Research Article
Statistical Analysis of Catalytic Removal of Soot Particles Based on Big Data
@INPROCEEDINGS{10.1007/978-3-030-67874-6_16, author={Xiu-hong Meng and Ping Yang and Hui-bo Qin and Lin-hai Duan}, title={Statistical Analysis of Catalytic Removal of Soot Particles Based on Big Data}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Big data Soot particles Catalytic removal Sol-gel preparation Low temperature Plasma Perovskite type catalyst}, doi={10.1007/978-3-030-67874-6_16} }- Xiu-hong Meng
Ping Yang
Hui-bo Qin
Lin-hai Duan
Year: 2021
Statistical Analysis of Catalytic Removal of Soot Particles Based on Big Data
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_16
Abstract
Different temperature, power, flow rate and other factors have different effects on the removal of soot particles in the tail gas of simulated diesel vehicles, and the removal effect of each kind of soot particle catalytic removal method is also different. In order to further improve the effect of soot particle catalytic removal, a statistical analysis method of soot particle catalytic removal method based on big data is designed. Using large data technology to extract catalytic removal methods of soot particles, detailed analysis of each method was carried out, and the soot combustion performance of soot particles catalytic removal method was compared. The results showed that the removal of soot particles based on perovskite catalyst was more effective than that of soot particle removal method based on sol-gel preparation method, and that soot particles were catalyzed by low temperature plasma. The combustion performance of the removal method is better, and the catalytic removal performance is more superior.
