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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.

This paper focuses on the use of vibration measurements for the purpose of cost-effective performance evaluation for the safety management and maintenance of Japan’s social infrastructure like bridges. Since modal properties are often used to diagnose damage of structures by analysing their changes, various modal identification methods have been developed in the past few decades. Among these, the FDD method has still attractive attention because of its simplicity and practicality. It is also highly applicable to simultaneous observation at multiple points and even complex modes can be identified instantly. On the other hand, the applicability of this method to impact tests applied to evaluate the condition of structures has not been sufficiently discussed to date. In this study, we will clarify the applicability to impact tests by reconstructing the theoretical background of the FDD method. Furthermore, we will show from theory that when there is a correlation between inputs, higher-order singular values, which should be noted when applied to impact tests, will be affected. The conclusions obtained from the reconstruction of the theoretical background will be verified based on numerical experiments and actual observation records.

In this work, a time–frequency analysis of two railway bridges included in the InBridge4EU project database is presented. The study focuses on the identification of modal parameters from free responses after train passages and their comparison with estimations obtained from ambient vibration data. The wavelet transform is introduced as a valuable tool for detecting both free and forced bridge responses due to different train passages, as well as for conducting time–frequency analysis. This approach is particularly relevant for the identification of structural damping, given its dependence on vibration amplitude, as it enables the estimation of realistic values representative of bridge behavior under operational conditions. Additionally, the paper examines the complementary use of free vibrations for identifying natural frequencies and comparing them with results from ambient vibration tests. Wavelet analysis further reveals the predominant frequencies in the structural response before, during, and after train crossings, thereby capturing the influence of the moving vehicle on bridge dynamics.

Linearized dynamic bearing parameters and models are of essential interest for rotordynamic analyses in machine design. This paper experimentally studies the impact of pad preload and pivot offset on the frequency-dependent characteristics of dynamic stiffness (K) and damping coefficients (C) of a KC-model for tilting-pad journal bearings. For this purpose, two four-pad test bearing configurations (preload m=0.17, pivot offset 0.5 and preload m=0.47, pivot offset 0.6) that differ highly with respect to the pad design parameters are investigated. Contributing effects on the results due to geometric differences are excluded as far as possible, as only one aligning ring and one pivot support design is used. The tests are conducted on a high-performance test rig for surface speeds up to 140 m/s and excitation frequencies of 500 Hz. Significant deviations between the two bearings are identified that generally match theoretically predicted differences and, therefore, contribute to the validation of dynamic bearing modeling.

For topology optimization problems under harmonic excitation in a frequency band, a large number of displacement and adjoint displacement vectors for different frequencies need to be computed. This leads to an unbearable computational cost, especially for large-scale problems. An effective approach, the Second-Order Arnoldi (SOAR) method, effectively solves the response and adjoint equations by projecting the original model to a reduced order model. The SOAR method generalizes the well-known Krylov subspace in a specified frequency point and can give accurate solutions for the frequencies near the specified point by using only a few basis vectors. However, for a wide frequency band, more expansion points are needed to obtain the required accuracy. This brings up the question of how many points are needed for an arbitrary frequency band. The traditional reduced order method improves the accuracy by uniformly increasing the expansion points. However, this leads to the redundancy of expansion points, as some frequency bands require more expansion points while others only need a few. In this paper, a bisection-based adaptive SOAR method (ASOAR), in which the points are added adaptively based on a local error estimation function, is developed to solve this problem. In this way, the optimal number and position of expansion points are adaptively determined, which avoids the insufficient efficiency or accuracy caused by too many or too few points in the traditional strategy where the expansion points are uniformly distributed. Compared to the SOAR, the ASOAR can deal with wide low/mid-frequency bands both for response and adjoint equations with high precision and efficiency. Numerical examples show the validation and effectiveness of the proposed method.

To enhance wind farm frequency regulation in renewable-dominant power systems, this paper proposes a bi-level hybrid framework integrating deep learning and model predictive control (MPC) by retaining the critical wake propagation delay while neglecting higher-order turbulence effects. The upper layer employs a synthetic inertial intelligent control strategy based on contractive autoencoder (CAE) and deep neural network (DNN). Particle swarm optimization (PSO) obtains optimal synthetic inertial parameters for dataset construction, CAE extracts features from multi-dimensional inputs, and DNN outputs optimal coefficients to determine the total power deficit the wind farm needs to supply. The lower layer uses a nonlinear model predictive control (NMPC) strategy with the discretized rotor motion equation as the prediction model and optimization under constraints to allocate the total power deficit to each turbine. MATLAB/Simulink case studies show that, compared with fixed-coefficient synthetic inertial control, the proposed framework raises the frequency nadir by 0.01–0.02 Hz, shortens the settling time by over 200 s under 2–4% load disturbances, and maintains rotor speed within the safe range. This work significantly enhances the wind farm’s frequency regulation performance, contributing to power system and energy sustainability.

An accelerometer mounting technique has large implications on the frequency range and accuracy of the measurement, with stiffness and the mass relative to the monitored structure as the primary concerns. The International Organization for Standardization (ISO) gives an extensive list in 5348:2021, detailing mounting methods, and provides recommendations for testing mounts that are not specifically defined. In the nuclear industry on the laboratory scale, there is a need for vibration measurements for predictive maintenance and process monitoring that are nondestructive and capable of working in high-temperature environments. Commercial adhesive products with easy application and removal were tested as nondestructive methods, while quick mounts to a commonly used aluminum frame were tested as nondestructive and have potential applicability in high-temperature environments. The sinusoidal excitation method was used, measuring frequencies from 50 Hz to 10 kHz in one-third octave band intervals, utilizing three accelerometers and comparing the results to those obtained with the stud-mounting method. Using the lowest ±3 dB threshold across each accelerometer, foam dots and poster strips were not successful, and foam tapes were accurate up to 2000 Hz, hose clamps and zip ties up to 800 Hz, and a custom 3D printed mount up to 1000 Hz. Knowing the limitations of each mounting technique allows for accurate measurements within the appropriate range.

To quantify the effect of frequency-range-specific hand–arm vibration (FRS-HAV) exposure on the risk of musculoskeletal disorders of the upper limb (UMSDs), we performed an analysis among the study sample of the German Hand–Arm Vibration Study. In total, 206 cases and 609 controls were included in this analysis. Cases were new patients with UMSDs. Controls were a random sample of people with compensable occupational injuries. Standardized personal interviews were performed among cases and controls. In addition to leisure activities and comorbidities, detailed work histories were obtained from all participants. To quantify FRS-HAV exposures, a database of vibration measurements of over 700 power tools was used. This database allows detailed quantification of vibration exposure over long periods of time. A dose–response relationship between FRS-HAV exposure and UMSDs was quantified using conditional logistic regression analyses. After adjustment for relevant confounders, consistent and statistically significant exposure–response relationships were observed between cumulative vibration exposure and UMSDs. The effect of vibration exposure on the risk of UMSDs is mainly concentrated in the frequency range ≤ 50 Hz. This suggests that the current ISO frequency-weighting curve for quantifying hand–arm vibration exposure is reasonable and can be used for vibration-related risk assessment, especially for musculoskeletal disorders.

Vibration-fatigue failure occurs when a structure is dynamically excited within its natural frequency range. Unlike metals, which have constant fatigue parameters, polymers can exhibit frequency-dependent fatigue parameters, significantly affecting the vibration resilience of 3D-printed polymer structures. This manuscript presents a study utilizing a novel vibration-fatigue testing methodology to characterize the frequency dependence of polymer material fatigue parameters under constant temperature conditions. In this investigation, 3D-printed PLA samples with frequency-tunable geometry were experimentally tested on an electro-dynamical shaker with a random vibration profile. Using the validated numerical models, the estimation of vibration-fatigue life was obtained and compared to the experimental results. Performing the numerical minimization of estimated and actual fatigue lives, the frequency-dependent fatigue parameters were assessed. In particular, the results indicate that the tested samples exhibit varying fatigue parameters within the loading frequency range of 250–750 Hz. Specifically, as the loading frequency increases, the fatigue exponent increases and fatigue strength decreases. These findings confirm the frequency dependence of fatigue parameters for 3D-printed polymer structures, underscoring the necessity of experimental characterization to reliably estimate the vibration-fatigue life of 3D-printed polymer structures. The utilization of the introduced approach therefore enhances the vibration resilience of the 3D-printed polymer mechanical component.

The slug frequency (SF), which refers to the number of liquid slugs passing through a pipe during a specific time, is an important parameter for characterizing the multiphase intermittent flows and monitoring some process involving this kind of flow. The simplicity of the definition of SF contrasts with the difficulty of correctly measuring it. This manuscript aims to review and discuss the various techniques and methods developed to determine the slug frequency experimentally. This review significantly reveals the absence of a universal measurement method applicable to a wide range of operating conditions. Thus, the recourse to recording videos with high-speed cameras, which can be used only at a laboratory scale, remains often necessary. From the summarized state-of-the-art, it appears that correctly defining the threshold values for detecting the liquid slugs/elongated bubbles interface from physical parameters time series, increasing the applicability of instrumentations at industrial scales, and properly estimating the uncertainties are the challenges that have to be faced to advance in the measurement of SF.