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A platform for research: civil engineering, architecture and urbanism
An autoadaptive Haar wavelet transform method for particle size analysis of sands
https://orcid.org/http://orcid.org/0000-0001-6603-9707
The Sed360 is a semi-automated image-based system for generating Particle Size Distributions (PSDs) of sands from an image of a sedimented soil specimen. The system expanded the size range of tested soils over its predecessors to include the entire range of sands, from 4.75 to 0.075 mm per the Unified Soil Classification System. In terms of exposed surface area, the largest particles are more than 4000 times larger than the smallest. This large size range posed a major challenge to image analysis. The solution, based on Haar Wavelet Analysis (HWT) was to autoadaptively adjust the sizes of HWT analysis squares: larger squares for parts of the image that contained larger particles, and progressively smaller squares working upward to the finest particles at the top of the sedimented soil column. From each analysis square, a single HWT index value, correlated to the size of the soil particles within the area, is determined. The particle sizes from across the entire image are combined to form the soil’s PSD. The new autoadaptive analysis square sizing method was utilized on five sand specimens taken from the same parent material but with varying gradations, including finer and coarser sands, smaller and larger particle size ranges, and a challenging gap-graded material. The results showed strong agreement with results by sieving.
An autoadaptive Haar wavelet transform method for particle size analysis of sands
https://orcid.org/http://orcid.org/0000-0001-6603-9707
The Sed360 is a semi-automated image-based system for generating Particle Size Distributions (PSDs) of sands from an image of a sedimented soil specimen. The system expanded the size range of tested soils over its predecessors to include the entire range of sands, from 4.75 to 0.075 mm per the Unified Soil Classification System. In terms of exposed surface area, the largest particles are more than 4000 times larger than the smallest. This large size range posed a major challenge to image analysis. The solution, based on Haar Wavelet Analysis (HWT) was to autoadaptively adjust the sizes of HWT analysis squares: larger squares for parts of the image that contained larger particles, and progressively smaller squares working upward to the finest particles at the top of the sedimented soil column. From each analysis square, a single HWT index value, correlated to the size of the soil particles within the area, is determined. The particle sizes from across the entire image are combined to form the soil’s PSD. The new autoadaptive analysis square sizing method was utilized on five sand specimens taken from the same parent material but with varying gradations, including finer and coarser sands, smaller and larger particle size ranges, and a challenging gap-graded material. The results showed strong agreement with results by sieving.
An autoadaptive Haar wavelet transform method for particle size analysis of sands
https://orcid.org/http://orcid.org/0000-0001-6603-9707
The Sed360 is a semi-automated image-based system for generating Particle Size Distributions (PSDs) of sands from an image of a sedimented soil specimen. The system expanded the size range of tested soils over its predecessors to include the entire range of sands, from 4.75 to 0.075 mm per the Unified Soil Classification System. In terms of exposed surface area, the largest particles are more than 4000 times larger than the smallest. This large size range posed a major challenge to image analysis. The solution, based on Haar Wavelet Analysis (HWT) was to autoadaptively adjust the sizes of HWT analysis squares: larger squares for parts of the image that contained larger particles, and progressively smaller squares working upward to the finest particles at the top of the sedimented soil column. From each analysis square, a single HWT index value, correlated to the size of the soil particles within the area, is determined. The particle sizes from across the entire image are combined to form the soil’s PSD. The new autoadaptive analysis square sizing method was utilized on five sand specimens taken from the same parent material but with varying gradations, including finer and coarser sands, smaller and larger particle size ranges, and a challenging gap-graded material. The results showed strong agreement with results by sieving.
An autoadaptive Haar wavelet transform method for particle size analysis of sands
Acta Geotech.
Ventola, Andrea (author) / Hryciw, Roman D. (author)
Acta Geotechnica ; 18 ; 5341-5358
2023-10-01
18 pages
Article (Journal)
Electronic Resource
English
Image analysis , Particle size distribution , Sand , SedImaging , Sed360 , Soil classification Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
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