High-Resolution Distributed Radiation Detector System Assisted by Intelligent Image Recognition

Abstract

With the development of machine learning and image recognition technology, the detector system tends to be standardized and intelligent. However, large numbers of distributed radiation detectors connected to the power grid will bring huge uncertainty to the operation of the power grid and even cause certain interference. The monitoring system of the distributed radiation detectors can control the running status of the distributed photoelectric detection system in real-time and guarantee the safe and stable operation of the detector system. This article proposes an improved genetic detector system to avoid “blind spots” in the radiation detector monitoring based on the characteristics of photovoltaic (PV) arrays, which are considered as individual pixels, and then the reliability of the monitoring is ensured by the monitoring coverage of these pixels by the detector nodes. The performance of the radiation detector monitoring is restored by activating those spare nodes with sufficient energy to replace those that fail, ensuring that the distributed detection system can be monitored in a timely and efficient manner at all times. The simulation results confirm the reasonable validity of the algorithm.