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Structural Health Monitoring (SHM) systems have widely been used to guarantee the safe functioning of electrical, mechanical, civil, and aerospace engineering assets. It is required to improve the SHM systems from different aspects in terms of smartification, performance, beneficiation, sustainment, automation, cost-effectivity, and safety using cutting-edge technologies. Blockchain is currently the most revolutionary technology in computer science. Implementation of Blockchain in different fields of academia and industry has recently given very good results. However, application of Blockchain in SHM is still in the infancy stage. Therefore, many challenges are still ahead. One of the main potential applications of Blockchain is to secure the sensor data. In this study, a local Blockchain approach is developed as a secure storage using the extracted Principal Components (PCs) of Frequency Response Function (FRF) data obtained from modal analysis of a plate-like structure. In general, Secure Hash Algorithm (SHA) is one of the most practical hash functions with efficient performance which has been employed in Bitcoin. Therefore, in this research, SHA-256 is considered to generate the hash for each block. To the best of our knowledge, this is the first attempt to develop a secure storage for SHM data using Blockchain.

Thin-walled parts are typically difficult-to-cut components due to the complex dynamics in cutting process. The dynamics is variant for part during machining, but invariant for machine tool. The variation of the relative dynamics results in the difference of cutting stage division and cutting parameter selection. This paper develops a novel method for whole cutting process optimization based on the relative varying dynamic characteristic of machining system. A new strategy to distinguish cutting stages depending on the dominated dynamics during machining process is proposed, and a thickness-dependent model to predict the dynamics of part is developed. Optimal cutting parameters change with stages, which can be divided by the critical thickness of part. Based on the dynamics comparison between machine tool and thickness-varying part, the critical thicknesses are predicted by an iterative algorithm. The proposed method is validated by the machining of three benchmarks. Good agreements have been obtained between prediction and experimental results in terms of stages identification, meanwhile, the optimized parameters perform well during the whole cutting process. [ABSTRACT FROM AUTHOR]

The static and dynamic performances of a machine tool structure are considered to constitute the primary factors affecting the load-carrying capacity, geometric accuracy and surface precision of the workpiece. The machining performance of a large machine tool under stable conditions is effectively determined by its dynamic response to the cutting force at low-frequency excitation. This study, therefore, investigated the static and dynamic characteristics of a large heavy-duty lathe machine tool in which the headstock and tailstock comprised critical component modules supporting a large workpiece during low-speed machining. Using a finite element model, the influences of the structural modules on the static and dynamic characteristics of the lathe were analyzed, considering the effects of the workpiece load. The results indicated that the fundamental vibration modes of the lathe were primarily dominated by headstock, tailstock, and workpiece behaviors. The maximum compliances of the lathe under the rated load were found to occur at relatively low frequencies (22, 40.7, and 82.7 Hz) and increase with the reduction in workpiece weight. Notably, these modal frequencies were significantly higher than the maximum rotational speed of the spindle (450 rpm). In addition, the dynamic rigidity corresponding to the rated speed was higher than that induced at the natural frequency. These results indicate that the subject lathe possesses sufficient capacity to sustain the cutting load during stable turning machining. This study can, therefore, help designers improve the performance of machine tools for future fabrication. [ABSTRACT FROM AUTHOR]

The application of oil-bearing joint that is widely used in various mechanical equipment can effectively improve the dynamic characteristics of integrated machineries. A fractal contact model of oil-bearing joint considering the effect of asperity interaction is proposed in this article. The equivalent stiffness and damping of oil-bearing joint are divided into a solid contact portion and a liquid contact portion. On the basis of elastic mechanics and fractal theory, the deformation of a single asperity of solid contact part is deduced. The stiffness and damping model considering the asperity interaction are obtained from the relationship between normal load and deformation. The stiffness and damping expression of the liquid contact part are also deduced based on the generalized Reynolds equation. It is concluded that the equivalent stiffness increases with the increase of the fractal dimension and the decrease of the fractal roughness parameter. At the same time, increasing the hydrodynamic viscosity can demonstrably improve the contact stiffness. Experiment shows that the proposed model is more in line with the actual load-stiffness relationship. The model considers the factor of asperity interaction and provides a theoretical basis for predicting the dynamic characteristics of oil-bearing joint. An accurate theoretical model of the dynamic characteristics for the oil-bearing joint surface was established. Identification of the dynamic properties of the oil-bearing joint surface using frequency response functions. The factors influencing the stiffness of solid portion and liquid portion were studied, respectively. [ABSTRACT FROM AUTHOR]

Purpose: This paper characterizes the dynamics and stability of metal cutting circular saws with distributed and lubricated guides. Though stability of point spring-guided circular saws is well studied, how the mass, damping, and stiffness properties of the fluid media between the rotating saw and distributed guides influences the saw's stress–stability relationship remains unexplored. Characterizing these aspects and describing how the fluid induces speed-dependent viscous shear stresses on the saw to potentially influence its cutting behaviour are the main new technical contributions of this paper. Methods: The governing equation of motion is solved using the Galerkin projection method, and through model-based investigations, we analyse the role of different lubricating fluids with differently sized guides and with changing clearances between the saw and the guides. We characterize the frequency–speed behaviour of the saw for its critical speeds and the forced vibration response of the saw using the frequency response function. Results: We note that stiffness of the fluid media plays a more significant role than its mass, damping, and/or viscosity. For large guides with stiff fluids and small clearances, instabilities occur at speeds lesser than the critical speed. For similar configurations, forced response characteristics are at least an order of magnitude dynamically stiffer than the case of the unguided saws. We further note that the free and forced vibration response for two smaller guides is better than one larger one. Conclusions: Our findings can instruct sizing and placing guides and in selecting appropriate fluid media for stabilizing metal sawing processes. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ground simulation of space quasi-zero gravity environment is essential in modal testing of space structures. The air flotation method is widely used, in which the air cushion unit is attached to the measured structure. This inevitably increases the total mass of the structure to be tested and leads to the incorrect prediction of modal parameters. And irregular airflow disturbances of the air cushion unit also have negative effects on the test. The fast elimination method is presented to remove the adverse impact in the test data based on measured frequency response functions. Numerical simulations are performed employing the magnetometer structure. Results show that this method effectively removes the adverse mass and the airflow effect. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, the flexural vibrations of rectangular AFM cantilever by supposing diverse polymeric specimens and immersion media has been studied. Here, poly styrene, poly propylene, poly carbonate, acrylonitrile butadiene styrene and high impact ploy styrene polymers are chosen as the soft specimens. Methods: At first the mechanical properties of the specimens have been obtained using NT-MDT SOLVER P47 atomic force microscope. To calibration the calculation of mechanical properties, poly ethylene and EPDM rubber have been used. To model the flexural vibrations of the rectangular AFM beam, Timoshenko cantilever model is used and DMT contact model is applied to supposed the adhesive force of the specimens. Results: The outcomes indicate that an increase of Young's modulus of the specimen, raises the resonant frequency of the beam, but reduces the amplitude of FRF of vertical displacement of the cantilever. By raising the viscosity of immersion media the resonant frequency and amplitude of FRF of vertical displacement of the cantilever reduce. Conclusions: The outcomes by FEM has been evaluated with experimental method. The comparison indicates good agreement. [ABSTRACT FROM AUTHOR]

Structural health monitoring of bridges based on train-induced vibrations has attracted extensive attention and takes advantage of the high-magnitude and regularly spaced features of trainloads. However, the monitoring process is restricted because the relationship between bridge characteristics and the dynamic features of train-induced vibration responses is not well represented. In this study, train-induced acceleration characteristics of a bridge are investigated, and the relationship between the train speed and spectral amplitude of the bridge acceleration at a frequency equal to the ratio of the speed to carriage length is revealed. Based on the phenomenon that the speed–amplitude correlation trend is consistent with the structural frequency response function (FRF), a dynamic index called the equivalent frequency response function (EFRF) is proposed. The evolution rules of the EFRF curve with varying natural frequencies and train loads are distinguished, and the structural performance variation can be determined according to the relationship between the structural stiffness, natural frequencies, and EFRF. Because the speed–amplitude points are scattered due to the train configuration parameters and measurement noise, the EFRF curve should be fitted first. In addition, the normal fluctuation in the speed–amplitude points is limited using the local Shewhart control chart, considering the heteroscedasticity of the speed–amplitude points. Then, speed–amplitude points that exceed the control limits are used to identify abnormal train-induced vibrations. Finally, the monitoring data for a railway bridge with multiple lanes are considered to verify the proposed method. The results show that the abnormal train-induced vibration warning based on speed–amplitude points have a similar performance to that based on the speed–acceleration correlation, but the causes of the abnormal vibration can be identified explicitly only with the speed–amplitude correlation. [ABSTRACT FROM AUTHOR]

In order to analyze the dynamics of a structural problem accurately, a precise model of the structure, including an appropriate material description, is required. An important step within the modeling process is the correct determination of the model input parameters, e.g., loading conditions or material parameters. An accurate description of the damping characteristics is a complicated task, since many different effects have to be considered. An efficient approach to model the material damping is the introduction of fractional derivatives in the constitutive relations of the material, since only a small number of parameters is required to represent the real damping behavior. In this paper, a novel method to determine the damping parameters of viscoelastic materials described by the so-called fractional Zener material model is proposed. The damping parameters are estimated by matching the Frequency Response Functions (FRF) of a virtual model, describing a beam-like structure, with experimental vibration data. Since this process is generally time-consuming, a surrogate modeling technique, named Polynomial Chaos Expansion (PCE), is combined with a semi-analytical computational technique, called the Numerical Assembly Technique (NAT), to reduce the computational cost. The presented approach is applied to an artificial material with well defined parameters to show the accuracy and efficiency of the method. Additionally, vibration measurements are used to estimate the damping parameters of an aluminium rotor with low material damping, which can also be described by the fractional damping model.

Metaheuristic algorithms have known vast development in recent years. And their applicability in engineering projects is constantly growing; however, their deferent exploration and exploitation techniques cause the engineering problems to favor some algorithms over others. This paper studies damage identification in steel plates using Frequency Response Function (FRF) damage indicator to detect and localize the healthy and damaged structure. The study is formulated as an inverse analysis, investigating the performance of three new metaheuristic algorithms of Wild Horse Optimizer (WHO), Harris Hawks Optimization (HHO), and Arithmetic Optimization Algorithm (AOA).� The objective function is based on measured and calculated FRF damage indicators. The results showed that the case of four damages with different damage severity levels presented a good challenge where the HWO algorithm was shown to have the best performance.� Both in convergence speed and CPU time.

Vibration-based damage detection tools are frequently employed because of their advantages over other non-destructive techniques. This paper presents an improved Frequency Response Function (FRF) indicator for damage identification in complex structures. To verify the effectiveness of the improved damage indicator, different structures are used, namely a 20-Bar Planar Truss (2D), a 28-Bar Space Truss (3D), a 72-Bar Space Truss, and a 600-bar Space Truss. The numerical models of all these structures are built in MATLAB using Finite Element Method (FEM). The improved indicator detects and localises single and multiple damages in the first stage. Next, after eliminating the healthy elements, it is used in a new objective function to solve the damage quantification problem using recent optimization techniques, including Artificial Gorilla Troops Optimizer (GTO), Dingo Optimization Algorithm (DOA), African Vulture Optimization algorithm (AVOA), and Gradient-Based Optimizer (GBO). The results demonstrate that all optimization techniques can accurately predict the exact level of damage. However, GTO is the most efficient in terms of convergence. To study the effectiveness of this indicator in case of noisy data, different levels of noise are considered in the damage assessment exercises.

The frequency response function (FRF) in the frequency domain is a black box used to collect physical information and to indicate the modal characteristics of a dynamic system. Analyzing the collected FRF data through the impact hammer test, dynamic parameters, such as stiffness, mass, and the damping matrix, can be estimated. By extracting and analyzing the FRFs within certain ranges of the lowest few resonance frequencies, this study presents a nondestructive method to estimate the dynamic parameters and the material properties. Updating of the dynamic parameters and material properties is a crucial process for the subsequent design and maintenance. This study presents a method to estimate the physical properties of structural members using measured FRF data and generalized inverse. By extracting and analyzing the FRFs within certain ranges of the lowest few resonance frequencies, the dynamic parameters were predicted. It was observed in numerical experiments that the proposed method could properly estimate the elastic modulus and dynamic parameters of steel beams, although the results were affected by the extracted FRF ranges. The physical properties were close to more accurate values in taking the FRFs at more resonance frequencies, as the member was flexible. The proposed method was also extended to a nondestructive test for an estimation of the compressive strength of concrete. However, it faced difficulty due to the external noise contained in the measured data. It was found sin the nondestructive test that the proposed technique was affected by external noise, unlike a simple steel beam. The concrete strength could be predicted by taking the FRFs in a wide frequency range containing the lowest two resonance frequencies and by averaging the repeated test results. [ABSTRACT FROM AUTHOR]

Viscoelastic material can significantly reduce the vibration energy and radiated noise of a structure, so it is widely used in lightweight sandwich structures. The accurate and efficient determination of the frequency-dependent complex modulus of viscoelastic material is the basis for the correct analysis of the vibro-acoustic behavior of sandwich structures. Based on the behavior of a sandwich beam whose core is a viscoelastic layer, a combined theoretical and experimental study is proposed to characterize the properties of the viscoelastic layer constituting the core. In this method, the viscoelastic layer is bonded between two constraining layers. Then, a genetic algorithm is used to fit the analytical solution of the frequency¬ response function of the free–free constrained beam to the measured result, and then the frequency-dependent complex modulus is estimated for the viscoelastic layer. Moreover, by varying the length of the beams, it is possible to characterize the frequency-dependent complex modulus of the viscoelastic material over a wide frequency range. Finally, the characterized frequency-dependent complex modulus is imported into a finite element model to compute the complex natural frequencies of a sandwich beam, and a comparison of the simulated and measured results displays that the errors in the real parts are within 2.33% and the errors in the imaginary parts are within 3.31%. It is confirmed that the proposed method is feasible, accurate, and reliable. This provides essential technical support for improving the acoustic vibration characteristics of sandwich panels by introducing viscoelastic materials. [ABSTRACT FROM AUTHOR]

The frequency response function (FRF) provides an input-output model that describes the system dynamics. Learning the FRF of a mechanical system can facilitate system identification, adaptive control, and condition-based health monitoring. Traditionally, FRFs can be measured by off-line experimental testing, such as impulse response measurements via impact hammer testing. In this paper, we investigate learning FRFs from operational data with a nonlinear regression approach. A regression model with a learned nonlinear basis is proposed for FRF learning for run-time systems under dynamic steady state. Compared with a classic FRF, the data-driven model accounts for both transient and steady-state responses. With a nonlinear function basis, the FRF model naturally handles nonlinear frequency response analysis. The proposed method is tested and validated for dynamic cutting force estimation of machining spindles under various operating conditions. As shown in the results, instead of being a constant linear ratio, the learned FRF can represent different mapping relationships under different spindle speeds and force levels, which accounts for the nonlinear behavior of the systems. It is shown that the proposed method can predict dynamic cutting forces with high accuracy using measured vibration signals. We also demonstrate that the learned data-driven FRF can be easily applied with the few-shot learning scheme to machine tool spindles with different frequency responses when limited training samples are available. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

This paper presents an analytical transfer matrix modeling framework for the forced vibration of a bending-torsional-warping coupling Euler-Bernoulli thin-walled beam carrying an arbitrary number of three degree-of-freedom (DOF) spring-damper-mass (SDM) subsystems. The thin-walled beam is divided into a series of distinct sub-beams whose ends are connected to the SDM subsystems. The transfer matrix for each sub-beam is developed based on the exact shape functions of the bending-torsional-warping coupling Euler-Bernoulli theory. Each SDM system is modelled by a set of effective springs based on the dynamic condensation method. The governing matrix equation is formulated based on the compatibility conditions of the placement and the force at the common interfaces of two adjacent sub-beams. Then, a closed-form expression for the frequency response function of the thin-walled beam system is proposed. The results computed by the proposed method achieve good agreement with those obtained by the conventional finite-element method, which shows the accuracy and reliability of the proposed method. The effects of the system parameters on the vibration transmission and vibration isolation properties of the thin-walled beam system are studied. The presented method can simultaneously consider arbitrary number of SDM subsystems and boundary conditions. Furthermore, none of the associated matrices are larger than 12 × 12, which provides a significant computational advantage. [ABSTRACT FROM AUTHOR]

This paper proposes a convolutional neural network (CNN)-based method with which to predict bolt clamping force using the frequency response of bolted structures. The dynamic characteristics of the bolted structure change with the bolt clamping force, which is predicted using a CNN trained with massive frequency response data. Big data required for training the CNN is constructed using prestressed frequency response analysis according to the clamping force of individual bolts. The numerical efficiency is increased using the Krylov subspace-based model order reduction (MOR) method. The frequency response for each set of bolt clamping forces calculated from the MOR method is converted into form of the magnitude and shape (MS) similarity spectrum by using the MS similarity function. Finally, an MS similarity map is generated by stacking the MS similarity spectrum at several output points. A CNN that is trained using massive MS similarity maps as training data, is used to predict the clamping force of bolted structures. To validate the efficiency and accuracy of a trained CNN in practical applications, the prediction results of the trained network in terms of computation time and accuracy were compared according to the size of the training input data. [ABSTRACT FROM AUTHOR]

This paper mainly studies the model design of a thin-film heat-flux sensor (TFHFS), and focuses on the comparison of three dynamic calibration methods. The primary motivation for studying this came from the urgent need for heat-flux dynamic measurements in extreme environments, and the one-sidedness of the dynamic performance evaluation of the corresponding TFHFS. The dynamic theoretical model of the TFHFS was originally established on the principle of a temperature gradient on the basis of a thermal radiation boundary. Then, a novel TFHFS sensor was developed, which can be used at temperatures above 880 °C and has a high sensitivity of 2.0 × 10−5 mV/(W/m2). It can function stably for long durations under a heat-flux density of 3 MW/m2. The steady-state, transient, and frequency calibration of a TFHFS were compared to comprehensively analyze the dynamic characteristics of the TFHFS. The steady-state response time measured by the step excitation method was found to be 0.978 s. The QR decomposition method was applied to the steady-state response experimental model construction, and the fitting degree of a second-order transfer function model obtained was 98.61%. Secondly, the transient response time of the TFHFS was 0.31 ms based on the pulse-excitation method. The transient relationship between the surface temperature and the heat flux, and the pulse-width dependence of the TFHFS transient response time were established. Surprisingly, the response frequency of the TFHFS, about 3000 Hz, was efficiently tested using the frequency response function (FRF), which benefitted from the harmonic characteristics of a periodic square-wave excitation signal. Finally, a comprehensive evaluation of the dynamic performance of the TFHFS was realized. [ABSTRACT FROM AUTHOR]

In energy harvesting systems, specifications of the generated electrical energy depend on the structure's dynamics. This dependence can be used to identify the system's joint characteristics. To this end, an innovative frequency-response-function (FRF) based identification method is presented. The investigated system is a cantilever beam shaped structure with an embedded bimorph piezoelectric bender, connected to a base via bolted joint as a depiction for wing of a UAV connected to fuselage. The implemented FRF is ratio of the piezoelectric output voltage to the base input displacement. The joint identification procedure consists of analytical modeling of the system with joint, experimental testing of the system and a real-coded Genetic Algorithm (GA) method. The joint is modeled as a combination of longitudinal and torsional springs, whose stiffnesses are obtained using the GA method. The obtained results indicate that the analytical model has good correlation with the experimental data. Then, effects of the joint characteristics on the energy harvester's performance are investigated by comparison of the system with two different joint assumptions, namely, rigid and realistic joint. Finally, the effects of various joint characteristics on the energy harvester's performance are presented and approaches to achieve the maximum performance of the system are suggested. [ABSTRACT FROM AUTHOR]

• Propose self-powered sensing of fluid-conveying piezoelectric pipes via energy harvesting. • Employ distributed-parameter electromechanical model to explore the nonlinear dynamics. • Identify the fluid-conveying piezoelectric pipes via output frequency response functions and system transfer functions. • Benefits of voltage OFRF of the transverse vibrations to self-powered sensing. This paper reports on an investigation of nonlinear energy harvesting from fluid-conveying piezoelectric pipes for self-powered sensing. Based on Euler Bernoulli theory, a distributed-parameter electromechanical model was employed to explore the nonlinear dynamics of fluid-conveying piezoelectric pipes. The Galerkin method and harmonic-balance analysis were employed to find output frequency response functions (OFRFs) and system transfer functions of the fluid-conveying piezoelectric pipes. The influences of fluid velocity on energy harvesting are also discussed. With an increase of fluid velocity, the resonance peak moves towards lower frequency, the odd-mode resonant peak amplitudes decrease, and the even mode resonant peak amplitudes increase. The semi-analytical results are supported by a numerical finite-difference method. The results demonstrate that the displacement, voltage, current, and power OFRFs can be increased by increasing the excitation amplitude and reducing the damping coefficient. The results show the advantage of using the voltage OFRF of the transverse vibrations of fluid-conveying piezoelectric pipes for self-powered sensing. [ABSTRACT FROM AUTHOR]

Vibration induced in a machining process due to variation in the chip thickness and dynamic stiffness of the cutting tool. Chatter is a serious issue since it causes poor quality characteristics, reduced production, and shortened tool life. The frequency response function (FRE) at the cutting tip has a massive effect on a cutting process's reliability. This study utilizes a piezoelectric transducer near to the cutting edge of the boring bar. Maximal damping achieved as the electrical circuit is shunted to the natural frequency. Experimental results revealed lower amplitude in shunt damping at different cutting condition in comparison with the non-damping conditions. Thus, making the boring operation dynamically stable as the harmonic oscillations are taken closer to the natural frequency. The percentage errors of damping ratios are also measured and found to be less than 1% respectively, which is rational, in the damping ratios and natural frequencies. Thus, piezoelectric damping is best suited dampers given in the present paper to minimize the vibrations. [ABSTRACT FROM AUTHOR]

Structures can be subjected to damage, leading to catastrophic failures and significant financial losses. Thus, researchers have been studying several tools to ensure reliability and safety. Thus, structural health monitoring has drawn attention, mainly by using tools such as vibration-based model and artificial neural networks. So, this work aims to develop a methodology to identify and classify damage in glass fiber-reinforced plastic composite beams through vibration data and artificial neural network. For this, healthy and damaged beams were manufactured considering different delamination sizes. Then, dynamic tests were performed to obtain both time and frequency domain data. As the large dimension of the data obtained by the vibrational tests, hinders its direct use to feed the neural networks, a strategy called dislocated series is used to reduce the raw signal size in mini batches, without losing important information to detect the damage. Results show that the artificial neural network topology and the parameters of the dislocated time series are crucial to the success of the proposed methodology. When these parameters are properly selected, it is possible to successfully detect and classify damage with less computational cost when compared to the direct use of the vibration-based model data. [ABSTRACT FROM AUTHOR]

In this study, a connecting rod that belongs to a diesel test engine is examined with an experimental method and the Finite Element Method (FEM). The purpose of the experimental method is to obtain the Frequency Response Function. The graph of this function provides the necessary vibrational qualifications of the connecting rod. Obtained vibrational characteristics can be considered as natural frequencies, damping ratios and mode shapes that belong to these vibrational modes. While natural frequencies can be obtained with both of these methods, mode shapes could only be produced with FEM. The natural frequencies that are obtained with experimental method is determined for the first mode as 0,625 Hz, for the second mode as 4,38 Hz, and for the third mode as 8,13 Hz. The natural frequencies that are obtained with FEM is determined for the first mode as 0,04575 Hz, for the second mode as 8,3861 Hz, and for the third mode as 8,9434 Hz. Considering the frequency range of the connecting rod, this study shows that the natural frequency values which is determined from this study and any frequency value of the connecting rod while the engine is running would not coincide. Besides damping ratios are calculated for the first mode as 19,766 %, for the second mode as 8,0116 %, and for the third mode as 3,4839 %. It is determined which modes have bending and torsion mode shapes. The results provide the useful information about the weaknesses and the vibrational qualifications that has to be improved in terms of dynamical and structural analysis of the connecting rod or engine itself. [ABSTRACT FROM AUTHOR]

This paper presents a novel adaptive probabilistic algorithm to identify damage characteristics by integrating the use of the frequency response function with an optimization approach. The proposed algorithm evaluates the probability of damage existence and determines salient details such as damage location and damage severity in a probabilistic manner. A multistage sequence is used to determine the probability of damage parameters including crack depth and crack location while minimizing uncertainties. A simply supported beam with an open edge crack was used to demonstrate the application of the algorithm for damage detection. The robustness of the algorithm was tested by incorporating varying levels of noise into the frequency response. All simulation results show successful detection of damage with a relatively high probability even in the presence of noise. Results indicate that the probabilistic algorithm could have significant advantages over conventional deterministic methods since it has the ability to avoid yielding false negatives that are quite common among deterministic damage detection techniques.

• The imaginary term of the FRFs and the imaginary part introduced by complex variable differentiation can be decoupled. • A multicomplex-step perturbation method is proposed for sensitivity analysis of FRFs. • The Cauchy-Riemann matrix representation simplifying sensitivity calculations into real matrix operations. • The derivation of multi-order and mixed-order sensitivity, particularly the Hessian matrix are obtained simultaneously. Imaginary perturbation is used in the complex step differentiation method to compute first-order derivatives, widely known as an effective approach for sensitivity analysis in structural dynamics. However, coupling of imaginary parts occurs in the damped frequency response functions when employing this method. To mitigate this coupling, a novel approach for sensitivity analysis based on multicomplex-step perturbation is proposed in this paper, for sensitivity analysis of Frequency Response Functions in structural dynamics. The structural parameters are perturbed in multicomplex domain, the dimensions of structural matrices are expanded using the Cauchy Riemann matrix representation, the equation of motion for sensitivity analysis in frequency domain is transformed to matrix operation in field of real numbers, imaginary term will not exist in the equation of motion for sensitivity analysis, the imaginary part of the frequency response function and the imaginary part of the perturbation are decoupled, the structural frequency response functions and the corresponding sensitivities are obtained from the dimension-expanded equation of motion. A truss structure and a solar wing are adopted to verify the accuracy of the proposed method. Results show that the sensitivity of FRFs can be effectively calculated using the proposed method. Compare to the finite difference method, the proposed method is not depended on the step-size selection procedure. The multi-order and mixed-order sensitivity matrices, especially Hessian matrix can also be obtained using the proposed method. [ABSTRACT FROM AUTHOR]

Recent Italian earthquakes have shown the high seismic vulnerability of pallet racking systems. In the down-aisle direction and in the absence of bracing systems, these structures are very flexible moment-resisting frames. Instead, in the cross-aisle direction they consist of slender trusses, stiffened by various bracing systems; the latter, although necessary for lateral stability, attract significant seismic accelerations, which can cause the stored goods to fall, posing a threat to human safety. To reduce this risk while increasing the rack structural performance, some mitigation systems were proposed, based on specific base-isolation or dissipation devices. In this paper, an innovative passive control system is investigated, i.e., the Load-Level Isolation System (LLIS), which consists of applying isolators to the load level to control the movement of pallets in the cross-aisle direction. The LLIS is based on the Tuned Mass Damper (TMD) strategy and exploits the high payload of these structures. Among the major uncertainties of this system are the amount of isolated mass and its position within the structure. Therefore, for a case study rack, the LLIS parameters (isolation stiffness and damping ratio) are optimized for various arrangements of this system, considering cases with one or two isolated levels. The applied optimization procedure is an extension of the classical TMD approaches. The effectiveness of the optimized LLISs is then investigated through bidirectional Time-History analyses on 3D Finite Element rack models. The results show that using the LLIS, even on a single load-level, can greatly reduce the upright stresses and the cross-aisle displacements and accelerations, and that the optimal position of the LLIS is in the upper part of the rack.

The main objective of this work is to propose a reliable routine standard operation procedures (SOP) for structural health monitoring and diagnosis of nuclear power plants (NPPs). At present, NPPs have monitoring systems that can be used to obtain the quantitative health record of containment (CTMT) buildings through system identification technology. However, because the measurement signals are often interfered with by noise, the identification results may introduce erroneous conclusions if the measured data is directly adopted. Therefore, this paper recommends the SOP for signal screening and the required identification procedures to identify the dynamic characteristics of the CTMT of NPPs. In the SOP, three recommend methods are proposed including the Recursive Least Squares (RLS), the Observer Kalman Filter Identification/Eigensystem Realization Algorithm (OKID/ERA), and the Frequency Response Function (FRF). The identification results can be verified by comparing the results of different methods. Finally, a preliminary CTMT healthy record can be established based on the limited number of earthquake records. It can be served as the quantitative reference to expedite the restart procedure. If the fundamental frequency of the CTMT drops significantly after the Operating Basis Earthquake and Safe Shutdown Earthquake (OBE/SSE), it means that the restart actions suggested by the regulatory guide should be taken in place immediately.

• Innovates wheel polygonal wear (WPW) diagnosis with calibrated wheel-rail FRF. • Cepstral-Bayesian FRF calibration using hybrid numerical-experimental data. • Weighted angle-synchronous moving average (WASMA) filter out rail disturbance. • FRF and WASMA synergy enhances accuracy for WPW quantitative diagnosis. The safety and efficiency of high-speed trains in China are significantly impacted by Wheel Polygonal Wear (WPW). Onboard monitoring methods for WPW currently suffer from reduced precision due to the intrinsic modal characteristics of the wheel-rail system and external disturbances such as rail roughness. To address this issue, this study develops a quantitative diagnostic approach for WPW employing a calibrated Frequency Response Function (FRF). A novel Cepstral-Bayesian calibration method is proposed for calibrating the FRF to precisely represent the real behaviors of the wheel-rail system, which is critical for considering system resonances. This method integrates information from dynamic simulation with sensor measurements. Furthermore, the weighted angle-synchronous moving average preprocessing is combined to reduce disturbances from rail roughness. Both dynamic simulations and field test data validate this technique, demonstrating its superior accuracy in quantifying WPW compared to existing methodologies. This offers a robust solution for both identifying and precisely quantifying WPW. [ABSTRACT FROM AUTHOR]

Vibration-based damage identification techniques have gained popularity immensely in the field of structural health monitoring (SHM). Frequency response function (FRF)-based damage quantification is mainly performed based on iterative model updating techniques. Most of these methods are time-consuming and erroneous in higher modes. Spectral element method (SEM) can overcome some of these limitations and can determine FRF expression directly for a broad class of civil structures. However, a closed-form expression for multiple damage severity is not proposed to date. In this study, an FRF-based formulation for quantifying damage has been proposed with the help of SEM in order to bypass the mode shape extraction for damage identification. To determine the effectiveness of the proposed formulation both numerical and experimental studies have been performed. A numerical simulation has been performed on a 14-storey shear building. Damage has been introduced by reducing the storey stiffness at intermediate and adjacent storeys. It has been perceived that damage severity at any storey can be estimated with only 3 sensors, one at the top storey and two others at the adjacent floors of the desired storey. To verify the effectiveness of the proposed expression, an experimental study has been carried out on a 9-storey miniature model. It has been observed that the first resonating peak amplitudes of the responses recorded simultaneously at desired locations of intact and damaged structures are sufficient to estimate the damage intensity. Thus, the proposed formulation is efficient as an output measurement-based approach. The novelty of this study lies in the proposed closed-form FRF-based multi-damage severity expression involving minimum number of sensors and without any information on the input excitation. The results obtained from both numerical and experimental study showcase the robustness, simplicity and applicability of the proposed formulation. [Display omitted] • FRF-based closed-form expression for damage quantification developed. • The proposed approach detoured mode shape extraction minimizing error and computational time. • The one-shot approach involves only 3 sensors to determine damage severity at a particular storey. • The effortless application of proposed approach with real data sets it apart. • Study novelty involves mathematical development and results within permissible range. [ABSTRACT FROM AUTHOR]

Microvibrations are one of the main factors contributing to platform jitter and a decline in pointing stability and precision. Among various disturbance sources, reaction wheel assembly (RWA) is one of the most significant ones and has drawn the interest of numerous scholars. How to evaluate the influence of the disturbances of RWA on the pointing accuracy of a spacecraft is an arduous task because it involves multiple disciplines. The acquisition of the frequency response function (FRF) from the disturbance source to the sensitive payload is one of the most crucial stages in integrated modeling. Direct measurement of the FRF in the six directions is challenging because of the restricted room for RWA installation in a spacecraft, particularly in small satellites. In this paper, a general method based on the Hv algorithm to obtain the FRF is presented. This method only needs the RWA, itself, as an excitation source. Then, in order to acquire the FRF, we use an optical remote-sensing satellite as the research object. The peak positions of FRF obtained by different RWAs are basically the same, while the amplitudes are slightly different, indicating that this method is effective. This method takes into consideration the coupling between the RWA and the spacecraft, making it possible to multiply the RWA disturbance measured at a fixed interface with the FRF, to determine the image motion of the sensitive payload.

The main purpose of this article is to monitor the natural frequency of stainless steel (SS304) with and without defect by spray-coated smart graphene nanoplatelet (GNPs)-doped poly (methyl methacrylate) (PMMA) nanocomposite strain sensor and human health by smart Lycra denim textile sensor. Methods such as impact hammer test and NI-daq, finite element method (FEM) simulation by Abaqus 6.12, and fast Fourier transform (FFT) study were applied for frequency monitoring of SS304. For human health monitoring, edema disease inspection, cough, and biceps locomotion were studied by graphene sol–gel textile sensor. We report eight sensors fabricated by scotch tape exfoliation method and their sensitivity was checked in terms of gauge factor (GF). The highest and lowest GF-based sensors were checked for sensitivity in the defect (hole) specimen. These sensors were used to sense the natural frequency of SS304 at three different positions in the cantilever beam. The same quantity of GNPs was used for making Lycra denim textile sensors for human health monitoring. The Lycra denim textile sensor showed a 216% change in resistance in the left calf muscle, which is less than right leg flexibility, indicating good sensitivity. In addition, the textile sensor helped in sensing coughing and biceps monitoring. The ease in fabrication and high sensitivity demonstrate the potential ability of GNPs for futuristic smart material for structural and human health monitoring. [ABSTRACT FROM AUTHOR]

Motion control analysis should consider the system's uncertainty to ensure the intelligent vehicle's autonomy. The clearance structure of the transmission shaft is modeled as a cantilever beam with double clearance to predict the clearance vibration for mitigating the nonlinearity. Based on the Kelvin–Voigt collision model, a clearance model was developed using time-varying parameters identified by the wavelet transform. Comparing the frequency response functions (FRF) of the initial model with constant parameters and the updated model with time-varying parameters, the experimental results from the updated model indicate that the modal assurance criterion (MAC) is increased by 42.92%, 31.08%, 38.97%, and 50.74% in the first-four order. Cross-signature assurance criteria (CSAC) and cross-signature scale factor (CSF) have been increased by 6.55% and 12.37%. The control method based on the clearance model has been verified. In the case of 120 km/h, compared with model-predictive control (MPC) and sliding mode control (SMC), the peak of the lateral position error was reduced by 35.7% and 14.3%, and the peak of the heading error was reduced by 50% and 15.6%. [ABSTRACT FROM AUTHOR]

This study presents iterative optimal sensor placement (OSP) techniques using the modal assurance criterion (MAC) and the effective independence (EI) algorithm. The algorithms use the proper orthogonal mode (POM) extracted from the frequency response functions (FRFs) of dynamic systems within a wide range of frequencies. The FRF-based OSP method proposed in this study has the merit of reflecting dynamic characteristics, unlike the mode shape-based method. Evaluating the MAC values and the EI indices at each iteration, the DOFs of low contribution to the objective function of candidate sensor DOFs are deleted from master DOFs and moved to slave DOFs. This process is repeated until the sensor number corresponds with the master DOFs. The validity of the proposed methods is illustrated in an example, the sensor layouts by the proposed methods are compared, and the layout inconsistency between the MAC and the EI techniques is analyzed. [ABSTRACT FROM AUTHOR]

Multipocket thin-walled parts are used extensively in aerospace industry, and their dynamics greatly depend on the structures. Available methods for the prediction of their dynamics are repetitive modeling and computational demanding. This paper presents a generalized equivalent method with high computational efficiency to predict the dynamics of multipocket thin-walled parts. The parts compose of a series of dynamics units, which can be further decomposed into thin plate and adjacent structure. The dynamics model of the thin plate is developed based on the characteristic of the dimension and the vibration in machining. The adjacent structure is regarded as the flexible boundary condition of the thin plate model, which is equivalent as cantilever beam. The cross sections of the beam are parameterized based on subareas, which makes the calculation rapidly. This generalized equivalent method is validated by the frequency response function (FRF) measurement of seven points on the benchmark including different thin plates and adjacent structures. The proposed method reaches a good agreement with the experimental tests; meanwhile, it can avoid reduplicative modeling and is ~ 100 times more computationally efficient than the typical finite element method. [ABSTRACT FROM AUTHOR]

To facilitate climate change adaptations and water management, estimates of precipitation retention time (time required for precipitation to reach a lake) can help to accurately determine a water body's terrestrial water storage capacity and water cycle. Although estimating the precipitation retention time on land is difficult, estimating the lag between precipitation on land and a rise in lake water levels is possible. In this study, the delay times (using a depth metre installed in the mooring system in the northern basin of Lake Biwa from August 2017 to October 2018) were calculated using response functions, and it evaluated the precipitation retention time in the catchment. However, as several delays between the river surface flow (<1 d) and shallow subsurface flow (≈45 d) remained unidentified, the delay times resulting from direct precipitation on the lake as well as from internal seiches were determined. The results suggest that delay times of approximately 20 d correspond to the paddy–waterway system between the river inflow and the subsurface flow, and that this effect corresponds to that of large rivers such as the Ane River. These findings can enhance water management strategies regarding the regulation of river flows, adapting to climate change-induced fluctuations in precipitation. [ABSTRACT FROM AUTHOR]

Increased attention has been given to ground-borne vibrations induced by railway vehicles and to the effects of these vibrations as they propagate through the ground into nearby buildings. Various studies, mainly based on numerical methods as well as physical modelling, have been carried out to investigate this problem. To study the dynamic response of tunnels and the surrounding soil due to train-induced vibration loads, a centrifuge test was conducted with a small-scale model in 1 g and 50 g stress field environments. An aluminum tube was embedded in sand to model the underground tunnel. A small parallel pre-stressed actuator (PPA) was employed to apply vibration loads on the tunnel invert. The model responses were measured using accelerometers. Both time and frequency domain analyzes were performed. The test results demonstrated that electronic noise had a clear impact on the test results and should be eliminated. It also found that the dynamic response of both the tunnel and soil were affected by the stress field. Therefore, it is important to account for the stress field effects when assessing the ground-borne vibration from tunnels. [ABSTRACT FROM AUTHOR]

Considering the frequency dispersion and the scale sensitivity in wave propagation, the central frequency and bandwidth should be carefully selected in Lamb wave-based structural health monitoring. These crucial parameters are hardly determined without the prior knowledge. Therefore, massive trials should be conducted before the formal test. A Fourier spectral Frequency Response Function (FRF) method is proposed to address this problem. As the FRF contains wide-band information on the relationship between excitation and output, the Lamb wave responses in a wide frequency range can be estimated by using an arbitrary virtual input within the frame of single FRF test, being free from the massive experimental works. The theoretical FRF can be obtained from the unit impulse response of a linear system, but this path is impracticable due to the difficulty of exciting the ideal impulse. Considering the integral relationship and Fourier differential properties between step excitation and the ideal impulse, a robust approximation of wave signal by FRF is developed. Synthetic data tests and experiments both verified that the present method can accurately extract the response in isotropic and anisotropic materials for the specifically designed excitation signal in a wide parameter range. [ABSTRACT FROM AUTHOR]

Machining is widely used for finishing process of the entire manufacturing process chain. Machining process of thin plate, however, is not an easy task. This is because excessive vibration (chatter) can rise during operation. To predict the chatter vibration, a stability lobe diagram (SLD) is usually utilized which is strongly dependent on the frequency response function (FRF). This paper proposes an alternative approach for analyzing modal analysis by finite element method (FEM) to obtain FRF during machining thin-walled plate. The result showed that simulation result has good enough agreement to experimental result with slight differences caused by the assumed boundary conditions in the FEM process. This approach can be used to reduce the use of hammering tests and can be used to get FRF of multi stage working.

The paper presents the method of assessment of the technical condition of the leading edge of the horizontal stabilizer of an F-16 Block C aircraft made from composite materials. The described method was an experimental measurement of the acoustic pressures generated by the technically operational element and the element with the distorted structural continuity and then a comparison of these pressures in the curves of time and frequency in order to assess how the damage impacts the parameters of the acoustic wave. The test was performed in a dual-channel system, the pressure was induced through impacts on the investigated element with an impact hammer and then, based on the measured induction parameters and the generated acoustic wave, the function of frequency response was calculated, based on which the authors assessed how the structural damage influenced the curve characteristics of the acoustic pressure in the domain of frequency. The described method may be used as an efficient method of non-destructive diagnostics of the airframe elements of an aircraft.