Mapping thermal imaging data is necessary to measure the energy efficiency in existing and future buildings. The thermal imaging data developed through 3D laser scanning can be accessed by architects and engineers during construction and retrofitting of current buildings. This helps reduce the overall environmental footprint and reach maximum energy savings. In order to accumulate the most precise data, 3D laser scanners team up with thermal cameras and color cameras that work simultaneously to create a 3D model that captures the heat distribution throughout a building environment. These models can be used to produce simulations of heat and air movement that contain detailed temperature information to locate heat sources and thermal bridging.
To properly evaluate the efficiency of a building, thermal cameras are used to accurately measure indoor temperatures; however, these cameras are only capable of producing 2D images of the building. Since the energy loss in a building can only be approximated with these cameras, a 3D terrestrial laser scanner must be used to reconstruct the missing images that produce reliable point cloud data. By scanning from different angles and distances from the building, the data from the 3D images reveals the entire building environment and any unresolved obstructions.
Although very few projects have been done by combining 3D scanners and thermal cameras, there are studies being performed using robots to acquire thermal imaging data with this technology. At Jacobs University in Bremen, Germany a study is being conducted on a robot (Irma3D) to obtain thermal imaging data. This robot uses four types of sensors including a total station, laser scanner, digital color camera, and a thermal camera. Eight natural control points are used in conjunction with the sensors to identify the geometry being scanned. After the 3D images are produced from the laser scanner, scanned data is combined with color information technology which is a process in itself consisting of four steps.
Step 1) Intrinsic Calibration of Thermal and Optical Cameras: Since each sensor uses a different coordinate system, the data retrieved inherits specific boundaries to join each coordinate. These boundaries are calculated through a procedure called “geometric camera calibration.”
Step 2) Extrinsic Calibration: After completing the intrinsic calibration, the camera images are aligned with a scanner coordinate system to create a relationship between the camera and laser scanner to generate 3D images.
Step 3) 3D to 2D Projection and Color Mapping: During the extrinsic calibration phase the laser scans and camera images are calibrated which forms a relationship between the two. This bond is used to color the point cloud based on the image.
Step 4) Scan Registration: Each laser scan taken from different angles and positions is compiled into one common coordinate system. The complete 3D model along with thermal data and color images can be accessed to uncover the different sources of waste energy in a more realistic, accurate view.
The procedures necessary to obtain thermal information using 3D laser scanners are still in the process of being refined. By combining sensor information from the laser scanner, thermal camera, and color camera a complete 3D thermal model can be established in order to reveal thermal issues that lie within a building. Mapping thermal imaging data is an important process in green building retrofits or simply to determine the heat distribution within new or current buildings.