Visualization of geomagnetic variations in time-frequency area of information signal

There are different methods and devices for the increase of the videosignal information in SEM. For example, with the help of special pure electronic [1] and opto-electronic [2] systems equipotential areas on the specimen surface in SEM were obtained. This report generalizes quantitative universal method for space distribution representation of research specimen parameter by contour equal signal lines. The method is based on principle of comparison of information signal value with the fixed levels.Transformation image system for obtaining equal signal lines maps was developed in two versions:1)In pure electronic system [3] it is necessary to compare signal U (see Fig.1-a), which gives potential distribution on specimen surface along each scanning line with fixed base level signals εifor obtaining quantitative equipotential information on solid state surface. The amplitude analyzer-comparator gives flare sport videopulses at any fixed coordinate and any instant time when initial signal U is equal to one of the base level signals ε.

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Performance of time-frequency coded spread spectrum systems operating over noisy fading channels

IEE Proceedings F Communications Radar and Signal Processing ◽

10.1049/ip-f-1.1988.0061 ◽

1988 ◽

Vol 135 (6) ◽

pp. 513 ◽

Cited By ~ 3

Author(s):

P. Belezinis ◽

L.F. Turner

Keyword(s):

Fading Channels ◽

Spread Spectrum ◽

Time Frequency ◽

Spread Spectrum Systems

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Time-Frequency Analysis between Renewable and Nonrenewable Energy Consumption, Economic Growth, and CO 2 Emissions in the United States: Evidence from the Transportation Sector

CICTP 2020 ◽

10.1061/9780784483053.250 ◽

2020 ◽

Author(s):

Qinghui Xu ◽

Muhammad Umar ◽

Xiangfeng Ji

Keyword(s):

United States ◽

Economic Growth ◽

Energy Consumption ◽

Frequency Analysis ◽

The United States ◽

Time Frequency Analysis ◽

Time Frequency ◽

Transportation Sector ◽

Nonrenewable Energy

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Structured methods for improving flow measurement accuracy in pipelines

Izmeritel`naya Tekhnika ◽

10.32446/0368-1025it.2020-5-30-35 ◽

2020 ◽

pp. 30-35

Author(s):

Gurami N. Akhobadze

Keyword(s):

Flow Measurement ◽

Measurement Accuracy ◽

Directional Coupler ◽

Signal To Noise Ratio ◽

Scattered Wave ◽

Orthogonal Polarization ◽

Flow Sensors ◽

Information Signal ◽

Mass Flows ◽

Processing Device

In the age of digital transformation of production processes in industry and science the development and design of intelligent flow sensors for granular and liquid substances transferring through pipelines becomes more important. With this in view new approaches for improving the accuracy of microwave flowmeters are proposed. Taking into account the characteristics ofelectromagnetic waves propagating through a pipeline, a wave scattered by inhomogeneities of the controlled medium is analyzed. Features of the transformation of the polarized scattered wave limiting the geometric dimensions of the pipeline and optimizing the values of the useful scattered signal are revealed. Expediency of collection of the information signal with orthogonal polarization of the scattered wave and through a directional coupler is substantiated. The method of estimating the measurement accuracy with reference to the signal-to-noise ratio at the input of the processing device is given. The research results can be used in cryogenic machine engineering to measure volume and mass flows of liquid cryogenic products.

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A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset207430 ◽

2020 ◽

pp. 129-139

Author(s):

Weihai Sun ◽

Lemei Han

Keyword(s):

Fault Detection ◽

Signal Analysis ◽

Energy Analysis ◽

Detection Method ◽

Sound Signal ◽

Practical Significance ◽

Time Frequency ◽

Detection Approach ◽

Machine Fault ◽

Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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