Infrared (IR) thermography is an indispensable tool for studying dynamic thermal phenomena. This type of imaging is accomplished with an IR camera (Figure 1) that converts infrared radiation into a visual image depicting temperature variations across an object or scene. In addition, a good IR camera makes accurate (±1°C to ±2°C) non-contact measurements of the object’s temperatures.

Purchasing one of these cameras for scientific research or product development is a significant investment. Several criteria should be considered prior to purchase:

  1. What temperatures do you expect to measure?
  2. How quickly will you need to capture data?
  3. What is the size and distance to your target object?
  4. What type of IR detector is best for your application?
  5. What kinds of temperature analysis and report generation are required?
  6. What camera accessories will you need?
  7. What support and training are you likely to need?

Temperature Range and Resolution

Figure 1. Typical IR camera used in R&D. This model is configured with a microscope lens that allows target measurements down to 5-micron spot size.
Typically, an IR camera is used to characterize target object temperatures. Normally, this involves temperature differences among various locations on the object, or between the target object and its background or another reference temperature. Therefore, temperature range and resolution are important.

Temperature range is defined by the coldest and hottest temperatures on the target object or scene within the camera’s field of view (FoV). For example, a thermographic image of an aircraft idling on the runway might be used to compare the engine to the body of the aircraft. Between the body and engine, the temperature range might be 25°C to 500°C. You would need a camera that could cover at least that range within a single thermographic image.

Temperature resolution is the smallest temperature difference you need to measure and is commonly referred to as temperature sensitivity. IR camera sensitivities can range from about 0.025°C up to 0.1°C, depending on the camera’s detector design.

Data Capture Speed

To determine if an IR camera will meet your speed requirements, consider:

  • The motion of your target object
  • How quickly your target object heats up or cools down
  • IR camera motion

An IR camera’s data acquisition time involves exposure time, frame rate, and total record time. Exposure time is how quickly an IR camera can capture a single frame of data (image), which is analogous to shutter speed on a traditional camera. Exposure time is determined by the integration time of the camera’s A/D converter or the thermal time constant of the camera’s detector.

Data capture speed is also related to a camera’s thermal resolution (sensitivity). For a given target or scene, a camera with higher sensitivity requires less exposure time than one with lower sensitivity. With a shorter exposure time and highly sensitive detector, a camera can provide superior images of cooler objects, and also capture fast movement or temperature changes without image blurring.

The camera frame rate is defined by the number of frames (images) the camera can acquire over a one-second time period. Frame rate should not be confused with the camera’s video display rate, which is the rate at which the camera displays frames to a video monitor. IR camera frame rates can vary from a few frames per second to thousands of frames per second.

Total record time depends on how you capture data, and makes data storage an important consideration. You might need to capture data at high speed in short bursts, or conversely, do data logging at slow rates for hours. Some cameras record to internal FLASH memory or a removable Compact SD card. Others can stream high-speed thermal data over Gigabit Ethernet or CameraLink to a PC or laptop for storage.

Target Size and Distance

Figure 2: Atmospheric transmission of infrared energy (blue areas). Molecules in the atmosphere absorb various IR wavelengths.
To get the best thermal imagery and most points of measurement, select a camera lens that fills most of the FoV with the target of interest. To optimize spatial resolution, make sure the smallest object detail you need to see matches your instantaneous field of view (IFoV). These two characteristics are a function of the smallest area covered by a single camera detector pixel. The closer you are to an object, the smaller the area a pixel will detect, and vice versa.

The math to determine FoV and spatial resolution for a given camera and lens can be tedious. Camera manufacturers can quickly determine this for you, and online FoV calculators are also available.

Camera Spectral Response

Different IR cameras are engineered with different types of infrared detectors. The reasons include detector cost, availability, and intended use. Different detectors sense infrared energy over different portions of the IR spectrum. Understanding the IR waveband characteristics of your application will ensure the best camera selection and thermographic analysis results.

For example, infrared energy does not propagate through the atmosphere uniformly (Figure 2). If your application involves the imaging of a target located at a substantial distance from the camera, you will want to select a camera waveband that best “sees” through the atmosphere.

Similar considerations apply to applications where the camera is sensing IR energy through other materials that have different transmission characteristics. For some wavelengths, they may be essentially transparent, but for others they may be largely opaque.

Collecting data is only half the battle. The other half is manipulating, analyzing, and reporting results. Techniques for image enhancement, image subtraction, emissivity adjustment, and the plotting of charts and graphs are extremely valuable. They allow the researcher to better visualize and understand thermal changes taking place on a target object. Some of these tools may be built directly into the IR camera and displayed on the camera video output, while others are available in software that runs on a PC.

Image enhancement involves adjustment of the level and span of the image color palette depicting temperatures on the target object or scene. This allows a researcher to see subtle temperature differences more easily. Software that subtracts a baseline (reference) image from the active (energized) image allows removal of any reflected ambient temperatures, and thereby reveals extremely small temperature variations.

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