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Relevant bibliographies by topics / Frequency Response Function(FRF)

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Academic literature on the topic 'Frequency Response Function(FRF)'

Author: Grafiati

Published: 4 June 2025

Last updated: 23 June 2025

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Journal articles on the topic "Frequency Response Function(FRF)"

1

Zhou, Jun Wei, Lin He, and Rong Wu Xu. "Typical Errors Analysis in Frequency Response Function Measurement." Applied Mechanics and Materials 419 (October 2013): 470–76. http://dx.doi.org/10.4028/www.scientific.net/amm.419.470.

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FRF measurements can suffer from various errors. The effect of deterministic errors become more prominent compared to random errors in FRF measurement. Excitation and sensor misalignment is the most common source of deterministic error, so mathematic model is established and the effect on FRF estimation was analyzed for senor and excitation misalignment situations. Finite element model simulation reveals that misalignment error can have the least effect on the dominant FRFs and a stronger effect on lesser FRFs, beside that it also results in the appearance of false peaks in the measured FRFs.

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Zhang, Qingxia, Jilin Hou, Zhongdong Duan, Łukasz Jankowski, and Xiaoyang Hu. "Road Roughness Estimation Based on the Vehicle Frequency Response Function." Actuators 10, no. 5 (2021): 89. http://dx.doi.org/10.3390/act10050089.

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Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

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Juraj, Úradníček, Miloš Musil, and Michal Bachratý. "Frequency Response Function Measurement on Simplified Disc Brake Model." Strojnícky casopis – Journal of Mechanical Engineering 68, no. 3 (2018): 225–30. http://dx.doi.org/10.2478/scjme-2018-0036.

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AbstractThe paper describes role of non-proportional damping in flutter type instability, demonstrated on simplified disc brake model. The discrete two degrees of freedom system is considered to imply damping induced instability through a system eigenvalues evaluation. The Frequency Response Function (FRF) is further calculated from measurements on the physical disc brake model. From FRF, damping properties are estimated and discussed. Several different loading states of the pad versus disc are considered to show loading impact on FRF and thus damping of the system.

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Wan Iskandar Mirza, W. I. I., M. N. Abdul Rani, M. A. Yunus, R. Omar, and M. S. Mohd Zin. "Alternative scheme for frequency response function measurement of experimental-analytical dynamic substructuring." Journal of Mechanical Engineering and Sciences 13, no. 2 (2019): 4946–57. http://dx.doi.org/10.15282/jmes.13.2.2019.13.0410.

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The accuracy of the predicted dynamic behaviour of an assembled structure using the frequency based substructuring (FBS) method is often found to be diverged from the experimental counterparts. The divergence which has become the paramount concern and major issue for structural dynamicists is because of the unreliable experimental FRF data of the interfaces of substructures, arising from the limited resources of appropriate excitation points and accelerometer attachments in the vicinity of the interfaces. This paper presents an alternative scheme for FRF measurement of the experimental FRF data of substructures. In this study, an assembled structure consisting of two substructures were used, namely substructure A (Finite element model) and substructure B (Experimental model). The FE model of substructure A was constructed by using 3D elements and the FRFs were derived via the FRF synthesis method. Specially customised bolts were used to allow the attachment of accelerometers and excitation to be made at the interfaces of substructure B, and the FRFs were measured by using impact testing. Both substructures A and B were then coupled by using the FBS method and the coupled FRF was validated with the measured FRF counterparts. This work revealed that the proposed scheme with specially customized bolts has led to a significant enhancement and improvement in the FBS predicted results.

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Steffensen, M. T., D. Tcherniak, and J. J. Thomsen. "Accurate frequency response function estimation using noise measurements in experimental modal analysis." Journal of Physics: Conference Series 2647, no. 21 (2024): 212003. http://dx.doi.org/10.1088/1742-6596/2647/21/212003.

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Abstract In experimental structural dynamics, reliable estimation of Frequency Response Functions (FRF) is important to correctly characterize a mechanical system. In Experimental Modal Analysis (EMA), the FRFs are used as input to a modal parameter estimation algorithm to obtain the modal characteristics of the system. Errors due to noisy measurements are inevitably present in the FRFs and propagate to the modal parameters. A consistent FRF-estimator with low uncertainty is therefore needed. Different FRF estimators have been proposed with some consistency when certain noise-related assumptions are fulfilled (H1, H2, etc.). To choose the appropriate frequency response function estimator, information about the noise in the experimental setup is desirable. In this work it is shown how to use measurements of noise, to characterize different noise components in the experimental setup and determine the appropriate number of averages needed for the experimental setup. The identified noise components can be used to identify the main source of uncertainty in the experimental setup and which FRF estimator to use.

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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.

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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.

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Zhang, Yan, Jijian Lian, Songhui Li, Yanbing Zhao, Guoxin Zhang, and Yi Liu. "Predicting Dam Flood Discharge Induced Ground Vibration with Modified Frequency Response Function." Water 13, no. 2 (2021): 144. http://dx.doi.org/10.3390/w13020144.

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Ground vibrations induced by large flood discharge from a dam can damage surrounding buildings and impact the quality of life of local residents. If ground vibrations could be predicted during flood discharge, the ground vibration intensity could be mitigated by controlling or tuning the discharge conditions by, for example, changing the flow rate, changing the opening method of the orifice, and changing the upstream or downstream water level, thereby effectively preventing damage. This study proposes a prediction method with a modified frequency response function (FRF) and applies it to the in situ measured data of Xiangjiaba Dam. A multiple averaged power spectrum FRF (MP-FRF) is derived by analyzing four major factors when the FRF is used: noise, system nonlinearity, spectral leakages, and signal latency. The effects of the two types of vibration source as input are quantified. The impact of noise on the predicted amplitude is corrected based on the characteristics of the measured signal. The proposed method involves four steps: signal denoising, MP-FRF estimation, vibration prediction, and noise correction. The results show that when the vibration source and ground vibrations are broadband signals and two or more bands with relative high energies, the frequency distribution of ground vibration can be predicted with MP-FRF by filtering both the input and output. The amplitude prediction loss caused by filtering can be corrected by adding a constructed white noise signal to the prediction result. Compared with using the signal at multiple vibration sources after superimposed as input, using the main source as input improves the accuracy of the predicted frequency distribution. The proposed method can predict the dominant frequency and the frequency bands with relative high energies of the ground vibration downstream of Xiangjiaba Dam. The predicted amplitude error is 9.26%.

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Ślaski, Grzegorz, and Zbyszko Klockiewicz. "The influence of shock absorber characteristics’ nonlinearities on suspension Frequency Response Function estimation and possibilities of simplified characteristics modelling." Archives of Automotive Engineering – Archiwum Motoryzacji 96, no. 2 (2022): 77–95. http://dx.doi.org/10.14669/am/151704.

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The paper shortly presents shock absorber design evolution and resulting achieved characteristics. The way in which suspension performance is evaluated is described giving information about models used for suspension parameter tuning during simulation testing of suspension transmissibility (FRF - Frequency Response Function) for most important suspension assessment criteria. More detailed information about models of shock absorber (damper) nonlinearities of characteristics allows for description of methods of linear and nonlinear suspension models FRF estimation. Testing linear suspension model is possible with the use of analytical transfer function formulas which were used to verify methods for estimation FRF using estimated power spectral density functions of excitation and response signals. Designing appropriate input signal allowing to get useful response signals was necessary to for the success of this research. Proposed FRF estimation method was used for linear estimation of nonlinear suspension for a given range of working condition. It was demonstrated that there is no single value of a damping coefficient which would make the linear model responses similar to the responses of the nonlinear one. Then the bilinear model was proposed, giving good damper static nonlinear characteristic.

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Li, Xin Hui, Tie Jun Yang, Jian Chao Dong, and Ze Qi Lu. "Secondary Path Estimation by PCA-Compressed Frequency Response Function in Active Vibration Control." Applied Mechanics and Materials 66-68 (July 2011): 721–26. http://dx.doi.org/10.4028/www.scientific.net/amm.66-68.721.

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The FXLMS algorithm is widely used in active vibration control system. The estimation of secondary path plays very important roles in such a system. This paper presents an experimental investigation of effective secondary path estimation in active vibration control using measured Frequency Response Function (FRF). Principal component analysis (PCA) is pursued to the measured FRF for noise elimination, and then the PCA-compressed FRF data are used for secondary path estimation. The control results indicate that the proposed method has good control performance.

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Jia, Libin, Jeffrey D. Naber, and Jason R. Blough. "Frequency response function adaptation for reconstruction of combustion signature in a 9-L diesel engine." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 17 (2015): 3071–83. http://dx.doi.org/10.1177/0954406215569256.

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An accelerometer as a low-cost non-intrusive transducer for sensing the combustion events in a diesel engine was investigated via the reconstruction of in-cylinder pressure using an adapting frequency response function (FRF). As the noise introduced into the accelerometer signal and the response to combustion vary with the operating condition, the FRF computed from a single operating condition only works for the same or similar conditions. To overcome this limitation, an adaptation process for the FRF was explored. Robustness of FRF over additional operational conditions with start of injection, start of combustion, and load variations was greatly improved. Frequency domain analysis shows that only the low-frequency content is determinant for the in-cylinder pressure reconstruction, and the adaptation of the first and second (0 Hz and 121 Hz) harmonics of the FRF results in the greatest improvement for the in-cylinder pressure estimation accuracy. The 0 Hz harmonic is adjusted based on the pre-measured in-cylinder pressure offset and the online measured accelerometer signal offset. Particle swam optimization as a computational algorithm is applied to adapt the 121 Hz harmonic of FRF. The results show that the adapted FRF, in comparison to the unadapted FRF, can reduce the phase error up to 1.3 crank angle degrees and reduce the amplitude error by up to 90%.

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Dissertations / Theses on the topic "Frequency Response Function(FRF)"

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Vasudeva, Vikas. "Characterization of MEMS devices on the basis of their frequency response function (FRF)." abstract and full text PDF (free order & download UNR users only), 2007. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1447635.

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Majba, Christopher. "A Review of Uncertainty Quanitification of Estimation of Frequency Response Functions." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1346171022.

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Ozturk, Murat. "Finite Element Structural Model Updating By Using Experimental Frequency Response Functions." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610608/index.pdf.

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Initial forms of analytical models created to simulate real engineering structures may generally yield dynamic response predictions different than those obtained from experimental tests. Since testing a real structure under every possible excitation is not practical, it is essential to transform the initial mathematical model to a model which reflects the characteristics of the actual structure in a better way. By using structural model updating techniques, the initial mathematical model is adjusted so that it simulates the experimental measurements more closely. In this study, a sensitivity-based finite element (FE) model updating method using experimental frequency response (FRF) data is presented. This study bases on a technique developed in an earlier study on the computation of the so-called Mis-correlation Index (MCI) used for identifying the system matrices which require updating. MCI values are calculated for each required coordinate, and non-zero numerical values indicate coordinates carrying error. In this work a new model updating procedure based on the minimization of this index is developed. The method uses sensitivity approach. FE models are iteratively updated by minimizing MCI values using sensitivities. The validation of the method is realized through some case studies. In order to demonstrate the application of the method for real systems, a real test data obtained from the modal test of a scaled aircraft model (GARTEUR SM-AG19) is used. In the application, the FE model of the scaled aircraft is updated. In the case studies the generic software developed in this study is used along with some commercial programs.

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Johansson, Tim, and Magdalena Cwenarkiewicz. "Experimental Dynamic Substructuring of an Ampair 600 Wind Turbine Hub together with Two Blades : A Study of the Transmission Simulator Method." Thesis, Linnéuniversitetet, Institutionen för maskinteknik (MT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-53605.

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In this work, the feasibility to perform substructuring technique with experimental data is demonstrated. This investigation examines two structures with different additional mass‑loads, i.e. transmission simulators (TSs). The two structures are a single blade and the hub together with two blades from an Ampair 600 wind turbine. Simulation data from finite element models of the TSs are numerically decoupled from each of the two structures. The resulting two structures are coupled to each other. The calculations are made exclusively in the frequency domain. A comparison between the predicted behavior from this assembled structure and measurements on the full hub with all three blades is carried out. The result is discouraging for the implemented method. It shows major problems, even though the measurements were performed in a laboratory environment.

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Sharma, Akhil. "A New Multiple Input Random Excitation Technique Utilizing Pneumatic Cylinders." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470671978.

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Patwardhan, Rohit S. "Frequency Response and Coherence function estimation methods." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592169805143687.

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Schulte, Walter B. III. "The frequency response, impulse response, and transfer function of an ocean waveguide." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1516.

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Approved for public release, distribution is unlimited<br>In this thesis, the ocean was modeled as a waveguide with an ideal pressure - release surface, and an ideal rigid bottom. The ocean waveguide was then treated as a linear, time - invariant, space - variant (TISV) filter or communication channel. The filter is time - invariant because no motion was modeled and because the properties of the ocean were assumed to be constant. The filter is space - variant because of the presence of the two boundaries, that is, the ocean surface and ocean bottom. This thesis investigates the ocean as a linear TISV filter by evaluating 1) the complex frequency response, 2) the impulse response, and 3) the transfer function of the ocean with respect to depth. It is shown that the TISV impulse response of the ocean contains information that can be used to help localize a target in range and whether the target is above or below the receiver. Computer simulation results were obtained by evaluating the three filter functions for several different test cases.<br>Ensign, United States Navy

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Schulte, Walter B. "The frequency response, impulse response, and transfer function of an ocean waveguide /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Jun%5FSchulte.pdf.

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Thesis (M.S. in Applied Science (Signal Processing))--Naval Postgraduate School, June 2004.<br>Thesis advisor(s): Lawrence J. Ziomek. Includes bibliographical references (p. 47). Also available online.

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Kim, Youngtae. "Spatial resolution limits for the reconstruction of acoustic source distribution by inverse techniques." Thesis, University of Southampton, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274706.

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McCune, Robert E. "Identification of Continuous-Time and Discrete-Time Transfer Function Models from Frequency Response Measurements." Ohio University / OhioLINK, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1239731009.

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Books on the topic "Frequency Response Function(FRF)"

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Swain, A. K. Generalised frequency response function matrix for MIMO nonlinear systems. University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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Billings, S. A. Reconstruction of MIMO nonlinear differential equation models from the generalised frequency response function matrix. University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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The Frequency Response, Impulse Response, and Transfer Function of an Ocean Waveguide. Storming Media, 2004.

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Macario, Ana L. G. Frequency response function analysis of the equatorial margin of Brazil using gravity and bathymetry. 1990.

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Davey, Kent. Magnetic field stimulation: the brain as a conductor. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0005.

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For the purposes of magnetic stimulation, the brain can be treated as a homogeneous conductor. A properly designed brain stimulation system starts with the target stimulation depth, and it should incorporate the neural strength–duration response characteristics. Higher-frequency pulses require stronger electric fields. The background of this article is the theoretical base determining, where in the brain TMS induces electrical activity, and whether this shifts as a function of differences in the conductivity and organization of gray matter, white matter, and cerebrospinal fluid. The use of strong electric fields to treat many neurological disorders is well established. Both in the treatment of incontinence and clinical depression, the electric field should be sufficiently strong to initiate an action potential. The frequency, system voltage, capacitance, core stimulator size, and number of turns are treated as unknowns in a TMS stimulation design. This article presents the possible topological changes to be considered in the future.

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Shapiro, Kimron, and Simon Hanslmayr. The Role of Brain Oscillations in the Temporal Limits of Attention. Edited by Anna C. (Kia) Nobre and Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.037.

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Attention is the ubiquitous construct referring to the ability of the brain to focus resources on a subset of perceptual input which it is trying to process for a response. Attention has for a long time been studied with reference to its distribution across space where, for example, visual input from an attentionally monitored location is given preference over non-monitored (i.e. attended) locations. More recently, attention has been studied for its ability to select targets from among rapidly, sequentially presented non-targets at a fixed location, e.g. in visual space. The present chapter explores this latter function of attention for its relevance to behaviour. In so doing, it highlights what is becoming one of the most popular approaches to studying communication across the brain—oscillations—at various frequency ranges. In particular the authors discuss the alpha frequency band (8–12 Hz), where recent evidence points to an important role in the switching between processing external vs. internal events.

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Froio, Sara, and Franco Valenza. Aspiration of gastric contents in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0106.

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This chapter focuses on the pathophysiology, clinical features, management and prevention of aspiration pneumonitis, aspiration pneumonia, and airway obstruction. Aspiration is defined as the inhalation of oropharyngeal or gastric contents into the larynx and lower respiratory tract. Pulmonary syndromes caused by aspiration are different, depending on the amount and nature of the aspirated material, the frequency of aspiration and the host’s response. This results in a chemical burn of tracheobronchial tree and pulmonary parenchyma. The caustic effects of the low pH of the aspirate cause an intense inflammatory reaction. As a consequence, severe hypoxaemia and infiltrates on chest radiograph occur. If colonized oropharyngeal material enters the lungs, aspiration pneumonia develops and antibiotics are needed. Even if not toxic per se, large volumes of fluids may cause suffocation by mechanical obstruction. Prevention of aspiration is of vital importance and the patient at risk must be identified. The major therapeutic approach is to correct hypoxia, support pulmonary function, and prevent pneumonia development.

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Magee, Patrick, and Mark Tooley. Physics in anaesthesia. Edited by Antony R. Wilkes and Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0023.

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This chapter covers the basic science of physics relevant to anaesthetic practice. Equipment and measurement devices are covered elsewhere. Starting with fundamentals, atomic structure is introduced, followed by dimensions and units as used in science. Basic mechanics are then discussed, focusing on mass and density, force, pressure, energy, and power. The concept of linearity, hysteresis, and frequency response in physical systems is then introduced, using relevant examples, which are easy to understand. Laminar and turbulent fluid flow is then described, using flow measurement devices as applications of this theory. The concept of pressure and its measurement is then discussed in some detail, including partial pressure. Starting with the kinetic theory of gases, heat and temperature are described, along with the gas laws, critical temperature, sublimation, latent heat, vapour pressure and vaporization illustrated by the function of anaesthetic vaporizers, humidity, solubility, diffusion, osmosis, and osmotic pressure. Ultrasound and its medical applications are discussed in some detail, including Doppler and its use to measure flow. This is followed by an introduction to lasers and their medical uses. The final subject covered is electricity, starting with concepts of charge and current, voltage, energy, and power, and the role of magnetism. This is followed by a discussion of electrical circuits and the rules governing them, and bridge circuits used in measurement. The function of capacitors and inductors is then introduced, and alternating current and transformers are described.

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Book chapters on the topic "Frequency Response Function(FRF)"

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Taghizadeh, Saeid, Matthew S. Bonney, David Wagg, and Hassan Ghadbeigi. "Tribo-Dynamics Digital Twins (TDDTs): Prediction of Friction and Frequency Response Function (FRF) in a Dry Sliding Tribological Contact." In Conference Proceedings of the Society for Experimental Mechanics Series. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-68893-5_15.

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Neighborgall, Campbell R., Karan Kothari, V. V. N. Sriram Malladi, Pablo Tarazaga, Sai Tej Paruchuri, and Andrew Kurdila. "Shaping the Frequency Response Function (FRF) of a Multi-Degree-of-Freedom (MDOF) Structure Using Arrays of Tuned Vibration Absorbers (TVA)." In Topics in Modal Analysis & Testing, Volume 8. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12684-1_33.

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Castro, L., P. Viéville, and P. Lipinski. "Experimental Methodology Destined to Establish the Frequency Response Function (FRF) between a Dynamic Force and the Signals Emitted by a Piezoelectric Dynamometer." In Materials Science Forum. Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-417-0.85.

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Weik, Martin H. "frequency response function." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_7684.

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Phillips, A. W., and R. J. Allemang. "Frequency Response Function Estimation." In Handbook of Experimental Structural Dynamics. Springer New York, 2022. http://dx.doi.org/10.1007/978-1-4614-4547-0_8.

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Phillips, A. W., and R. J. Allemang. "Frequency Response Function Estimation." In Handbook of Experimental Structural Dynamics. Springer New York, 2020. http://dx.doi.org/10.1007/978-1-4939-6503-8_8-1.

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Akaike, Hirotugu, and Yasufumi Yamanouchi. "On the Statistical Estimation of Frequency Response Function." In Springer Series in Statistics. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-1694-0_8.

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Nematipoor, N., M. R. Ashory, and E. Jamshidi. "Vibration Absorber Design via Frequency Response Function Measurements." In Structural Dynamics, Volume 3. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9834-7_143.

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Litovski, Vančo. "Transfer Function and Frequency and Time Domain Response." In Electronic Filters. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9852-1_3.

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Yaghoubi, Vahid, and Thomas Abrahamsson. "Automated Modal Analysis Based on Frequency Response Function Estimates." In Topics in Modal Analysis I, Volume 5. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2425-3_2.

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Conference papers on the topic "Frequency Response Function(FRF)"

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Rahimi Dizadji, Mostafa, Songwei Wang, Vahid Jafarpour, David Reynoso, and Haiying Huang. "Extracting dispersion curve from frequency response function (FRF) of flexural beams: a Fabry-Perot resonator perspective." In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2025, edited by Maria Pina Limongelli, Ching Tai Ng, and Didem Ozevin. SPIE, 2025. https://doi.org/10.1117/12.3052058.

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Wade, Daniel, Hieu Ngo, Frances Love, et al. "Measurement of Vibration Transfer Functions to Inform Machine Learning Based HUMS Diagnostics." In Vertical Flight Society 72nd Annual Forum & Technology Display. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11479.

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The US Army has improved a method for accelerating the maturity of vibration-based mechanical diagnostics, by measuring the Frequency Response Functions (FRFs) between potential failure locations and sensor locations within epicyclic gearboxes, and by building Condition Indicators (CIs) using these FRFs. The previous FRF methodology has been expanded to include frequencies up to 100 kHz, using the piezo-exciters, aircraft-installed Health and Usage Monitoring Systems (HUMS), and custom data acquisition hardware described herein. Previous CI development methodology has been improved by filtering captured vibration data with the FRFs. Using a recent process for generating diagnostic algorithms using machine learning, these FRF-based CIs outperform conventional CIs, and meet Aeronautical Design Standard 79D diagnostic classification criteria for use on board aircraft.

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Qu, Yongzhi, Gregory W. Vogl, and Zechao Wang. "A Deep Neural Network Model for Learning Runtime Frequency Response Function Using Sensor Measurements." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-64065.

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Abstract The frequency response function (FRF), defined as the ratio between the Fourier transform of the time-domain output and the Fourier transform of the time-domain input, is a common tool to analyze the relationships between inputs and outputs of a mechanical system. Learning the FRF for mechanical systems can facilitate system identification, condition-based health monitoring, and improve performance metrics, by providing an input-output model that describes the system dynamics. Existing FRF identification assumes there is a one-to-one mapping between each input frequency component and output frequency component. However, during dynamic operations, the FRF can present complex dependencies with frequency cross-correlations due to modulation effects, nonlinearities, and mechanical noise. Furthermore, existing FRFs assume linearity between input-output spectrums with varying mechanical loads, while in practice FRFs can depend on the operating conditions and show high nonlinearities. Outputs of existing neural networks are typically low-dimensional labels rather than real-time high-dimensional measurements. This paper proposes a vector regression method based on deep neural networks for the learning of runtime FRFs from measurement data under different operating conditions. More specifically, a neural network based on an encoder-decoder with a symmetric compression structure is proposed. The deep encoder-decoder network features simultaneous learning of the regression relationship between input and output embeddings, as well as a discriminative model for output spectrum classification under different operating conditions. The learning model is validated using experimental data from a high-pressure hydraulic test rig. The results show that the proposed model can learn the FRF between sensor measurements under different operating conditions with high accuracy and denoising capability. The learned FRF model provides an estimation for sensor measurements when a physical sensor is not feasible and can be used for operating condition recognition.

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Hosoya, Naoki, and Takuya Yoshimura. "Estimation of Frequency Response Function on Rotational Degrees of Freedom of Structures." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/movic-8406.

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Abstract In conventional vibration testing, measurement of frequency response function (FRF) has been limited to translational degrees of freedom (DOF). Rotational DOFs have not been treated in experimental analysis. However, the rotational DOF is indispensable in further analysis, such as substructure synthesis, prediction of structural dynamics modification, etc. Hence, measurement of FRFs on rotational DOF is essential for expanding applicability of experimental modal analysis. This paper proposes a new method for FRF estimation on rotational DOF of structures. The following is the estimation procedure: A rigid block is fixed on the measurement point of the structure; the block is excited by conventional impact hammer; the inner force and the response of the connection point including rotational DOFs are estimated; and lastly, the FRF including rotational DOF at the connection point of the structure is obtained. The feasibility of the method is investigated experimentally by applying it to a beam structure.

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Kushnir, Emmanuil. "Determination of Machine Tool Frequency Response Function During Cutting." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59573.

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The dynamic compliance (frequency response function - FRF) of a machine tool structure in the cutting zone under a cutting load is one of the major dynamic characteristics that define a machine’s cutting performance. The roundness and surface finish define the quality of the manufactured parts. These characteristics are developed during finishing and semi-finishing cuts. The kinowledge of machine tool dynamic compliance, defined in these steady-state cutting conditions, ensures parts quality and increase in machine tool productivity. The dynamic compliance is usually evaluated in tests, which are performed by means of hammers or vibrators (exciters). During these tests the machine does not cut and the machine components do not move relative to each other. The loads in the machine during cutting are defined by different internal and external sources that are acting in different points of the machine and in different directions. The real spectrum and frequency range of these forces is unknown. Experimental data acquired by different types of tests clearly show the difference in dynamic compliance for the same machine tool during cutting and idling. The machine tool dynamic tests performed by different types of external exciting devices do not take in consideration the real load conditions and interactions of moving components, including the cutting process itself and external sources of vibration. The existing methods of experimental evaluation of machine tool dynamic compliance during steady-state cutting condition require dynamometers to measure the cutting force and a special sensor to measure relative displacement between the cutting tool and workpiece. The FRF that is computed from these measurements represents a dynamic characteristic of the close loop system (machine structure and cutting process) and only under certain conditions may be considered as FRF of machine tool structure itself. The theory of stationary random processes allows defining the cutting conditions, under which the obtained data represent the FRF of machine tool structure, and provide estimations of random and bias errors of this evaluation. The simplified methodology of FRF estimation, based only on measurement of the spindle and tool vibration, is also presented in this paper. This methodology is used on an assembly line to obtain FRF for machine tools performance comparison and quality assurance.

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Xu, Y. F., and W. D. Zhu. "Efficient and Accurate Calculation of Discrete Frequency Response Functions and Impulse Response Functions." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47779.

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Modal properties of a structure can be identified by experimental modal analysis (EMA). Discrete frequency response functions (FRFs) and impulse response functions (IRFs) between responses and excitation are bases for EMA. In calculation of a discrete FRF, discrete Fourier transform (DFT) is applied to both response and excitation data series, and a transformed data series in DFT is virtually extended to have an infinite length and be periodic with a period equal to the length of the series; the resulting periodicity can be physically incorrect in some cases, which depends on an excitation technique used. There are various excitation techniques in EMA, and periodic extension in DFT for EMA using periodic random and burst random excitation is physically correct. However, EMA using periodic random excitation needs a relatively long excitation time to have responses to be steady-state and periodic, and EMA using burst random excitation needs a long sampling period for responses to decay to zero, which can result in relatively long response and excitation data series and necessitate a large number of spectral lines for associated DFTs, especially for a high sampling frequency. An efficient and accurate methodology for calculating discrete FRFs and IRFs is proposed here, by which fewer spectral lines are needed and accuracies of resulting FRFs and IRFs can be maintained. The relationship between an IRF from the proposed methodology and that from the least-squares method is shown. A new coherence function that can evaluate qualities of FRFs and IRFs from the proposed methodology in the frequency domain is used, from which meaningful coherence function values can be obtained even with response and excitation series of one sampling period. Based on the new coherence function, a fitting index is used to evaluate overall qualities of the FRFs and IRFs. The proposed methodology was numerically and experimentally applied to a two-degree-of-freedom mass-spring-damper system and an aluminum plate to estimate their FRFs, respectively. In the numerical example, FRFs from the proposed methodology agree well with the theoretical one; in the experimental example, a FRF from the proposed methodology with a random impact series agreed well with the benchmark one from a single impact test.

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Mansour, Hossein, Siamak Arzanpour, Hedayat Alghassi, and Mehdi Behzad. "Vibration Analysis of Setar for Extracting the Frequency Response Function (FRF)." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-13031.

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Extraction of the frequency response of a musical instrument is the first step to analyze its vibration characteristic. This research introduces the results of several experiments implemented on Setar, a Persian long-necked lute. Setar has a wooden, reflective sound-box which is highly coupled with its surrounding air. High level of damping in addition to the composite properties in Setar, consequences dissimilar frequency domain vibration patterns. At lower frequencies, the response exhibits very distinct modal behavior, while in higher frequencies an overall effect of close modes is demonstrated. In this paper different approaches are utilized to handle both frequency regimes; and their advantages and limitations are compared to each other. The utilized methods are swept sine excitation, impact hammer, and the traditional Tap-Tone method. The characteristics of force excitation on body are first investigated, and then the frequency response function of Setar’s body is extracted between the excitation force as the input and resultant sound and acceleration as the outputs. This study not only leads us to modifications in design of Setar, but also serves as a platform for numerical modeling.

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Zin, M. S. Mohd, M. N. Abdul Rani, M. A. Yunus, M. S. M. Sani, W. I. I. Wan Iskandar Mirza, and A. A. Mat Isa. "Frequency response function (FRF) based updating of a laser spot welded structure." In INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, MATERIALS AND APPLIED SCIENCE. Author(s), 2018. http://dx.doi.org/10.1063/1.5032017.

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ROLOFF, THOMAS, and MICHAEL SINAPIUS. "GENERATION OF MODE-SELECTIVE FREQUENCY RESPONSE FUNCTIONS FROM TEMPORALLY SAMPLED, BROADBAND AND MULTIMODAL GUIDED ULTRASONIC WAVE SIGNALS." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/36828.

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Structural health monitoring (SHM) systems for thin-walled, large-scale structures using guided ultrasonic waves (GUW) have recently been complemented by methods based on frequency response functions (FRF). These approaches enable the calculation of the structure’s response to any artificially generated excitation signal within the frequency range under investigation. This study presents a novel concept for extracting separate FRFs for the two fundamental modes from temporally sampled, broadband and multimodal GUW signals. In this work, quasi-ideal impulse response functions (IRF) are generated by retransforming multimodal broadband FRFs into the time domain. These FRFs are recorded energy-efficiently using sweep excitation and contain all occurring GUW components at the sensing position. The extended dispersion based frequency-domain intrinsic component decomposition (DBFICD) algorithm and the iterative frequency-domain envelopetracking filter (IFETF) algorithm are used to extract the corresponding signal components from the IRFs. Based on their different dispersive behaviour they can be assigned to the fundamental modes and combined to form the two respective IRFs. Transforming the latter back into the frequency domain results in two separate FRFs. This allows damage detection algorithms to estimate the structure’s mode-selective response to any selected signal within the frequency range under investigation. The method is validated experimentally by recording multimodal and single-mode FRFs in an aluminium plate with a mode-selective, two-sided piezoelectric actuator setup and a laser Doppler vibrometer. The estimated single-mode structural responses based on the FRFs extracted by the presented approach agree well with the actual responses to mode-selective excitation. The presented concept enables mode-selective FRF-based SHM systems to work with multimodal excitation, which reduces setup complexity and increases the application range by providing information for both fundamental modes over a wide frequency range.

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Hajdu, David, Tamas Insperger, and Gabor Stepan. "The Effect of Non-Symmetric FRF on Machining: A Case Study." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47037.

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Stability prediction of machining operations is often not reliable due to the inaccurate mechanical modeling. A major source of this inaccuracy is the uncertainties in the dynamic parameters of the machining center at different spindle speeds. The so-called tip-to-tip measurement is the fastest and most convenient method to determine the frequency response of the machine. This concept consists of the measurement of the tool tip’s frequency response function (FRF) usually in two perpendicular directions including cross terms. Although the cross FRFs are often neglected in practical applications, they may affect the system’s dynamics. In this paper, the stability diagrams are analyzed for milling operations in case of diagonal, symmetric and non-symmetric FRF matrices. First a time-domain model is derived by fitting a multiple-degrees-of-freedom model to the FRF matrix, then the semi-discretization method is used to determine stability diagrams. The results show that the omission of the non-symmetry of the FRF matrix may lead to inaccurate stability diagram.

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Reports on the topic "Frequency Response Function(FRF)"

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Tyack, Peter L. Cetaceans and Naval Sonar: Behavioral Response as a Function of Sonar Frequency. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada531164.

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Miller, Patrick. Cetaceans and Naval Sonar: Behavioral Response as a Function of Sonar Frequency. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada531190.

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Miller, Patrick. Cetaceans and Naval Sonar: Behavioral Response as a Function of Sonar Frequency. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada602551.

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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.

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George, Darin, and Christopher Grant. PR-015-15601-R01 Pulsation Effects on Ultrasonic Meters Phase II. Pipeline Research Council International, Inc. (PRCI), 2016. http://dx.doi.org/10.55274/r0010905.

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Transmission and storage operations frequently move natural gas using reciprocating compressors that may generate flow pulsations. Most measurement systems cannot accurately measure the flow rate of a pulsating gas stream, and the resulting errors can cause inaccurate gas volumes and accounting imbalances. A previous PRCI research project tested whether recent advances in ultrasonic meters may allow them to function without measurement error in pulsating flows. This project expanded on the previous work and tested similar ultrasonic meters to look for relationships between ultrasonic meter transducer sampling rates, the frequency and amplitudes of pulsations from reciprocating compressors, and meter accuracy. Diagnostics and flow data were collected from the meters and analyzed, and a useful relationship was found between the pulsation conditions and the meter measurement error. The findings were used to recommend a basis for installing ultrasonic meters in gas pipelines with varying pulsations. Additional testing evaluated a fast-response differential pressure transducer connected across a plate flow conditioner as a potential pulsation diagnostic tool.

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Conery, Ian, Nicholas Olsen, Shannon Brown, and Katherine Brodie. Quantifying coastal evolution and project performance at beaches by using satellite imagery. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48671.

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Accurately delineating the shoreline is crucial for tracking coastal evolution, community vulnerability, storm impacts, and for coastal management decision-making. However, existing shoreline measurement methods are often time-consuming and expensive and therefore, USACE Districts are often forced to narrow areas of interest or monitoring frequency, decreasing the likelihood of making data-driven management decisions, especially over regional scales. In the last decade, space-borne earth observations have captured images subweekly, and can potentially be used for shoreline monitoring. This work investigated the Python-based CoastSat toolkit and compared the shorelines derived from publicly available satellite imagery to ground truth surveys at 37 sites across the nation chosen in coordination with Districts. Mean horizontal errors ranged from 4.21 to 20.58 m with an overall mean of 11.32 m. Tidal corrections improved accuracies at 82% of sites. The CoastSat slope function was tested and there were negligible differences in shoreline accuracy when compared with user-defined slopes. Twenty-year satellite-derived trends generally align well with ground truth trends. The satellite approach identified quantifying storm impacts and recovery, beach nourishment equilibration, diffusion and decay, shoreline response to nearshore berm placements and decadal shoreline evolution at the evaluated district sites. Work is ongoing to transition to a user-friendly software tool.

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