Simultaneous Determination of Metal Ions in Zinc Sulfate Solution Using UV-Vis Spectrometry and SPSE-XGBoost Method.

UV–vis spectroscopy extreme gradient boosting feature selection and combination metal ion measurement singular perturbation spectrum estimator zinc hydrometallurgy

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
31 Aug 2020
Historique:
received: 08 07 2020
revised: 22 08 2020
accepted: 25 08 2020
entrez: 4 9 2020
pubmed: 4 9 2020
medline: 4 9 2020
Statut: epublish

Résumé

Excessive discharge of heavy metal ions will aggravate environment pollution and threaten human health. Thus, it is of significance to real-time detect metal ions and control discharge in the metallurgical wastewater. We developed an accurate and rapid approach based on the singular perturbation spectrum estimator and extreme gradient boosting (SPSE-XGBoost) algorithms to simultaneously determine multi-metal ion concentrations by UV-vis spectrometry. In the approach, the spectral data is expanded by multi-order derivative preprocessing, and then, the sensitive feature bands in each spectrum are extracted by feature importance (VI score) ranking. Subsequently, the SPSE-XGBoost model are trained to combine multi-derivative features and to predict ion concentrations. The experimental results indicate that the developed "Expand-Extract-Combine" strategy can not only overcome problems of background noise and spectral overlapping but also mine the deeper spectrum information by integrating important features. Moreover, the SPSE-XGBoost strategy utilizes the selected feature subset instead of the full-spectrum for calculation, which effectively improves the computing speed. The comparisons of different data processing methods are conducted. It outcomes that the proposed strategy outperforms other routine methods and can profoundly determine the concentrations of zinc, copper, cobalt, and nickel with the lowest RMSEP. Therefore, our developed approach can be implemented as a promising mean for real-time and on-line determination of multi-metal ion concentrations in zinc hydrometallurgy.

Identifiants

pubmed: 32878223
pii: s20174936
doi: 10.3390/s20174936
pmc: PMC7506957
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : 61533021
Organisme : National Natural Science Foundation of China
ID : 61773403
Organisme : Fundamental Research Funds for the Central Universities of Central South University
ID : 2019zzts561
Organisme : State Key Laboratory of High Performance Complex Manufacturing in Central South University
ID : ZZYJKT2019-14

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Auteurs

Fei Cheng (F)

School of Automation, Central South University, Changsha 410083, China.

Chunhua Yang (C)

School of Automation, Central South University, Changsha 410083, China.

Can Zhou (C)

School of Automation, Central South University, Changsha 410083, China.
State Key Laboratory of High Performance Complex Manufacturing, Changsha 410083, China.

Lijuan Lan (L)

School of Automation, Central South University, Changsha 410083, China.

Hongqiu Zhu (H)

School of Automation, Central South University, Changsha 410083, China.

Yonggang Li (Y)

School of Automation, Central South University, Changsha 410083, China.

Classifications MeSH