Windmill Software Ltd
Data Acquisition Intelligence

October 2008

The Newsletter for PC-Based Data Acquisition and Control
Issue 123       October 2008
--------------------ISSN 1472-0221----------------------

Welcome to Monitor.  This month we're extolling the 
virtues of Pivot Tables in Excel, and discussing the use 
of LVDTs to measure displacement.

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* Measuring Small Changes in Position
* Analysing Data in Excel: Are Pivot Tables the Answer
* DAQ News Roundup

Measuring Small Changes in Position

When monitoring small movements a  Linear Variable 
Differential Transformer, or an LVDT, is commonly used.  
For instance, you can use an LVDT in shock testing, to 
measure the thickness of machined parts and to measure 
displacement of concrete during strength testing.

How an LVDT Works

An LVDT comprises three coils wrapped around a tube. 
The two outer coils are called the secondary coils, 
whilst the middle coil is the primary coil. Inside the 
tube is a moveable magnetic core.  You attach the object 
whose position is to be measured to this core. As the 
object moves, the core slides within the tube. 

A constant alternating current driven through the 
primary coil of the transformer causes a voltage to be 
induced in each secondary coil. As the core moves, the 
inductances change, causing the voltages induced in 
each secondary coil to change.  

When the core is exactly between the two secondary coils, 
the voltage output is zero. As it is displaced in one
 direction, the voltage in one coil increases as the 
other decreases, causing an output voltage. The magnitude 
of the output voltage is proportional to the distance 
moved by the core. 

The sliding core does not touch the inside of the tube. 
Parts do not rub together or wear out, making the LVDT 
very reliable. This lack of friction also leads to the 
LVDT being able to measure infinitely small changes in 
core position.  The only limiting factor is in the 
resolution of the data acquisition equipment used to 
monitor the LVDT.  

Computerised Data Logging

LVDTs normally use an AC excitation, and give an 
AC output signal. Data acquisition equipment for AC 
energised LVDTs therefore require additional oscillator 
and demodulation circuits. Given the specification of 
the LVDT, these circuits will be supplied in the 
appropriate physical format. 

DC energised LVDTs are available with the oscillator-
demodulator circuit built-in. These require an 
excitation supply and give a normal low voltage 
DC output signal. The Microlink 3806 module, for example, 
provides the excitation and signal conditioning for 
LVDT probes. This is part of the Microlink 3000 measurement
and control range from Biodata Ltd 

For more information on using LVDTs contact 
[email protected]

Analysing Data in Excel: Are Pivot Tables the Answer?

In issue 116 of Monitor 
( I explained 
how to use an array formula to perform calculations on 
values matching two or more criteria. I also told you 
how to return several values from one formula - the 
three largest readings in a list for example. This 
month we'll find out how to do similar things using 
a pivot table. You can download an example spreadsheet 

Pivot tables can be quite fiddly to set up. Once you 
have done so though, it is easy to display different 
pieces of information with a few mouse clicks. If you 
were using, say, an array formula to do the same thing 
you would have to keep editing the formula.

Another advantage is that a pivot table eliminate 
errors than could otherwise creep into your formula, 
either through typing mistakes or a faulty understanding 
of how the formula works.   A pivot table's data is 
valid and transparent: it is easy to see if you have 
made a mistake creating your pivot table.  It is not 
always obvious if you have made a mistake when using 
a formula to analyse data.

Imagine you have a table of data with temperature and 
humidity readings.  With a pivot table you can quickly 
display the average temperature at each humidity level.

Creating a Pivot Table

To create a pivot table your data needs to be laid out 
in a particular way. Readings collected by the free 
Windmill Logger program comprises lists of timestamped 
data. For example
Time      Temp  Humidity
Secs      oC    %
16:27:42  9.23  63
16:27:43  9.23  63
16:27:44  9.22  62

To create a pivot table the first row must contain 
the name of the column of data below it. The next 
row must contain the first set of data items. As 
you can see, Windmill Logger also includes a row 
of unit names. Before creating your pivot table 
you need to move these to above the data names - 
like so
Secs      oC    %
Time      Temp  Humidity
16:27:42  9.23  63
16:27:43  9.23  63
16:27:44  9.22  62

Now, in Excel, click anywere in any of the data 
columns. From the Data menu select Pivot Table. 
Choose to analyse an Excel list and create a 
PivotTable. Step through the rest of the Wizard.

A grid appears with instructions to "drop data and 
fields here". Above this is the PivotTable 
dialogue box showing your column names.  For our 
example you need to drag "Humidity" to the 
Rows area and "Temperature" to the Columns area. 
By default the pivot table thinks you want to sum 
the data. However, we want the average. So 
double-click "Sum of Temperature" and change to 
"Average of Temperature". If you make a mistake 
right-click the pivot table, select Wizard > Layout 
and change your selections. To remove a data column 
just drag it off the pivot table.

The pivot table will show the average temperature 
for each distinct humidity reading.

With a pivot table you can easily change the data 
you are analysing. For instance, you could drag 
Humidity off the table and replace it with Windspeed 
(assuming you have a column of Windspeed readings 
of course). You can also show average Temperature 
against both Humidity and Windspeed.  Using 
Wizard > Layout put Humidity in the Row area, 
Windspeed in the Column area and Average of 
Temperature in the Data area. (Just drag anything 
in the wrong area away in the Layout Wizard.)

When I discussed Array Formulae, I showed how to 
find a conditional value. For example, the 
average temperature when humidity was 62%. You 
can't do this directly with a pivot table, but 
can achieve a similar result by hiding some 
results. Click the down arrow by Humidity in the 
pivot table, and deselect values below 63%.  Only 
average temperatures for readings over 62% are 
now shown. Hiding some readings in this way can 
be extremely useful. For instance, using an array 
formula you can show the three largest readings in 
a column. Using a pivot table you can not only show 
the three largest values but also how often they 
occurred and at what temperature or humidity.

You can sort and format the data in a pivot table 
exactly as you would normally. Just select the data 
values then use Excel's Format and Data menus.

A pivot table has many advantages but it does have 
limitations.  For instance, you can only use the 
functions provided: sum, count, average, max, min, 
product, standard deviation, etc. You cannot create 
your own custom formulae. 

To answer the question posed at the beginning of 
this article - are pivot tables always the answer? 
Of course not, but as they offer flexibility and 
error free analysis I've been won over to them and 
they are now the first analysis technique I consider.

Further Reading

Using Excel for Data Acquisition and Control

Monitor 116: Using Array Formulae

DAQ News Roundup

Welcome to our roundup of the data acquisition and 
control news.  If you would like to receive more 
timely DAQ news updates then grab our RSS newsfeed 
at  Read for notes
on how to display the news on your own web site, 
read it via e-mail, mobile phone or in your browser.

Thermocouple accurate beyond 1300 oC
   One of the ways to make aircraft engines more 
   efficient is to run them at higher temperatures. 
   However to do so safely requires heat-treating the 
   super-alloys of which certain engine components are 
   made to ensure they can withstand hotter conditions.  
   This process involves exposing these components to 
   very specific temperatures in excess of 1300 oC. 
   Achieving exact temperatures is critical and getting 
   it wrong by more than two degrees in either direction 
   can have major implications. Thermocouples are used 
   to ensure correct temperatures are achieved in this 
   process.  Previously, thermocouples only offered an 
   accuracy of plus or minus three degrees.  Now NPL 
   has reduced thermocouple uncertainties to less than 
   one degree.
   Source: NPL

Battery-Free Chemical Sensors
   GE Global Research have developed a battery-free,  
   radio-frequency identification (RFID) sensor.  Billed 
   the "first-of-its-kind", a single sensor provides a 
   highly selective response to multiple chemicals under 
   variable conditions.  Without a battery, new sensors 
   can be designed to be smaller than a penny and 
   manufactured at very low cost.  The power is obtained 
   wirelessly from the sensor reader.
   Source: GE Global Research

Fastest Bar Code Reader
   Building on a series of recent breakthroughs in 
   ultrafast analogue-to-digital conversion, UCLA 
   engineers have designed a bar code reader that is 
   nearly a thousand times faster than any device 
   currently in use. There is a need for speed as the 
   volume of information in bar codes is increasing and 
   they are becoming integrated into real-time sensor 
   networks;  plus there is a requirement for high-speed 
   scanners for non-contact position and displacement 
   sensing, as used in real-time inspection and 
   monitoring in industrial applications.
   Source: UCLA

Sensor Could Help Avert Pipeline Failures
   Researchers at the National Institute of Standards 
   and Technology and Colorado School of Mines have 
   developed a sensor that quickly detects very small 
   amounts of hydrogen accumulation in pipeline steel. 
   The new sensor could provide early warning of pipes 
   that have accumulated excessive amounts of hydrogen - 
   a notorious source of embrittlement - and avert 
   potentially disastrous failures of pipelines carrying 
   hydrogen fuel.
   Source: NIST

Fieldbus Foundation and ISA Announce Collaborative Wireless Initiative
   The Fieldbus Foundation and ISA have announced an 
   agreement to implementat wireless backhaul transport 
   networks.  This technology initiative is based on 
   shared interests in serving the needs of end users 
   and suppliers of wireless systems in 
   industrial automation.
   Source: ISA

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Windmill Software Ltd, PO Box 58, North District Office,
Manchester, M8 8QR, UK
Telephone: +44 (0)161 833 2782
Facsimile: +44 (0)161 833 2190
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