scholarly journals Frequency response areas of neurons in the mouse inferior colliculus. III. Time-domain responses: Constancy, dynamics, and precision in relation to spectral resolution, and perception in the time domain

PLoS ONE ◽  
2020 ◽  
Vol 15 (10) ◽  
pp. e0240853
Author(s):  
Marina A. Egorova ◽  
Alexander G. Akimov ◽  
Gleb D. Khorunzhii ◽  
Günter Ehret
Keyword(s):  
Frequency Response ◽  
Inferior Colliculus ◽  
Spectral Resolution ◽  
Time Domain ◽  
The Time Domain

scholarly journals Time-Domain Substructure Transient Vibration Transfer Path Analysis Based on Time-Varying Frequency Response Functions under Operational Excitations

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Rong He ◽  
Hong Zhou
Keyword(s):  
Path Analysis ◽  
Frequency Response ◽  
Time Domain ◽  
Time Varying ◽  
Response Functions ◽  
Transient Vibration ◽  
Transfer Path ◽  
Time Varying Systems ◽  
Transfer Path Analysis ◽  
The Time Domain

The time-domain substructure inverse matrix method has become a popular method to detect and diagnose problems regarding vehicle noise, vibration, and harshness, especially for those impulse excitations caused by roads. However, owning to its reliance on frequency response functions (FRFs), the approach is effective only for time-invariable linear or weak nonlinear systems. This limitation prevents this method from being applied to a typical vehicle suspension substructure, which shows different nonlinear characteristics under different wheel transient loads. In this study, operational excitation was considered as a key factor and applied to calculate dynamic time-varying FRFs to perform accurate time-domain transient vibration transfer path analysis (TPA). The core idea of this novel method is to divide whole coupled substructural relationships into two parts: one involved time-invariable components; normal FRFs could be obtained through tests directly. The other involved numerical computations of the time-domain operational loads matrix and FRFs matrix in static conditions. This method focused on determining dynamic FRFs affected by operational loads, especially the severe transient ones; these loads are difficult to be considered in other classical TPA approaches, such as operational path analysis with exogenous inputs (OPAX) and operational transfer path analysis (OTPA). Experimental results showed that this new approach could overcome the limitations of the traditional time-domain substructure TPA in terms of its strict requirements within time-invariable systems. This is because in the new method, time-varying FRFs were calculated and used, which could make the FRFs at the system level directly adapt to time-varying systems from time to time. In summary, the modified method extends TPA objects studied in time-invariable systems to time-varying systems and, thus, makes a methodology and application innovation compared to traditional the time-domain substructure TPA.

On the Dynamics of Large Systems With Localized Nonlinearities

1988 ◽  
Vol 55 (4) ◽  
pp. 946-951 ◽  
Author(s):  
P. Hagedorn ◽  
W. Schramm
Keyword(s):  
Integral Equation ◽  
Dynamical Systems ◽  
Nonlinear Systems ◽  
Dynamic System ◽  
Frequency Response ◽  
Time Domain ◽  
Numerical Procedure ◽  
Linear Subsystem ◽  
Large Systems ◽  
The Time Domain

In this paper, a certain class of dynamical systems is discussed, which can be decomposed into a large linear subsystem and one or more nonlinear subsystems. For this class of nonlinear systems the dynamic behavior is represented in the time domain by means of an integral equation. A simple numerical procedure for the solution of this integral equation is given. It is also shown how the decomposition of the system can be used in measuring the frequency response of the large linear subsystem, without actually separating it from the nonlinear subsystems. An elastostatic analogy is used to illustrate the ideas and a numerical example is given for a dynamic system.

scholarly journals Retrieval of temperature, H<sub>2</sub>O, O<sub>3</sub>, HNO<sub>3</sub>, CH<sub>4</sub>, N<sub>2</sub>O, ClONO<sub>2</sub> and ClO from MIPAS reduced resolution nominal mode limb emission measurements

2009 ◽  
Vol 2 (1) ◽  
pp. 181-236 ◽  
Author(s):  
T. von Clarmann ◽  
M. Höpfner ◽  
S. Kellmann ◽  
A. Linden ◽  
S. Chauhan ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Time Domain ◽  
Lower Stratosphere ◽  
Temperature Gradients ◽  
Measurement Noise ◽  
High Spectral Resolution ◽  
The Time Domain ◽  
Along Track ◽  
Horizontal Temperature Gradients ◽  
Nominal Mode

Abstract. Retrievals of temperature, H2O, O3, HNO3, CH4, N2O, ClONO2 and ClO from MIPAS reduced spectral resolution nominal mode limb emission measurements outperform retrievals from respective high spectral resolution measurements both in terms of altitude resolution and precision. The estimated precision (including measurement noise and propagation of uncertain parameters randomly varying in the time domain) and altitude resolution are typically 0.5–1.4 K and 3 km for temperature between 10 and 50 km altitude, and 5–6%, 2–4 km for H2O below 30 km altitude, 4–5%, 3–4.5 km for O3 between 15 and 40 km altitude, 3–8%, 3–5 km for HNO3 between 10 and 35 km altitude, 5–8%, 3 km for CH4 between 15 and 35 km altitude, 5–10%, 3 km for N2O between 15 and 35 km altitude, 8–14%, 2.5–9 km for ClONO2 below 40 km, and larger than 35%, 5–6 km for ClO in the lower stratosphere. As for the high spectral resolution measurements, the reduced spectral resolution nominal mode horizontal sampling (410 km) is coarser than the horizontal smoothing (often below 400 km), depending on species, altitude and number of tangent altitudes actually used for the retrieval. Thus, aliasing might be an issue even in the along-track domain. In order to prevent failure of convergence, it was found to be essential to consider horizontal temperature gradients during the retrieval.

Development of High Frequency Virtual Thermocouples

2017 ◽  
Author(s):  
James Braun ◽  
Shengqi Lu ◽  
Guillermo Paniagua
Keyword(s):  
Frequency Response ◽  
Time Domain ◽  
High Frequency ◽  
Conjugate Heat Transfer ◽  
Numerical Procedure ◽  
Navier Stokes ◽  
Digital Compensation ◽  
Fine Wire ◽  
The Time Domain ◽  
Thermocouple Probe

This paper presents a numerical procedure to enhance the frequency response of temperature probes equipped with two thermocouple junctions of different diameter. The output of the two thermocouples exposed to the same flow transient can be used to predict the output of a virtual smaller thermocouple, which cannot be physically realized. The approach is demonstrated numerically, with the aid of conjugate heat transfer simulations performed with 3D Unsteady Reynolds Averaged Navier-Stokes. The dual junction thermocouple with wire diameters of 50 μm, 25 μm were exposed to several inlet temperatures and pressures to analyze the overall recovery factor. Then multiple unsteady tests were performed. The analysis of those transient tests was used to determine the transfer function in the time domain between the two wires and to perform a digital compensation to predict the performance of a much thinner wire thermocouple. This method was assessed by recovering the theoretical response of the 12.5 μm thermocouple with our dual-junction thermocouple probe for several pressures and wall temperatures. Finally, the procedure was applied to a virtual fine wire thermocouple of 6 μm and a frequency response around 700 Hz.

Efficient 3D frequency response modeling with spectral accuracy by the rapid expansion method

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. T117-T123 ◽  
Author(s):  
Chunlei Chu ◽  
Paul L. Stoffa
Keyword(s):  
Fourier Transform ◽  
Frequency Response ◽  
Time Domain ◽  
Wave Equations ◽  
Time Integration ◽  
Expansion Method ◽  
Rapid Expansion ◽  
The Fourier Transform ◽  
The Time Domain ◽  
Response Modeling

Frequency responses of seismic wave propagation can be obtained either by directly solving the frequency domain wave equations or by transforming the time domain wavefields using the Fourier transform. The former approach requires solving systems of linear equations, which becomes progressively difficult to tackle for larger scale models and for higher frequency components. On the contrary, the latter approach can be efficiently implemented using explicit time integration methods in conjunction with running summations as the computation progresses. Commonly used explicit time integration methods correspond to the truncated Taylor series approximations that can cause significant errors for large time steps. The rapid expansion method (REM) uses the Chebyshev expansion and offers an optimal solution to the second-order-in-time wave equations. When applying the Fourier transform to the time domain wavefield solution computed by the REM, we can derive a frequency response modeling formula that has the same form as the original time domain REM equation but with different summation coefficients. In particular, the summation coefficients for the frequency response modeling formula corresponds to the Fourier transform of those for the time domain modeling equation. As a result, we can directly compute frequency responses from the Chebyshev expansion polynomials rather than the time domain wavefield snapshots as do other time domain frequency response modeling methods. When combined with the pseudospectral method in space, this new frequency response modeling method can produce spectrally accurate results with high efficiency.

The Spine of the Root Locus for the Viscous Damper

1982 ◽  
Vol 104 (2) ◽  
pp. 466-475
Author(s):  
D. Stern
Keyword(s):  
Frequency Response ◽  
Frequency Domain ◽  
Time Domain ◽  
Viscous Damper ◽  
Vibration Isolator ◽  
Root Locus ◽  
New Approach ◽  
Single Mass ◽  
The Time Domain

At present the optimization of a vibration isolator is performed in either the time domain or the frequency domain. A new approach, for optimization in the S-plane, is outlined and performed for the viscous damper. Optimization of the viscous damper in the S-plane results in a line that is defined as the spine of the root locus. Transformations are required between the S-plane and either the frequency domain or the time domain, therefore, time and frequency response plots are included for the spine damper. Two examples are used to illustrate the application of the root locus for single mass and multi-mass models.

scholarly journals The Researches on Damage Detection Method for Truss Structures

2018 ◽  
Vol 38 ◽  
pp. 03030
Author(s):  
Meng Hong Wang ◽  
Xiao Nan Cao
Keyword(s):  
Numerical Simulation ◽  
Frequency Response ◽  
Response Function ◽  
Time Domain ◽  
Experimental Analysis ◽  
Frequency Response Function ◽  
Principal Component ◽  
Truss Structures ◽  
Time Domain Signal ◽  
The Time Domain

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

scholarly journals Retrieval of temperature, H<sub>2</sub>O, O<sub>3</sub>, HNO<sub>3</sub>, CH<sub>4</sub>, N<sub>2</sub>O, ClONO<sub>2</sub> and ClO from MIPAS reduced resolution nominal mode limb emission measurements

2009 ◽  
Vol 2 (1) ◽  
pp. 159-175 ◽  
Author(s):  
T. von Clarmann ◽  
M. Höpfner ◽  
S. Kellmann ◽  
A. Linden ◽  
S. Chauhan ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Time Domain ◽  
Lower Stratosphere ◽  
Temperature Gradients ◽  
Measurement Noise ◽  
Uncertain Parameters ◽  
The Time Domain ◽  
Along Track ◽  
Horizontal Temperature Gradients ◽  
Nominal Mode

Abstract. Retrievals of temperature, H2O, O3, HNO3, CH4, N2O, ClONO2 and ClO from MIPAS reduced spectral resolution nominal mode limb emission measurements outperform retrievals from respective full spectral resolution measurements both in terms of altitude resolution and precision. The estimated precision (including measurement noise and propagation of uncertain parameters randomly varying in the time domain) and altitude resolution are typically 0.5–1.4 K and 2–3.5 km for temperature between 10 and 50 km altitude, and 5–6%, 2–4 km for H2O below 30 km altitude, 4–5%, 2.5–4.5 km for O3 between 15 and 40 km altitude, 3–8%, 3–5 km for HNO3 between 10 and 35 km altitude, 5–8%, 2–3 km for CH4 between 15 and 35 km altitude, 5–10%, 3 km for N2O between 15 and 35 km altitude, 8–14%, 2.5–9 km for ClONO2 below 40 km, and larger than 35%, 3–7 km for ClO in the lower stratosphere. As for the full spectral resolution measurements, the reduced spectral resolution nominal mode horizontal sampling (410 km) is coarser than the horizontal smoothing (often below 400 km), depending on species, altitude and number of tangent altitudes actually used for the retrieval. Thus, aliasing might be an issue even in the along-track domain. In order to prevent failure of convergence, it was found to be essential to consider horizontal temperature gradients during the retrieval.

scholarly journals Filters, Waves and Spectra

Econometrics ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 35 ◽  
Author(s):  
D. Pollock
Keyword(s):  
Frequency Response ◽  
Frequency Domain ◽  
Time Domain ◽  
Econometric Analysis ◽  
Frequency Domain Methods ◽  
The Time Domain ◽  
Filtering Techniques

Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its emphasis in the frequency domain; and it shows how the frequency-domain methods can be adapted to cater to short trended sequences. Working in the frequency domain allows an unrestricted choice to be made of the frequency response of a filter. It also requires that the data should be free of trends. Methods for extracting the trends prior to filtering and for restoring them thereafter are described.

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