sedimaging for soil classification

SEMINAR ON

by

SUDARSHAN BAROLE

15CE64R07

DEPARTMENT OF CIVIL ENGINEERING

INDIAN INSTITUTE OF TECHNOLOGY

KHARAGPUR

SIZE DISTRIBUTION OF COARSE- GRAINED

SOIL BY SEDIMAGING

1. INTRODUCTION

1.1 PARTICLE SIZE DISTRIBUTION

Most fundamental property of coarse grained soil

Traditional method for particle size distribution is sieve

analysis.

Fig 1.1- Apparatus for Performing Sieve analysis test on soil.(a) Set of Sieve (b) mechanical sieve shaker

2.SEDIMAGING

A new method recently develop to determine the particle size distribution of coarse grain soil by using imaging technique.

practically implemented by Hyon-shok Ohm and Roman D. Hryciw

it gives the particle size distribution for particles between 0.075mm and 2.0 mm

This test also help to determine the percentage finer than .075mm

2.1 INTRODUCTION

In 2004 shin and Hryciw developed an image processing

technique based on wavelet transformation.

But due to absence of high resolution camera and laboratory

testing system at that time, the above concept was only a

theoretical concept

Ohm and hryciw then tracked the development of camera

technology until 20-40 megapixel camera became available in

early 2010.

2.2 EARLY ATTEMPS TOWARD SEDIMAGING

2.3 SEDIMAGING HARDWARE

Sedimentation column

Sediment accumulator

Pre segregationtube

Sedimaging Hardware

2.4 TEST PROCEDURE

Sedimentation with time

Pixel-

It is the smallest controllable element of a picture represented on the screen.

Pixels per diameter(PPD)-

It is the most important and useful in sedimaging. It is define as average number of pixel per particle diameter.

2.5 THEORETICAL CONCEPT

Grey scale -The intensity of a pixel is expressed within a given

range between a minimum and a maximum, inclusive. This

range is represented in an abstract way as a range from 0 (total

absence, black) and 1 (total presence, white), with any

fractional values in between.

WAVELET TRANSFORMATION

In sedimaging wavelet transformation is used for image processing and to determine it particle size distribution.

The sedimaging program performs all the wavelet operations in the background with no user input require.

Wavelet transformation decompose a image of 2ⁱ x 2ⁱ pixel size image into i decomposition level and calculate energy correspond to each level.

Energy is the measure of the magnitude of the difference between average gray scale of adjacent regions in a image.

Seven levels of downscaling beginning with a 128 x 128 image at PPD=13.2

As the concentration of

energy shifts to higher

energy level.

Wavelet index – The

centroid of area beneath a

normalize energy line with

respect to vertical axis

They gave the relation

between PPD and CA based

on experiments on pre-

seived soil

IMPORTANT POINT BASED ON ABOVE CONCEPTS

They produced the calibration curve as shown.

The relationship between CA and PPD is given as

Where A= 5.1 for saturated soil behind a glass window(A=5.9 for dry soil)

Once you determine CA for a portion, you can easily determine the PPD by using equation.

The actual grain size can be computed as

Where D- diameter of soil particle (mm) and M = camera magnification(pixels/mm)

Fig showing particle sorted by size

This image is analyzed incrementally with height to produce the particle size distribution

colorful squares represent area under analysis(128x128 pixels).

It gives about 5500 values of D from a 4520 x 1280 pixel image

Random values of D(only 20% of total value obtained

After sorting all the data points by particle size, final particle size distribution

Software for analyzing image was coded using MATLAB R2013a

comparison between sieve and sedimaging results of different soil

COMPARISON

Comparison of particle size distribution curve

5.ADVANTAGES OF SEDIMAGING

It is a quick test and takes 5-10 minutes.

Installation, operation and maintenance is easy.

It gives about 5000 points but in case of sieve analysis we get

only 10-11 data points for plotting the curve

In sedimaging energy consumption is low.

It help in improving work environment.

6.LIMITATIONSAs this test uses calibration curve which is developed using

sieving results and so this test just mimics sieving and yield comparable results.

It shows variation in results due to internal particle texture.

It does not redefine the particle.

7.CONCLUSION As we discussed earlier, sedimaging has many advantages over

sieving like reducing test time, low energy consumption, less

equipment maintenance and improvement in work

environment,

But before completely adopting this method, a little more

research on sedimaging to overcome the limitation is required.

Future research and advances in camera will make it possible

to develop sedimaging for fine soil like silt

Finally there is a need to put attention toward development of

sedimaging.

8. REFERENCES Ohm. H.S.(2013) “image based soil particle size and shape

characterization”

Shin, S., and Hryciw, R.D.(2004). “wavelet analysis of soil

mass images for particle size determination.” J. comput. Civ.

Eng. 10.1061/(ASCE) 0887-3801(2004)18:1(19),19-27

Ohm, H S., and Hryciw, R.D.(2013b). “the translucent segregation table test for sand and gravel particle size distribution.” J. ASTM Geotech Test.,36(4),592-605

THANK YOU