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Prototyping of automated systems
Published in Fuewen Frank Liou, Rapid Prototyping and Engineering Applications, 2019
An infrared sensor can detect heat, which is infrared radiation. It can be used to detect the hot objects. One example of this application is in a small assembly environment for the laser welding of a part that is difficult to observe from outside. As a welded component is hot, it can be revealed using an infrared sensor just like an X-ray. One can trace whether two welded parts were successfully bound together with an infrared sensor.
A belt-like assistive device for visually impaired people: Toward a more collaborative approach
Published in Cogent Engineering, 2022
Erick Javier Argüello Prada, Lina María Santacruz Forero
The proposed system successfully detected the foot-level obstacle when tests were conducted indoors (Table 5), but it failed in four out of twelve trials when tests were conducted outdoors (Table 6). A possible explanation is that the performance of the infrared sensor was affected by environmental light conditions (e.g., sunlight). Several authors have pointed out that high sensitivity to environmental light is one major drawback of infrared-based detection systems (Katzschmann et al., 2018; Pyun et al., 2013; Wahab et al., 2011). An alternative to address this issue is to replace the GP2Y0A02YK0F infrared sensor with another one with adjustable sensitivity. Thus, data acquired from a luminance sensor might be used to make foot-level obstacle detection more reliable. Nevertheless, it could increase the computational burden, power consumption and economic cost. Another option is to replace the infrared sensor with another ultrasonic sensor, which could also prevent false drop-off detections because of reflective surfaces (Pyun et al., 2013). However, detection errors might increase due to the wide sensing field resulting from several front view-aligned ultrasonic sensors. Conversely, infrared sensors have a narrower sensing range, so they may perform well when their orientation is carefully chosen (Nada et al., 2015).
Inverse estimation method for internal defects based on surface stress of carbon-fiber-reinforced plastics using machine learning
Published in Advanced Composite Materials, 2022
Yuta Kojima, Kenta Hirayama, Katsuhiro Endo, Kazuya Hiraide, Mayu Muramatsu
Infrared thermography is a method of measuring the infrared energy distribution emitted from the surface of an object using an infrared sensor. The measured infrared energy is converted into a temperature distribution. Compared with existing damage analysis methods, this method has the following advantages: there is no need for safety control, the analysis and time costs are low, no contact medium is required, and the skill of the test engineer does not affect the results. Recently, the sum of principal stresses at the surface (DSPSS) is often calculated from the temperature change obtained by infrared analysis, and DSPSS is used in damage analysis. There is a study that confirmed the usefulness of infrared stress analysis of structures for detecting defects in objects such as bridges [33]. The infrared stress analysis is applied to the evaluation of processing damage [34, 35].
Comparison of different body measurement techniques: 3D stationary scanner, 3D handheld scanner, and tape measurement
Published in The Journal of The Textile Institute, 2019
Sibei Xia, Siming Guo, Jiayin Li, Cynthia Istook
With the technological development, millimeter wave and infrared light as new light sources have entered the body scanner market. However, millimeter body scanners lack reliability for body measurement and therefore have been mainly used in airports for security checking. In contrast, infrared light has been applied to make low-cost body scanners. The latest [TC]2 19B body scanner employs infrared depth sensors to obtain body shapes. Its output formats include obj, txt, ord, rbd, pdf, and bin file types. The exported 3D avatars can be imported to other software, such as Browzwear, Gerber, Human Solution, Lectra, Optitex, Telestia, and Tukacad for further processing (http://www.tc2.com). The first version of the Kinect sensor was a popular depth sensing device. It collects 3D scene information using projected infrared structured light and an infrared sensor. It also has an RGB camera (Biswas & Basu, 2011). The Kinect sensor can return depth images with each pixel value representing the distance to the scanned point (Andersen et al., 2012). By using different numbers of sensors, both stationary scanners and handheld scanners can be developed from the Kinect sensor.