Name
Title | ||
|---|---|---|
Soft sensor for parameters of mill load based on multi-spectral segments PLS sub-models and on-line adaptive weighted fusion algorithm |
Abstract | ||
|---|---|---|
The parameters of mill load (ML) not only represent the load of the ball mill, but also determine the grinding production ratio (GPR) of the grinding process. In this paper, a novel soft sensor approach based on multi-spectral segments partial least square (PLS) model and on-line adaptive weighted fusion algorithm is proposed to estimate the ML parameters. At first, frequency spectrums of the shell vibration acceleration signals are obtained. Then the PLS sub-models are constructed with the low, medium and high frequency spectral segments. At last, the PLS sub-models are fused together with a new on-line adaptive weighted fusion algorithm to obtain the final soft sensor models. This soft sensor approach has been successfully applied in a laboratory-scale wet ball mill grinding process. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.neucom.2011.05.028 | Neurocomputing |
Keywords | Field | DocType |
final soft sensor model,multi-spectral segment,novel soft sensor approach,ball mill,mill load,on-line adaptive weighted fusion,pls sub-models,frequency spectrum,ml parameter,laboratory-scale wet ball mill,soft sensor approach,soft sensor | Least squares,Mill,Ball mill,Pattern recognition,Soft sensor,Algorithm,Fusion,Artificial intelligence,Acceleration,Vibration,Grinding,Mathematics | Journal |
Volume | Issue | ISSN |
78 | 1 | 0925-2312 |
Citations | PageRank | References |
9 | 0.67 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Tang | 1 | 526 | 148.30 |
| Tianyou Chai | 2 | 2014 | 175.55 |
| Lijie Zhao | 3 | 41 | 9.72 |
| Wen Yu | 4 | 246 | 52.12 |
| Heng Yue | 5 | 22 | 4.59 |