Measured Vibration Response Research Articles

An optimized bearing parameter identification approach from vibration response spectra

In the present work, an effective identification methodology bearing dynamic parameters using measured vibration responses at the bearing is proposed. The flexible rotor is analyzed by using finite element beam model with nonlinear hydrodynamic bearing forces due to floating ring bearing supports. The frequency domain responses at different operating speeds are initially obtained in both the lateral directions. The error function is formulated as an average difference in amplitudes of two lateral displacements at a bearing node with known reference signals over a frequency range. The design variables are the speed dependent direct and cross-coupled stiffness and damping parameters of the bearing. With the side constraints on the variables, the error is minimized by using a modified particle swarm optimization scheme. The accuracy of the approach is tested with noisy input signals.

Non-modal vibration-based methods for bridge damage identification

Many methods of damage identification in bridge structures have focused on the use of numerical models, modal parameters or non-destructive damage tests as a means of condition assessment. These techniques can often be very effective but can also suffer from specific pitfalls such as, numerical model calibration issues for non-linear and inelastic behaviour, modal parameter sensitivity to environmental and operational conditions and bridge usage restrictions for non-destructive testing. This paper covers alternative approaches to damage identification of bridge structures using empirical parameters applied to measured vibration response data obtained from two field experiments of progressively damaged bridges subjected to ambient and vehicle-induced excitation, respectively. Numerous non-modal vibration-based damage features are detailed and selected for the assessment of either the ambient or vehicle-induced excitation data based on their inherent properties. The results of the application to two real bridges, one under ambient vibration and the other of forced vibration, demonstrate the robustness of the proposed damage features for damage identification using measurements of ambient and vehicle excitations. Moreover, this investigation has demonstrated that the novel empirical vibration parameters assessed are suitable for damage detection, localisation and quantification.AbbreviationsCAVcumulative absolute velocityCADcumulative absolute displacementDVIdistributed vibration intensityMCVImean cumulative vibration intensityIVIinstantaneous vibration intensityAIVIAmalgamated instantaneous vibration intensityEMDempirical mode decompositionICEEMDANimproved complete ensemble empirical mode decomposition with adaptive noiseHHTHilbert–Huang TransformIMFintrinsic mode functionsMCDminimum covariance determinateMSDmahalanobis squared distanceMTSMahalanobis Taguchi system

IMPLEMENTATION OF FREQUENCY RESPONSE FUNCTION ON TAPPER BEARING MAINTENANCE

Bearing acts as a pad that supports a shaft to rotate without excessive friction, hold the radial load and maintain the motion towards the left and right shafts (Thrust Load) when turning together. Due to frequent taper bearing damage to the wheels, predictive maintenance is therefore necessary. One of the predictive maintenance methods widely used today is vibration analysis. The principles of vibration-based bearing damage detection using the Frequency Response Function (FRF) method will be shown in this paper. Harmonics signal is given to the bearing surface in a vertical or perpendicular direction to the taper bearing surface. The vibration response measurement was carried out on three axes (x, y, and z). The results of this study indicated the ability of FRFs to predict any damage on the bearing taper.

Fisher information-based optimal input locations for modal identification

A method is proposed to determine optimal locations of input forces for experimental modal analysis. The input locations are optimal in a sense that the measured vibration responses, under inputs thus located, contain maximum information about unknown modal parameters of interest. These optimal input locations are obtained by maximizing the trace of the associated Fisher Information Matrix (FIM). Analytical expressions are obtained for the different derivatives involved, by expressing acceleration responses in terms of pseudo-modal responses. A dimensionless scaling is introduced to normalize the effect of different types of modal parameters. An explicit relation is also derived between the FIM and the mode shape components at input locations. It is shown that, in certain experimental scenarios, this relation may be used to directly obtain the optimal input locations from only the mode shapes. An extensive series of numerical simulations, including situations of single/multiple inputs and single/multiple modes of interest, is used to illustrate the proposed approach. It is observed that the modal parameters, identified using any suitable modal identification technique, have the lowest estimation uncertainty when the inputs are optimally located. As an application in damage detection, it is shown that modal parameters estimated from experiments with non-optimally located inputs may lead to incorrect damage localization. The proposed method is also applied to data from experiments performed on a laboratory scale truss model.

Application of Hilbert Huang transform to identify the natural frequencies of steel frame

Identification of dynamic structural characteristics such as natural frequency based on measured vibration responses at site is one of the important steps in the structural investigation work of loading test and structural health monitoring. During the service stage, the dynamic characteristics can be changed due to the stiffness reduction and nonlinear of structure under extrema excitation. Therefore, the identification of instantaneous parameters of structure is very necessary in detecting and monitoring the structural deterioration continuously by the time. This paper presents the data processing method using Hilbert Huang Transform (HHT) algorithm in determining a time-dependent frequencies of steel frame. The vibration experiment for steel frame was conducted in this study. The acceleration responses in time domain were recorded and analyzed by HTT to determine the fundamental natural frequencies of frame. The instantaneous frequencies in the time domain of steel frame are the main finding in this research. The traditional data processing method using a Fast Fourier Transform (FFT) was conducted and compared with the HHT method.
 Keywords: Hilbert Huang Transform (HHT); steel frame; Fast Fourier Transform (FFT); natural frequency.

Target-free vision-based technique for vibration measurements of structures subjected to out-of-plane movements

Vibration measurements have been widely used for structural health monitoring (SHM). Usually, wired sensors are required to attach on the testing structure, which may be arduous, costly and sometimes impossible to install those sensors on the remote and inaccessible part of the structure to be monitored. To overcome the limitations of contact sensors based vibration measurement methods, computer vision and digital image processing based methods have been proposed recently to measure the dynamic displacement of structures. Real-life structure subjected to bi-directional dynamic forces is susceptible to significant out-of-plane movement. Measuring the vibrations of structures under the out-of-plane movements using target-free vision-based methods have not been well studied. This paper proposes a target-free vision-based approach to obtain the vibration displacement and acceleration of structures subjected to out-of-plane movements from minor level excitations. The proposed approach consists of the selection of a region of interest (ROI), key-feature detection and feature extraction, tracking and matching of the features along the entire video, while there is no artificial target attached on the structure. The accuracy of the proposed approach is verified by conducting a number of experimental tests on a reinforced concrete structural column subjected to bi-directional ground motions with peak ground accelerations (PGA) ranging from 0.01 g to 1.0 g. The results obtained by the proposed approach are compared with those measured by using the conventional accelerometer and laser displacement sensor (LDS). It is found that the proposed approach accurately measures the displacement and acceleration time histories of the tested structure. Modal identification is conducted using the measured vibration responses, and natural frequencies can be identified accurately. The results demonstrate that the proposed approach is reliable and accurate to measure the dynamic responses and perform the system modal identification for structural health monitoring.

Time-space identification of mechanical impacts and distributed random excitations on plates and membranes

The identification of dynamic loads acting on structures is a key aspect of several engineering domains involving structure-borne sound and vibration problems, stress analysis, or even the study of fatigue-induced structural damages. This work is concerned with the reconstruction of localized transient and distributed random excitations on plates and membranes from their measured vibration response. In previous investigations by the authors, the virtual fields method, an identification approach based on the principle of virtual work, was employed to identify mechanical and acoustic loadings applied to a bending panel. However, vibration data were obtained using scanning laser Doppler vibrometry, which limits the application of the virtual fields method to stationary excitations in both space and frequency. In contrast, the deflectometry technique used here is an optical method that directly provides a full-field measurement of local slopes. With the addition of a high-speed camera, the measurements are resolved in both space and time, enabling the study of nonstationary excitations. Moreover, since the acquisition time is independent of the number of measurement points, high spatial density measurements can be performed in seconds. This paper reviews the principles of the virtual fields method for nonstationary excitations on plates and membranes. The deflectometry technique is then demonstrated and experimental reconstruction results on an aluminum panel are presented for two different load cases: impacting metal marbles (multiple unknown transient excitations) and a diffuse acoustic field excitation. Finally, the identification of acoustic and aerodynamic (turbulent boundary layer) excitations is considered using a membrane as the receiving structure.

Dynamic inversion method for the material parameters of a high arch dam and its foundation

• Dynamic inversion method for the material parameters of a high arch dam and its foundation is proposed. • A stochastic subspace modal identification theory based on singular entropy is constructed. • The mathematical model for the inversion of the zoning material parameters based on modal parameters is established. • This method is applied to project examples. The overall mechanical behavior of the structure of an arch dam is comprehensively reflected by the vibration modal information included in measured vibration response. Hence, the results obtained from inverting material parameters based on measured vibration data are often superior to those based on static monitoring data. In this study, a dynamic inversion method for the material parameters of a high arch dam and its foundation is proposed on the basis of the measured vibration response. First, an arch dam prototype test is conducted to obtain the measured dynamic displacement response as input. Then, a stochastic subspace identification method based on singular entropy is formulated to determine the modal parameters. Second, a dynamic elastic modulus (DEM) with a great influence on the modal parameters is selected as the material parameter to be inverted. Then, a response surface model (RSM), which reflects the nonlinear relationship between the material and modal parameters of each zone, is constructed. Latin hypercube sampling is used to generate the sample library of the DEM. The RSM is fitted by modal parameters calculated on the basis of the arch dam finite element model (FEM) and is applied to replace the FEM. Finally, the optimization mathematical model of the inversion of the DEM is established. Then, the objective function is optimized through a genetic algorithm, and the optimal combination of the DEM in each zone is inverted. The modal parameters of the arch dam calculated by inversion results are consistent with those measured by variation law and values. Therefore, the inversion results are reasonable and reliable. This method provides a new idea for determining the material parameters of a high arch dam and its foundation during the operation period.

Dynamic Performance of a Squeeze Film Damper with a Cylindrical Roller Bearing under a Large Static Radial Loading Range

Turbomachine rotors, supported by little damped rolling element bearings, are generally sensitive to unbalance excitation. Accordingly, most machines incorporate squeeze film damper technology to dissipate mechanical energy caused by rotor vibrations and to ensure stable operation. When developing a novel geared turbomachine able to cover a large power range, a uniform mechanical drivetrain needs to perform well over the large operational loading range. Especially, the rotor support, containing a squeeze film damper and cylindrical roller bearing in series, is of vital importance in this respect. Thus, the direct objective of this research project was to map the performance of the envisioned rotor support by estimating the damping ratio based on the simulated and measured vibration response during run-up. An academic test rig was developed to provide an in-depth analysis on the key components in a more controlled setting. Both the numerical simulation and measurement results exposed severe vibration problems for an insufficiently radial loaded bearing due to a pronounced anisotropic bearing stiffness. As a result, a split first whirl mode arose with its backward component heavily triggered by the synchronous unbalance excitation. Hence, the proposed SFD does not function properly in the lower radial loading range. Increasing the static load on the bearing or providing a modified rotor support for the lower power variants will help mitigating the vibration issues.

Serviceability assessment of subway induced vibration of a frame structure using FEM

It is necessary to predict subway induced vibration if a new subway is to be built. To obtain the vibration response reliably, a three-dimensional (3D) FEM model, consisting of the tunnel, the soil, the subway load and the building above, is established in MIDAS GTS NX. For this study, it is a six-story frame structure built above line 3 of Guangzhou metro. The entire modeling process is described in detail, including the simplification of the carriage load and the determination of model parameters. Vibration measurements have been performed on the site of the building and the model is verified with the collected data. The predicted and measured vibration response are used together to assess vibration level due to the subway traffic in the building. The No.1 building can meet work and residence comfort requirement. This study demonstrates the applicability of the numerical train-tunnel-soil-structure model for the serviceability assessment of subway induced vibration and aims to provide practical references for engineering applications.

Measurement of Vibration Response of a Cultured Cell for its Mechanosensing Mechanism under Mechanical Vibration

Measurement of Vibration Response of a Cultured Cell for its Mechanosensing Mechanism under Mechanical Vibration

Vibration source identification of offshore wind turbine structure based on optimized spectral kurtosis and ensemble empirical mode decomposition

Offshore wind turbines are influenced not only by environmental loads such as the wind and waves, but also by various harmonic excitations and have always been considered as complex coupled vibration systems under operational conditions. Generally, the proposed excitations and corresponding vibration sources have a direct relationship with the structural operational safety of the offshore wind turbine and can be reflected by the vibration responses. Nevertheless, existing studies in this area mainly focus on understanding the effect of environmental excitations on the structural vibrations of offshore wind turbines and identifying the dynamic parameters. The research on the identification of the vibration sources and the corresponding energy distribution of offshore wind turbine structures based on the observation data have not yet been carried out. Therefore, using the measured vibration responses of an offshore wind turbine prototype, an identification technology based on optimized spectral kurtosis (OSK) and the ensemble empirical mode decomposition (EEMD) methods, which is capable of determining both the structural vibration sources and the corresponding energy distribution was presented for the first time. It can be demonstrated that the structural vibration sources changed from environmental excitations to forced harmonic loads when the rotating speed and power of the turbine increased. At the same time, the main vibration energy underwent a transformation from random vibration energy to harmonic vibration energy with a change in the operational factors. Furthermore, it is suggested that the relationship between the rotating frequency and structural modal frequencies in the structural operational safety assessment of offshore wind turbines should be further investigated.

Frequency domain decomposition-based multisensor data fusion for assessment of progressive damage in structures

In this paper, we focused on the development and verification of a solid and robust framework for structural condition assessment of real-life structures using measured vibration responses, with the presence of multiple progressive damages occurring within the inspected structures. A self-tuning learning method for structural condition assessment was proposed. Damage sensitive features were extracted using a frequency domain decomposition (FDD) approach to fuse all the measured responses, followed by random projection algorithm for dimensionality reduction. An automatic parameter selection method called Appropriate Distance to the Enclosing Surface (ADES) was used for tuning the classifier parameter. The effect of operational conditions on the robustness of the proposed method was also investigated, and it was realized that application of FDD to extract damage sensitive feature reduces the variation in the results. Promising results in the assessment of damage were obtained based on two comprehensive case studies, which included single and multiple damage scenarios. The contributions of the work are threefold. First, through two comprehensive case studies, we demonstrate that the frequency-based feature from a single sensor might not be adequate enough to detect the progress of damage, even if the sensor is in the vicinity of damage. Second, we show that data fusion using FDD can reliably assess the severity of damage, and finally, we propose a new automated approach for tuning the classifier parameter.

Model updating of periodic structures based on free wave characteristics

Many civil engineering structures have a repetitive or quasi-periodic geometry. Such structures have clustered modes with closely spaced natural frequencies corresponding to mode shapes with similar wavelengths. Such modes may be difficult to distinguish in modal tests and lead to difficulties when pairing calculated and experimentally determined modal characteristics in vibration-based model updating. For repetitive structures, the free wave characteristics, i.e. propagation constants and free waves, can be used alternatively to characterize their dynamic behaviour. The free wave characteristics can therefore be used instead of modal characteristics as data features in model updating of repetitive structures. This paper investigates the feasibility of model updating of repetitive structures based on free wave characteristics. First, the identification of the free wave characteristics from the measured vibration responses of a periodic structure is investigated. A stabilization diagram is constructed to pick up the stable free waves. Second, model updating of repetitive structures is performed through a match of the calculated and experimentally identified free wave characteristics. A least-squares cost function is formulated and minimized using a gradient-based optimization algorithm. This algorithm requires the sensitivity of the free wave characteristics to the model parameters that need to be updated. The analytical expressions for the free wave sensitivities are therefore derived. The proposed model updating procedure is demonstrated and validated by a numerical case study involving a repetitive frame structure and by an experiment on a four-storey steel frame structure. The results confirm the feasibility of model updating based on free wave characteristics for repetitive structures.

Data-driven damage diagnosis under environmental and operational variability by novel statistical pattern recognition methods

Feature extraction by time-series analysis and decision making through distance-based methods are powerful and efficient statistical pattern recognition techniques for data-driven structural health monitoring. The motivation of this article is to propose an innovative residual-based feature extraction approach based on AutoRegressive modeling and a novel statistical distance method named as Partition-based Kullback–Leibler Divergence for damage detection and localization by using randomly high-dimensional damage-sensitive features under environmental and operational variability. The key novel element of the proposed feature extraction approach is to establish a two-stage offline and online learning algorithms for extracting the residuals of AutoRegressive model as the main damage-sensitive features. This technique brings the great benefit of reducing the computational time and storage space for feature extraction in long-term monitoring conditions. The major contribution of Partition-based Kullback–Leibler Divergence method is to exploit a partitioning strategy for dividing random features into individual partitions and utilize numerical information of partitioning in distance calculation rather than directly applying random samples. Dealing with the major challenging issue of using the high-dimensional features in decision making and applicability to both correlated and uncorrelated random datasets are the main advantages of Partition-based Kullback–Leibler Divergence method. The accuracy and reliability of the proposed approaches are experimentally validated by two well-known benchmark structures. The stationarity and linearity of measured vibration responses for using in AutoRegressive modeling are evaluated by two hypothesis tests. Comparative studies are also conducted to demonstrate the superiority of the proposed methods over some exciting state-of-the-art techniques. Results show that the methods presented here succeed in detecting and locating damage and make time-saving and efficient tools for feature extraction and damage diagnosis.

Influence of induction motorcycle in electricity generator which involved stated turbine protection reviewed by characteristic vibration and time domain

Study of vibration characteristics of an induction motor that is not controlled and is not closely monitored and regularly adversely affects the vibration and the impact on comfort and engine life. This study aims to investigate the characteristics of vibration on electric-driven generator steam turbine at PT. Perkebunan Nusantara III (PTPN III) Rambutan Tebing Tinggi. The object of research is protected steam turbine engine palm oil processing factory company PTPN III Rambutan Tebing Tinggi. The results of this study show from both the point of measurement at engine speed rpm compared 4800, 4900, and 5000 obtain that the vibration velocity is highest at 120 seconds, 5000 rpm rotation vertical direction at the point G1. ISO 10816-3 standard for velocity on the highest vibration response measurements at two measurement points on the position of the engine cradle generator of 0.650 x 10-6 m/s Zone A is green, the vibration of the engine is very good and below the allowable vibration.

Measurement of nonlinear vibration response in aerospace composite blades using pulsed airflow excitation

With increased use of composite materials and more complex designs, nonlinear behaviour of aero engine components has become a more common occurrence. However, both numerical and experimental tools currently available are mostly limited to linear dynamics range. The development of new or improved tools is therefore needed in order to deal more reliably with the identification and quantification of nonlinearities.In this work, an experimental method for the structural testing of composite components in presence of nonlinear vibrations is presented. The method is based on the use of a chopped air-jet vibration exciter providing non-contact input force at the frequency of the pulsating airflow. The non-contact nature of this type of exciter prevents the impedance mismatch issue existing when more traditional systems such as electromagnetic shakers are used. This way, the excitation force is transmitted more efficiently over the whole dynamic response range.Results of forced and free decay response tests carried out on different types of composite blades are presented and discussed. They demonstrate that the proposed vibration exciter provides the capacity to identify geometrical nonlinearities and their effects in all the cases investigated.

A method for detecting damage-induced nonlinearity in structures using weighting function augmented curvature approach

Structural damages can result in nonlinear dynamical signatures that can significantly enhance their detection. In this article, we present a new method for identifying damage-induced nonlinearity using vibration response measurements. Among the various types of damages that induce nonlinearity, we focus on the breathing crack. We use the spatial curvature of Fourier power spectrum augmented with rectangular weighting function as a damage-sensitive feature for breathing crack identification. The proposed rectangular weighting function significantly enhances the resolution of superharmonics and intermodulation exhibited by the frequency domain response of the structure with breathing crack for breathing crack identification and characterization. The proposed algorithm is simple, does not involve any complex post-processing and also does not require any numerical model. Both numerical and experimental studies have been carried out to test and verify the proposed algorithm.

Measurement and Analysis of Wind-induced Vibration Response of the Overhead Working Truck

We obtained the vibration response of the GKZ17 overhead working truck under normal wind load through field measurement made for four operating conditions. In the test, a vibration test system was arranged on the working platform of this overhead working truck. The time-domain and frequency-domain characteristics of displacement and acceleration were obtained from analysis on the measured data. The results show that when the wind direction is perpendicular to the working plane, the downwind response is dominated, but the crosswind response is also large and shall be highly valued; and when the wind direction is parallel with the working plane, the downwind wind-induced vibration response is small and the crosswind response is dominated. The frequency domain analysis indicates that this overhead working truck is more sensitive to low-order frequencies.

Structural scaling factor identification from output-only data by a moving mass technique

Abstract Ambient vibration testing is a convenient and cost-effective alternative to impact testing as it doesn’t require artificial excitation devices and traffic control. The lack of input force measurement in ambient vibration testing, however, does impede the identification of structural scaling factors, which are extremely important for Frequency Response Functions (FRFs) estimation and flexibility identification. A moving mass technique of identifying structural scaling factors from output-only data is proposed in this article. By this method, a vehicle passing over a bridge is regarded as a moving mass with spatial and time variation on the structure, inducing a vehicle-bridge system with time-varying modal properties. Theoretical derivation will be performed to identify scaling factors from the measured vibration responses of the bridge with and without the moving vehicle. Magnitudes of FRFs and the structural flexibility matrix can be obtained once the scaling factors are identified. The proposed method delivers comparable results to impact testing but is considerably more convenient. Numerical and experimental examples are studied to verify the effectiveness of proposed method. The effects of vehicle speed, mass value and measurement noise are also investigated.