SLURRY ANALYZER CALIBRATION MANUAL

Outocal
Courier 6X SL analyzer calibration
Doc. No. OU500568923, English 2015

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Courier 6X SL Calibration Manual
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SLURRY ANALYZER CALIBRATION MANUAL
COURIER 6X SL
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Language: EN

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Contents
Contents .............................................................................................................................3
1 Calibration process.................................................................................................5
2 Planning calibration process .................................................................................6
2.1 Determining when to take samples............................................................6
2.2 Number of calibration samples ..................................................................7
2.3 Selecting measurement time for first calibration........................................7
3 Taking calibration samples ....................................................................................8
3.1 Preparations...............................................................................................8
3.1.1 Checking process conditions ................................................................8
3.1.2 Preparing equipment.............................................................................9
3.2 Collecting calibration samples ...................................................................9
3.3 After sample collection.............................................................................11
4 Checking data collected for calibration ..............................................................12
4.1 Range of variation....................................................................................12
4.2 Restrictions due to process......................................................................13
5 Creating calibration model...................................................................................14
5.1 Symbols used in calibration models.........................................................15
5.2 Importing laboratory data to Outocal........................................................15
5.2.1 Adding and editing laboratory data in calibration database................19
5.3 Evaluating calibration model ....................................................................20
5.4 Starting calibration model creation...........................................................23
5.5 Selecting variables...................................................................................25
5.5.1 Taking percentage solids into account ...............................................25
5.5.2 Taking interfering elements into account............................................27
5.6 Checking data points................................................................................28
5.6.1 Deselecting points with errors.............................................................29
5.6.2 Deselecting points with high influence................................................30
5.7 Creating non-linear variables ...................................................................31
5.8 Checking measurement time ...................................................................32
5.9 Inputting calibration model into analyzer .................................................32
6 Maintenance of calibration ...................................................................................34
6.1 Updating calibration model after 2-3 months ...........................................34
6.2 Special cases...........................................................................................35
6.2.1 Slow changes in stream characteristics..............................................35
6.2.2 Sudden changes in stream characteristics.........................................35
6.2.3 Recalibration after major equipment change......................................35

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1 Calibration process
In online analysis, Courier 6X SL analyzer measures samples taken from the process
stream. Each process stream has its own characteristic composition of elements, or of
minerals, and its own characteristic relationship between measured intensities and
concentrations. Calibration is the experimental determination of the equations to
calculate the concentrations from the intensities. A separate calibration equation, called
a calibration model, is needed for each element and for each process stream with
significantly different characteristics.
This means that the calibration must be updated whenever the average character of the
stream changes significantly. Therefore, the maintenance of the calibration is also very
important.
A prerequisite for calibration is that the analyzer is properly set up and in normal
working condition. This document does not cover the setting up of the analyzer. For
more information about setting up the analyzer, refer to the Courier 6X SL Installation
and Courier 6X SL Commissioning and start-up manual.
Before you start actual work, you must plan the calibration as described in chapter 2
Planning calibration process.
Calibration always includes two more or less simultaneous activities:
• Collection of information, which includes:
- Measuring the X-ray intensities of sample streams with the analyzer
- Taking physical calibration samples
- Analyzing the calibration sample in the laboratory. For more information about
analysis, refer to chapters 3 Taking calibration samples and 4 Checking data
collected for calibration.
• Determination of calibration model with the Outocal regression analysis program.
- The aim is to find calibration models with which the laboratory concentrations
can be calculated as precisely as possible based on the intensity data from
the online analyzer. This activity is described in chapter 5 Creating calibration
model.
The calibration of the analyzer can also be divided into different phases according to the
commissioning phase.
• The calibration normally starts with a simple calibration done during the first week
after the start-up when only few calibration samples have been taken and analyzed.
• The final stage of calibration is reached during the first month or months after the
start-up. At this stage, the calibration model is more complicated and normally gives
more accurate results than in the beginning.
• Follow-up of the calibration. To achieve good accuracy at all times, the calibration
must be maintained continuously, but the maintenance requires less effort than the
first two stages.
• Recalibration after major changes in the equipment setup.

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2 Planning calibration process
Plan the calibration process in advance to ensure accuracy of calibration and to avoid
unnecessary work and unnecessary breaks in normal plant operation. Proper sample
are the basis of calibration process.
• In the beginning, you need to determine the number of samples the laboratory can
analyze daily for the calibration without risking the accuracy.
• Next, you have to decide the calibration priority: you can either calibrate all the
streams at the same time or calibrate only the important streams first and other
streams later.
• At a later stage, you need to take samples only of concentrations seldom occurring
in the process.
2.1 Determining when to take samples
Calibration samples must have as diverse concentrations or intensities as possible
within the normal range of process.
• In the beginning, take samples regularly once a shift or once a day.
• In continuous processes, significant changes in the sample contents occur slowly.
Recommended number of measurements is two measurements per one shift or at
most three measurements per day.
• Artificial disturbances to the process causing changes seldom reflect the changes
occurring in reality and should be avoided. Calibration samples taken in such
situations often have to be deleted later.
• Watering the sample is, on the contrary, allowed to artificially lower the solids
content. For example, you can temporarily increase launder sprays or add a small
spray of water (5–10 liters per minute) into the multiplexer tank. The spray must be
diffuse enough to mix well with the slurry.
• When a new process is being started, avoid taking samples because process
parameters may vary widely as the process is being run in.
• After the laboratory results of the first 7–10 samples from a stream are available,
you can make a preliminary calibration and start looking for samples that have
different concentrations from the previous ones by following the concentrations
given by the analyzer.
.
WARNING
Never try using more variables in your calibration model than half the number of your
observations.

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2.2 Number of calibration samples
The number of measurements to make depends on how many elements interact, that is,
how many of them interfere with each other's analyses. Usually most elements with an
absolute concentration above 1 percent interfere with the measurement of other
elements.
The following table shows the number of measurements required for a good calibration.
For the first calibration used for process control, 10–15 measurements are enough.
Table 1. Number of calibration samples
Number of elements
interacting
Number of measurements
required
1 15
2 20
3 30
4 40
Example
The calibration is done for a Cu & Zn ore dressing plant. In many streams, there are the
two major metals and, in addition, Fe interacting with each other, which forms a system
of 3 interacting elements. For these streams, 30 measurements are needed for a good
calibration.
Frequently, in the final tail, only Fe has a significant concentration forming an interacting
pair with the measured Cu or Zn. 20 observations are sufficient in this case. Some
concentrates also need fewer than 30 samples because some metal concentrations
may be minor.
2.3 Selecting measurement time for first calibration
During calibration phase, use the following measurement times. (For normal analyzer
operation, divide the measurement times in half.)
• 30 seconds for most streams
• 1–2 minutes for concentrates
• 1–2 minutes for tails, impurities or secondary metals.
NOTE: When an ED channel is in use for some streams, times may need to be
longer.

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3 Taking calibration samples
In addition to this document, refer also to the analyzer IOMS manual when making
measurements for calibration.
Before starting the calibration process, decide the number of calibration samples to be
collected in one day. Typically, one calibration sample is collected.
Start the calibration process by collecting samples from the most relevant sample lines.
When you have approximately 10 comparable results from one sample line, make the
preliminary calibration for the sample line. After preliminary calibration, collect samples
which have diverse concentrations within the set limits. Follow the concentrations given
by the analyzer and collect the samples when the concentration is suitable.
Collecting representative samples takes time to collect because major disturbances that
create variability are usually developed in the process feed composition.
.
CAUTION
Do not take calibration samples from the calibration sampler directly by hand.
3.1 Preparations
Before calibration sample collection, make sure the samples are representative as
follows:
3.1.1 Checking process conditions
1. Check that the process state is normal.
- During serious problems samples may have characteristics that are too
different to be used for calibration of normal process conditions.
- Do not make measurements when element contents, solids contents of
slurries, or the particle size of solids are abnormal.
- When a new process is being started, take into account the fact that process
parameters may vary widely as the process is being run in.
2. Check that the analyzer is properly installed and configured.
3. Check that the analyzer, multiplexer, and the entire sampling system are in normal
operating condition and work correctly.
- Sample line status is OK.
- No alarms or warnings are shown on the analyzer CLI.
- Multiplexer screens are clean of trash.
- Primary sample flow to the multiplexer is within normal range.

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3.1.2 Preparing equipment
For calibration sample collection, you need sample buckets and a pen for marking the
sample data (time, date, and the stream name or symbol) on the bucket.
Bucket requirements:
• Reserve a separate bucket for each sample line.
• Identify the sample bucket with the sample line name.
• Buckets must be clean.
• Recommended bucket volume is 2–3 liters.
• Each bucket must be equipped with a watertight cover to prevent contamination or
spilling of sample during transportation.
3.2 Collecting calibration samples
To collect calibration samples:
1. Select in the analyzer user interface Operation > Sampling.
2. Click a sample line to open the Sample Details display.
3. Click Calibration sample to activate the calibration sample request.
- Click Cancel Calibration to cancel the sample request before the
measurement starts.
Figure 1. Collecting calibration sample

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4. Use a water hose to flush the calibration sampler with water.
5. Make sure that the sample cutters of the calibration sampler are clean.
Figure 2. Cleaning calibration sampler
6. Place a sample bucket under the correct outlet, which is shown on CLI.
7. Make sure that the measurement and calibration sampling starts.
- The sample measurement can stop before the intensity measurement and
sample cutting because the multiplexer does not fill, the sample is not flowing,
or an alarm has occurred.
8. Wait until the measurement and calibration sampling is finished.
9. Make sure that the sample volume is normal.
- If the sample volume is not normal, make sure that the sample flow is normal
and the sample is valid.
10. Close the sample bucket with the cover.
11. Write the sample ID on the label of the sample bucket.
- Sample ID is shown on CLI.
Figure 3. Writing sample ID
12. Click Accept to save the calibration sample data.

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- If the calibration sample is not valid, click Discard not to save the data.
13. Use water hose to flush the calibration sampler and its cutters with water.
NOTE: If the measurement does not provide a valid result, the reason is shown on
CLI and calibration sample data is not produced.
14. If measurement failed, destroy the sample.
3.3 After sample collection
After the first 10–15 samples have been taken from a stream and the preliminary
calibration has been made, add only certain samples essential to the calibration to the
data set.
Compare the concentration values including solids content with the values of all
previous calibration samples. In particular, compare samples that are different from the
previous ones or rarely occurring samples that are worth analyzing in the laboratory.
This comparison can be done before or after the sample has been taken. For more
information, refer to chapter 4 Checking data collected for calibration.

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4 Checking data collected for calibration
You need to check the concentrations of the elements determined in the laboratory. An
adequate variation of element contents and their combinations is the basis for
regression analysis calculation.
4.1 Range of variation
The range of variation of element contents must be sufficient to achieve good
calibration. The difference between the minimum and maximum element contents must
be at least 6 times the expected accuracy. For example, if the required absolute
accuracy is 0.8%, the minimum content must be 35% and the maximum content must
be 40%.
The following table shows an example where this rule is applied using the expected
accuracy for different concentrations. The table shows the ranges exceeding the
minimum for different levels of average element content.
Table 2. Ranges of element content variation
Average element content for slurry Ratio of variation (lowest :
highest)
< 0.3 % (low) 1 : 2
0.3 - 10 % (midrange) 1 : 1.6
> 10 % (high) 1 : 1.3
1 : 1.2
The following table shows an example where all variation ranges are satisfactory but Pb
is close to the limit.
Table 3. Example of ranges for slurry
Element Average Range Ratio
Fe 6 % 4 - 9 % 1 : 2.25
Cu 0.7 % 0.5 - 1.2 % 1 : 2.4
Zn 3.2 % 1.5 - 6 % 1 : 4
Pb 0. 68 % 0.6 - 0.9 % 1 : 1.5

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Make sure the measurements include a sufficient number of measurements of contents
clearly higher or lower than the average.
• The range can be considered as divided into four areas. At least 15 % of
measurements must be inside each area of the range.
The following figure shows an example of a calibration sample set that could be
improved, because data variation is not optimal. Circled areas marked with 1 have no
samples, whereas areas marked with 2 have too many samples.
Figure 4. Example of data variation
4.2 Restrictions due to process
The nature of the process can restrict the element contents distribution that can be
measured as follows:
• It may be impossible to measure simultaneously high contents of all elements in
slurry.
- The sum of the contents of all minerals cannot exceed 100 percent.
• Some element contents may correlate strongly: one decreases as other decreases
or vice versa.
• Some element contents can be almost constant in a process stream. In this case,
measure as varying a distribution as possible.

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5 Creating calibration model
This chapter describes how to find a reliable calibration model for each measured
concentration in each stream by using new web-based Outocal software. To use
Outocal, open it in your browser. The default URL is 192.168.56.20:9000, but this can
vary depending on your site configuration.
NOTE: Outocal requires a network connection to the analyzer and Internet Explorer
10 or newer, Chrome 40 or newer, or Firefox 35 or newer.
To create a calibration model, you need to:
• Import laboratory analysis data to Outocal.
- By default, Courier data is imported automatically to Outocal, but you can also
import it manually.
• Select linear variables with a high absolute t-value (typically above 2).
• Deselect data points with a high residual error or high influence if required.
• Create non-linear variables if required.
This creation process is iterative: you have to evaluate the calibration model after each
step that comes after the selection of linear variables, and if the model is not
acceptable, you may have to return to the previous step. Outocal updates the model
automatically as you select variables or points.
The following figure shows the general, simplified principle of calibration model creation.
Figure 5. Calibration process (simplified)

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Each arrow in the previous figure represents an evaluation of the model. If the model is
good, you can take it into use without proceeding to other steps. If the model is not
good, move one step forward or backwards in the process. You can also move several
steps backwards as required.
5.1 Symbols used in calibration models
The following table shows the symbols used in calibration models.
Table 4. Symbols used in calibration models
Symbol Description
C[E] Calibration model C for element E
N[E] Variable, called model input in Outocal.
The intensity of the element, for example
N[Fe].
scC Compton scattering.
scR Rayleigh scattering.
R Regression coefficient. All Rs (R0, R1, R2
and so on) are empirical calibration constants.
# Measurement channel in Outocal. This
channel is called an element channel in the
Courier analyzer.
% Symbol for laboratory assay in Outocal.
5.2 Importing laboratory data to Outocal
For creating a calibration model, you need to have both the analyzer measurements
and laboratory analysis for calibration samples. By default, the Courier analyzer adds its
calibration measurements to the calibration database in Outocal. You have to import or
manually type the laboratory analysis results into the calibration database. Outocal
automatically combines imported Courier data and laboratory data based on the
matching Courier measurement ID and laboratory analysis ID.
NOTE: Only CSV files are supported in addition to Courier calibration (.clb) and
Outocal calibration model (.ocl) files. If the laboratory analysis is in Excel format, you
need to save it into CSV format with Save As in Excel before importing data to
Outocal.

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To import calibration data to Outocal:
1. Click the Manage Calibration Database icon in the stream card to open the
calibration database.
Figure 6. Stream card
2. Click Import from File.
3. Click Open File and select a file format supported by Outocal.
4. Click Open.
5. The Import settings dialog opens. In this dialog, you can preview the file to be
imported under File preview.

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Figure 7. Import settings dialog
6. Define whether the file has a header row by selecting or deselecting the Imported
file contains a header row check button.
7. In the Start import from line field, define the line number in the file from which the
data import is started.
8. Click Open File to open the import wizard view.
- This view shows the measurement channels (marked with #) and laboratory
assays (marked with %) for which Outocal proposes data to be imported.

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Figure 8. Import wizard view
9. Check and adjust import columns as required by dragging and dropping the
columns.
10. Once every data column is in the correct slot, click Import to start importing data.
11. The Confirm Data Format dialog opens. Select the date and time format you want
to use for the data to be imported and click the Set Date Format button to confirm
the settings.
12. The File successfully imported dialog opens. Click OK to open the calibration
database where you can view the data you imported.
NOTE: Only .csv files are supported in addition to Courier calibration (.clb) and
Outocal calibration model (.ocl) files. If the laboratory analysis is in Excel format, you
need to save it into csv format with Save As in Excel before importing data to
Outocal.
You can also import existing calibration models from Outocal (.ocl files) by following
these same steps.

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5.2.1 Adding and editing laboratory data in calibration database
To add or edit laboratory data in the calibration database:
1. Double-click the cell that you want to edit.
2. Accept changes by pressing Enter or by clicking some other cell in the database.
- Outocal shows at maximum 16 rows of data per page. You can scroll the data
with the navigation buttons at the bottom of the display.
Figure 9. Managing data in calibration database
.
CAUTION
Never edit any calibration data coming from the Courier analyzer, as this ruins the
calibration.

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5.3 Evaluating calibration model
NOTE: Keep the model as simple and easily understandable as possible: the simpler
the model, the more robust it will be.
Calibration model has to be evaluated repeatedly during the model creation process.
Outocal supports this process by updating the model’s statistical indicators in the Model
Info column. The Value column shows the latest changes and the Old Value column
shows the last saved changes.
Figure 10. Evaluating calibration model

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The following table shows the statistical quantities used in evaluation of calibration
models. An acceptable calibration model must meet the requirements listed in the table.
Table 5. Statistical quantities used in evaluation of calibration models
Statistical quantity Description Requirement
σ (absolute sigma) Absolute error of the model as one standard deviation.
Also called standard error or residual error. Its calculation
is based on the difference between the laboratory assay
and the value given by the calibration model.
• The estimate is not accurate for small observation
numbers.
None
Relative σ (relative
sigma)
This is the residual error as one standard deviation in
percent relative to the average of the concentrations of
the calibration samples.
Typical values for slurries are:
• Concentrate main
components: 2– 5 %
• Feed main components:
3–8 %
• Waste rock and
secondary constituents:
6–12 %.
R^2 R^2 is the correlation coefficient between the known
laboratory value (x-axis) and the predicted value (y-axis).
It tells how well the y-axis values explain the x-axis
values.
• Increases as the number of variables increases.
• Increases as the variation range of the estimated
concentration increases or the residual error
decreases.
R^2
> 0.6
F Describes the reliability and stability of the calibration
equation.
• A too low value means that for a different set of
samples the calibration coefficients might be quite
different.
• Generally increases as the number of independent
variables of low significance decreases.
F > 10
σ-Count (counting
sigma)
Statistical counting error.
• Decreases as measurement time increases.
• In the case of very low concentrations, the too short
measurement time of the element intensity sometimes
limits the measurement accuracy.
σcount < 0.8…~1.2 σabs

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Statistical quantity Description Requirement
t-value Shows whether the regression coefficient of a variable is
significant for a given combination of variables.
• Note that this is not the standard t-test value as
defined in statistics.
• Used for comparing the coefficients of a calibration
model with each other in respect of their significance.
• Warning: High t-values alone are not a sufficient
criterion of calibration model quality. Never use them
as a basis of comparison between models.
|t| > 2
Residual The absolute error of the assay calculation for one
observation.
None
Standard residual The error of the assay calculation for one observation
divided by the absolute standard deviation for the whole
set.
< 3
Studentized residual Studentized residual is the quotient resulting from the
division of a residual by an estimate of its standard
deviation and is used in the detection of outliers.
None
Influence Influence index tells the magnitude of influence each
observation has on the regression equation.
• Influence index is calculated in Outocal based on
Cook statistics but improved so that it is more
sensitive to outliers in data.
• For some observations, the influence index is above 3
even if the standard residual is small. This means that
the observation has been singled out to have a big
influence on the regression. When the number of
observations is small, many of the observations often
have high influence numbers.
• Sometimes, if an observation with an exceptionally
high influence number is deleted, some variable in the
model is not needed any more by the other
observations. Therefore this observation needs
special attention.
≈ standard residual
For more details, refer to
Table 6.
σ -Type Sigma of the measurements: the standard deviation of
the measurements for each measurement channel.
None
If the calibration model does not meet the requirements listed in the previous table, you
need more observations or less explaining variables. Delete also suspicious points. If
the last requirement in the table is not met, add more bad points.

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5.4 Starting calibration model creation
To start creating a calibration model in Outocal:
1. On the Outocal tab, select an assay (for example. Au, Cu, Fe or similar) for a
stream.
Figure 11. Stream selection view
2. Click the Add New Model button to start the creation of a new model.
3. You can rename a model and edit its description by clicking the model title.
Figure 12. Editing the name and description of calibration model
4. Click the Edit Model button. The Calibration Models view opens.

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Figure 13. Calibration models view
The following figure shows the whole Outocal calibration model view where you can
create your own calibration models.
Figure 14. Outocal calibration model view

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5.5 Selecting variables
1. Start selecting variables (Model Inputs), that is, all Courier-measured intensities,
one by one.
2. As you select the variables, Outocal updates the calibration model automatically.
Figure 15. Variable selection view
3. Remember to evaluate the calibration model as you make changes.
- Do not include variables with absolute t-values lower than 2 in the calibration
model. Removing these variables should typically improve F-value.
NOTE: The number of observations/calibration measurements (points) must be at
least twice the number of variables.
5.5.1 Taking percentage solids into account
The aim is to obtain the concentration values of the elements as percentage in solids.
The following subsections describe typical basic calibration models that take the slurry
density into account in different ways.
5.5.1.1 Single scattering line (Compton)
To measure, and compensate for, solids content of a sample, use the scattering
intensity. Compton scatter is dominantly caused by light elements (atomic number Z
below 20). The main source of Compton scatter in slurry samples is caused by
hydrogen and oxygen in water, therefore the Compton scattering correlates with water
in the sample and is inversely correlated with the percentage of solids. Therefore
scattering intensity generally decreases when solids content increases.
The Compton (incoherent) scattering reflects the solids best.
In addition to the fluorescence intensity caused by the element in question, some
scattering-based background is always present in the element channel. Depending on
the ratio of the background intensity to the element intensity being measured, you can
use the following calibration models that take the slurry density into account.

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Normal element concentration
C[E] = R1 N[E] + R2 N[scC] + R0
In this case, the intensity N[E] in the element channel increases as slurry density
increases. The increase is offset by the scattering intensity, N[scC], which decreases at
the same time.
Low element concentration
C[E] = R1 N[E] + R0
In this case, the element channel contains a suitable scattering-based background, so
that N[E] is almost constant, even if the solids content varies.
Very low element concentration
C[E] = R1 N[E] + R2 N[scC] + R0
In this case, N[E] decreases as slurry density increases, because it contains a large
background. Subtracting a term proportional to the scattering eliminates the extra
background.
High and varying element concentration
If there are large relative variations in the concentration of an element, use the model:
C[E] = R1 N[E] + R2 N[scC] + R3 N[E] x N[scC] + R0
or
C[E] = R1 N[E] + R2 N[scC] + R3 N[E] / N[scC] + R0
One or both linear terms are often not needed. This model takes into account that the
slurry density correction must be smaller for a low element concentration and larger for
a high element concentration.
5.5.1.2 Two scattering intensities (Rayleigh and Compton)
When both Rayleigh (coherent) and Compton (incoherent) scattering line intensities are
used, you can compensate for the influence of solids composition.
This method requires a fairly long measurement time about 1 minute. It has improved
calibration for nickel concentrates measured with a Mo tube. Nickel concentrates have
typically a complex mineralogical composition with both Ni and Fe in several minerals
each yielding a different intensity per unit metal. The concentrate also often contains
fine talc. This method can also be useful for similar other concentrates with a complex
structure.
This method has also been useful for Fe concentrates that have a simple structure but
for which a good accuracy, about 1% relative, can be achieved with this method.

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Use the linear model: R1 N[E] + R2 N[scC] + R3 N[scR] + R0
5.5.1.3 Constant element
When the concentration of an element in the solid matter is almost constant, use the
following calibration models.
When element concentration is normal:
C[E] = R1 N[E1] + R2 N[E2] + R0
When concentration is high and varying:
C[E]= R1 N[E] + R2 N[E2] + R3 N[E1]/N[E2] + R0
5.5.2 Taking interfering elements into account
The following figure shows an example about an element interfering with the
measurement of another element. In the figure, Fe content affects the Cu intensity I.
Figure 16. Effect of Fe content on Cu intensity
I = intensity Cps = counts per second
I
(cps)
Cu (%)
Cu
High Fe
Low Fe

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When you have to take element interference into account, use the following basic
calibration models.
When the variation of the measured element is small:
C[E] = R0 + R1 N[E1] + R2 N[E2]
When the variation of the measured element is large:
C[E] = R0 + R1 N[E1] + R2 N[E2] + R3 N[E1] N[E2]
If the measured element absorbs a large part of its own radiation, replace the interfering
element with itself:
C[E] = R0 + R1 N[E] + R3 N[E] N[E]
When X-ray peaks overlap, use:
C[E] = R0 + R1 N[E1(+E2)] + R2 N[E2(+E1)]
5.6 Checking data points
Check data points for errors or high influence and deselect the points as instructed in
the following subsections.
You can deselect data points from the Correlation and Residual plots and data tables.
Data tables can be sorted for each column to support the selection process. Deselecting
and selecting data points automatically updates both the calibration model and the
statistical indicators for the model.
Figure 17. Deselecting datapoints from table

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Figure 18. Correlation plot
NOTE: Outocal automatically deselects all Courier calibration data points without
laboratory assay values. To add laboratory assay values to Outocal, refer to section
5.2 Importing laboratory data to Outocal.
5.6.1 Deselecting points with errors
1. Examine each point using Outocal Correlation plot (analyzer estimate versus
laboratory analysis) or Residual plot (error for each data point) and deselect any
points with high errors.
2. Re-examine the residual errors for the previously deselected data points. For
example, if a point now has a lower standard residual error, return the point to the
data set.
NOTE: You can deselect at maximum 10 percent of the points.

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5.6.2 Deselecting points with high influence
1. Deselect points with an influence number higher than shown here:
Table 6. Suspect influence number as function of number of observations
Number of
observations
<10 10–15 16–25 26>
Suspect
influence
number
8 5 4 3.4
2. Re-examine the residual errors for the previously deselected points and re-select
those points if their standard residual error has decreased.
NOTE: Lonesome extreme points with very low or very high assay values often have
high influence numbers. You have to retain them in the beginning of the calibration
process, when only few points are available.

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5.7 Creating non-linear variables
If you are not able to create a satisfactory calibration model with linear variables and by
deselecting data points because the data is non-linear by nature, you can choose to use
non-linear variables. However, remember that non-linear variables often give only a
marginally better accuracy or F-value, and therefore it is usually safer to use only linear
variables. Non-linear terms can give high errors for observations outside of the
calibration range unless the non-linear variables are well founded.
By multiplication and division, you can create non-linear variables from the linear
variables selected for calibration model.
• Typical linear variables used for creating non-linear variables are N[E1] x N[E2],
N[E1]/N[E2] and N[E] x N[scC] or N[E] / N[scC] for slurries.
• Select linear variables with high t-values above 5.
• Use only two linear variables per one combination.
Try to find combinations of linear variables mathematically as follows:
• Identify two variables: N[1], the variable with the highest t-value in the linear model,
and N[2], the variable with the second highest t-value in the linear model.
• Multiply the variable with the highest t-value with itself: N[1]2.
• Combine the two variables N[1] and N[2]:
- If the two variables have the same sign in the linear model, multiply the
variables with each other: N[1] x N[2].
- If the two variables do not have the same sign in the linear model, divide the
+variable with the -variable: +N[1] / -N[2] or +N[2] / -N[1].
• Multiply the variable with the second highest t-value with itself: N[2]2.
• You can also try combining the variable with the third highest t-value, N[3], with the
two previous variables N[1] and N[2] in a similar way.
NOTE: Sometimes non-linear variables allow you to accept points that you had to
deselect for the linear calibration model. Check the situation. It may also be useful to
deselect some additional points.
NOTE: If a point has been deselected based on the influence number, check once
more all points for high standard residuals or influence numbers.

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5.8 Checking measurement time
Outocal suggests a minimum theoretical measurement time based on the assumption
that the error due to measurement time (sigma count) must be at maximum half of the
total measurement error. Outocal updates the measurement time as you edit the
calibration model.
Measurement time needs to be set separately for the Courier analyzer. Because the
changeover from one sample to another takes time, there is a minimum measurement
time after which the analyzer cycle time cannot improve.
For Courier X systems, the minimum measurement time is 30 seconds. For more
information about setting the measurement time in the analyzer, refer to the Courier 6X
SL IOMS.
5.9 Inputting calibration model into analyzer
To take the calibration model into use:
1. Copy the model from Outocal.
Figure 19. Copying model from Outocal
2. Paste the model to the HMI view in Courier CLI as follows:
- Select Main Menu.
- Select More.
- Select Options – Courier Management.
- Click Login and log in.
- Click Get parameters.
- Select the Lock parameters for editing option.
- Click OK button.
- Select Assay Models:

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Figure 20. HMI view
3. Click OK.
4. Log out of Courier CLI by clicking Logout .
5. If you want to keep track of the calibration models used in production, click in
Outocal the Set as Production Model button. Note that this does not automatically
update the model to the analyzer.

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6 Maintenance of calibration
Once you have used a sufficient number of calibration samples and found the
appropriate calibration model, you can start the maintenance of the model. During
maintenance, variables do not generally change, only coefficients.
6.1 Updating calibration model after 2-3 months
As you continue getting more calibration measurements, you can now and then repeat
the procedures described earlier in this chapter. The significance of the calibration
model (F-value) normally increases as the model evolves. The range of applicability
also increases, likewise the accuracy through the addition of more linear and non-linear
variables.
Once you have 30–50 observations from a period of 2–3 months, a good calibration
model for the process conditions during that period should be ready. If the result is
unsatisfactory, you must carefully delete abnormal observations from the calibration
data set.
When a good calibration model has been obtained, increasing the number of
observations starts reducing the accuracy at some point. This is caused by the changes
in the control and feed quality of the plant. The general characteristics of the streams
change with time, and the same calibration model is not good for both the beginning
and the end of the period covered by the calibration measurements. When this
happens, you can start the maintenance of the calibration.
.
CAUTION
Do not use composite samples to fine-tune the calibration. Bad sample flow or no
sample flow can corrupt the Courier average.
It is recommended to occasionally continue taking calibration samples and analyze
them in the laboratory. The new data is added to the previous data in the calibration
database in Outocal. When the calibration model in use is reviewed in Outocal, the new
data is not shown, so it is not used in the regression analysis. In this way, the existing
calibration model coefficients do not change. To use new calibration samples, you need
to create a new calibration model in Outocal.
• If there is no significant improvement in statistical values for the new model
compared with the old model (all new points are more or less randomly between ±
2σ in the Correlation plot), there is no need to change the calibration model.
• If the error seems to grow, many new observations are beyond ± 2σ, or if errors are
practically all to one side for several observations, you probably have to create a
new model including the new observations and excluding the oldest ones.

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6.2 Special cases
If several consecutive assays show a bias in comparison to the analyzer concentrations,
a short-term solution is to change the additive constant of the calibration formula to
remove the bias. Note that this does not change the trends detected by the analyzer.
There are two long-term solutions: one for slow changes in stream characteristics and
other for sudden changes.
6.2.1 Slow changes in stream characteristics
1. Delete the oldest observations as new ones become available.
2. Repeat the regression analysis from time to time to develop new coefficients.
Keep the number of calibration measurements used at 30–60 from a time period short
enough from a time period short enough in comparison to the expected rate of change.
6.2.2 Sudden changes in stream characteristics
1. Determine which observations occurred before the change and which after the
change.
2. Save the old calibration model with a new name by clicking the Save As button and
use the model to calculate a new calibration model based on samples taken after
the change in stream.
6.2.3 Recalibration after major equipment change
When an X-ray tube, spectrometer, detector or a similar piece of equipment is changed
in the analyzer, the analyzer is renormalized as specified in the analyzer IOMS. After
that, the old calibration models should apply. However, depending on the parts replaced
and the analyzer, there can be errors that you can correct as instructed in this chapter.
A prerequisite for recalibration is that the standard reference briquettes have been
measured at regular intervals. The minimum requirement is that the intensities of the
standard briquettes have been measured during the time the measurements for the
current calibration were made, possibly excluding level shifts.
No large scale metallurgical recalibration is required.

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