Nonstationary Processes Studying Based on “Caterpillar”—SSA Method

Polukoshko, Svetlana; Hiļķeviča, Gaļina; Gonca, Vladimirs

doi:10.1007/978-3-319-09918-7_88

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…The caterpillar method of SSA was used, as described by Golyandina et al [34]. This version of SSA emphasized the separability of the various Reconstructed Components (RCs) generated [35]. Initial uses of SSA were climatological and sociological.…”

Section: Introductionmentioning

confidence: 99%

Singular spectrum analysis as a tool for early detection of centrifugal compressor flow instability

2021

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Centrifugal compressor machinery is subject to a potentially damaging phenomenon called surge at low mass flow rates. This effect may be preceded by a phenomena known as inlet recirculation -a flow reversal upstream of the impeller. A methodology to isolate inlet recirculation as a characteristic feature for monitoring of centrifugal compressor instability is presented in this study. The methodology is based on a nonparametric time series analysis technique called as singular spectrum analysis (SSA). SSA decomposes a signal into a number of Reconstructive Components (RCs), from which data trends and oscillatory components may be extracted. The frequency spectra of each RC and their relative contributions to the reconstruction of the original signal were examined and comparisons were made with spectral maps in existing literature. Individual and independent RCs were chosen to construct a compressor's instability monitoring system. Additionally, the performance of SSA was determined by the Window length parameter. The effect of modification of this parameter was also studied, and the various viable choices of component for the basis of inlet recirculation diagnosis were considered. The methodology was implemented in pressure dynamical signals measured in an experimental centrifugal compressor rig. High frequency pressure measurements were taken at a number of flow conditions and locations within the compressor. The results demonstrated the potential of a methodology based on SSA to identify and extract oscillatory components with information about the local effect of inlet recirculation and eventually successfully monitor centrifugal compressor's instability.

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Section: Introductionmentioning

confidence: 99%

Singular spectrum analysis as a tool for early detection of centrifugal compressor flow instability

2021

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A retrospective analysis technology of the Green Software Ecosystems development on the parametric identification of the Brown's model

Shostak

Danova

Romanenkov

et al. 2018

2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT)

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Analyzing and forecasting financial series with singular spectral analysis

Makshanov

Мусаев

Grigoriev

2022

Dependence Modeling

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Modern techniques for managing multidimensional stochastic processes that reflect the dynamics of unstable environments are proactive, which refers to decision making based on forecasting the system’s state vector evolution. At the same time, the dynamics of open nonlinear systems are largely determined by their chaotic nature, which leads to a violation of stationarity and ergodicity of the series of observations and, as a result, to a catastrophic decrease in the efficiency of forecasting algorithms based on traditional methods of multivariate statistical data analysis. In this article, we make an attempt to reduce the instability influence by employing singular spectrum analysis (SSA) algorithms. This technique has been employed in a wide class of applied data analysis problems formulated in terms of singular decomposition of data matrices: technologies of immunocomputing and SSA.

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Nonstationary Processes Studying Based on “Caterpillar”—SSA Method

Cited by 3 publications

References 8 publications

Singular spectrum analysis as a tool for early detection of centrifugal compressor flow instability

Singular spectrum analysis as a tool for early detection of centrifugal compressor flow instability

A retrospective analysis technology of the Green Software Ecosystems development on the parametric identification of the Brown's model

Analyzing and forecasting financial series with singular spectral analysis

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