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Torii (2020) Remote detection of radioactive hotspot using a Compton camera mounted on a moving multi-copter drone above a contaminated area in Fukushima,

At the Fukushima Daiichi Nuclear Power Station (FDNPS) where an accident occurred due to a large tsunami caused by the Great East Japan Earthquake, understanding the distribution of radioactive substances is important to reduce the exposure dose to workers and establish decontamination plans. We focused on the importance of visualizing beta-emitting radiation sources in addition to gamma-emitting ones and proposed a method for three-dimensionally (3D) visualizing the location of beta-emitting radiation sources, which is important in discussing the effective dose for the crystalline lens of the eye. In this report, we have developed a technique to visualize the location of beta-emitting radiation sources in 3D by combining a directional Geiger-Mueller counter (G-M counter) with Structure from Motion (SfM). An image of 90Sr beta-ray source reconstructed using a beta-ray detector was projected onto a 3D model of the measurement area created using SfM, and the source location is identified in 3D. Additionally, we estimated the radioactivity of the visualized source. Then, by combining the beta-ray detector with a Compton camera, distinguishing between beta- and gamma-emitting radiation sources was possible. This study was based on the concept of integrated radiation imaging system (iRIS), which integrates multiple radiation detectors and environmental recognition devices.

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Identifying and visualizing the radiation source location are important in reducing the radiation exposure of workers at the decommissioning site of the Fukushima Daiichi Nuclear Power Station and in improving the radiation protection functions in other sites where radiation sources are handled. In this paper, we developed the COMpton camera for Radiation Imaging System (COMRIS) to identify and visualize the radiation source location in 3D using output data from a Compton camera and a simultaneous localization and mapping (SLAM) device as input data. Here, we presented COMRIS to visualize a 137Cs-radiation source in a dark environment using data acquired by a commercial Compton camera and a LiDAR-based SLAM device mounted on a robot as input data. The radiation source image obtained using the Compton camera was drawn on the 3D work environment model acquired by the SLAM device, and the radiation source location was visible in 3D.

Technology for measuring and identifying the positions and distributions of radioactive substances is important for decommissioning work sites at nuclear power stations. A three-dimensional (3D) image reconstruction method that locates radioactive substances by integrating Structure-from-Motion (SfM) with a Compton camera (a type of gamma-ray imager) has been developed. From the photographs captured while freely moving in an experimental environment, a 3D structural model of the experimental environment was created. By projecting the radioactive substance image acquired by the Compton camera on the 3D structural model, the positions of the radioactive substance were visualized in 3D space. In a demonstration study, the 137Cs-radiation source was successfully visualized in the experimental environment captured by the freely moving cameras. In addition, how the imaging accuracy is affected by uncertainty in the self-localization of the Compton camera processed by SfM, and by positional uncertainty in the gamma-ray incidence determined by the sensors of the Compton camera was investigated. The created map depicts the positions of radioactive substances inside radiation work environments, such as decommissioning work sites at nuclear power stations.

To reduce the exposure doses of workers and to establish decontamination plans, it is important to understand and visualize the distribution of radioactive substances at the Fukushima Daiichi Nuclear Power Station in Japan, where an accident occurred on the 11th of March, 2011. In this decommissioning work environment, radioactive substances adhered to various objects, such as rubble and equipment, and it was necessary to visualize the distribution of these contaminants in all three dimensions. The technology used to automatically and remotely acquire data to visualize the distribution of radioactive substances in three dimensions was useful for reducing the exposure dose of the workers and to shorten the survey time. We constructed an automatic data acquisition system that consisted of a Compton camera and a 3D-light detection and ranging sensor mounted on an autonomously moving robot. We also evaluated the system feasibility using radiation sources and succeeded in automatically acquiring the data required for visualizing the radiation sources. For this data acquisition, the operator did not need to operate the system after the measurements were started. The effects of the imaging parameters of the Compton camera and the accuracy of the self-position estimation of the system on the radiation-imaging accuracy are also discussed.