Random Decrement Research Articles

Ambient vibration measurements to support morphometric analysis of a pyroclastic cone

Pyroclastic cones are a typical feature on volcanoes characterized by flank activity. Their distribution and orientation are important markers to obtain information on the maximum horizontal compressional stress acting on a volcano. A geophysical survey was performed on the pyroclastic cone of Mt. Vetore (Mt. Etna volcano, Southern Italy) to obtain information on its internal structural setting and to support the standard morphometric analysis. Results highlighted evident frequency peaks at 1.0 Hz inside the cone, which are attenuated away from it. The random decrement method was applied to this peak to compute damping and then to exclude links with anthropogenic sources. Moreover, time-frequency polarization analysis revealed that ambient vibrations are strongly polarized in a narrow frequency band, centered at a frequency of 1.0 Hz, with a preferred oscillation azimuth of 70–90° N. Array measurement of ambient vibrations was also used to obtain a shear wave velocity profile and then to retrieve the main interfaces with high seismic impedance. Results suggest a cone structure having a feeder dike consisting of fractured rocks with thickness of about 50 m surrounded by pyroclastic material lying on a high-velocity substrate. Finally, a 3D model of Mt. Vetore cone was built employing the finite element method to reproduce an experimental modal frequency of the cone itself. The numerical results successfully reproduced the experimental ones collected by the geophysical survey.

Identification of modal parameters of a 600‐m‐high skyscraper from field vibration tests

SummaryAccurate prediction of the dynamic responses of a high‐rise building subjected to dynamic loads such as earthquake and wind excitations requires the information of its structural dynamic properties such as modal parameters including natural frequencies and damping ratios. This paper presents the identification results of the modal parameters based on field vibration tests on a 600‐m high skyscraper. A set of tests, including ambient vibration test (AVT) and free vibration test (FVT), were conducted on the skyscraper to identify its modal parameters. Firstly, this paper presents and discusses the modal parameters of the skyscraper assessed by several identification methods applied to the AVT measurements. These methods include the wavelet transform (WT) method, the stochastic subspace identification (SSI) method, and the random decrement technique (RDT). Secondly, an active mass damper (AMD) system with total mass 1000 tons equipped into the skyscraper was used to excite the building for estimation of the modal parameters by FVT. Thirdly, this paper presents observations on the structural dynamic behavior of the skyscraper with the operation of the AMD system during a typhoon event. The field measurement results show that the AMD system functioned efficiently for suppression of the wind‐induced vibrations of the skyscraper during the typhoon. This paper aims to further understand the structural dynamic properties of super‐tall buildings and provide useful information for structural design and vibration control of future skyscrapers.

Dynamic parameter identification of a super tall building based on field measurement

This work aims to identify the dynamic parameters (i.e. natural frequencies and damping ratios) of a super tall building under construction (i.e., Tianjin 117 Tower). Real time kinematic - global navigation satellite system (RTK-GNSS) receivers are applied to monitor the vibration of the structure. Considering the errors of receivers, a joint denoising method is proposed to weaken the influence of noise. Meanwhile, random decrement method (RDM) and fast Fourier transform (FFT) are adopted to derive the dynamic parameters of the structure. Moreover, the identified results from field measurement are compared with predicted values obtained from finite element model (FEM) of the structure. The outcomes of this study are that: (1) the proposed joint denoising method can be employed to weaken the RTK-GNSS observation errors; (2) the first natural frequency of the structure is derived successfully based on FFT analysis, and it agrees well with the finite element results; (3) the damping ratio of the structure is obtained by using RDM.

Measuring inherent structural damping of structure-TMD systems

A practical method is proposed to enable the inherent structural damping of structures equipped with tuned mass dampers (TMDs) to be quantified. While the traditional random decrement technique cannot be applied to structure-TMD systems, a modified version is presented which accommodates the energy transfer between the structure and TMD. It is shown that cross-correlation functions can be used to determine the random decrement signatures of the structural and TMD responses. Linear regression is combined with an energy balance approach to estimate the inherent structural damping. The total effective damping of the structure is then estimated by using an existing method to predict the added effective damping provided by the TMD.Numerical simulations reveal that the method predicts the inherent structural damping with acceptable accuracy if the duration of the measured response captures at least two thousand structural oscillation cycles, which corresponds to 3–6 h of data for most tall buildings. The method is most accurate when the inherent structural damping is relatively high, and the TMD mass ratio is relatively low. The method is applied to data collected from an anonymous super-tall building equipped with a TMD. The TMD is found to increase the effective damping of the tower from 1.0% to 3.0% of critical. These damping values are supported by measurements conducted when the TMD was briefly locked from moving, and also by theoretical predictions using the assessed dynamic properties of the structure and TMD.

Estimation of Random Friction Forces on the Microbearing Cooperating Surfaces

Abstract Presented paper concerns a new mathematical form of stochastic theory of hydrodynamic friction forces occurring on the real cooperating surfaces in computer micro bearing fan and computer microbearing in hard disc driver HDD. This paper presents particularly a new-review of stochastic analytical considerations realized by the authors for friction forces estimation during hydrodynamic lubrication performed on the ground of the measurements of the gap height between two roughness surfaces. After numerous experimental measurements directly follows that the random unsymmetrical increments and decrements of the gap height of computer microbearings have important influence on the load carrying capacities and finally on the friction forces and wear of cooperating surfaces. The main topic demonstrates the influence of the variations of expectancy values and standard deviation of the computer microbearing gap height on the friction forces occurring in the HDD and microbearing fan. Moreover, it is observed the evident connection between the apparent dynamic viscosity and the features of the microbearing superficial surface. Hence after abovementioned remarks follows the corollary that the influence of the microbearing gap height stochastic variations connected with the surface roughness tend moreover indirect from the apparent viscosity into the friction forces variations. The synthetic, complex elaboration of obtained results indicates finally the influence of the random roughness in micro and nano level of microbearing surfaces on the friction forces distribution. A new results contained in this paper are obtained taking into account 3D variations of dynamic viscosity of the non-Newtonian lubricant, particularly variations crosswise the film thickness and influences of surface superficial layer features on the lubricant apparent viscosity.

Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method

Vortex-induced vibration (VIV) has been occasionally observed on a few long-span steel box-girder suspension bridges. The underlying mechanism of VIV is very complicated and reliable theoretical methods for prediction of VIV have not been established yet. Structural health monitoring (SHM) technology can provide a large amount of data for further understanding of VIV. Automatic identification of VIV events from massive, continuous long-term monitoring data is a non-trivial task. In this study, a method based on the random decrement technique (RDT) is proposed to identify the VIV response automatically from the massive acceleration response without manual intervention. The raw acceleration data is first processed by RDT and it is found that the RDT-processed data show different characteristics for the VIV response and conventional random response. A threshold based on the coefficient of variation (COV) of peak values of processed data is defined to distinguish between the two kinds of responses. Both random vibration and VIV for a three-DOF (degree-of-freedom) mass-spring-damper system are obtained by numerical simulation to verify the proposed method. The method is finally applied to the Xihoumen suspension bridge for identifying VIV response from three-month monitoring data. It is shown that the proposed method performs comparably with the method of novelty detection. A total of 60 VIV events have been successfully identified. Vortex-induced vibrations for the second to ninth vertical modes with modal frequency within 0.1~0.5 Hz occurs at wind velocity 5–18 m/s, with wind direction nearly perpendicular to bridge axis. Amplitude of VIV generally decreases with increase of wind turbulence intensity; however, noticeable VIV amplitude are still observed for turbulence intensity up to 13% in some cases.

DETERMINATION OF RANDOM FRICTION FORCES ON THE BIOLOGICAL SURFACES OF A HUMAN HIP JOINT WITH A PHOSPHOLIPID BILAYER

The paper presented concerns a new mathematical form of the stochastic theory of hydrodynamic friction forces occurring on real human hip joint surfaces with a phospholipids bilayer. This paper particularly presents a new review of stochastic analytical considerations realized by the authors for friction forces estimation during hydrodynamic lubrication of biological surfaces performed on the basis of the gap height measurements in the human hip joint. After numerous experimental measurements, it directly follows that the random unsymmetrical increments and decrements of the gap height of human joints have an important influence on the load carrying capacities and finally on the friction forces and wear of cooperating cartilage surfaces. The main topic demonstrates the impact of the variations of expectancy values and the standard deviation of the human joint gap height on the friction forces occurring in the human joint. Moreover, an evident connection is observed between the apparent dynamic viscosity and the features of the cartilage surface coated by the phospholipid cells. Hence, after the abovementioned remarks, follows the corollary that the influence of the gap height stochastic variations and random surfaces coated by the PL cells tend indirectly from the apparent viscosity into the friction force variations. The synthetic, complex elaborations of the results obtained indicate the influence of the random roughness and stochastic growth of living biological cartilage surfaces on the friction forces distribution.

Enhanced EMD-RDT Method for Output-Only Ambient Modal Identification of Structures

AbstractAn enhanced approach of empirical mode decomposition based random decrement technique (EMD-RDT) is proposed for output-only modal parameter identification of structures using ambient vibrat...

Dynamic monitoring of a super high-rise structure based on GNSS-RTK technique combining CEEMDAN and wavelet threshold analysis

To capture the dynamic characteristics of a super high-rise structure under construction (i.e. Tianjin 117 Tower), multi-constellation GNSS-RTK (global navigation satellite system – real time kinematic) sensors are employed to derive the displacement information of the structure. A combined approach (CEEMDAN–WT) of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet threshold (WT) technique is put forward to weaken the influence of background noise of sensors. For the sake of testing the effect of noise reduction via employing CEEMDAN–WT, a nonlinear signal with additive noise is introduced. Subsequently, the natural frequencies and the corresponding damping ratios of the structure are extracted based on the fast Fourier transform (FFT) and random decrement technique. In addition, the finite element model (FEM) of the structure is built to forecast the natural frequencies via modal analysis. The results show that: (1) The dynamic displacement information of super high-rise structures can be effectively determined based on GNSS-RTK technique; (2) The presented CEEMDAN–WT approach outperforms the single CEEMDAN and WT approaches; (3) The result obtained via the field measurement coincides with the FEM.

Dynamic Parameter Identification of a Long-Span Arch Bridge Based on GNSS-RTK Combined with CEEMDAN-WP Analysis

Under the action of wind, traffic, and other influences, long-span bridges are prone to large deformation, resulting in instability and even destruction. To investigate the dynamic characteristics of a long-span concrete-filled steel tubular arch bridge, we chose a global navigation satellite systems-real-time kinematic (GNSS-RTK) to monitor its vibration responses under ambient excitation. A novel approach, the use of complete ensemble empirical mode decomposition with adaptive noise combined with wavelet packet (CEEMDAN-WP) is proposed in this study to increase the accuracy of the signal collected by GNSS-RTK. Fast Fourier transform (FFT) and random decrement technique (RDT) were adopted to calculate structural modal parameters. To verify the combined denoising and modal parameter identification methods proposed in this paper, we established the structural finite element model (FEM) for comparison. Through simulation and comparison, we were able to draw the following conclusions. (1) GNSS-RTK can be used to monitor the dynamic response of long-span bridges under ambient excitation; (2) the CEEMDAN-WP is an efficient method used for the noise reduction of GNSS-RTK signals; (3) after signal filtering and noise reduction, structural modal parameters are successfully derived through RDT and illustrated graphically; and (4) the first-order natural frequency identified by field measurement is slightly higher than the FEM in this work, which may have been caused by bridge damage or the inadequate accuracy of the finite element model.

A novel technique for experimental modal analysis of barotropic seiches for assessing lake energetics

Basin scale seiches in lakes are important elements of the total energy budget and are a driver of fluxes of important ecological parameters, such as oxygen, nutrients, and sediments. At present, the extraction of the damping ratios of surface seiches, which are directly related to the capacity of seiches to drive these fluxes through the increased mixing of the water column, is reliant on spectral analysis which may be heavily influenced by the transformation of water level records from the time domain to the frequency domain, and which are sensitive to the level of noise present within the data. Existing spectral-based methods struggle to extract the periods of surface seiches which are of similar magnitude due to the overlap between their spectral responses. In this study, the principles of operational modal analysis, through the random decrement technique (RDT), currently used primarily in the analysis of high rise structures and in the aeronautical industry and not previously applied within the fields of limnology or ecology, are applied to barotropic seiches through the analysis of water level data for Lake Geneva, Switzerland, and Lake Tahoe, USA. Using this technique, the autocorrelation of the measurements is estimated using the RDT and modal analysis can then be carried out on this time-domain signal to estimate periods of the dominant surface seiches and the corresponding damping ratios. The estimated periods show good agreement with experimental results obtained through conventional spectral techniques and consistent damping ratios are obtained for the dominant surface seiche of Lake Tahoe. The effect of input parameters is discussed, using data for the two lakes, alongside discussion of the application of RDT to the study of internal seiches and current barriers to its application. RDT has great potential for the analysis of both surface and internal seiches, offering a method through which accurate damping ratios of seiche oscillations may be obtained using readily available data without necessitating spectral analysis.

Using sparsity to estimate oscillatory mode from ambient data

In this paper, a sparse-technique-based representation of the signal over a learned dictionary and random decrement technique are explored to extract the oscillatory mode from the ambient data. The main contribution of the present work is to design a dictionary and compute the coefficients that best represent the clean signal to estimate the modes. In this work, the noise embedded in the ambient signal is minimized by representing the ambient signal in sparse domain with respect to the dictionary. Comparison between the proposed method and other methods such as nonlinear filtering, etc., has been done on the test signal, two-area power system on the data generated through simulation in Matlab, two-area data simulated on real-time digital simulator and real measurement from Phasor data concentrator (PDC) of Indian power system and Western Electricity Coordinating Council (WECC) network.

Modal parameter estimation for a wetted plate under flow excitation: A challenging case in using POD

In this paper some issues related to the use of the Proper Orthogonal Decomposition (POD) for the identification of the modal parameters of 2D structures are highlighted with reference to the experimental identification of the vibration modes of a plate excited on one side by a turbulent boundary layer. The poor convergence of the POD modes to the linear normal modes is explained analytically and provides also the theoretical framework to avoid these issues by applying band-pass filtering (BP-POD). The application of the POD with data pre-filtering has allowed for the evaluation of the modal damping from the proper orthogonal coordinates by using the Random Decrement Technique to obtain the corresponding free-decay function. Though the emphasis is about methodological aspects related to the POD, as a byproduct of the performed analysis some more physical insights concerning the damping sensitivity and the hydrodynamic added mass are finally carried out.

Operational modal identification of structures based on improved empirical wavelet transform

This paper proposes an improved Empirical Wavelet Transform (EWT) approach for structural operational modal identification based on measured dynamic responses of structures under ambient vibrations. Two steps are involved in the improved EWT approach. In the first step, the standardized autoregressive power spectrum of the measured response is calculated to define the boundaries of frequency components for the subsequent EWT analysis. The second step is to decompose the measured response into a number of Intrinsic Mode Functions (IMFs) by using EWT. When the Intrinsic Mode Functions are obtained, structural modal information such as natural frequencies, mode shapes, and damping ratios can be identified by using Hilbert transform and Random Decrement Technique. In numerical studies, a simulated signal is used to investigate the effectiveness of the proposed approach. Operational modal identification based on the proposed approach and procedure is conducted to identify the modal parameters of a simulated spatial frame structure under the ambient excitations. The proposed approach is further used for operational modal identification of a seven-storey shear type steel frame structure in the laboratory and a real footbridge under ambient vibrations to verify the accuracy and performance. The modal identification results from both numerical simulations and experimental validations demonstrate that the proposed approach can effectively and accurately decompose the vibration responses and identify the structural modal parameters under operational conditions.

Modal identification of a high-rise building subjected to a landfall typhoon via both deterministic and Bayesian methods.

Modal identification involves primarily the determination of natural frequencies, damping ratios, mode shapes of a dynamic system, etc. It is usually regarded as an essential task in a wide branch of structural dynamics and civil engineering, such as structural vibration control and damage identification of buildings or bridges. There are many modal identification techniques. Basically, these techniques can be categorized into two groups: deterministic methods and Bayesian approaches. The first group can be used to provide deterministic (or optimal) estimations of modal parameters, but they are unable to quantify the estimation uncertainties. The second group is based on a usage of the Bayesian framework. Compared to the first group, the second group of methods has a typical merit of being able to offer uncertainty information of identified parameters, which is of great interests, or even necessary, for some follow-up studies. In this paper, both a deterministic method, i.e., a combination of spectral analysis, filtering and Random Decrement Technique (RDT), and a Bayesian method, i.e., Bayesian Spectral Density Approach (BSDA), are exploited to experimentally identify the modal parameters of a 303 m high-rise building that was subjected to a landfall typhoon. The validity and efficiency of each method is verified by comparing the two kinds of results. Meanwhile, the identified modal parameters are used for the serviceability assessment of this high-rise building against some frequency-specific criteria.

Investigation of the Dynamic Behavior of a Super High-rise Structure using RTK-GNSS Technique

Super high-rise structures have a significant deformation under ambient excitations such as earthquake and wind, which may lead to structural instability and even damage. To capture the dynamic characteristics of a super high-rise structure under construction (i.e., Tianjin 117 tower), Real Time Kinematic - Global Navigation Satellite Systems (RTK-GNSS) sensors are employed to derive the horizontal displacement of the structure. Considering the defects in measurement accuracy of RTK-GNSS sensors, a Type 1 Chebyshev high-pass digital filter is firstly employed and thus the output results are smoothed. Subsequently, based on the smoothed signals, the natural frequencies and the corresponding damping ratios are extracted via FFT (Fast Fourier Transform) and RDT-LDM (random decrement technique combined with logarithmic decrement method). It is found that the results from the field measurement coincide with the numerical simulation. Finally, the structural parameters are successfully obtained and illustrated graphically.

Observations of typhoon effects on a high-rise building and verification of wind tunnel predictions

This paper presents the analysis results of 18-h-long field measurement data collected at a 420-m-high building and four meteorological stations in Hong Kong during the passage of Typhoon Usagi (1319) which was the most intense tropical cyclone that attacked Hong Kong in 2013. In this paper, the wind characteristics during Typhoon Usagi over five different sites in Hong Kong are presented and discussed; the modal parameters of the monitored high-rise building are estimated by a probabilistic approach in a Bayesian framework (i.e., Bayesian spectral density approach) and a deterministic method (i.e., Random decrement technique), respectively; the serviceability of the high-rise building under typhoon condition is evaluated against four comfort criteria. Furthermore, the wind tunnel predictions of structural dynamic responses of the monitored building are validated by the field measurements. The goal of this study is to further the understanding of the effects of wind on high-rise buildings so as to provide useful information for the wind-resistant structural design in tropical cyclone-prone regions.

Data-driven methods for operational modal parameters identification: A comparison and application

The operational modal parameters identification under ambient excitation has been widely applied in structural dynamics analysis, where the input force is difficult to measure. This paper makes comprehensive and systematic comparisons of four statistical learning algorithms (PCA, ICA, SOBI, LLE) on analyzing their performance for resolving operational modal parameters identification. It mainly focuses on the comparison and evaluation of the four data-driven methods based for operational modal analysis and explores the use of Hilbert Transform and Random Decrement Technique for the identification of modal damping ratios. The further tests, the robustness of four algorithms, are conducted for investigating the influences of external noise to the performance of the algorithms. On the basis of the modal expansion theory, the vibration response signals could be decomposed into the inner product of modal shapes matrix and modal responses vector in the modal coordinate, from which the modal shapes, modal natural frequencies and modal damping ratios can be well estimated. Hence, a one-to-one mapping between the mathematical model of four statistical learning algorithms and physical model of dynamic systems is established. To validate the effectiveness of the proposed methods, performance and comparison of the proposed methods are studied using a discrete three degree-of-freedom (DOF) system and continuous cantilever steel plate. The simulation and experimental results show that, for the same experimental data, the SOBI algorithm has better performance than other algorithms, and it is more suitable for operational modal identification. Finally, the characteristics of four algorithms and further directions are concluded and discussed in this paper.

Dynamic system identification of a high-rise building during Typhoon Kalmaegi

This paper presents a series of dynamic system identifications based on field measurements in a high-rise building located in Haikou, China during the passage of Typhoon Kalmaegi on September 16, 2014. The high-rise building, with a height of 108 m, has 32 stories. Wind-field characteristics atop the building, acceleration responses along both axes on the 6th, 12th, 18th, 24th, 30th, 32nd floors were measured synchronously, based on which time and frequency domain characteristics, and dynamic characteristics of the building were analyzed by the ERA-NExT, improved random decrement technique and Half-power bandwidth method. The results reveal that root-mean-squared (RMS) of accelerations and peak values along both the longitudinal and lateral axes vary according to an increasing power function as the wind speed increases. The probability density of acceleration responses on different floors approximates to the Gaussian distribution during the whole process of the typhoon impinging on the building. The guarantee rate was used to calculate the ratio of peak to mean acceleration. The resulting value of acceleration peak factor is recommended to be 3.5 when target guarantee rate is 99.38%. The first three modal amplitude-dependent damping and frequency characteristics were investigated in detail based on the identified non-linear characteristics of the measured building. The first three modal damping ratios increase significantly with RMS of accelerations before reaching a maximum value. At greater values of RMS of accelerations the damping ratios stabilized or reduced after reaching a maximum value. The first three modal frequencies decreased with increasing acceleration amplitude. The rate of reduction of the frequency reduced after reaching a critical amplitude. The reduction in the modal frequencies were 8.6%, 8.8% and 8.9%, in sequence, when the acceleration amplitude reached a maximum value. An empirical formula of amplitude-dependent fundamental frequency considering the influences of tip drift ratio (the ratio of RMS of accelerations at the top floor to building height) has been proposed. The field measurement data and statistical parameters provide useful information on the wind-resistant design of high-rise buildings in typhoon-prone regions.

Output-only modal analysis of wind turbine tower based on vibration response under emergency stop

The identification technique of output-only modal parameters is proposed for the large wind turbine tower under emergency stop. Compared with the response of regular operating conditions, the immediate tower structural response under emergency stop much more resembles a state of free vibration, which is more appropriate for the modal identification of the wind turbine tower. The vibration response is measured in the nacelle, which is easy to perform in the field modal test. The variational mode decomposition (VMD) is applied to decompose the vibration response into several band-limited intrinsic mode functions. The free responses of decomposed functions are extracted by applying the random decrement technique (RDT). Finally, the modal damping ratio and natural frequency are identified from each free modal response by using the Hilbert transform method. Simulations and a 1.5 MW wind turbine field modal test results verify the effectiveness of the proposed identification method. The main modal parameters of wind turbine, including weak modes, are effectively extracted by using output-only vibration responses under emergency stop. The modal parameter identification method is provided for the large wind turbine structure under the engineering condition.