A New Random Data Description and Its Use in Transferring Road Roughness to Vehicle Response

1974 ◽  
Vol 96 (2) ◽  
pp. 676-679 ◽  
Author(s):  
J. C. Wambold ◽  
W. H. Park ◽  
R. G. Vashlishan
Keyword(s):  
Spectral Density ◽  
Frequency Distribution ◽  
Descriptive Analysis ◽  
Joint Probability ◽  
Amplitude Distribution ◽  
Matrix Functions ◽  
Initial Portion ◽  
Power Spectral ◽  
Road Roughness ◽  
Cross Spectral Density

The initial portion of the paper discusses the more conventional method of obtaining a vehicle transfer function where phase and magnitude are determined by dividing the cross spectral density of the input/output by the power spectral density (PSD) of the input. The authors needed a more descriptive analysis (over PSD) and developed a new signal description called Amplitude Frequency Distribution (AFD); a discrete joint probability of amplitude and frequency with the advantage of retaining amplitude distribution as well as frequency distribution. A better understanding was obtained, and transfer matrix functions were developed using AFD.

A New Algorithm for Long-Term Estimation Based on AR Model

2014 ◽  
Vol 614 ◽  
pp. 440-443 ◽  
Author(s):  
Wen Jun Su ◽  
Hai Tao Chen
Keyword(s):  
Spectral Density ◽  
Poor Performance ◽  
Ar Model ◽  
Estimation Methods ◽  
Wiener Model ◽  
Training Set ◽  
Power Spectral ◽  
Cross Spectral Density ◽  
Term Data

Traditional estimation methods have poor performance for long-term data forecast. Using Wiener model to estimate, power spectral density of the input signal, and cross-spectral density of the input and output signals are needed, that are difficult to obtain. And the large amount of calculation is needed using Wiener model. Using AR model and Kalman model, estimated results tend to mean of the training set while the estimated distance increases. For these cases, a new algorithm for long-term estimation based on AR model, named sampling AR model, is presented. Grouping the training set and using a different group of the training set to estimate each value. Sampling AR model improves the accuracy of long-term estimation.

The Response of Rotating Machinery to External Random Vibration

1974 ◽  
Vol 96 (2) ◽  
pp. 477-489 ◽  
Author(s):  
J. M. Tessarzik ◽  
T. Chiang ◽  
R. H. Badgley
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
High Speed ◽  
Thrust Bearing ◽  
Dynamic Environment ◽  
Amplitude Distribution ◽  
Random Vibrations ◽  
Mass Model ◽  
Power Spectral ◽  
Rotor Axis

A high-speed turbogenerator employing gas-lubricated hydrodynamic journal and thrust bearings was subjected to external random vibrations for the purpose of assessing bearing performance in a dynamic environment. The pivoted-pad type journal bearings and the step-sector thrust bearing supported a turbine-driven rotor weighing approximately twenty-one pounds at a nominal operating speed of 36,000 rpm. The response amplitudes of both the rigid-supported and flexible-supported bearing pads, the gimballed thrust bearing, and the rotor relative to the machine casing were measured with capacitance type displacement probes. Random vibrations were applied by means of a large electrodynamic shaker at input levels ranging between 0.5 g (rms) and 1.5 g (rms). Vibrations were applied both along and perpendicular to the rotor axis. Response measurements were analyzed for amplitude distribution and power spectral density. Experimental results compare well with calculations of amplitude power spectral density made for the case where the vibrations were applied along the rotor axis. In this case, the rotor-bearing system was treated as a linear, three-mass model.

scholarly journals Stochastic bursting in networks of excitable units with delayed coupling

2021 ◽  
Author(s):  
Chunming Zheng ◽  
Arkady Pikovsky
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Directed Tree ◽  
Basic Assumptions ◽  
Delayed Coupling ◽  
Power Spectral ◽  
Delay Feedbacks ◽  
Cross Spectral Density ◽  
Tree Lattice ◽  
The One

AbstractWe investigate the phenomenon of stochastic bursting in a noisy excitable unit with multiple weak delay feedbacks, by virtue of a directed tree lattice model. We find statistical properties of the appearing sequence of spikes and expressions for the power spectral density. This simple model is extended to a network of three units with delayed coupling of a star type. We find the power spectral density of each unit and the cross-spectral density between any two units. The basic assumptions behind the analytical approach are the separation of timescales, allowing for a description of the spike train as a point process, and weakness of coupling, allowing for a representation of the action of overlapped spikes via the sum of the one-spike excitation probabilities.

Improved Methods for the Fast Fourier Transform (FFT) Calculation of the Frequency Response Function

1982 ◽  
Vol 104 (2) ◽  
pp. 277-279 ◽  
Author(s):  
L. D. Mitchell
Keyword(s):  
Spectral Density ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Coherence Function ◽  
Input And Output ◽  
At Resonance ◽  
Power Spectral ◽  
Cross Spectral Density ◽  
Improved Methods

Most FFT machines today compute an estimate of the frequency response function, H(f), by the cross-spectral density of input to output divided by the power spectral density of the input. This estimator is contaminated by noise at the input. One uses the coherence function to help measure the level of contamination. However, the coherence function detects, among other things, noise at both the input and output. Several alternate methods are proposed for the computation of the frequency response function. One generates more accurate estimates at resonance, one has half or less of the contamination contained in the present methods, and the last one proposes to eliminate the biasing contamination all together.

scholarly journals Experimental Study on Characteristics of Short Wave Irregularity in Urban Rail Transit

2020 ◽  
Author(s):  
Jian Fang ◽  
Wenwen Zheng ◽  
Xiaoyan Lei
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Amplitude Distribution ◽  
Short Wave ◽  
Point Of View ◽  
Rail Transit ◽  
Track Structure ◽  
Power Spectral ◽  
Surface Irregularities ◽  
Maximum Entropy Spectrum

Based on the measured irregularity data of Shanghai rail transit 11# line, firstly from the angle of time domain the amplitude stability and amplitude distribution characteristics of the rail surface short wave irregularity whose wavelengths are in the range of 0.01 ∼ 1 m are analyzed. Secondly from the point of view of frequency domain by using the maximum entropy spectrum method the short wave power spectral density is estimated. Then the power spectral density curves are compared with the short spectrum of Wang Lan and Sato and the different track structure effects on the states of the rail surface irregularities are also analyzed. The research show that the amplitude distribution of track surface short wave irregularity is close to the normal distribution. And the maximum amplitudes of some sections in Jiading Xincheng – Malu and Nanxiang – Taopu saemaul undong exceed 2.0mm. In the section of Liziyuan-Shanghai West Railway Station, the power spectral density curves of track structure with the supporting block, DTIII-2 type fasteners and with the conventional integral track bed are also similar to that of Sato spectrum. And it is obviously superior to that of other track structures in this section.

Fuzzy Modeling of Multi-Degree-of-Freedom Power Spectral Density Systems

2009 ◽  
Vol 2 (1) ◽  
pp. 40-47
Author(s):  
Montasser Tahat ◽  
Hussien Al-Wedyan ◽  
Kudret Demirli ◽  
Saad Mutasher
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Fuzzy Modeling ◽  
Degree Of Freedom ◽  
Power Spectral
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