InfraMation 2012 – Call for Abstracts

Call for Papers

The InfraMation 2012 Call for Papers is open until April 2, 2012. FLIR Systems and the Infrared Training Center (ITC) are accepting 150-250 word abstracts of presentations to be delivered to an InfraMation audience consisting of more than 500 condition monitoring engineers, maintenance technicians, building inspectors, restoration contractors, and test and measurement buyers. Submit your abstract through this simple online form.

Important Dates

• Presentation Abstracts Due: April 2, 2012
• Authors Learn of Acceptance by: May 18, 2012
• Complete Manuscripts and InfraMation Registration Due: July 20, 2012
• Complete PowerPoint Presentations due: August 17, 2012
• InfraMation 2012 Kicks Off: November 6, 2012

Benefits & Requirements
Why should you present at InfraMation 2012?

• Conference registration fee discount
• Qualify for full refund on already discounted conference registration fee
• Identify yourself as an infrared expert in your field
• Future validation for clients and customers
• Expand your professional and business referral network
• Represent your organization on a big stage
• Publish your paper on a searchable CD that every InfraMation attendee receives

InfraMation is the largest infrared camera user conference in the world. As thermal imaging becomes more mainstream, early adopters such as yourself will be sought out for your expertise, and InfraMation is the place to get recognized!

The only “hard” requirements are that your paper be non-commercial in nature (for sponsorship or exhibition opportunities, click here) and submitted in English. Abstract approval is based on clarity, appropriateness and technical merit of work.

About Emissivity Tables

Emissivity tables may or may not contain real useful information concerning the actual emissivities of the objects you wish to measure.

There can be many variations within and among different emissivity tables. Here are some factors of concern:

• Total Normal (broadband, perpendicular) emissivity - This is the emissivity over a very wide waveband. It may or may not be close to the actual emissivity with respect to your infrared camera.
• Midwave emissivity - Some tables are listed as shortwave (now called midwave) or at a specific narrow short waveband. Even if the emissivity is specified to be within the same spectral waveband as your infrared camera, it still may not be as accurate as you suspect. This is due to differences in camera detector responses.
• Longwave emissivity - Longwave tables can also be somewhat unreliable for the same reasons described for the shortwave. Older cameras used different detectors that had different responses within the long wave band.
• Narrow waveband - A narrow band can be just as unreliable as a wide band. Some materials can have significant changes in emissivity over small wavebands.
• Temperature - Some tables take into account the temperature of the object when the emissivity was measured. If you consider the previously mentioned variables, this does not necessarily make the tables any more reliable.
• Conditional (rough, smooth, corroded, rusty) - Conditional parameters seem to offer useful information concerning emissivities, but it is sometimes quite difficult to ascertain the condition of a metal surface by looking at it. If you use an emissivity table to determine the emissivity of copper, you may find values ranging from 0.05 to 0.86, depending on the surface. Copper that appears to be very tarnished can still have an extremely low emissivity.

So, what is one to do regarding emissivity tables? First, realize their limitations. They can offer a ball park estimate. If you really would like to use emissivity tables, the best thing to do is to create your own based on measurements taken with your camera.

Click this link for instructions on how to measure emissivity.

Accuracy Specification of FLIR Cameras

How accurately can the camera measure an absolute temperature?

Most FLIR Thermography cameras have a specified accuracy of  ±2 ºC (±3.6 ºF) or ±2% (whichever is greater) of reading for a blackbody target (emissivity ~ 1).

For example, for objects that are 100 °C or lower, the temperature reading off a blackbody can be 98°C to 102°C and be within specification. Similarly for objects above 100°C, say 200 °C, the reading could vary between 196°C and 204°C.

Some science cameras such as the SC660 are specified ±1°C or ±1% of reading.

This means that any camera, at any environment condition (within specification), at any time will give a reading within the accuracy specification.

However, a particular camera, at the same environment condition, will have a statistical repeatability of measurement that is much better than this. Typically close to the NETD value. This is also applicable when you compare adjacent pixels, provided your target(s) are optically resolved. This means that much higher accuracies can be achieved by comparing values with a known reference source in the image scene.

Errors & Omissions Liability Insurance

Error and Omissions Liability Insurance is a topic that has come up repeatedly in our message boards through the years. I have consolidated the most relevant information from all or our posts here for convenience. Hope this is useful.

---

We found a reasonable policy through this agent:
Elsa Escobar
Commercial Lines Underwriter
Costanza Insurance Agency, Inc.
e.escobar@cia-ca.com  
800.300.9775 x12
It took her some time but she says it would be much easier now that she's researched it once. Send her an email and add "Thermography insurance referral" on the subject line.

---

We ended up purchasing a General Liability Policy with 3M coverage, and added a Marine Policy to cover the camera. (The Marine Policy) is also used for contractor's Tools, and anything movable. Your best bet appears to be with and Independent Insurance company who has access to a wide variety of companies to draw from.

Infrared Thermography for Buildings

Learn how a Thermal Imaging Camera can benefit you for building work.

Infrared Thermography for Buildings

Measuring Body Temperature with an Infrared Camera

by Mikael Cronholm and Gary Orlove

From a biological standpoint, human beings are so called warm blooded animals. That means that we maintain a fairly constant body temperature, regardless of the surrounding temperature. The term body temperature (that we compare with when we decide whether a person has a fever or not) refers to the inside temperature, or core temperature of the body. The outside of the body is nearly always colder. It must be, because as we convert the energy from our food when we do work, we also produce heat. That heat has to go somewhere and if the outside and inside temperatures were the same, no heat transfer would be occurring.

None of us have a constant metabolism, or energy conversion, over time. It varies with our activity level. That means that the amount of heat we need to lose also changes with time. Our surrounding temperature also changes up and down, which means that sometimes we need to conserve heat and sometimes we need to increase the cooling by increased evaporation of liquid, we start to sweat more. Sweating is something we always do, just more or less depending on the situation.

To be able to use non-contact measurement for fever screening purposes, we need to find a point on the outside of the body that is close to the inside temperature – our “body temperature”. Because the outside is colder, and varies from place to place on the body, it is obviously the highest temperature on the outside of the body that is also the closest to the inside temperature. So we want to look for a warm spot on the outside.

Measuring Thin Film Plastics

A common application that is well suited to IR filters is that of measuring thin film plastics. Since the process of making thin plastic film itself is highly temperature critical, it is imperative to evaluate both the temperature and the uniformity of the plastic as it exits the extruder or web process. The product is typically moving at high speeds which precludes the use of contact temperature methods.

Most plastic films have spectral characteristics similar to polyethylene (depicted in the figure below) which is transmissive in both the short wave and long wave IR regions. Measuring thin film plastics can be challenging since without using a filter, you see “through” the plastic and measure the objects behind the plastic, rather than the plastic itself.

Spectral transmission of Polyethylene film with spectral response of plastics filter

Black Ice Thermal Images

Please see thermal images and associated visual images of black ice below:

Infrared Wildlife and Black Ice Detector - Looking for Feedback

by Rosaele Tremblay

Hello, I am a high school student writing a paper for my science project and I would like any feedback from the InfraMation readers (scientists or thermographers to see if I am on track with this idea or if anyone has suggestions as to how we can make this work. Thank you for any input.

You can provide comments and suggestions for Rosaele by leaving a comment on this post - Editor

Introduction
The electromagnetic spectrum includes gamma rays, X-rays, ultraviolet, visible, infrared, microwaves, and radio waves and each of them has a different wavelength and frequency. Infrared radiation is between visible light and the microwave portions of the electromagnetic spectrum and it is not visible to the human eye. Some animals do exist which see in infrared such as a few different snakes. Three categories exist in infrared: near, mid and far-infrared. Near-infrared is the closest to visible light and far-infrared is closer to the microwave portions. Infrared radiations are all around us every day coming from sunlight, a fire, radiator, a warm sidewalk and the TV remote. Everything on earth gives off heat when molecules begin to move and the higher the temperature of an object, the more the atoms and molecules will be moving which will produce a greater amount of infrared radiation. Objects with a temperature above absolute 0 radiate in infrared including the objects we perceive to be cold or freezing such as ice cubes or objects which are hot but do not visibly appear to be hot emit heat.

These shots of a coffee mug are in three different palettes to show that we assign the colors to gray steps. Human eyes see ten gray steps so to see the colors in definition we can assign 10 colors to them like in these shots. In these, white is hot and black is cool, but we can also invert these so that white is cool and black is hot, this is up to the thermographer.

Analyzing Building Images Acquired at Different Times

A camera user writes:

"I find that images taken of the same structure, not much separated in time, sometimes look very different.  This poses a problem for me as I’m trying to compare the heat images of different houses (to detect homes that need weatherization).  Presently I’m not confident that images of two homes reflect actual differences in the structures, or are caused by minor environmental changes or even by artifacts in the photography.  Here is an example.

Attached are two nighttime images of the front of my house, which faces east.  IR0310 was taken at 10:40 PM, IR0408 at 11:11 PM. (The clock on the camera is two hours fast.)  It was a cold night with little temperature change over the half hour between pictures.  The house thermostat was constant. 

I've set the palette and temperature range to give me good differentiation of houses along the street.  I took the first image of my house as I began imaging houses on my street, and I took the second image when I finished the street scan. 

I am surprised, first, that my house looks so different in the two images. And second, that the outside looks warmer in the later image.  If anything, I'd have expected the outside to have cooled.

Glad for any interpretation of this.  Needless to say, with this kind of variation on a single house, it is hard to get good images for comparing houses. "