Designing the technology of express diagnostics of electric train's traction drive by means of fractal analysis

Бабанін, Олександр Борисович; Bulba, Vladislav

doi:10.15587/1729-4061.2016.76520

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…A fractal is scale-invariant and self-affine, and an indicator called fractal dimension is used to quantify its complexity. Fractal analysis is successfully used in natural sciences [17][18][19], engineering technologies [20,21], medicine [22][23][24], meteorology [25], finance [26] and other fields [27]. In the 1980s, Grassberger introduced the concept of a multifractal.…”

Section: Introductionmentioning

confidence: 99%

Detection of Pipeline Leaks Using Fractal Analysis of Acoustic Signals

Zagretdinov,

Ziganshin,

Izmailova

et al. 2024

Fractal Fract

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In this paper, the possibility of using monofractal and multifractal analysis of acoustic signals of pipelines to detect leaks is considered. An experimental stand has been created to study the fractal characteristics of acoustic signals of pipelines with “slit” type defects. During the experiments, defects of the “slit” type pipeline with dimensions of 2 mm, 8 mm, and 20 mm were modeled. Detrended fluctuation analysis (DFA) and the multifractal detrended fluctuation analysis (MF-DFA) were used. As a result of the experimental studies, it was found that the occurrence of leakage leads to the occurrence of anticorrelated vibrations in a pipeline with multifractal properties. The analyses of acoustic signals by DFA and MF-DFA methods make it possible to reliably determine the leakage. The Hurst exponent and the width of the multifractal spectrum can serve as indicators of the occurrence of leaks in pipelines.

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Section: Introductionmentioning

confidence: 99%

Detection of Pipeline Leaks Using Fractal Analysis of Acoustic Signals

Zagretdinov,

Ziganshin,

Izmailova

et al. 2024

Fractal Fract

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show abstract

“…Recently, fractal theory has been widely used in practical engineering to study the laws governing various complex, irregular and chaotic processes. Fractal methods are used in industries such as medicine (for analyzing data to detect cancer cells) [14][15][16], finance (to determine trends in securities charts) [17], meteorology [18], engineering [19][20][21][22], and other fields [23,24]. Monofractal models cannot always provide a complete description of patterns, especially when attempting to capture subtle spatial and temporal variations that are governed by natural laws.…”

Section: Introductionmentioning

confidence: 99%

Detection of Gate Valve Leaks through the Analysis Fractal Characteristics of Acoustic Signal

Zagretdinov,

Ziganshin,

Izmailova

et al. 2024

Fractal Fract

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This paper considers the possibility of using monofractal and multifractal analysis of acoustic signals to detect water leaks through gate valves. Detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MF-DFA) were used. Experimental studies were conducted on a ½-inch nominal diameter wedge valve, which was fitted to a ¾-inch nominal diameter steel pipeline. The water leak was simulated by opening the valve. The resulting leakage rates for different valve opening conditions were 5.3, 10.5, 14, 16.8, and 20 L per minute (L/min). The Hurst exponent for acoustic signals in a hermetically sealed valve is at the same level as a deterministic signal, while the width of the multifractal spectrum closely matches that of a monofractal process. When a leak occurs, turbulent flow pulsations appear, and with small leak sizes, the acoustic signals become anticorrelated with a high degree of multifractality. As the leakage increases, the Hurst exponent also increases and the width of the multifractal spectrum decreases. The main contributor to the multifractal structure of leak signals is small, noise-like fluctuations. The analysis of acoustic signals using the DFA and MF-DFA methods enables determining the extent of water leakage through a non-sealed gate valve. The results of the experimental studies are in agreement with the numerical simulations. Using the Ansys Fluent software (v. 19.2), the frequencies of flow vortices at different positions of gate valve were calculated. The k-ω SST turbulence model was employed for calculations. The calculations were conducted in a transient formulation of the problem. It was found that as the leakage decreases, the areas with a higher turbulence eddy frequency increase. An increase in the frequency of turbulent fluctuations leads to enhanced energy dissipation. Some of the energy from ordered processes is converted into the energy of disordered processes.

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Determination of Pipeline Leaks Based on the Analysis the Hurst Exponent of Acoustic Signals

Zagretdinov

Ziganshin

Vankov

et al. 2022

Water

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Currently, acoustic methods are widely used as a way to detect pipeline leaks. This is due to the fact that the acoustic signal has sufficiently capacious information about the state of the pipeline. The effectiveness of acoustic monitoring depends on the correct extraction of this information from the diagnostic signal. Currently, there is a search for new, more effective methods for analyzing acoustic signals. The article proposes to apply the theory of fractals to determine pipeline leaks. One of the most accurate methods for determining the fractal dimension of time series is R/S analysis using the Hurst exponent. An experimental stand has been developed and created, which includes a steel pipeline with water circulating in it. Water leakage from the pipeline was simulated by installing discs with holes of different diameters. The discs were placed in a special fitting on the surface of the pipeline. Acoustic signals recorded from the pipeline surface at different leakages and water pressure were analyzed. A relationship has been established between the size of the leak and the Hurst exponent of acoustic signals. The proposed method is compared with spectral analysis. Empirical experience has proven that R/S analysis can be used to determine pipeline leaks, as well as their classification by size.

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Designing the technology of express diagnostics of electric train's traction drive by means of fractal analysis

Abstract: Doctor of Technical Sciences, Professor Department of operation and repair of a rolling stock Ukrainian state university of a railway transportation Feyerbaxa sq.,

Cited by 3 publications

References 7 publications

Detection of Pipeline Leaks Using Fractal Analysis of Acoustic Signals

Detection of Pipeline Leaks Using Fractal Analysis of Acoustic Signals

Detection of Gate Valve Leaks through the Analysis Fractal Characteristics of Acoustic Signal

Determination of Pipeline Leaks Based on the Analysis the Hurst Exponent of Acoustic Signals

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