Title
Analysis of Converter Combustion Flame Spectrum Big Data Sets Based on HHT.
Abstract
The characteristics of the converter combustion flame are one of the key factors in the process control and end-point control of steelmaking. In a big data era, it is significant to carry out high-speed and effective processing on frame spectrum data. By installing data acquisition devices at the converter mouth and separating the spectrum according to the wave length, high-dimensional converter flame spectrum big data sets are achieved. The data of each converter is preprocessed after information fusion. By applying the SM software, the correspondence with the carbon content is obtained. Selecting the relative data of the two peak ratios and the single-peak absolute data as a one-dimensional signal, due to the obvious nonlinear and nonstationary characteristics, using HHT to do empirical mode decomposition and Hilbert spectrum analysis, the variation characteristics after 70% of the converter steelmakmg process are obtained, from data acquisition, data preprocessing to data analysis and results, it provides a new perspective and method for the study of similar problems.
Year
DOI
Venue
2018
10.1155/2018/8682725
COMPLEXITY
Field
DocType
Volume
Hilbert spectrum,Combustion,Control theory,Data acquisition,Algorithm,Data pre-processing,Software,Process control,Big data,Mathematics,Hilbert–Huang transform
Journal
2018
ISSN
Citations 
PageRank 
1076-2787
0
0.34
References 
Authors
3
5
Name
Order
Citations
PageRank
Jincai Chang144.18
Jiecheng Wang200.34
Zhuo Wang300.34
Shuaijie Shan400.34
Chunfeng Liu516928.81