FIELD OF THE INVENTION
The present invention relates to a fast, low cost, non-cumbersome and non-
invasive method for compositional analysis of iron ores based on variation in
thermal absorptivity of the ore constituents via Infrared (IR) thermography.
BACKGROUND OF THE INVENTION
In mineral processing industries, compositional analysis of ores plays a crucial
role at different stages of the process of extraction from mines, beneficiation of
the ore, blending and despatch. Standard industry practice is to collect a few
samples of the ore, prepare and analyse either through conventional wet
chemical methods or through instrumental analysis in XRF or ICP etc. While the
analysis time in the ICP is significantly less, sample preparation time however
remaining a concern. Thus the total process of sampling, preparation and
chemical analysis of any bulk material including iron ore is a time consuming and
cumbersome process. Further, the time-lag between collecting the samples and
receiving the chemical analysis data poses a serious problem to the plant
operators including the quality assurance managers in decision making on
process optimization. Commercially available cross-belt analysers using the
techniques such as X-Ray Fluorescence (XRF), Prompt Gamma Neutron
Activation Analysis (PGNAA), Pulsed Fast and Thermal Neutron Analysis PFTNA)
etc. are capital intensive and their performance in iron ore applications in terms
of minor constituents such as alumina, are not adequately established.
Therefore a need exists to develop a relatively capital inexpensive, reliable, and
non-invasive method for a faster and accurate determination of ore composition
in real time for application in mineral industries.
OBJECT OF THE INVENTION
It is therefore an object of the present invention is to propose an infrared

thermography (IR)- based non-invasive method for fast compositional analysis of
iron ores with one constituents exhibiting variation in thermal absorptivity.
SUMMARY OF THE INVENTION
Accordingly, there is provided an infrared thermography (IR)- based non-invasive
method for fast compositional analysis of iron ores with one constituents
exhibiting variation in thermal absorptivity.
The disclosed method has been developed and tested with iron ore fines, having
nominal top size of 10mm with Fe(t) in the range of 58 to 67% and
corresponding alumina levels of 7.5 to 1%, produced in various stages of
beneficiation.
According to the process, a fixed quantity of different categories of iron ore
samples are uniformly heated in a microwave oven, for a time period sufficient to
create a difference between the ore particles in the extent of their respective
infrared emissions. The thermal image of the heated ore specimens is captured
by IR Thermography and the average temperature of these ore specimens is
evaluated. It is known that the average temperature of the heated ore particles
vary with the gangue content, primarily alumina and silica, in the ores. The
higher the gangue content in the ores, the lower is the average temperature.
According to the invention, more emphasis was given to determine alumina
content in the ore, considering the influencing factor of the alumina content in
process control including its downstream impact. Through IR imaging of different
ores with varying alumina, a calibration curve is generated which correlates the
average temperature of the ores with their corresponding alumina content
obtained through chemical analysis in the laboratory. Therefore, alumina content
in the unknown iron ore samples can now be estimated from the calibration
curve. The IR imaging technique for analysing iron ore composition provides a
reliable and an accurate analysis and can replace the known laboratory analysis

for bulk materials, where sample preparation and analysis time remain as the
prime concern. The inventive process being fast and accurate, this invention
having immense potential for application in mining industries, not only in process
control of beneficiation circuits, material sorting, homogenization and blending,
but also in mine grade control by providing accurate and faster analysis of blast
cone chips upstream.
As per the disclosed process, samples of iron ore fines (<10mm nominal size)
are collected from the beneficiation plant having Fe compositions ranging from
58% -67% and alumina ((Al2O3) 7.5-1.0%). The samples are reduced into
smaller quantity and uniformly heated using energy from a microwave oven
(Rating :1.25 KW, domestic with turntable) for a period of 10 sec. The invention
employs IR thermography and image analysis techniques to determine the
average temperature of the heated iron ore particles which varies with their
composition. A calibration curve relating to alumina content in the ores vis-a-vis
the average temperature of the heated ore particles measured by IR
thermography, is generated. Thus, the process allows non-invasively determines
the alumina content in bulk quantity of iron ore samples based on the calibration
curve. The inventive process is simple and cost-effective compared to the known
techniques.
As described hereinabove, the present invention is enabled to provide data
regarding quality of different category of ores based on alumina content in them,
in various stages of iron ore processing.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
Figure 1 - Schematic representation of IR thermography based technique
according to the invention for compositional analysis of ores.

Figure 2 - Pictorial view of the steps to be followed for alumina prediction in
iron ore according to the invention
Figure 3 - A screen snapshot-view for alumina prediction from av.
temperature according to the invention
Figures 4(a) & 4(b) - Arrangement and Thermal image of ore samples
Figure - 5 Av. Temperature vs. Alumina content at 300W
Figure 6 - Av. Temperature vs. Alumina content at 450W
Figure 7 - Av. Temperature v/s Alumina content at 600W
Figure 8 - Average temperature v/s alumina content plot for different types of
ore samples at 450W
DETAIL DESCRIPTION OF THE INVENTION
According to the present invention provides an infrared thermography (IR)-
based non-invasive method for fast compositional analysis of iron ores with one
constituents exhibiting variation in thermal absorptivity, the process comprising
the steps of :-
- providing an Infrared Thermography camera (1) to capture thermal
images of the heat radiated by iron ore specimens (2) placed at a fixed
distance from the IR camera during uniform heating of he specimens (2)
using a microwave oven (3);
- collecting the heated specimens (2) having Fe(t) composing ranging from
58% - 67% and alumina (A12O3) 7.5 -1.0%), including crushing of oversize
ores to make the sample size less than 10mm;

- heating a fixed quantity of iron ore particles uniformly employing a
microwave oven for a duration of 10 sec;
- determining the average temperature of the test ores from the captured
thermal image;
- generating a calibration curve correlating the average temperature of the
heated ores with measured alumina content in the ores based on chemical
analysis; and
- estimating the alumina content of unknown iron ore samples from the
calibration curve.
In an embodiment of the present invention, different categories of iron ore
samples with Fe compositions ranging from 58% - 67% and alumina (A12O3) 7.5
-1.0%) are collected from the iron ore processing and jigging plant.
A fixed quantity of the collected iron ore samples is uniformly heated in a
microwave oven with turntable for a period of 10 sec to create a difference
between the ore particles in respect of their respective infrared emissions. The
heat radiated from the heated ores is captured in the form of a thermal image by
using an IR camera.
The area of interest from the captured thermal images is selected and the
average peak temperature of the heated ore particles is determined from a
histogram plot of the thermal image.
A chemical analysis of the ore samples is carried out in the laboratory to detect
alumina % in all the test ore samples.

A calibration curve is generated based on the average peak temperature of all
the test samples vis-a-vis corresponding values of % alumina as obtained from
the chemical analysis.
According to the present invention the % alumina in iron ore fines can be
determined from the calibration curve after determining the average temperature
of the ore sample from the thermal image of the ore, without carrying-out
laboratory analysis of the ore through chemical analysis.
The present invention utilises a non-invasive IR Thermography technique to
identify alumina-rich iron ores as well as gradation of different category of ores
on the basis of % alumina present in the ore. The present invention adapts a
microwave oven for uniform heating of iron ore samples and an IR camera for
capturing the radiation from the heated iron ore particles. The IR camera is
placed above a petri dish carrying the samples, at a fixed distance. The average
peak temperature of the heated ore particles is measured by capturing the
radiant heat from the ore samples by said cameras and evaluating the
temperature from said histogram plot of a selected area in the capture thermal
images. The average peak temperature vary with the variation in alumina
content in each category of ore. For iron ore particles with low %alumina (ie.
high iron), the average peak temperature is found to be high, whereas it's the
reverse for iron ore with high %alumina. The present invention relates the
average peak temperature of uniformly heated iron ore particles with the
%alumina present in such ores through said calibration curve.
The present invention allows a faster estimation of the % of alumina present in
different grades of iron ores handled during a beneficiation process, based on
the average peak temperature of the heated ores.

Accordingly, the present invention teaches an IR thermography based non-
invasive method for compositional analysis of iron ores. This innovative method
is much faster, low cost and less cumbersome as compared to the known
techniques for determination of concentration of alumina in iron ore. Moreover,
implementation of this technique in the beneficiation process in operating mines
would lead to more systematic and improved decision making across the value
chain in mine grade control, material sorting, process control, homogenization
and blending.
The following examples are given by way of illustration and should not be
construed to limit the scope of invention.
Pictorial view of the alumina prediction system implemented in accordance with
one aspect of the invention is shown in figure 2 and the screen-snapshot views
in a process to predict alumina from the average temperature is shown in figure
3.
EXAMPLE - 2
Optimisation of Power level of Microwave oven:
Iron ores with Fe composition in the range of 58 to 67 wt. % and alumina
(A1203) from 7.5 to 1.0 wt% are being beneficiated in Noamundi mines of India's
renowned steel plant, Tata Steel. In order to establish IR thermography as a
viable technique for compositional analysis of iron ores, experiments were
performed on different grades of iron ore samples collected from different shifts
running in the beneficiation plant in Noamundi mines. Depending upon the

location in the beneficiation plant from which the iron ore samples are collected,
these samples are classified as:
a) Jig Concentrate (JC)
b) Jig Feed (JF)
c) Jig Reject (JR)
d) Classifier fines (CFO)
In JF category 22 samples, JC category 23 samples, JR category 14 samples
while in CFO category 19 samples have been collected and henceforth these total
78 samples were subjected to experimentation. A fixed quantity from each
category was taken from these as-received samples after homogenization and
reduction through coning and quartering and considered as test sample. Each of
these samples is taken in a Petri dish as shown in Figure 4(a) and heated
uniformly using a microwave oven for duration of 10s. The thermal image of the
test ores were captured and analysed as explained in step 4. The thermal images
of one set of samples of JF, JC, JR, CFO is shown in figure 4(b).
1. Jig Feed (JF) 2. Jig Concentrate (JC) 3. Jig Reject (JR) 4. Classifier
Fines(CFO)
In order to optimize the heating source, the experiments have been
performed at different power levels of a microwave oven, i.e. 300W, 450W,
600W. The average peak temperature of the heated ores at different
microwave power level and the corresponding Fe (wt. %) and alumina (wt.
%) obtained from chemical analysis of JC, JF, JR and CF samples are given in
Table 4, 5, 6 and 7 respectively.

The average temperature of the heated ores with percentage of alumina present
in the ores has been plotted for different power levels of microwave such as
300W, 450W, 600W as shown in figures 5,6 and 7 respectively.

The correlation factor (R2) for the linear fit obtained at 300W, 450W and 600W is
0.763, 0.827 and 0.809 respectively. Microwave oven power level is established
to be 450W for the test.
EXAMPLE - 3
Experiments are carried out in iron ore samples collected from different locations
of ae steel plant. The average peak temperature of the heated ores obtained
from their IR imaging at power level of 450W and the alumina content in these
ores from chemical analysis is plotted in Figure 8. It can be clearly observed
from Figure 8 that the lowest quality ore (Jig reject) lies at top left area of the
plot, indicating lower average temperature which corresponds to higher alumina
content while highest quality ore (Jig Cone.) lies at extreme right at the bottom
of the plot indicating higher average temperature ores having low alumina
content. In between these two region lies medium quality ores (Jig feed and
Classifier fines) with moderate amount of alumina.
EXAMPLE - 4
Experiment are carried out on iron ore samples collected from the different
locations of a steel plant having iron ore mine at different period of time. A
calibration curve as obtained for 450W power level is used as a reference to
estimate the alumina content in the test ore samples. Verification of the results
as obtained from the average temperature of the thermal image of test ore using
the developed technique is done through the conventional chemical analysis.
Results of predicted %alumina in test ores through the developed technique and
the conventional chemical analysis alongwith the difference in two techniques is
depicted in table 7.

The main advantages of the present invention are:
1. The IR Thermography based method of the present invention is a useful
tool for detection of alumina-rich iron ores and having potential for
estimation of composition for other commodities as well.
2. This is a fast, low cost and non-invasive technique for compositional
analysis of iron ore.
3. This method can be considered to be an alternative for known chemical
analysis methods which is time-consuming and cumbersome. This
inventive method apart from dry processing is also a quick method for
indirect chemical analysis of ore due to which the delay time can be saved
and production can be increased.
4. From the developed calibration curve, the alumina content in the ores can
be determined within a duration of just 60 seconds and the quality of the
feed grade can be estimated from the alumina percentage.
5. Implementation of the method in the beneficiation process in operating
mines would lead to more systematic and improved decision making
inputs to effective planning and control leading to resource optimization in
a safe and environmental friendly manner.
6. Real time analysis of feed grade to the plant operators allows an effective
plant optimization for achieving targeted production and grade.

WE CLAIM
1. An infrared thermography (IR)- based non-invasive method for fast
compositional analysis of iron ores with one constituents exhibiting
variation in thermal absorptivity, the process comprising the steps of :-
- providing an Infrared Thermography camera (1) to capture thermal
images of the heat radiated by iron ore specimens (2) placed at a fixed
distance from the IR camera during uniform heating of he specimens (2)
using a microwave oven (3);
- collecting the heated specimens (2) having Fe(t) composing ranging from
58% - 67% and alumina (A12O3) 7.5 - 1.0%), including crushing of
oversize ores to make the sample size less than 10mm;
- heating a fixed quantity of iron ore particles uniformly employing a
microwave oven for a duration of 10 sec;
- determining the average temperature of the test ores from the captured
thermal image;
- generating a calibration curve correlating the average temperature of the
heated ores with measured alumina content in the ores based on chemical
analysis; and
- estimating the alumina content of unknown iron ore samples from the
calibration curve.

2. The process as claimed in claim 1, wherein the thermal images of the heat
radiated from the ore samples are captured immediately after heating in
the microwave over for duration of 10 seconds.
3. The process as claimed in claim 1 or claim 2, wherein average peak
temperatures of the heated iron ore particles are determined from the
histogram plot of temperature distribution along the region of interest in
the respective thermal images.
4. The process as claimed in any of the proceeding claims, wherein the %
alumina in iron ore fines can be determined from the calibration curve
after determining the average temperature of the ore sample from the
thermal image of the ore, without carrying-out laboratory analysis of the
ore through chemical analysis

ABSTRACT

The invention relates to an infrared thermography (IR)- based non-invasive
method for fast compositional analysis of iron ores with one constituents
exhibiting variation in thermal absorptivity, the process comprising the steps of
providing an Infrared Thermography camera (1) to capture thermal images of
the heat radiated by iron ore specimens (2) placed at a fixed distance from the
IR camera during uniform heating of he specimens (2) using a microwave oven
(3); collecting the heated specimens (2) having Fe(t) composing ranging from
58% - 67% and alumina (A12O3) 7.5 - 1.0%), including crushing of oversize ores
to make the sample size less than 10mm; heating a fixed quantity of iron ore
particles uniformly employing a microwave oven for a duration of 10 sec;
determining the average temperature of the test ores from the captured thermal
image; generating a calibration curve correlating the average temperature of the
heated ores with measured alumina content in the ores based on chemical
analysis; and estimating the alumina content of unknown iron ore samples from
the calibration curve.