Project Description:
The team has conducted research on an online detection system for liquid hazardous materials in public spaces. The research focuses on three main areas: the development of a BP neural network and low-rank sparse single-liquid signal classification algorithm, blind source separation algorithms for multi-sample liquid signals in complex noise environments, and algorithm transplantation based on a general embedded platform.
Application Fields:
After further development, the detection system can be applied in public places such as airports, subways, and rapid bus stations. The technology is at a leading domestic level.
Technical Advantages:
Low radiation, low cost, and broad application scope.
Research Achievements:
One SCI paper, one EI paper, two invention patents, and one utility model patent.
