The specification of oscillator characteristics from measurements made in the frequency domain.
Cross correlation measurements of oscillator frequency stability and thermal noise and application to atomic hydrogen maser
OSCILLATOR↗
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Overview of multi-input frequency domain modal testing methods with an emphasis on sine testing
An overview of the current state of the art multiple-input, multiple-output modal testing technology is discussed. A very brief review of the current time domain methods is given. A detailed review of frequency and spatial domain methods is presented with an emphasis on sine testing.
Rost, Robert W.↗
Modal model reduction or model reduction of large space structures in frequency domain
Large space structures are characterized by a large number of modes, grouped frequencies, and small inherent damping. Model reduction techniques in time domain may not be effective due to small damping. The model truncation method is generally used. This method can not solve the problem of grouped frequencies, and will lose all the information about the higher order modes. A new method developed in this paper, which tries to minimize the error of interested transfer functions, makes use of all the information of the original system, and achieves improvement not only from a smaller error of transfer functions but also from better frequency distribution.
Mifang, Ruan↗
Unsteady aerodynamics in time and frequency domains for finite time arbitrary motion of rotary wings in hover and forward flight
Several incompressible finite-time arbitrary-motion airfoil theories suitable for coupled flap-lag-torsional aeroelastic analysis of helicopter rotors in hover and forward flight are derived. These theories include generalized Greenberg's theory, generalized Loewy's theory, and a staggered cascade theory. The generalized Greenberg's and staggered cascade theories were derived directly in Laplace domain considering the finite length of the wake and using operational methods. The load expressions are presented in Laplace, frequency, and time domains. Approximate time domain loads for the various generalized theories, discussed in the paper, are obtained by developing finite state models using the Pade approximant of the appropriate lift deficiency functions. Three different methods for constructing Pade approximants of the lift deficiency functions were considered and the more flexible one was used. Pade approximants of Loewy's lift deficiency function, for various wake spacing and radial location parameters of a helicopter typical rotor blade section, are presented.
Dinyavari, M. A. H.↗
Characterization of microstrip discontinuities in the time and frequency domains
A number of impedance transitions and interconnections to a microstrip were designed and investigated. The double-step discontinuity on a microstrip was studied in detail, and a procedure was developed to design these structures. Their response was determined by making measurements in both the frequency and time domains in a consistent and repeatable manner. The time-domain presentation of the data was the most useful feature of the measuring system. All undesirable signal components were filtered out through the use of gating functions. Theoretically computed results were verified experimentally.
Feldman, U.↗
Optimal System Realization in Frequency Domain
Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation begins with a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. An approach is introduced to fine-tune the model using non-linear programming methods to minimize the desired cost function. The method deals with the model in the real Schur or modal form and reassigns a subset of system poles using a nonlinear optimizer. At every optimization step, the input and output influence matrices are refined through least-squares procedures. The proposed approaches are used to identify an analytical model for a NASA testbed from experimental data.
Juang, Jer-Nan↗
Frequency domain laser velocimeter signal processor
A laser velocimeter signal processor for measuring the signal frequency within a signal burst. The input signal is converted to digital by an ADC 16 and then shifted into shift registers 30 and 31. An automatic gain circuit 15 controls the gain of the input signal. A signal integration circuit 32 determines when a signal burst has been captured by the shift registers and then transfers the contents of the registers to data latches 33 and 34. The data in data latches 33 and 34 is processed by digital bandpass filters 57-63, square law detectors 64-70, burst counters 71-77 and signal processor 78 to determine the frequency of the signal within the captured signal burst.
James F Meyers↗
Optimal Frequency-Domain System Realization with Weighting
Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation uses a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. Three different approaches are introduced to fine-tune the model using nonlinear programming methods to minimize the desired cost function. The first method uses an eigenvalue assignment technique to reassign a subset of system poles to improve the identified model. The second method deals with the model in the real Schur or modal form, reassigns a subset of system poles, and adjusts the columns (rows) of the input (output) influence matrix using a nonlinear optimizer. The third method also optimizes a subset of poles, but the input and output influence matrices are refined at every optimization step through least-squares procedures.
Juang, Jer-Nan↗
Frequency Domain Identification Toolbox
This report documents software written in MATLAB programming language for performing identification of systems from frequency response functions. MATLAB is a commercial software environment which allows easy manipulation of data matrices and provides other intrinsic matrix functions capabilities. Algorithms programmed in this collection of subroutines have been documented elsewhere but all references are provided in this document. A main feature of this software is the use of matrix fraction descriptions and system realization theory to identify state space models directly from test data. All subroutines have templates for the user to use as guidelines.
Horta, Lucas G.↗
Frequency domain system identification methods - Matrix fraction description approach
This paper presents the use of matrix fraction descriptions for least-squares curve fitting of the frequency spectra to compute two matrix polynomials. The matrix polynomials are intermediate step to obtain a linearized representation of the experimental transfer function. Two approaches are presented: first, the matrix polynomials are identified using an estimated transfer function; second, the matrix polynomials are identified directly from the cross/auto spectra of the input and output signals. A set of Markov parameters are computed from the polynomials and subsequently realization theory is used to recover a minimum order state space model. Unevenly spaced frequency response functions may be used. Results from a simple numerical example and an experiment are discussed to highlight some of the important aspect of the algorithm.
Horta, Luca G.↗
Method and Apparatus of Multiplexing and Acquiring Data from Multiple Optical Fibers Using a Single Data Channel of an Optical Frequency-Domain Reflectometry (OFDR) System
A method and system for multiplexing a network of parallel fiber Bragg grating (FBG) sensor-fibers to a single acquisition channel of a closed Michelson interferometer system via a fiber splitter by distinguishing each branch of fiber sensors in the spatial domain. On each branch of the splitter, the fibers have a specific pre-determined length, effectively separating each branch of fiber sensors spatially. In the spatial domain the fiber branches are seen as part of one acquisition channel on the interrogation system. However, the FBG-reference arm beat frequency information for each fiber is retained. Since the beat frequency is generated between the reference arm, the effective fiber length of each successive branch includes the entire length of the preceding branch. The multiple branches are seen as one fiber having three segments where the segments can be resolved. This greatly simplifies optical, electronic and computational complexity, and is especially suited for use in multiplexed or branched OFS networks for SHM of large and/or distributed structures which need a lot of measurement points.
Parker, Jr., Allen R↗
Frequency-Domain Identification With Composite Curve Fitting
Improved method of parameter identification based on decomposing single wide-band model into two or more component systems in parallel. Each component model predominates in specific frequency range. Wide-band mathematical model of system identified as two narrow-band models: one containing most of information on high-frequency components of dynamics, and one containing most of information on low-frequency components. Applicable to diverse systems, including vibrating structures, electronic circuits, and control systems.
Bayard, David S.↗
Frequency domain stability criteria. ii.
Approach for generating stability criteria, applying odd function and power law nonlinearity
FREQUENCY CONTROL↗
A look at motion in the frequency domain
A moving image can be specified by a contrast distribution, c(x,y,t), over the dimensions of space x,y, and time t. Alternatively, it can be specified by the distribution C(u,v,w) over spatial frequency u,v and temporal frequency w. The frequency representation of a moving image is shown to have a characteristic form. This permits two useful observations. The first is that the apparent smoothness of time-sampled moving images (apparent motion) can be explained by the filtering action of the human visual system. This leads to the following formula for the required update rate for time-sampled displays. W(c)=W(l)+ru(l) where w(c) is the required update rate in Hz, W(l) is the limit of human temporal resolution in Hz, r is the velocity of the moving image in degrees/sec, and u(l) is the limit of human spatial resolution in cycles/deg. The second observation is that it is possible to construct a linear sensor that responds to images moving in a particular direction. The sensor is derived and its properties are discussed.
Watson, A. B.↗
Frequency domain analysis of the random loading of cracked panels
The primary effort concerned the development of analytical methods for the accurate prediction of the effect of random loading on a panel with a crack. Of particular concern was the influence of frequency on the stress intensity factor behavior. Many modern structures, such as those found in advanced aircraft, are lightweight and susceptible to critical vibrations, and consequently dynamic response plays a very important role in their analysis. The presence of flaws and cracks can have catastrophic consequences. The stress intensity factor, K, emerges as a very significant parameter that characterizes the crack behavior. In analyzing the dynamic response of panels that contain cracks, the finite element method is used, but because this type of problem is inherently computationally intensive, a number of ways of calculating K more efficiently are explored.
Doyle, James F.↗
Frequency domain laser velocimeter signal processor
A new laser velocimeter signal processor is described which uses advanced digital circuitry to configure itself to maximize measurement accuracy based on the characteristics of the input signals. This processor maintains measurement independence from burst to burst and yields measurement accuracies better than 0.2 percent for signal frequencies up to 100 MHz.
Meyers, James F.↗
Remote sensing of sea ice thickness by a combined spatial and frequency domain interferometer : formulations, instrument design & development
The thickness of Arctic sea ice plays a critical role in Earth's climate and ocean circulation. An accurate measurement of this parameter on synoptic scales at regular intervals would enable characterization of this important component for the understanding of ocean circulation and the global heat balance. Presented in this paper is a low frequency VHF interferometer technique and associated radar instrument design to measure sea ice thickness based on the use of backscatter correlation functions. The sea ice medium is represented as a multi-layered medium consisting of snow, seaice and sea water, with the interfaces between layers characterized as rough surfaces. This technique utilizes the correlation of two radar waves of different frequencies and incident and observation angles, scattered from the sea ice medium. The correlation functions relate information about the sea ice thickness. Inversion techniques such as the genetic algorithm, gradient descent, and least square methods, are used to derive sea ice thickness from the phase information related by the correlation functions.
remote sensing↗
Frequency-Domain Signal Processor For Laser Velocimeter
Dynamic range and accuracy increased. New signal processor for laser-velocimeter (LV) applications overcomes major limitations of present signal processors. System requires no input-signal conditioning other than that provided by amplifiers; it operates in instantaneous mode at signal levels from bursts containing as few as 150 photons down to photon-resolved regime in averaging mode. Digital value of signal-burst frequency sent to external computer system for conversion to value of absolute frequency. Residual turbulence intensity 0.2 percent, with little dependence on signal-to-noise ratio.
Meyers, James F.↗