Heatwave : the next generation of thermography devices

• Main Authors: Moghadam, Peyman, Vidas, Stephen
• Other Authors: Colbert, Fred P.
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
• Online Access: https://hdl.handle.net/10356/99676; http://hdl.handle.net/10220/24065
• Institution: Nanyang Technological University

Energy sustainability is a major challenge of the 21st century. To reduce environmental impact, changes are required not only on the supply side of the energy chain by introducing renewable energy sources, but also on the demand side by reducing energy usage and improving energy efficiency. Currently, 2D thermal imaging is used for energy auditing, which measures the thermal radiation from the surfaces of objects and represents it as a set of color-mapped images that can be analysed for the purpose of energy efficiency monitoring. A limitation of such a method for energy auditing is that it lacks information on the geometry and location of objects with reference to each other, particularly across separate images. Such a limitation prevents any quantitative analysis to be done, for example, detecting any energy performance changes before and after retrofitting. To address these limitations, we have developed a next generation thermography device called Heat Wave. Heat Wave is a hand-held 3D thermography device that consists of a thermal camera, a range sensor and color camera, and can be used to generate precise 3D model of objects with augmented temperature and visible information. As an operator holding the device smoothly waves it around the objects of interest, Heat Wave can continuously track its own pose in space and integrate new information from the range and thermal and color cameras into a single, and precise 3D multi-modal model. Information from multiple viewpoints can be incorporated together to improve the accuracy, reliability and robustness of the global model. The approach also makes it possible to reduce any systematic errors associated with the estimation of surface temperature from the thermal images.