discrepancies attributed to parameter uncertainty. Wave decomposition of the simulated and measured velocity fields yields the power reflection coefficient ρ(ω) and power absorption coefficient α(ω) over the 0–15.3 kHz band. The spring stiffness and damping coefficient exhibit frequency-dependent optima and act as complementary, jointly tuned design variables. Expressing dashpot location in wavelength-normalized coordinates reveals a recurring spatial pattern in which absorption minima cluster around half-wavelength multiples, while multiple spanwise positions yield near-peak absorption at any given frequency. This pattern is governed primarily by the flexural wavelength, decoupling placement from parameter tuning, and persists across clamped–clamped, clamped–free, and free–free boundary conditions. Two independently tuned dampers further broaden the effective absorption band by suppressing local minima in α(ω). These results demonstrate that measurement-driven wave decomposition provides compact, physically grounded guidelines for passive damper placement in beam structures. Full article

Rockfall from slope unstable rock masses is a typical geological hazard induced by brittle failure, with abrupt occurrence, limited macroscopic deformation before failure, and a short warning lead time. Conventional static analysis methods are useful for design-stage stability checks, but they cannot continuously capture structural-plane damage or update the stability state in real time. Dynamic evaluation based on structural dynamics links measurable parameters such as natural frequency, damping ratio, mode shape, vibration trajectory, wave velocity, and energy dissipation to the degradation of structural planes. This review synthesizes the dynamic behavior mechanism, parameter system, theoretical models, sensing technologies, and engineering applications for slope unstable rock masses. Different from previous reviews that mainly summarize rockfall monitoring or conventional slope stability analysis, this paper organizes the literature by failure mode, monitoring scale, model assumptions, field validation, uncertainty sources, and engineering applicability. The single-degree-of-freedom models for sliding-, toppling-, and falling-type rock masses, multi-block chain-collapse models, and data-physics dual-driven surrogate models are compared critically. Contact monitoring based on MEMS sensors, non-contact LDV monitoring, acoustic emission, microseismic monitoring, coda wave interferometry, and cloud-edge early-warning architectures are further reviewed. Key challenges include field-scale validation under heterogeneous and anisotropic geological conditions, environmental compensation, robust threshold calibration, and probabilistic linkage between dynamic indicators and failure probability. The review provides guidance for selecting dynamic evaluation models, designing field monitoring systems, and developing full-life-cycle digital-twin platforms for rockfall risk mitigation. Full article

The identification of natural vibration modes in turbomachinery components is essential to ensure safe and reliable operation, particularly with respect to resonance avoidance. In lightweight structures such as bladed disks, conventional contact-based measurement techniques may alter the dynamic response of the system. This study presents an experimental comparison of one-dimensional (1D) and three-dimensional (3D) laser Doppler vibrometry for non-contact modal analysis of a miniature turbofan engine rotor. The investigation focuses on measurement accuracy, experimental complexity, and the practical applicability of both approaches. Experimental tests were conducted on an isolated rotor of the DGEN-380 engine using a scanning laser vibrometer system. The obtained natural frequencies and mode shapes were compared for both techniques. The results indicate that, for vibration modes dominated by axial motion, the differences between 1D and 3D measurements are typically below 1%. At the same time, the 1D approach significantly simplifies the experimental setup and reduces measurement time. These findings suggest that 1D vibrometry can be effectively used in selected engineering applications, while 3D measurements remain necessary for the full spatial characterization of complex vibration modes. Full article

A substantial share of reinforced-concrete infrastructure assets has reached an age where deterioration mechanisms such as cracking, delamination, and voiding may develop, potentially increasing safety risks and maintenance demands. Conventional condition assessment commonly relies on localized intrusive testing (e.g., coring) and manual sounding, which can be disruptive, labor-intensive, and partly subjective. Vibration-based Non-Destructive Testing (NDT) provides an alternative by exciting the structure and evaluating changes in its dynamic response. In contrast to previous studies, which typically assess a single excitation method in isolation, this study provides a systematic side-by-side comparison of three vibration-based NDT excitation approaches: mechanical impact using a custom compressed-air impact device, acoustic excitation, and shaker excitation. All three methods were evaluated under identical measurement conditions. The vibration response is measured using Laser Doppler Vibrometry (LDV), enabling non-contact acquisition of frequency-response signatures. A custom mechanical excitation device was developed and evaluated, and the results indicate that it provides stable and repeatable excitation with good defect discrimination. Experiments on specimens with representative defect types show that mechanical impact and shaker excitation yield the most repeatable and discriminative response features, whereas acoustic excitation provides insufficient signal-to-noise ratios (SNRs) for the smallest tested specimens. Among the evaluated setups, the Qsources surface-mounted shaker and the compressed-air impact device provided the most promising laboratory results. However, the large electrodynamic shaker was used mainly as a controlled reference excitation method, and scalable field inspection would require more compact and automated excitation solutions. The goal of this work is therefore to support the development of efficient LDV-based non-contact inspection methods for safer and more reliable monitoring of reinforced-concrete infrastructure. Full article

This paper presents a fully automated platform for real-time monitoring of fatigue-induced microstructural changes in metallic materials, using Rayleigh surface waves and Laser Doppler Vibrometry (LDV). The system integrates ultrasonic excitation, non-contact optical sensing, and high-speed signal processing in a unified LabVIEW environment. Rayleigh waves are generated via a contact transducer, while LDV captures surface vibrations with sub-nanometric velocity resolution, ensuring repeatability and eliminating coupling variability. The software automates synchronization, deterministic data acquisition, filtering, FFT analysis, and extraction of nonlinear coefficients (β₂, β₃) at high execution rates without the need for post-processing. Experimental validation under cyclic loading revealed a clear sensitivity hierarchy: the Rayleigh wave velocity remained invariant, the acoustic attenuation responded gradually, while the nonlinear parameters exhibited the earliest and steepest response to fatigue damage, confirming their superiority as early-stage indicators. The system offers low-latency timing, long-term stability, and modular design, establishing a robust data-streaming foundation that can support future integration with digital twin frameworks and machine learning models. Furthermore, the acoustic findings were successfully cross-validated using Infrared Thermography, which confirmed the critical damage transition phase. This work bridges nonlinear acoustics and software automation, providing a scalable diagnostic solution for predictive maintenance within structural health monitoring systems. Full article

Sensing audio using non-acoustic modalities such as millimeter-wave radar and laser-based systems has emerged as an active research area with significant implications for privacy, security, and robust speech processing. These approaches recover speech-related information from vibration measurements captured by non-acoustic sensing modalities. Prior work spans a wide range of techniques, from classical signal-processing pipelines to modern machine-learning and deep-learning models, enabling applications such as speech reconstruction, eavesdropping, automatic speech recognition, and noise-robust enhancement. Some systems rely on radar or laser sensing as a standalone audio surrogate, while others fuse radar-derived features with microphone signals to improve robustness in noisy or non-line-of-sight environments. Experimental results across the literature demonstrate that recovering intelligible speech or discriminative speech features from radar or laser-sensed vibrations is feasible under controlled conditions. However, performance remains sensitive to practical factors including sensing distance, object material and geometries, environmental interference, multipath effects, and task complexity. Not all speech-related tasks are reliably solved, particularly in unconstrained real-world scenarios. Overall, the field is rapidly evolving, with open challenges in robustness, generalization, and deployment, offering several promising directions for future research. Full article

Conventional excitation signals used in ultrasonic measurements, such as the one-cycle pulse, produce waveforms that experience significant attenuation and dispersion during propagation in highly attenuative materials, resulting in a low signal-to-noise ratio (SNR) and unreliable signal interpretation. Coded excitation is a well-established technique for improving the SNR; however, its practical benefit for ultrasonic guided-wave measurements under low-voltage and limited averaging conditions has not been systematically quantified. This paper presents an experimental investigation of coded excitations for accelerating ultrasonic guided-wave data acquisition through SNR improvement. A one-cycle pulse is compared with Barker-coded and complementary Golay-coded excitations over a wide range of excitation voltages (0.5–10 V) and averaging numbers (1–40). Guided waves are generated using piezoelectric excitation and measured using laser Doppler vibrometry, ensuring repeatable and coupling-independent measurements. The results show that the SNR achieved with Barker-coded excitations using fewer than ten averages is comparable to that obtained with a one-cycle pulse using forty averages. The 16-bit complementary Golay codes achieve a comparable SNR while requiring fewer than five averages. These findings demonstrate that coded excitations can significantly reduce the number of data acquisition cycles in guided-wave measurement, offering a practical pathway toward faster and more energy-efficient ultrasonic measurement systems. Full article

This work presents the design, fabrication, and experimental characterization of microelectromechanical system (MEMS) ultrasonic transducers engineered for multi-frequency operation in photoacoustic imaging (PAI). The proposed devices integrate multiple resonant geometries, including circular diaphragms, floated crosses, anchored cross membranes, and cantilever arrays, within compact footprints to overcome the inherently narrow frequency response of conventional MEMS transducers. All devices were fabricated using the PiezoMUMPs commercial microfabrication process, with finite element simulations guiding modal optimization and laser Doppler vibrometry used for experimental validation in air. The circular diaphragm exhibited a narrowband response with a dominant resonance at 1.69 MHz and a quality factor (Q) of 268, confirming the bandwidth limitations of traditional geometries. In contrast, complex designs such as the floated cross and cantilever arrays achieved significantly broader spectral responses, with resonances spanning from 275 kHz to beyond 7.5 MHz. The cantilever array, with systematically varied arm lengths, achieved the highest modal density through asynchronous activation across the spectrum. Results demonstrate that structurally diverse MEMS devices can overcome the bandwidth constraints of traditional piezoelectric transducers. The integration of heterogeneous MEMS geometries offers a viable approach for broadband sensitivity in PAI, enabling improved spatial resolution and depth selectivity without compromising miniaturization or manufacturability. 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

Unmanned Aerial Vehicles (UAVs) have become integral to modern applications, including smart agricultural robotics, where reliability is essential to ensure safe and efficient operation. It is commonly recognized that traditional fault diagnosis approaches usually rely on vibration and noise measurements acquired via onboard sensors or similar methods, which typically require continuous data acquisition and non-negligible onboard computational resources. This study presents a portable Laser Doppler Vibrometer (LDV)-based system designed for noncontact, offboard, and high-sensitivity measurement of UAV vibration signatures. The LDV measurements are analyzed using a Deep Extreme Learning-based Neural Network (DeepELM-DNN) capable of identifying both propeller fault type and severity from a single 1 s measurement. Experimental validation on a commercial quadcopter using 50 datasets across multiple induced fault types and severity levels demonstrates a classification accuracy of 97.9%. Compared to conventional onboard sensor-based approaches, the proposed framework shows strong potential for reduced computational effort while maintaining high diagnostic accuracy, owing to its short measurement duration and closed-form learning structure. The proposed LDV setup and DeepELM-DNN framework enable noncontact fault inspection while minimizing or eliminating the need for additional onboard sensing hardware. This approach offers a practical and scalable diagnostic solution for large UAV fleets and next-generation smart agricultural and industrial aerial robotics. Full article

With the growing use of 3D-printed polymers in structural applications, understanding their damage response under impact is critical for reliability and safety. This study investigates the impact response and damage progression in Fused Deposition Modelling (FDM)-printed Polylactic Acid (PLA) plates with varying infill densities (40%, 60%, and 100%) using a combination of scanning laser Doppler vibrometry (SLDV) and electromechanical impedance (EMI) techniques. Progressive impacts were applied in four stages, and damage was evaluated through wave attenuation, impedance deviation, and phase distortion metrics. Results show that lower infill densities exhibit more severe degradation, with increased damping and poor wave transmission, while 100% infill demonstrates higher damage resistance and better detectability. The findings underscore the importance of infill design in optimizing mechanical performance and structural health monitoring in additively manufactured components. Full article

The Laser Doppler Vibrometer (LDV) is widely used in precision vibration measurement due to its non-contact nature and high accuracy. However, when measuring non-cooperative targets, the internal stray light in the LDV interferes with the target’s return light, creating competition with the reference light, a phenomenon known as interference competition. This issue is particularly prominent in integrated transceiver LDV systems, where the backscattered light from the lens can be comparable in intensity to the target’s return light, significantly degrading phase extraction accuracy and limiting the LDV’s applicability. To address this challenge, this paper proposes a noise suppression algorithm based on the In-phase and Quadrature (IQ) demodulation. The algorithm uses the power spectrum within each frame’s relevant frequency band as an evaluation metric and employs the Three-point Probe Extremum Localization (3P-PEL) method to estimate the amplitude and phase of the stray light interference with the reference light in real time. This enables the accurate extraction of the interference signal between the measurement light and the reference light. Both simulations and experiments validate the effectiveness of the proposed method. The simulation results demonstrate that when the stray-to-measurement power ratio is below 0.25, the proposed algorithm can suppress spurious signals induced by multi-beam interference by more than 25 dB, while experimental results show it can reduce such signals below the LDV’s noise floor in various motion scenarios. The proposed algorithm holds potential applications in laser interferometry and effectively enhances LDV measurement accuracy. Full article