Detection and recognition of water quality based on UV-visible spectroscopy in different living areas of Urumqi

Yushuai Yuan; Cheng Chen; Chen Chen; Ziwei Yan; Ziwei Zhang; Xiaoyi Lv Sr.; Shengya Feng

doi:10.1117/12.2537616

18 November 2019 Detection and recognition of water quality based on UV-visible spectroscopy in different living areas of Urumqi

Yushuai Yuan, Cheng Chen, Chen Chen, Ziwei Yan, Ziwei Zhang, Xiaoyi Lv Sr., Shengya Feng

Author Affiliations +

Proceedings Volume 11189, Optical Metrology and Inspection for Industrial Applications VI; 111890F (2019) https://doi.org/10.1117/12.2537616
Event: SPIE/COS Photonics Asia, 2019, Hangzhou, China

Abstract

In recent years, water quality testing has become an increasingly important topic. Compared with some common water quality identification methods, this study proposes a new method for identifying water samples in UV-visible spectroscopy. In this study, the UV-visible spectra of water samples from two different regions of tianchi and shuimogou in Urumqi were measured, and the pattern recognition algorithm was used to identify the two types of water samples. The acquired UV-visible spectra of water samples were extracted from 80 original high-dimensional spectral data by Partial Least Squares Regression (PLS), and the extracted features were modeled and classified by Support Vector Machine (SVM) classifier. The parameters C and g are optimized by Grid Searching (GS). The classification accuracy of the tianchi water sample and the water mill ditch water sample was 100%. The results of this study illustrate the great potential for rapid detection of water samples using UV-visible spectroscopy in the future.

Citation Download Citation

Yushuai Yuan, Cheng Chen, Chen Chen, Ziwei Yan, Ziwei Zhang, Xiaoyi Lv Sr., and Shengya Feng "Detection and recognition of water quality based on UV-visible spectroscopy in different living areas of Urumqi", Proc. SPIE 11189, Optical Metrology and Inspection for Industrial Applications VI, 111890F (18 November 2019); https://doi.org/10.1117/12.2537616

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