Radiotechnical Signal Processing Techniques for Polymer Materials Structure Analysis

2017 ◽  
Vol 381 ◽  
pp. 59-63 ◽  
Author(s):  
Vladimir Klimentievitch Kachanov ◽  
Igor Vacheslavovitch Sokolov ◽  
Serguei Vladimirovitch Lebedev ◽  
Vladimir Vladimirovitch Pervushin
Keyword(s):  
Structure Analysis ◽  
Polymer Materials ◽  
Material Structure ◽  
New Approach ◽  
Time Frequency ◽  
Structure Assessment ◽  
Processing Techniques ◽  
Short Time ◽  
Signal Processing Techniques ◽  
Structure Inhomogeneity

Paper describes new approach to material structure analysis by means of ultrasound probing. Short-time Fourier transform and time-frequency analysis used to determine structure inhomogeneity present and perform structure condition assessment. Experimental results show possibilities of polymer materials structure assessment.

scholarly journals A New Approach for the Characterization of Nonstationary Oscillators Using the Wigner-Ville Distribution

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Chagai Levy ◽  
Monika Pinchas ◽  
Yosef Pinhasi
Keyword(s):  
New Approach ◽  
Time Frequency ◽  
Physical Mechanisms ◽  
Phase Errors ◽  
Amplitude Fluctuations ◽  
Time Invariance ◽  
Processing Techniques ◽  
Oscillator Stability ◽  
Signal Processing Techniques

Oscillators and clocks are affected by physical mechanisms causing amplitude fluctuations, phase noise, and frequency instabilities. The physical properties of the elements composing the oscillator as well as external environmental conditions play a role in the characteristics of the oscillatory signal produced by the device. Such instabilities demonstrate frequency drifts and modulation and spectrum broadening and are observed to be nonstationary processes in nature. Most of tools which are being used to measure and characterize oscillator stability are based on signal processing techniques, assuming time invariance during a temporal window, during which the signal is assumed to be stationary. This paper proposes a new time-frequency metric for the characterization of frequency sources. Our technique is based on the Wigner-Ville distribution, which extends the spectral measures to consist of the temporal nonstationary behavior of the processes affecting the accuracy of the clock. We demonstrate the use of the technique in the characterization of phase errors, frequency offsets, and frequency drift of oscillators.

scholarly journals Multi-Domain Communication Systems and Networks: A Tensor-Based Approach

Network ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 50-74
Author(s):  
Divyanshu Pandey ◽  
Adithya Venugopal ◽  
Harry Leib
Keyword(s):  
Communication Systems ◽  
Physical Layer ◽  
Mathematical Framework ◽  
Trade Off ◽  
Information Theoretic ◽  
Time Frequency ◽  
Tensor Formulation ◽  
Processing Techniques ◽  
Multiple Domains ◽  
Signal Processing Techniques

Most modern communication systems, such as those intended for deployment in IoT applications or 5G and beyond networks, utilize multiple domains for transmission and reception at the physical layer. Depending on the application, these domains can include space, time, frequency, users, code sequences, and transmission media, to name a few. As such, the design criteria of future communication systems must be cognizant of the opportunities and the challenges that exist in exploiting the multi-domain nature of the signals and systems involved for information transmission. Focussing on the Physical Layer, this paper presents a novel mathematical framework using tensors, to represent, design, and analyze multi-domain systems. Various domains can be integrated into the transceiver design scheme using tensors. Tools from multi-linear algebra can be used to develop simultaneous signal processing techniques across all the domains. In particular, we present tensor partial response signaling (TPRS) which allows the introduction of controlled interference within elements of a domain and also across domains. We develop the TPRS system using the tensor contracted convolution to generate a multi-domain signal with desired spectral and cross-spectral properties across domains. In addition, by studying the information theoretic properties of the multi-domain tensor channel, we present the trade-off between different domains that can be harnessed using this framework. Numerical examples for capacity and mean square error are presented to highlight the domain trade-off revealed by the tensor formulation. Furthermore, an application of the tensor framework to MIMO Generalized Frequency Division Multiplexing (GFDM) is also presented.

scholarly journals Identification of Grain Oriented SiFe Steels Based on Imaging the Instantaneous Dynamics of Magnetic Barkhausen Noise Using Short-Time Fourier Transform and Deep Convolutional Neural Network

Materials ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 118
Author(s):  
Michal Maciusowicz ◽  
Grzegorz Psuj ◽  
Paweł Kochmański
Keyword(s):  
Fourier Transform ◽  
Barkhausen Noise ◽  
Magnetic Barkhausen Noise ◽  
Short Time Fourier Transform ◽  
Deep Convolutional Neural Networks ◽  
Electrical Steels ◽  
New Approach ◽  
Time Frequency ◽  
Short Time

This paper presents a new approach to the extraction and analysis of information contained in magnetic Barkhausen noise (MBN) for evaluation of grain oriented (GO) electrical steels. The proposed methodology for MBN analysis is based on the combination of the Short-Time Fourier Transform for the observation of the instantaneous dynamics of the phenomenon and deep convolutional neural networks (DCNN) for the extraction of hidden information and building the knowledge. The use of DCNN makes it possible to find even complex and convoluted rules of the Barkhausen phenomenon course, difficult to determine based solely on the selected features of MBN signals. During the tests, several samples made of conventional and high permeability GO steels were tested at different angles between the rolling and transverse directions. The influences of the angular resolution and the proposed additional prediction update algorithm on the DCNN accuracy were investigated, obtaining the highest gain for the angle of 3.6°, for which the overall accuracy exceeded 80%. The obtained results indicate that the proposed new solution combining time–frequency analysis and DCNN for the quantification of information from MBN having stochastic nature may be a very effective tool in the characterization of the magnetic materials.

scholarly journals Characterization of Nonstationary Phase Noise Using the Wigner–Ville Distribution

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Chagai Levy ◽  
Monika Pinchas ◽  
Yosef Pinhasi
Keyword(s):  
Phase Noise ◽  
Nonstationary Processes ◽  
Time Frequency ◽  
Physical Mechanisms ◽  
Amplitude Fluctuations ◽  
Time Invariance ◽  
Processing Techniques ◽  
Oscillator Stability ◽  
Signal Processing Techniques

Oscillators and atomic clocks, as well as lasers and masers, are affected by physical mechanisms causing amplitude fluctuations, phase noise, and frequency instabilities. The physical properties of the elements composing the oscillator as well as external environmental conditions play a role in the coherence of the oscillatory signal produced by the device. Such instabilities demonstrate frequency drifts, modulation, and spectrum broadening and are observed to be nonstationary processes in nature. Most of the tools which are being used to measure and characterize oscillator stability are based on signal processing techniques, assuming time invariance within a temporal window, during which the signal is assumed to be stationary. This letter proposes a new time-frequency approach for the characterization of frequency sources. Our technique is based on the Wigner–Ville time-frequency distribution, which extends the spectral measures to include the temporal nonstationary behavior of the processes affecting the coherence of the oscillator and the accuracy of the clock. We demonstrate the use of the technique in the characterization of nonstationary phase noise in oscillators.

Vibration Analyses of the Bearing Using the Time Frequency Domain Technique

2014 ◽  
Vol 592-594 ◽  
pp. 2091-2096
Author(s):  
H.N. Sharma ◽  
Santosh Verma
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Energy Levels ◽  
Vibration Signal ◽  
Test Rig ◽  
Time Frequency ◽  
Bearing Vibration ◽  
Processing Techniques ◽  
Signal Processing Techniques ◽  
Bearing System

This work employs the wavelet transform for reading the fault diagnosis in a rotor-bearing system. Initiating with literature review with some relevant studies of bearing fault and the signal processing techniques used followed by the theory of wavelet transform. A bearing test rig is shown which is used for implementing wavelet transform. A faulty bearing vibration signal is measured from the test rig; thereafter the fast Fourier transform is plotted to show the critical frequencies, bearing characteristics frequency and its harmonics. A scalogram showing the energy levels of signal is plotted as result. Faulty signal is analyzed using wavelet transform.

Simulating and Detecting a Vibration-Induced Failure in an Air-Handling Assembly

2001 ◽  
Author(s):  
C. Gavin McGee ◽  
Douglas E. Adams
Keyword(s):  
Condition Based Maintenance ◽  
Spectral Signature ◽  
Structural Dynamic ◽  
Time Frequency ◽  
Mechanical Parts ◽  
Analysis Techniques ◽  
Contour Maps ◽  
Response Data ◽  
Processing Techniques ◽  
Signal Processing Techniques

Abstract Excessive vibrations usually cause mechanical parts to fail. This paper describes a vibration-induced failure in an air handling assembly. Cyclic impacts between a valve and a set of powdered metal bushings cause the failure. A variety of signal processing techniques are used to analyze experimental response data from the failing part including standard spectral signature approaches (i.e. Fourier, cepstral) in addition to more advanced time-frequency analysis techniques (i.e. wavelet contour maps). The theory and application of each method is reviewed in the context of the specific failure mode under consideration. The paper demonstrates that where friction or impact related vibrations are present, structural dynamic “health” monitoring schemes can be used to track changes in operating response signatures and schedule condition-based maintenance or re-design.

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