Abstract
Knowledge of the structure of a flow is really significant for the proper conduct a number of industrial processes. In this case a description of a two-phase flow regimes is possible by use of the time-series analysis e.g. in frequency domain. In this article the classical spectral analysis based on Fourier Transform (FT) and Short-Time Fourier Transform (STFT) were applied for analysis of signals obtained for water-air flow using gamma ray absorption. The presented method was illustrated by use data collected in experiments carried out on the laboratory hydraulic installation with a horizontal pipe of 4.5 m length and inner diameter of 30 mm equipped with two 241Am radioactive sources and scintillation probes with NaI(Tl) crystals. Stochastic signals obtained from detectors for plug, bubble, and transitional plug – bubble flows were considered in this work. The recorded raw signals were analyzed and several features in the frequency domain were extracted using autospectral density function (ADF), cross-spectral density function (CSDF), and the STFT spectrogram. In result of a detail analysis it was found that the most promising to recognize of the flow structure are: maximum value of the CSDF magnitude, sum of the CSDF magnitudes in the selected frequency range, and the maximum value of the sum of selected amplitudes of STFT spectrogram.
Highlights
Knowledge of a two-phase flow structure is significant for the proper conduct a number of industrial processes, so flow regime identification inspires many studies
In this article the classical spectral analysis based on Fourier Transform (FT) and Short-Time Fourier Transform (STFT) were applied for analysis of signals obtained for water-air flow using gamma ray absorption
In this work FT and STFT are applied to signals obtained in two-phase liquid-gas flow measurements using gamma-ray absorption, where data were collected in experiments carried out on a laboratory hydraulic installation with a horizontal pipe of 4.5 m length and inner diameter of 30 mm
Summary
Knowledge of a two-phase flow structure is significant for the proper conduct a number of industrial processes, so flow regime identification inspires many studies. Computational intelligence methods utilize various features of signals in the time, frequency and state-space domain. Features of signals in the frequency domain may be determined using the Fourier Transform (FT), Short-Time Fourier Transform (STFT), wavelet transform and other methods [13,14,15]. In this work FT and STFT are applied to signals obtained in two-phase liquid-gas flow measurements using gamma-ray absorption, where data were collected in experiments carried out on a laboratory hydraulic installation with a horizontal pipe of 4.5 m length and inner diameter of 30 mm. Stochastic signals obtained for three structures of air-water flow as plug, bubble, and transitional plug – bubble one were considered. Laboratory stand and gamma absorption equipment are presented in the first part of this work and and are described in detail in [16,17,18,19]
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