给无人机装上“电子鼻”:中国团队突破低空大气精准感知技术
Ke Ji Ri Bao·2025-10-13 05:46

Core Insights - The article discusses a breakthrough technology developed by a research team led by Professor Chen Da at the Civil Aviation University of China, which enables drones to detect carbon monoxide (CO) at concentrations as low as parts per million (ppm) and create three-dimensional concentration distribution maps [1][8]. Group 1: Technology Development - A miniaturized onboard gas sensing module, comparable in size to a coin, serves as the "olfactory nerve" for the drone, facilitating intelligent atmospheric monitoring [1][8]. - The technology has been published in the international journal "ACS Sensors," marking significant progress in low-altitude environmental sensing in China [1]. - The sensing module can detect CO levels with precision and has a response time reduced to seconds, matching the accuracy of large ground-based analytical instruments [8]. Group 2: Application and Market Potential - The technology addresses the limitations of traditional ground-based monitoring stations, which are sparse and slow to update, making them inadequate for capturing pollution dispersion in complex environments [2]. - Drones equipped with this technology can enhance environmental monitoring and emergency response capabilities, providing timely data for decision-making during pollution events [2][9]. - The research team is actively pursuing industrial applications, collaborating with various drone system integrators and environmental management departments to implement the technology in real-world scenarios [9][10]. Group 3: Safety and Risk Management - The technology also includes a feature for early warning of lithium battery thermal runaway, which is critical for ensuring drone flight safety [3][10]. - By detecting CO as a byproduct of battery decomposition, the system can provide warnings up to several minutes earlier than traditional methods [8]. - The integration of the sensing module with the drone's flight control system allows for real-time data analysis and autonomous decision-making in emergency situations [8][9].