3D Augmented Reality on Nuclear Plant Water Coolant Process in RTP Malaysia
Ensuring the safety of a nuclear plant's environment requires monitoring its water coolant process. Traditional monitoring of nuclear plant water coolant process has a lot of physical inspection, monitoring, and checking processes. The process takes time and visual inspection of data is needed...
| 要約: | Ensuring the safety of a nuclear plant's environment requires monitoring its water coolant process. Traditional monitoring of nuclear plant water coolant process has a lot of physical inspection, monitoring, and checking processes. The process takes time and visual inspection of data is needed which is a slower progression. Augmented reality (AR) offers a solution by displaying information through virtual assets on mobile devices in a real environment to support monitoring and maintenance intervention. This research has designed a 3D AR mobile application to monitor the water coolant process of a nuclear reactor. Nuclear plant target images were designed using marker-based Unity 3D software to track virtual objects in real-life environments. The apps will employ a target image to detect the virtual object. Five target images were designed for five sensors that monitor the primary cooling system. Five target size images at 10cmx10cm are Temperature sensor1(TT1), Temperature sensor2(TT2), Temperature sensor3(TT3), Flow rate sensor (FT1) and Conductivity Sensor (CT1) are created. The mobile apps activate an admin menu to monitor the water coolant process. The result presents a technical analysis of the app's functionality the best distance range is between 15cm and 120cm, and the ideal operation angle is between 30 and 165 degrees. It has been identified that 90% of the plants' performance can be monitored and operated via 3D AR apps. It is recommended to use the app in a semi-bright environment for optimal performance in monitoring the nuclear plant water coolant process. This research is significant in enhancing the monitoring process of nuclear plants process with new computer vision-augmented technology. © 2024 IEEE. |
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| DOI: | 10.1109/ICECCME62383.2024.10796400 |