The utilization of specialized Infrared cameras consisting of infrared sensors to capture and develop the image of an object constitutes the process of thermal imaging. Our eyes detect visible light; however, the thermal radiation being emitted in the infrared region can only be detected by the cameras used for thermal imaging. The temperature variations are used for mapping the objects to develop an image, and the modern thermal imaging systems are being utilized in almost every major industry.
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A Brief History of Thermal Imaging
The basic science of thermal imaging came into existence with the invention of the bolometer in 1860 by American astronomer Samuel Pierpont Langley. Further studies were taken to develop a technology for capturing infrared radiations.
The efforts bore fruit in 1929 when physicist Kálmán Tihanyi invented an infrared-sensitive electronic television camera for anti-aircraft defense. The effectiveness of this invention spread throughout the world and the United States military developed the very first infrared line scanner around 1947.
Early developed for the military and defense sector, thermal imaging systems have undergone significant development, and several commercial companies are now offering thermal imaging services and systems all over the world.
The Basic Science Behind Thermal Imaging
The visible light spectrum has a wavelength spanning 400 nm to 700 nm. The infrared region consists of much larger wavelengths beyond 1.7 µm. Infrared radiation, which is generated by heat, occupies a significant portion of the infrared electromagnetic spectrum. Thermal imaging cameras operate by capturing and analyzing the interplay of heat as it is absorbed, reflected, and sometimes transmitted by objects.
The amount of thermal radiation emitted by an object is referred to as its heat signature. Essentially, the hotter an object is, the more thermal radiation it emits into its surroundings. Thermal imagers are capable of discerning heat sources and even subtle variations in thermal radiation. They compile this information into a comprehensive "heat map" that distinguishes various levels of heat.
Thermal imaging cameras operate by converting thermal energy into visible light to analyze a particular object. The resulting image is referred to as a “thermogram”, and it is examined through a method called thermography. These cameras are sophisticated devices that process and display the captured image on a screen for analysis and interpretation.
Limitations of Thermal Imaging
Thermal imaging cameras have limitations when it comes to observing through certain materials. They cannot create thermal images of objects located behind a glass surface because thermal radiation can be reflected off glossy surfaces, making it challenging for the camera to capture the thermal information on the other side of the glass. While they can collect data about the interior of a wall, they cannot "see through" it in the sense of providing a detailed image of what is behind the wall.
Another drawback of infrared-based technologies is that their range at night is constrained by the distance that the scene can be illuminated. Since these devices emit energy to create the thermal image, they tend to consume more electrical power compared to passive sensors, which can be a limiting factor in certain applications.
Different Devices for Thermal Imaging
Thermal Infrared Imaging is the most basic and common type of thermal imaging. These imaging systems utilize specialized cameras to create thermal images of various objects.
A bolometer is another type of thermal device used for measuring thermal radiation. It operates by determining the temperature of an object that becomes heated due to the absorption of radiation. When exposed to radiant energy, the bolometer's resistance changes in response to the thermal energy generated by the absorbed radiation. One of the most prevalent types of bolometric detectors is the thermistor, which is widely used in various applications for its sensitivity to temperature changes caused by incoming radiation.
Use of UAV Thermal Remote Sensing for Agriculture Industries
Thermal imaging systems have found profound applications in various industries. Unmanned Armed Vehicles (UAVs) incorporating modern thermal imaging systems have been utilized in precision agricultural activities, as per the latest article published in Remote Sensing.
Remote sensing (RS) involves gathering information about an object, area, or phenomenon by analyzing images acquired through devices that don't physically touch the subject. Thermal remote sensing has emerged as a valuable tool for measuring surface temperatures. Surface temperature data from thermal sensors offer quick insights into monitoring plant growth and detecting stress.
In terms of monitoring water stress, thermal images have shown their effectiveness in revealing subtle changes that may go unnoticed by other methods like the normalized difference vegetation index (NDVI). Temperature-based indices provide a fast and practical means of assessing and estimating crop water status, offering valuable information about plant water content.
One significant limitation of thermal cameras is their lower geometric resolution compared to sensors like RGB (red, green, blue) cameras. Nevertheless, it's expected that ongoing technological advancements will continue to improve user-friendliness for all types of users in the development of UAVs and thermal sensors, potentially increasing their adoption in various applications.
Thermal Imaging in the Construction Industry
Electric impact drills are extensively employed in both the construction industry and for household purposes. These drills often incorporate commutator motors as a key component. Commutator motors are utilized in various types of power tools such as demolishing hammers and cordless screwdrivers.
The latest article in Measurement focuses on fault diagnosis methods that rely on the analysis of thermal images. The study introduces an innovative approach called BCAoID (Binarized Common Areas of Image Differences) for extracting features from thermal images. The analysis was conducted using thermal images from three electric impact drills (EID): a healthy EID, an EID with a faulty fan (featuring 10 broken fan blades), and an EID with a damaged gear train.
The BCAoID method was employed to extract distinctive features from these thermal images. These computed features were then subjected to analysis using both the Nearest Neighbor classifier and the backpropagation neural network.
The results of this analysis demonstrated a high level of accuracy, with recognition rates falling within the range of 97.91% to 100%. This approach to fault diagnosis based on thermal images holds significant potential for applications in safeguarding rotating machinery and engines, offering an effective means of detecting and addressing faults to prevent potential issues.
Implementation of AI to Thermal Imaging
Researchers at Purdue University in the US have introduced a thermal imaging system known as HADAR, which utilizes machine learning techniques to decipher the information embedded in infrared images. This innovative system has the potential to enable passive thermal imagers to generate images that resemble those captured in daylight conditions, expanding the capabilities of thermal imaging technology and enhancing its utility in various applications.
HADAR employs hyperspectral thermal imaging, a technique that captures thermal images of a scene across hundreds of different colors within the thermal infrared spectrum. This approach allows for a more detailed and comprehensive analysis of thermal information, enhancing the system's ability to discern subtle temperature variations and extract valuable data from thermal images.
HADAR holds the potential for a wide range of applications, including autonomous navigation, robotics, and smart healthcare monitoring, particularly in nighttime or low-light conditions.
The applications of thermal imaging systems are numerous. From environmental monitoring applications for the study of ecosystems to the study of celestial bodies, thermal imaging is playing its part in every field of life. With the implementation of modern AI algorithms and faster data processing, thermal imaging systems are expected to commercialize at an even faster rate.
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References and Further Reading
Omega, 2023. Thermal Imaging Camera. [Online]
Available at: https://www.omega.com/en-us/resources/thermal-imagers
Messina G. et. al. (2020). Applications of UAV Thermal Imagery in Precision Agriculture: State of the Art and Future Research Outlook. Remote Sensing. 12(9):1491. Available at: https://doi.org/10.3390/rs12091491
Association for Advancing Automation, 2016. What is Thermal Imaging?. [Online]
Available at: https://www.automate.org/blogs/what-is-thermal-imaging
Physics World, 2023. Machine learning brings sharpness and colour to thermal images. [Online]
Available at: https://physicsworld.com/a/machine-learning-brings-sharpness-and-colour-to-thermal-images/
Glowacz, A. (2021). Fault diagnosis of electric impact drills using thermal imaging. Measurement, 171, 108815. Available at: https://doi.org/10.1016/j.measurement.2020.108815
Waitt, T., 2022. The Revolutionary Technology behind Thermal Imaging Cameras. [Online]
Available at: https://americansecuritytoday.com/the-revolutionary-technology-behind-thermal-imaging-cameras/
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