A general mechanical model for |f|αspectral density random noise with special reference to flicker noise 1/|f|

1968 ◽  
Vol 56 (3) ◽  
pp. 251-258 ◽  
Author(s):  
D. Halford
Keyword(s):  
Spectral Density ◽  
Special Reference ◽  
Mechanical Model ◽  
Flicker Noise ◽  
Random Noise

Acoustic emission waveforms for damage monitoring in composite materials: Shifting in spectral density, entropy and wavelet packet transform

2021 ◽  
pp. 147592172110446
Author(s):  
Claudia Barile ◽  
Caterina Casavola ◽  
Giovanni Pappalettera ◽  
Vimalathithan Paramsamy Kannan
Keyword(s):  
Acoustic Emission ◽  
Spectral Density ◽  
Flicker Noise ◽  
Wavelet Packet ◽  
Research Work ◽  
Wavelet Packet Transform ◽  
Spectral Energy ◽  
Emission Data ◽  
Cfrp Composites ◽  
Damage Process

Signal-based acoustic emission data are analysed in this research work for identifying the damage modes in carbon fibre–reinforced plastic (CFRP) composites. The research work is divided into three parts: analysis of the shifting in the spectral density of acoustic waveforms, use of waveform entropy for selecting the best wavelet and implementation of wavelet packet transform (WPT) for identifying the damage process. The first two methodologies introduced in this research work are novel. Shifting in the spectral density is introduced in analogous to ‘flicker noise’ which is popular in the field of waveform processing. The entropy-based wavelet selection is refined by using quadratic Renyi’s entropy and comparing the spectral energy of the dominating frequency band of the acoustic waveforms. Based on the method, ‘dmey’ wavelet is selected for analysing the waveforms using WPT. The slope values of the shifting in spectral density coincide with the results obtained from WPT in characterising the damage modes. The methodologies introduced in this research work are promising. They serve the purpose of identifying the damage process effectively in the CFRP composites.

Approximation and the point of flicker-noise formation

2021 ◽  
Author(s):  
A.S. Matsaev
Keyword(s):  
Spectral Density ◽  
Flicker Noise ◽  
Electronic Devices ◽  
Electrical Circuit ◽  
Maximum Magnitude ◽  
Noise Characteristics ◽  
Exponential Increase ◽  
Accurate Definition ◽  
Definition Of ◽  
Flat Section

The article refers to the field of research of noise fluctuations or flicker noise in electronic amplifiers and is devoted to the exact definition of the magnitude and shape of the spectral density of flicker-noise. The 1/f approximation of flicker noise is analyzed and the problem of its non-constructiveness in analyzing the noise characteristics of electronic amplifiers is shown. To eliminate this problem, the mechanism of physical formation of the envelope, a form of spectral density flicker-noise is defined. The physics of flicker-noise is detailed by accurate definition of the place of its formation. An accurate definition of the maximum difference of the amplifier flickernoise on the flat section of noise characteristics is given, using an explanation of the physics of flicker noise. The mechanism and conditions of the exponential increase of flicker noise and its subsequent exponential desire for maximum magnitude are explained. A simple physical approximation is given to determine the processes of forming the envelope form of the spectral density of flickernoise. The physical understanding of the formation of spectral density of flicker-noise tension in the internal structure of the transistor with the participation of external circuits of the amplifier electrical circuit is detailed. The results of the study will help developers to solve many problems of building electronic devices and optimizing their characteristics at a qualitatively new level.

scholarly journals CORRELATION-SPECTRAL ANALYSIS OF THE TOPOGRAPHY OF ENGINEERING SURFACES AT THE NANOSCALE LEVEL

2021 ◽  
pp. 457-464
Author(s):  
Владимир Васильевич Измайлов ◽  
Марина Вячеславовна Новоселова
Keyword(s):  
Spectral Density ◽  
Normal Distribution ◽  
Random Process ◽  
Goodness Of Fit ◽  
Random Noise ◽  
Low Frequency ◽  
Surface Profile ◽  
Wide Band ◽  
Goodness Of Fit Test ◽  
Significance Level

Исследована нанотопография некоторых типичных технических поверхностей и экспериментально определены характеристики профиля наношероховатости как случайного процесса - автокорреляционная функция и спектральная плотность. Показано, что для исследованных поверхностей их профилограммы могут рассматриваться как реализации случайного стационарного нормального эргодического процесса. Проведена визуальная проверка нормальности процесса сравнением экспериментальных значений ординат профиля с теоретическими значениями, подчиняющимися нормальному распределению, а также сравнением полигона частот с теоретической функцией плотности вероятности нормального распределения. Количественное подтверждение нормальности процесса выполнено с применением критерия согласия Колмогорова. Показано, что на уровне значимости p = 0,05 гипотеза о нормальности случайного процесса (профиля наношероховатости поверхности) не противоречит экспериментальным результатам. Определены интервалы корреляции рассмотренных процессов. Вид автокорреляционных функций и величины интервалов корреляции говорят о случайном характере профиля поверхности: на интервале, равном одному - двум средним значениям шага неровностей профиля его ординаты становятся практически некоррелированными. Графики спектральных плотностей свидетельствуют о том, что профиль поверхности можно рассматривать как широкополосный случайный шум с преобладанием низкочастотных составляющих. The nanotopography of some typical technical surfaces is investigated and the characteristics of the nanoroughness profile as a random process are experimentally determined - the autocorrelation function and spectral density. It is shown that for the investigated surfaces, their profilograms can be considered as realizations of a random stationary normal ergodic process. A visual check of the process normality was carried out by comparing the experimental values of the profile ordinates with theoretical values obeying the normal distribution, as well as by comparing the frequency polygon with the theoretical probability density function of the normal distribution. Quantitative confirmation of the process normality was carried out using the Kolmogorov goodness-of-fit test. It is shown that at the significance level p = 0,05, the hypothesis about the normality of a random process (surface nanoroughness profile) does not contradict the experimental results. The correlation intervals of the considered processes are determined. The form of the autocorrelation functions and the values of the correlation intervals indicate the random nature of the surface profile: in the interval equal to one or two average values of the step of the irregularities of the profile, its ordinates become practically uncorrelated. Spectral density plots indicate that the surface profile can be considered as a wide-band random noise with a predominance of low-frequency components.

scholarly journals On the Whittle estimator for linear random noise spectral density parameter in continuous-time nonlinear regression models

2019 ◽  
Vol 23 (1) ◽  
pp. 129-169 ◽  
Author(s):  
A. V. Ivanov ◽  
N. N. Leonenko ◽  
I. V. Orlovskyi
Keyword(s):  
Spectral Density ◽  
Nonlinear Regression ◽  
Continuous Time ◽  
Regression Models ◽  
Random Noise ◽  
Sufficient Conditions ◽  
Density Parameter ◽  
Noise Spectral Density ◽  
Nonlinear Regression Models ◽  
Consistency And Asymptotic Normality

Abstract A continuous-time nonlinear regression model with Lévy-driven linear noise process is considered. Sufficient conditions of consistency and asymptotic normality of the Whittle estimator for the parameter of spectral density of the noise are obtained in the paper.

SPECTRAL FEATURES OF THE ALTERNATING CLUSTER PROCESS

2010 ◽  
Vol 09 (03) ◽  
pp. 301-312
Author(s):  
FERDINAND GRÜNEIS
Keyword(s):  
Spectral Density ◽  
Poisson Process ◽  
Power Spectral Density ◽  
Random Noise ◽  
Excess Noise ◽  
Spectral Features ◽  
Cluster Process ◽  
State Process ◽  
Power Spectral ◽  
The Impact

The alternating cluster process is a Poisson process the rate of which is modulated by an underlying two-state process. We derive the power spectral density of the alternating cluster process; besides random noise we obtain excess noise due to the impact of modulation.

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