Signal Enhancement Algorithm for On-Line Detection of Multi-Metal Ions Based on Ultraviolet-visible Spectroscopy

Zhu

2020

IEEE Access

Self Cite

Considering the requirements of miniaturization, integration, digitization and high precision of online detection instrument, a miniature spectrometer based on ultraviolet-visible spectroscopy is developed for the on-line detection of copper and cobalt in the purification process of zinc hydrometallurgy. Firstly, the serial port protocol of spectrometer is developed to realize remote online acquisition of spectral signal. Then, a wavelet threshold denoising method is proposed to eliminate the noise interference caused by the spectrometer and the circuit system. Next, based on the invariance of the dual-wavelength light intensity ratio in the spectral detection, an error correction algorithm is proposed to dynamically eliminate the systematic measurement error caused by light source fluctuations. Finally, the partial least squares method is used to detect the concentration of copper and cobalt, and the detection performance of online miniature spectrometer is compared with that of dual-beam spectrometer. The results show that the developed online analysis instrument can detect polymetal ions in less than 5 min, the average relative error is less than 10%, and the detection accuracy is higher than 94.74%, which is suitable for the online acquisition and analysis of polymetal ions in high concentration zinc solution.

Section: B Wavelet Threshold Denoisingmentioning

confidence: 99%

Development of a Miniature Spectrometer Based on Ultraviolet-Visible Spectroscopy for Quantitative Analysis of Copper and Cobalt

Zhu

2020

IEEE Access

Self Cite

“…Among these, the UV-vis spectrophotometry can achieve online analysis on multi-ions without expensive sample pretreatment and is easily operated, making it cheaper and faster in the applications [ 10 , 11 , 12 ]. Our previous work focused on detecting copper and cobalt concentrations using UV–vis spectroscopy and multivariate regression model based on the wavelet denoising and locally weighted partial least squares methods [ 13 , 14 ]. However, due to the complex background and similar chemical properties of detected ions, the spectra are excessively overlapped and exist severe nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

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

Cheng

Yang

et al. 2020

Sensors

Self Cite

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.

“…In this paper, an overlapping peak separation algorithm based on multi-objective optimization was proposed for simultaneous detection of copper and cobalt in high concentration zinc solution by ultraviolet-visible spectroscopy [37][38][39]. First, according to the characteristics of the spectral signal, the derivative spectroscopy by continuous wavelet transform was used to separate the spectral overlapping peaks of copper and cobalt and shield the zinc interference.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimized Overlapping Peak Separation Algorithm for Simultaneous Detection of Copper and Cobalt by Ultraviolet-Visible Spectroscopy

Zhu

2020

IEEE Access

Self Cite

In the zinc hydrometallurgy, the excessive impurity ions of copper and cobalt are very harmful to the electrolysis process, which affects product quality and wastes resources. In order to solve the problems of low sensitivity, severe spectral overlap and narrow effective band, an overlapping peak separation algorithm based on multi-objective optimization was proposed for simultaneous detection of copper and cobalt in high concentration zinc solution by ultraviolet-visible spectroscopy. First, according to the characteristics of the spectral signal, the derivative spectroscopy by continuous wavelet transform was used to separate the spectral overlapping peaks of copper and cobalt and shield the zinc interference. Then, taking decomposition scale as decision variable, and the information occupancy and peak separation as the optimization targets, a multi-objective optimization model was established and solved using the particle swarm multi-objective optimization method. Finally, derivative spectroscopy combined with zero-crossing method was used to establish calibration curves for simultaneous detection of copper and cobalt. The experimental results show that the proposed method is suitable for simultaneous detection of trace amounts of copper and cobalt in high concentration zinc solution.