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Operational modal analysis (OMA) is required to maintain large-scale and necessary civil infrastructures. The non-contact method of OMA using digital image correlation and point tracking algorithms requires a speckle pattern placed on the structure. Alternatively, advanced computer vision methods like optical flow and phase-based video motion magnification (PBVMM) techniques are used to measure modal parameters. Despite the importance of PBVMM, the users should know the range of frequencies in which the natural structure frequency lies. A methodology based on an unsupervised machine learning technique is developed to extract the modal parameters blindly from its recorded digital video. The proposed methodology uses complex steerable pyramids and an unsupervised machine learning technique, also known as principal component analysis, and analytical mode decomposition with a random decrement technique to blindly extract the modal parameters of a structure. This study validated the proposed methodology using a multi-degree of freedom (DOF) numerical model. The results are compared with theoretical and estimated values and are in good agreement. Furthermore, it is implemented on a laboratory benchmark SDOF, MDOF, and real-time videos of the London Millennium and Tacoma Narrows bridges for blindly extracting the modal frequencies and damping ratios. [ABSTRACT FROM AUTHOR]

This study employs advanced techniques, namely the improved multi-synchrosqueezing transform (IMSST) and the Fouriersynchrosqueezed transform (FSST), to extract the instantaneous frequency of the Humber Bridge, in the UK, in operational conditions. First, a brief overview of the relevant theories behind the techniques used is provided. These techniques are then applied to track the instantaneous frequencies within the monitored vertical acceleration data of the bridge. The instantaneous frequencies extracted by both techniques are verified against each other. The investigation further encompasses the development of three distinct regression models: a simple regression model, an expanded regression model and a regression model based on principal component analysis (PCA). The efficacy of the PCA-based model is scrutinised by generating and testing datasets that mirror the monitored data, with the Kolmogorov-Smirnov (KS) test confirming theirvalidity. The findings of this research indicate a statistically significant inverse relationship between modal frequency and acceleration intensity. Furthermore, by incorporating wind effect considerations into the regression analysis, the R-squared values in both the expanded and PCA-based models exhibit substantial improvements. This demonstratesthe performance of the enhanced model in capturing the dynamics of the bridge. The robustness of the PCA-based model is furthercorroborated by its performance during testing, proving its potential as a reliable tool in structural health monitoring (SHM). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering 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.)

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology 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.)

Copyright of Chinese Journal of Applied Mechanics is the property of Chinese Journal of Applied Mechanics 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.)

The use of tuned liquid dampers (TLDs) as an alternative to reduce the response of flexible structures with a low amount of structural damping is a viable option. The correct characterization of the dynamic properties of the TLD plays an important role in the performance of the TLD-main structure system. This work presents the results of an experimental study to evaluate the dynamic properties of a scaled rectangular TLD using high-speed videos. For the experimental investigation, a scaled rectangular TLD is subjected to lateral displacement of the sinusoidal type with amplitudes that range from 5 to 40 mm and frequency equal to 0.625 Hz. The dynamic properties of the TLD system are identified with the use of high-speed videos with a duration of 28.96 s and recorded at 500 frames per second (fps). The recorded videos are analyzed with the software Tracker to extract time histories of wave elevation at predefined locations. The frequency and damping of the TLD system are identified from the time histories of wave elevation through Fourier analysis and free-vibration decay. The findings of this study revealed that the identified dynamic properties of the TLD by using high-speed videos presented small differences with respect to the target values, with errors that range from 0.93 to 2.9% for frequency and from 1.6 to 8.8% for damping, indicating that the use of high-speed videos can be an alternative to evaluate the dynamic properties of TLD systems. [ABSTRACT FROM AUTHOR]

Purpose: The real-time dynamics of the single-link flexible manipulator is a challenging problem due to its inherent instability and in situ vibration. In order to add the criticalities to these real-time dynamics, run-time vibration does play a pivotal role in designing a robust control system for the flexible robotic manipulator. Methodology: Governing differential equations and the boundary conditions are usually considered exact of the single-link manipulator and the formulation leads to an Eigenvalue problem where the elements of the matrices are in exact form. Double parametric form has been used to solve the fuzzy differential equation. Results and Conclusions: In this paper, a new idea has been introduced in the above problem for a representative single-link robotic manipulator considering the uncertainty in the associated parameter(s) in the governing differential equation, which may mimic the actual scenario of the real environment. The uncertainty has been considered in terms of a novel fuzzy model which agrees with the crisp case model too. [ABSTRACT FROM AUTHOR]

The energy amplification factor transmitted from the excitation source to the response end cannot be identified quickly and accurately using the method of obtaining modal frequency combined with damping through modal frequency resonance. As a result, the above method cannot be used to further evaluate the effect of structural improvement. In this paper, a frequency difference sensitivity method is proposed in order to improve the efficiency of the above identification and evaluation processes while also guaranteeing accuracy. Firstly, a theoretical model suitable for the damping and rigid-body-mode frequency range of the cooling module is established according to the frequency difference between the excitation frequency,.system mode frequency, and vibration response sensitivity. Then, the accuracy and effect of the model are studied from the perspective of a simulation and experiment. The model can be used to identify and evaluate the resonance problem of the vehicle cooling module quickly and accurately. The energy amplification factor of the fan to the passive end of the cooling module can be efficiently predicted using the frequency difference sensitivity method proposed in this paper while ensuring accuracy. The quantized noise-reduction effect of the interior before and after the improvement can be efficiently predicted and evaluated using said model. The literature shows that the resonance of a vehicle cooling module can be identified and evaluated quickly and accurately via the frequency difference sensitivity method, which can overcome the problems that the conventional modal frequency resonance method encounters in identifying and evaluating quickly. [ABSTRACT FROM AUTHOR]

Purpose: Single walled carbon nanotubes (SWCNT) are materials described as nanoscale cylindrically shaped allotropes of carbon possessing high surface area and aspect ratio (length to diameter ratio) which makes them to be modelled as one-dimensional tubes. SWCNTs have superior mechanical properties, which makes them a primary filler in the polymer matrix to enhance its mechanical characteristics. This study aims to examine the longitudinal forced vibration of SWCNT embedded in elastic medium subjected to different types of axial loads such as uniform, linearly varying and sinusoidal. Methods: Formulation is considered based on Hamilton's principle and Eringen's nonlocal elasticity theory. Analytical solution is obtained based on variation of parameters to get modal frequencies, shapes and dynamic displacements within the nanotube. Results: Obtained frequency results are compared with those available in the literature and a high level of accuracy is achieved. Parametric analyses are carried out to examine the influences of elastic medium stiffness, nonlocal parameter and aspect ratio on mode shapes and dynamic displacements. Conclusion: Increase in the elastic medium stiffness leads to increase in the modal frequencies and this increase is greater for nanotubes with clamped-free (C-F) boundary conditions. Dynamic displacement value of the midpoint decreases as stiffness is increased at the same non-dimensional frequency. Change in modal frequency due to the increase in stiffness remains the same for different aspect ratios. The influence of nonlocal parameter on modal frequencies is the highest at smaller aspect ratios, which implies the necessity of the use of nonlocal elasticity theory at nano-scale vibration analysis. [ABSTRACT FROM AUTHOR]

Abstract The displacement function was constructed using Carrera unified formulation (CUF) in combination with Taylor polynomials and the improved Fourier series method (IFSM). This study investigated the vibration characteristics of cylindrical beam made of functionally graded materials (FGM) in a thermal environment. The accuracy of the theoretical model was verified by comparing the calculation results with those obtained using the finite element method. Subsequently, the influential factors were investigated. The variations in material properties with temperature and volume rate index were studied. Additionally, the effects of temperature changes and volume rate index on the thermoelastic vibration of the FGM cylindrical beam were examined. The results indicate that in a uniform temperature field, temperature and volume rate index variations result in changes in the material’s physical properties. The modal frequency of the FGM cylindrical beam decreases gradually with increasing temperature and volume rate index. [ABSTRACT FROM AUTHOR]

The monitoring of bridges is a crucial operation for their structural health examination and maintenance. GNSS technology is one of the methods which are applied with the main advantage that the direct measurement of the bridge displacement is conducted in an independent global coordinate system. However, the high cost of the GNSS stations, which are consisted of dual-frequency receivers and geodetic GNSS antennas, is the main reason of the limited application of GNSS for bridge monitoring. In this study, we assessed the performance of low-cost multi-GNSS receivers in monitoring dynamic motion, similar to that of bridge response. The performance of the low-cost GNSS receivers was assessed based on controlled experiments of horizontal and vertical motion. For the horizontal motion, controlled experiments of circular motion of various predefined radius between 5 and 50 cm were executed where the low-cost GNSS receivers were assessed against dual-frequency geodetic receivers. For the vertical motion, manually controlled experiments of vertical oscillations of amplitude 8 and 15 mm were executed where the low-cost GNSS receivers were assessed against the Robotic Total Station (RTS). Finally, a low-cost monitoring system formed by two closely spaced low-cost GNSS receivers was applied in dynamic displacement monitoring of the Wilford Suspension Bridge. The analysis of the low-cost GNSS data revealed the beneficial contribution of (i) the multi-constellation on the accuracy and precision of the GNSS solution and (ii) the combination of closely spaced low-cost GNSS receivers, to limit potential cycle slips and the low-cost GNSS noise level and reach accuracy and precision similar to that of geodetic-grade GNSS receivers. This was confirmed in the bridge monitoring application, where the main modal frequency and the response amplitude of the bridge were identified successfully by the low-cost GNSS receivers' data analysis. [ABSTRACT FROM AUTHOR]

Natural fiber composites (NFC) exhibit good specific mechanical properties in comparison to synthetic fiber composites (SFC). The study investigates interlaminar glass (G) fiber hybridized jute (J) and flax (F) reinforced epoxy composites designated as JGGJ, GJJG, FGGF, and GFFG along with their virgin counterparts. Composite laminates of four plies are manufactured by hand-layup followed by compression molding to investigate tensile, flexural, and interlaminar shear properties. Further the effect of hybridization is also investigated for modal frequencies and damping ratio obtained from experimental modal analysis. Glass fiber hybridization as extreme layers shows significant improvement in flexural and shear properties as compared to tensile. Glass fiber reinforcement, as core layers improve the damping by 155.55% and 101.31% for JGGJ and FGGF, respectively, over pure glass epoxy. However with increase in bending stiffness of GJJG and GFFG, the bending modal frequency is improved. Also, the modal frequency and damping ratio increases following a power-law variation with a decrease in the free length. Finite element and analytical validations are presented to the experimental frequencies and flexural modulus, respectively. These studied hybrid composites can serve as semi-structural members like interior trim panels in automotive applications that possess significant strength and dissipate in-service vibrations effectively.

The use of tuned liquid dampers (TLDs) as an alternative to reduce the response of flexible structures with a low amount of structural damping is a viable option. The correct characterization of the dynamic properties of the TLD plays an important role in the performance of the TLD-main structure system. This work presents the results of an experimental study to evaluate the dynamic properties of a scaled rectangular TLD using high-speed videos. For the experimental investigation, a scaled rectangular TLD is subjected to lateral displacement of the sinusoidal type with amplitudes that range from 5 to 40 mm and frequency equal to 0.625 Hz. The dynamic properties of the TLD system are identified with the use of high-speed videos with a duration of 28.96 s and recorded at 500 frames per second (fps). The recorded videos are analyzed with the software Tracker to extract time histories of wave elevation at predefined locations. The frequency and damping of the TLD system are identified from the time histories of wave elevation through Fourier analysis and free-vibration decay. The findings of this study revealed that the identified dynamic properties of the TLD by using high-speed videos presented small differences with respect to the target values, with errors that range from 0.93 to 2.9% for frequency and from 1.6 to 8.8% for damping, indicating that the use of high-speed videos can be an alternative to evaluate the dynamic properties of TLD systems.

The energy amplification factor transmitted from the excitation source to the response end cannot be identified quickly and accurately using the method of obtaining modal frequency combined with damping through modal frequency resonance. As a result, the above method cannot be used to further evaluate the effect of structural improvement. In this paper, a frequency difference sensitivity method is proposed in order to improve the efficiency of the above identification and evaluation processes while also guaranteeing accuracy. Firstly, a theoretical model suitable for the damping and rigid-body-mode frequency range of the cooling module is established according to the frequency difference between the excitation frequency, .system mode frequency, and vibration response sensitivity. Then, the accuracy and effect of the model are studied from the perspective of a simulation and experiment. The model can be used to identify and evaluate the resonance problem of the vehicle cooling module quickly and accurately. The energy amplification factor of the fan to the passive end of the cooling module can be efficiently predicted using the frequency difference sensitivity method proposed in this paper while ensuring accuracy. The quantized noise-reduction effect of the interior before and after the improvement can be efficiently predicted and evaluated using said model. The literature shows that the resonance of a vehicle cooling module can be identified and evaluated quickly and accurately via the frequency difference sensitivity method, which can overcome the problems that the conventional modal frequency resonance method encounters in identifying and evaluating quickly.

Bridge modal frequency is an important parameter reflecting its overall property change and widely used for bridge condition assessment. However, the effects of multiple environmental conditions on the modal frequency will mask the variation induced by structural damage. Traditional single regression models cannot quantify measurable and unmeasurable environmental effects simultaneously, resulting in poor prediction and separation performance. Therefore, a two-stage elimination model (TSEM) integrating regression analysis and trend decomposition technique was developed. Environmental principal components (PCs) sensitive to the single-order modal frequency were extracted based on partial least-squares analysis. To quantify the nonlinear effects of measurable environmental factors, the baseline predictor with respect to modal frequency and environmental PCs was constructed through relevance vector machine technology. An error compensation model based on singular spectrum analysis was established to extract trend-related components and remove the part of residual modal variability unknot considered by the baseline model. On this basis, exponential weighted moving average control chart was established to highlight slight abnormal changes in modal frequency. A cable-stayed bridge case verified its validity and accuracy. The results indicate that the proposed TSEM has better modeling, generalization, and separation performance than the baseline model, and the variation of normalized frequency tends to be more stable. Additionally, the significant differences of damage sensitivity of different orders were determined. [ABSTRACT FROM AUTHOR]

Freezing weather can introduce challenges in long-term structural health monitoring of civil structures, particularly bridges. A noticeable impact of freezing temperature is the emergence of sudden and sharp increases in structural modal frequencies, causing false alarm and mis-detection errors in change detection of civil structures. This paper proposes an innovative unsupervised data normalization method to mitigate freezing effects. The proposed method integrates locally robust principal component analysis (LRPCA) with Gaussian density distance (GDD) clustering, called GDD-LRPCA, which automatically determines the number of clusters. Initially, a training set of original modal frequencies is partitioned via the GDD clustering. Subsequently, an individual LRPCA model is fitted to each partition to extract new normalized modal frequencies insensitive to freezing effects. The groundbreaking nature of this research relies on developing an integrated unsupervised data normalizer by leveraging advanced machine learning algorithms such as local learning, robust learning, and hybrid unsupervised learning. The major advantage of the proposed method is its non-parametric nature obviating any supplementary technique for hyperparameter optimization. The validity of this method is benchmarked by real-world bridge structures along with several comparative analyses. Results demonstrate that GDD-LRPCA effectively removes the freezing effects from structural modal frequencies and outperforms its counterparts in unsupervised data normalization. • Proposing an unsupervised data normalizer for removing freezing effects from modal frequencies under statistical learning. • Leveraging cutting-edge machine learning algorithms including local learning, robust learning, and hybrid learning. • Suggesting a non-parametric framework for unsupervised data normalization without any hyperparameter optimization • Lacking the need for temperature sensor installation and measurement for removing freezing effects. [ABSTRACT FROM AUTHOR]

Cylindrical roller bearing is an important component of the airflow root blower of a power generation plant, and its malfunction has been identified as one of the root causes of poor quality demineralized water produced during operation. Hence, there is need to study the dynamic behaviour of a typical cylindrical roller bearing of an airflow root blower. In this study, the dynamic analysis of a cylindrical roller bearing subjected to different rotational speeds was simulated using finite element analysis software, Abaqus. The frequency response of the bearing was determined experimentally and analytically, and the modal frequency results obtained from both analyses were compared. The outcome of the dynamic analysis showed that the maximum temperature and Hertzian stress was developed on the outer ring of the bearing during operation, thus making this component most prone to failure. It was observed that the value of the temperature and stress developed increase with an increase in rotational speed. However, at a rotational speed greater than 503 rad/s, a drop in the Hertzian stress was developed due to the stress relaxation the bearing experience at the higher temperatures. A good agreement was obtained when the modal frequency of the frequency response obtained numerically was compared with those obtained experimentally.

Natural fiber composites (NFC) exhibit good specific mechanical properties in comparison to synthetic fiber composites (SFC). The study investigates interlaminar glass (G) fiber hybridized jute (J) and flax (F) reinforced epoxy composites designated as JGGJ, GJJG, FGGF, and GFFG along with their virgin counterparts. Composite laminates of four plies are manufactured by hand-layup followed by compression molding to investigate tensile, flexural, and interlaminar shear properties. Further the effect of hybridization is also investigated for modal frequencies and damping ratio obtained from experimental modal analysis. Glass fiber hybridization as extreme layers shows significant improvement in flexural and shear properties as compared to tensile. Glass fiber reinforcement, as core layers improve the damping by 155.55% and 101.31% for JGGJ and FGGF, respectively, over pure glass epoxy. However with increase in bending stiffness of GJJG and GFFG, the bending modal frequency is improved. Also, the modal frequency and damping ratio increases following a power-law variation with a decrease in the free length. Finite element and analytical validations are presented to the experimental frequencies and flexural modulus, respectively. These studied hybrid composites can serve as semi-structural members like interior trim panels in automotive applications that possess significant strength and dissipate in-service vibrations effectively. [ABSTRACT FROM AUTHOR]

In the present study, an attempt is made to replace the synthetic glass fiber used in the FRP structures in terms of natural flax fibers without much sacrifice on static and dynamic stability of the structure. Three types of glass/flax hybrid composite laminates were prepared with different fiber volume fraction of glass and flax fibers. For better understanding purpose, a dedicated glass and dedicated flax laminates were also fabricated. All the laminates were fabricated by vacuum bag molding method with uniform laminate thickness. The mechanical properties of the fabricated laminates, such as tensile strength and flexural strength, were evaluated in accordance with ASTM standards. The impulse excitation technique was used to assess the free vibration characteristics of glass/flax laminates such as modal frequency and material damping. Based on experimentally evaluated mechanical and vibration characteristics a suitable fiber volume fraction for the preferred laminate thickness was suggested to achieve optimum static and dynamic stability. [ABSTRACT FROM AUTHOR]

A method to estimate modal frequency based on empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) is proposed. This method can decrease the difficulties in identifying modal frequency of combine harvesters. First, we used 16 acceleration sensors installed at different test points to collect vibration signals of a corn combine harvester under operating conditions (mass time-varying conditions). Second, we calculated mean value, variance and root mean square (RMS) value of the vibration signals, and analyzed its stationarity of vibration signals. Third, the main frequencies of the 16 points were extracted using the EMD and EEMD methods. Finally, we considered modal frequencies identified by the SSI algorithm as standard, and calculated the fitting degrees of the EMD and EEMD methods. The results show that in different time periods (0~60 s and 60~120 s), the maximum differences of the mean value, variance and RMS value of signals were 0.8633, 171.1629 and 11.3767, and the vibration signal under the operating condition of field harvesting can be regarded as a typical non-stationary random vibration signal. The EMD method had more modal aliasing than EEMD, and when we obtained the fitting equations of EMD, EEMD and SSI methods, the value of the Euler distance between the EMD fitting equation and the SSI fitting equation was 446.7883, while that for EEMD and SSI was 417.2845. The vibration frequencies calculated by the EEMD method is closer to the modal frequencies identified by SSI algorithm. The proposed method provides a reference for modal frequency identification and vibration control in a complex working environment. [ABSTRACT FROM AUTHOR]

Stay cables are crucial components in cable-stayed bridges. The time-varying cable tension is an important indicator for the condition assessment of cables because the variation in tension will cause fatigue damage. This paper proposes an adaptive identification method for time-varying cable tension based on an improved variational mode decomposition (VMD) algorithm. In the proposed method, the cable vibration signal is decomposed by improved VMD to identify the time-varying modal frequencies by the Hilbert transform, and then the time-varying cable tension is calculated by the vibration method. To realize adaptive and accurate identification, the VMD algorithm is improved by optimizing parameters: the number of decomposed modes is determined by the characteristic that frequency differences between the adjacent modal frequencies of the cable vibration signal are equal, and the balancing parameter is optimized by constructing an evaluation index and searching for the minimum of the index. A numerical simulation illustrates that the accuracy of the proposed method is satisfactory. To verify the practicability of the proposed method, the monitoring data of a single tower cable-stayed bridge are used. The results demonstrate that the proposed method is a practical and reliable method to identify the time-varying cable tension. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) has been widely used for the performance assessment of bridges, especially the methods based on dynamic characteristics. Meanwhile, bridge modal frequency is influenced significantly by environmental factors, such as temperature and humidity. Combined with SHM, a reliability assessment of bridges with the temperature and humidity effects eliminated is proposed. Firstly, the bridge deflection verification coefficient is adopted as the evaluation indicator for bridge condition, which is the ratio of deflection-measured value to deflection-calculated value. It is obtained from the relationship between verification coefficient and modal frequency through theoretical derivation. Secondly, a back propagation (BP) neural network is improved by using an artificial bee colony algorithm and employed as a surrogate model to eliminate the effect of temperature and humidity on frequency. Thirdly, a dynamic Bayesian network is applied to establish the reliability analysis model combined with the monitoring results, so that the probability distribution of bridge parameters is updated to improve the accuracy of the reliability analysis. Finally, a simply supported bridge is used as the case study, based on the proposed method in this work. The results indicate that the proposed method can eliminate the temperature and humidity effect on frequency precisely and effectively. With the effect of temperature and humidity on frequency eliminated, the bridge condition assessment can be evaluated accurately through the reliability analysis based on SHM and the dynamic Bayesian network. [ABSTRACT FROM AUTHOR]

• Closed-form CP responses for 3D vehicle passing over the AMGB are derived firstly. • A new two-step retrieving strategy of AMGB's modal frequencies is presented. • Hinge joint stiffness can be estimated briefly by retrieved bridge frequencies. • Reliability and robustness of proposed procedure is verified by various examples. This paper presents a theoretical framework for extracting the modal frequencies of thin-walled assembled multi-girder bridges (AMGBs), which are widely adopted in small- and medium-span highway bridges, using the dynamic response of a three-dimensional (3D) moving vehicle. For the first time, closed-form solutions for the responses of the bridge and contact point (CP) are derived when the test vehicle passes through the AMGB. Based on the derived CP response, a guiding procedure for retrieving the modal frequency and hinge joint stiffness of the bridge is proposed. The correctness of the analytical solutions for the CP response and the reliability of the bridge frequency identification are verified through numerical examples. Additionally, the robustness of the proposed technique is examined under various influence factors. The results show that maintaining a moderate vehicle speed can balance the accuracy and efficiency of the bridge frequency identification. The damping of vehicle tires has a small effect on frequency extraction using the CP response, while an increase in bridge damping ratio diminishes the visibility of its frequencies. Nevertheless, for the investigated bridge damping ratios, the effectiveness remains satisfactory, as the first four frequencies still being discernible. The residual contact response of the front and rear wheels can effectively eliminate the masking effect of pavement roughness, thereby enhancing the frequency extraction effect. Furthermore, the proposed method exhibits strong robustness against measurement noise. [ABSTRACT FROM AUTHOR]

In this study, the possibility of using the rail vibration frequency to assess the longitudinal temperature force on the rail of ballasted track was investigated experimentally. An empirical formula was subsequently derived to link the frequency index to multiple factors, including the longitudinal temperature force, under-rail stiffness, and fastener spacing. Further tests were conducted to analyse the applicability and accuracy of the frequency index in continuous longitudinal force measurements under different line conditions (i.e. in the non-expansion zone and expansion zone). A technique for using the frequency index to assess the longitudinal temperature force was finally developed. The main results are as follows. (1) The first-order pinned–pinned modal frequency and peak frequency of the mid-span response are very close, and they both change linearly with the longitudinal temperature force on the rail. The rate of change in the vertical direction is larger than that in the horizontal direction. (2) Even if influenced by multiple factors, the peak frequency of the rail mid-span response is suitable for continuous longitudinal temperature force assessment under appropriate measures, and longitudinal temperature force detection could be realized with proper preparation. (3) Using the mid-span response frequency to detect the temperature force of rail located in the expansion zone causes deviation of the results, and under-rail materials whose stiffnesses are insensitive to temperature help reduce this deviation. [ABSTRACT FROM AUTHOR]

Cylindrical roller bearing is an important component of the airflow root blower of a power generation plant, and its malfunction has been identified as one of the root causes of poor quality demineralized water produced during operation. Hence, there is need to study the dynamic behaviour of a typical cylindrical roller bearing of an airflow root blower. In this study, the dynamic analysis of a cylindrical roller bearing subjected to different rotational speeds was simulated using finite element analysis software, Abaqus. The frequency response of the bearing was determined experimentally and analytically, and the modal frequency results obtained from both analyses were com- pared. The outcome of the dynamic analysis showed that the maximum temperature and Hertzian stress was developed on the outer ring of the bearing during operation, thus making this component most prone to failure. It was observed that the value of the temperature and stress developed increase with an increase in rotational speed. However, at a rotational speed greater than 503 rad/s, a drop in the Hertzian stress was developed due to the stress relaxation the bearing experience at the higher tempera- tures. A good agreement was obtained when the modal frequency of the frequency response obtained numerically was compared with those obtained experimentally. [ABSTRACT FROM AUTHOR]

Metallic-ceramic functionally graded materials have potential application value in the design of thermal barrier systems for aircraft panels due to their ultrahigh temperature resistant and high strength properties. In this article, the FGMs plate was used as the object to study the influence of parameters such as the volume fraction index, the geometric size of the plate and the thermal environment on the modal frequencies of a FGMs plate. Firstly, the power law distribution function was employed to discuss the influence of thermal environment on the physical properties of FGMs plates. Thereafter, the FGMs linear layered model dependent on temperature field was established by using the temperature continuously changing with the spatial position trait in the finite element, and the validity of this model in dynamic analysis was verified. Finally, the effects of ceramic volume fraction index, FGMs plate length-to-width ratio, temperature gradient and other variables on the modal frequencies of a FGMs plate were comprehensively analyzed and discussed. Results indicate that the higher order modes are mostly impacted by the uniform temperature field, while the linear and nonlinear temperature fields have the greatest impact on the first-order modes. In linear and nonlinear temperature fields, the volume fraction index is the most sensitive one to the effects of modal frequency drop ratio, while the modal frequency drop ratio is mainly affected by the coupling effect of the volume fraction index and the temperature gradient in uniform temperature field.

In this article, a magnetic suspension technique was introduced into the field of vibration absorption. Using the advantage of adjustable control parameters of a magnetic suspension system, a type of a magnetic suspension dynamic vibration absorber that can achieve broadband vibration suppression was designed. First, the theoretical model of a magnetic suspension dynamic vibration absorber was established. Then, the cantilever beam with sinusoidal excitation is seen as the main system of vibration suppression; combined with the fixed point theory (Seto K (2013) Dynamic Vibration Absorber and its Application. Mechanic Industry Press), the specific structure of the magnetic suspension dynamic vibration absorber was designed. Based on that, the simulation study of vibration suppression performance of the magnetic suspension dynamic vibration absorber was carried out. The results indicated that the vibration of the main system at the 1st modal frequency was reduced by 65.38% under the action of the magnetic suspension dynamic vibration absorber, compared with that without the action of the magnetic suspension dynamic vibration absorber. Furthermore, the vibration of the main system can be suppressed in the frequency band of [16 Hz, 32 Hz]. Finally, a vibration test rig of the magnetic suspension dynamic vibration absorber was built up for experimental study. And the results showed that the absorber can decrease the vibration of the main system by 43.03% at the 1st modal frequency compared with that without the action of magnetic suspension dynamic vibration absorber and had a certain suppression effect (decrease varies from 0 to 43.03%) on the vibration of the main system in the frequency band of [20 Hz, 32 Hz]. [ABSTRACT FROM AUTHOR]

In this paper, the vibration and buckling behavior of a functionally graded piezoelectric porous cylindrical microshell under thermo-electro-mechanical loads are explored on the basis of modified couple stress theory and higher-order shear deformation theory. First, the model of a functionally graded piezoelectric porous cylindrical microshell composed of piezoelectric materials with gradient change in the thickness direction was described. Second, the governing equations of the microshell were derived by Hamilton's principle and Maxwell equation. Third, the modal frequency and buckling equations of the microshell with simply supported ends were obtained on the basis of harmonic trigonometric functions. Finally, the effects of parameters on the modal frequency and buckling behavior were carried out by case studies. The results show that the modal frequency of the microshell can be adjusted by changing the porosity volume fraction, power index, applied voltage, axial load and geometric dimensions. It is also found that the vibration of the microshell is suppressed by positive voltage and axial compression but is strengthened by negative voltage and axial tension, and the material length scale parameter increases stiffness. In addition, the effects of applied voltage and axial load on the buckling behavior are larger than those of temperature. Results can be used to guide the design and application of piezoelectric devices. [ABSTRACT FROM AUTHOR]

Modal frequencies are often used in structural model updating, based on the finite element model, while the metamodel approach is often used in the respective optimization process. In this work, the Kriging model is adopted as the metamodel. First, the influence of different correlation functions of Kriging model is inspected, followed by the investigation of the approximate capability of Kriging model by inspecting the approximate accuracy of nonlinear functions. Next, a model updating procedure is proposed, based on the Kriging model, constructed using samples generated via the method of Optimal Latin Hypercube. Finally, a typical frame structure is taken as a case study, demonstrating the feasibility and efficiency of the proposed approach. The results show that, the Kriging model can match the target functions very well, while the finite element model can achieve accurate frequencies and can reliably predict the frequencies after model updating. [ABSTRACT FROM AUTHOR]

In field harvesting conditions, the non-stationary random vibration characteristics of the harvester are rarely considered, and the results of vibration frequency calculated by different time–frequency transformation methods are different. In this paper, the harvester’s vibration characteristics under the time-varying mass were studied, and the correlation between vibration frequency and modal frequency was analyzed. Firstly, under the conditions of time-varying mass (field harvesting conditions) and non-time-varying mass (empty running condition), the non-stationarity characteristics of vibration signals at 16 measurement points of a combined corn harvester frame were studied. Then, fast Fourier transform (FFT), short-time Fourier transform (STFT), and continuous wavelet transform (CWT) were used to calculate the vibration frequency distribution characteristics of the corn harvester. Finally, based on the EFDD (enhanced frequency domain decomposition) algorithm, the correlation between the primary vibration frequency and the operating mode frequency is studied. The results show that the mean, variance, and maximum difference of the vibration amplitude under harvesting conditions (mass time-varying system) are 0.10, 26.5, and 1.0, respectively, at different harvesting periods (0~10 s, 10~20 s, 20~30 s). The harvesting conditions’ vibration signals conform to the characteristics of non-stationary randomness. The FFT algorithm is used to obtain more dense vibration frequencies, while the frequencies based on STFT and CWT algorithms are sparse. The correlation between the FFT method and the EFDD algorithm is 0.98, and the correlation between the STFT, CWT, and the EFDD algorithm is 0.99 and 0.98. Therefore, the primary frequency of the STFT methods is closer to the modal frequency. Our research laid the foundation for further study and application of mass time-varying combined harvester system non-stationary random vibration modal frequency identification and vibration control.

Summary: The influence of varying environmental/operational situations on damage‐sensitive properties is a vital problem when the vibration responses are employed for structural damage detection. In this work, singular spectrum analysis (SSA) and the statistical control chart are combined to develop a new damage identification approach for structural damage detection under variable environmental/operational situations. The SSA is utilized to decompose the measured frequency sequence into the sum of independent components, including a tardily changing trend, oscillatory, and noise components. The trend‐related decomposed components can be identified by finding the corresponding slow‐varying eigenvectors. The trend components induced by varying environmental/operational conditions are discarded, while the remaining ones, including oscillatory and noise components, are selected to reconstruct the new frequency sequence. Hence, the impact of variable environmental/operational situations on the original frequency sequence is removed. The reconstructed frequency shift from its reference status (undamaged status) is utilized to construct the damage features, which are employed as the control chart samples. Accordingly, the damage features obtained from the undamaged status are utilized to calculate the control limits. The subsequent damage indices in unknown status are monitored considering the control limits. A considerable number of damage indices out of the control limits range show a system transformation from an undamaged status to a damaged one. The feasibility of the presented approach is analytically and experimentally evaluated through an offshore platform in the presence of a white noise excitation. [ABSTRACT FROM AUTHOR]

Quantifying the uncertainty in the dynamic properties of large-scale complex engineering structures presents significant computational challenges. Monte Carlo simulation (MCS) method is extensively employed to perform uncertainty quantification (UQ) because of its generality, stability, and easy implementation. However, a brute-force MCS approach may be unaffordable and impractical when the target model contains a large number of uncertain parameters. In this circumstance, MCS requires a potentially burdensome (if not computationally intractable) number of model evaluations to obtain a credible estimate of the global statistics. In this study, a general framework for analytical UQ of model outputs using a Gaussian process (GP) metamodel is presented, where case inputs are characterized as normal and/or uniform random variables. A detailed derivation of important low-order statistical moments (mean and variance) is given analytically. This analytical method is adopted to characterize the uncertainty of modal frequencies of two bridges with assumed normally- and uniformly-distributed parameters. Meanwhile, the brute-force MCS approach is used for comparison of GP metamodel-derived statistics. Results show that the GP method outperforms the MCS methodology in terms of computational cost, with consistency in the "true" values obtained by MCS. It demonstrates that this GP method is feasible and reliable for modal frequency UQ of complex structures. © 2014 Elsevier Ltd.

Quantifying the uncertainty in the dynamic properties of large-scale complex engineering structures presents significant computational challenges. Monte Carlo simulation (MCS) method is extensively employed to perform uncertainty quantification (UQ) because of its generality, stability, and easy implementation. However, a brute-force MCS approach may be unaffordable and impractical when the target model contains a large number of uncertain parameters. In this circumstance, MCS requires a potentially burdensome (if not computationally intractable) number of model evaluations to obtain a credible estimate of the global statistics. In this study, a general framework for analytical UQ of model outputs using a Gaussian process (GP) metamodel is presented, where case inputs are characterized as normal and/or uniform random variables. A detailed derivation of important low-order statistical moments (mean and variance) is given analytically. This analytical method is adopted to characterize the uncertainty of modal frequencies of two bridges with assumed normally- and uniformly-distributed parameters. Meanwhile, the brute-force MCS approach is used for comparison of GP metamodel-derived statistics. Results show that the GP method outperforms the MCS methodology in terms of computational cost, with consistency in the "true" values obtained by MCS. It demonstrates that this GP method is feasible and reliable for modal frequency UQ of complex structures. © 2014 Elsevier Ltd.

A method to estimate modal frequency based on empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) is proposed. This method can decrease the difficulties in identifying modal frequency of combine harvesters. First, we used 16 acceleration sensors installed at different test points to collect vibration signals of a corn combine harvester under operating conditions (mass time-varying conditions). Second, we calculated mean value, variance and root mean square (RMS) value of the vibration signals, and analyzed its stationarity of vibration signals. Third, the main frequencies of the 16 points were extracted using the EMD and EEMD methods. Finally, we considered modal frequencies identified by the SSI algorithm as standard, and calculated the fitting degrees of the EMD and EEMD methods. The results show that in different time periods (0~60 s and 60~120 s), the maximum differences of the mean value, variance and RMS value of signals were 0.8633, 171.1629 and 11.3767, and the vibration signal under the operating condition of field harvesting can be regarded as a typical non-stationary random vibration signal. The EMD method had more modal aliasing than EEMD, and when we obtained the fitting equations of EMD, EEMD and SSI methods, the value of the Euler distance between the EMD fitting equation and the SSI fitting equation was 446.7883, while that for EEMD and SSI was 417.2845. The vibration frequencies calculated by the EEMD method is closer to the modal frequencies identified by SSI algorithm. The proposed method provides a reference for modal frequency identification and vibration control in a complex working environment.

The Xihoumen Bridge, with a main span of 1650 m and two side spans of 578 m and 485 m, respectively, is a long-span suspension bridge spanning the Jintang and Cezi islands in Zhejiang Province, China. In order to establish a reference baseline for vibration mitigation and condition assessment of the bridge under typhoons, the wind field properties, vibration energy distribution, and modal parameters of the bridge are identified through in-situ monitoring. Dynamic responses at different locations on main span and wind speeds at 1/2 main span of the bridge under 10 typhoons and under normal wind were collected for this study. Vibration energy distribution is estimated using wavelet packet transform. Modal parameters are identified by the peak-picking (PP) and data-driven stochastic subspace identification (SSI-DATA) methods. The results indicate that in the low-frequency range, the fluctuating wind energy of typhoons changes more significantly than that of normal wind. More than 80% of the vibration energy is concentrated in the frequency band (0–1.5625 Hz) under typhoons, while nearly 90% of the vibration energy under normal winds is evenly distributed in three frequency bands (0–1.5625 Hz, 1.5625–3.125 Hz, and 3.125–4.6875 Hz). When using typhoon-induced dynamic responses as input, the SSI-DATA method performs better than the PP method in the identification of modal parameters. The results obtained in this study can be used as a baseline for future structural condition assessment of the bridge after typhoon events. [ABSTRACT FROM AUTHOR]