Investigation into Pressure Signal Fluctuations during Fluidized Dense-Phase Pneumatic Conveying of Powders

Abstract

This thesis aims to provide a new method based on signal analysis for flow mode investigation in dense phase pneumatic conveying. In spite of numerous benefits offered by dense-phase pneumatic conveying of powders (which include minimum gas flows and power consumption; improved product quality and increased workplace safety etc) only limited progress has been achieved so far in understanding the fundamental transport mechanisms due to the highly concentrated and turbulent mode of the solids-gas flow. As a result, for the accurate design of dense phase pneumatic conveying systems, further research should be carried out.

For carrying out analysis work, extensive amount of test data made available from University of Wollongong, Australia has been considered, which included two types of materials conveyed in different flow regimes varying from fluidized dense- to dilute phase including fly ash (median particle diameter 30 m; particle density 2300 kg m-3; loose-poured bulk density 700 kg m-3) conveyed through a 69 mm I.D. × 168 m long pipeline and white powder (median particle diameter 55 m; particle density 1600 kg m-3; loose-poured bulk density 620 kg m-3) conveyed through a 69 mm I.D. × 148 m long test rig. Analysis work also included data analysis from the pressure signals obtained during pneumatic conveying experiments conducted at the test setup of Thapar University, Patiala by conveying Indian fly ash (median particle diameter 19 m; particle density 1950 kg m-3; loose-poured bulk density 950 kg m-3) through two different test set ups i.e. 54 mm I.D. × 70 m long and 54 mm I.D. × 24 m long.

Various methods of analysis involve different techniques, which could be grouped into two categories. First group of techniques (i.e., Hurst exponent, phase space diagram and Shannon entropy) aim to provide information on the qualitative nature of entire time-series as a whole, i.e. content of information (Shannon entropy) in the signal, degree of co-correlation between different parts of the signal (Hurst exponent) and amount of chaos (attractor analysis). These techniques mainly focus on searching for the hidden information in the time series signal and using these techniques, emphasis is made on the extraction and selection of key features that distinguish different pressure time signals to represent different flow mechanisms. Results show that with increasing conveying distance (i.e. with an increase in conveying velocity in the direction of flow), there is an overall decrease in the values of Hurst exponent, an increase in the area covered by the phase-space diagram and an increase in the Shannon entropy values, indicating an increase in the degree of complexity of flow mechanism (or turbulence) along the length of the conveying pipeline. All the three methods have revealed that the closely coupled bends reverse the trend of change of Hurst exponent, phase-space diagram area and Shannon entropy values. This is due to the slowing down of particles caused by the friction of particles along the bend wall resulting in dampened particle turbulence (particle roping effect).

Second group of techniques includes analysis based on frequency domain or both frequency and time domain need to be performed so as to obtain information on the frequency content of the pressure signals. These include power spectral density (PSD), Wavelet transformation and Hilbert-Huang transformation (HHT). Power spectra obtained from PSD analysis, energy distribution of intrinsic mode functions (IMF) obtained from HHT transformation and wavelet scalogram show unique features related to the changing flow mechanism along the length of the pipeline. Results indicate variation from low frequency to higher frequency components in the signal, along the flow direction. Higher frequency components and wide range of frequencies in the signal obtained at pipeline exit might have resulted from the increased level of interactions amongst the solid particles, carrier gas and pipe wall as compared to the power spectra with single dominant frequency (which corresponds to probable periodic dune formation) at the pipeline entry region.

The Present work also aims to represent minimum transport boundary by analyzing the pressure signals obtained from pneumatic conveying trials, which were conducted for low conveying velocity and high solid flow rates. Results show that various signal parameters could be used for the online prediction of blockage boundary. Present work attempts to test the applicability of pressure fluctuations to be used for dune velocity estimation. It was found that the degree of cross-correlation between two signals from adjacent transducers was not sufficient to correlate the dunes (as the signal characteristics were modified while moving from one location to the other).