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Detection and recognition of water quality based on UV-visible spectroscopy in different living areas of Urumqi
Author(s): Yushuai Yuan; Cheng Chen; Chen Chen; Ziwei Yan; Ziwei Zhang; Xiaoyi Lv Sr.; Shengya Feng
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Paper 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.

Paper Details

Date Published: 18 November 2019
PDF: 6 pages
Proc. SPIE 11189, Optical Metrology and Inspection for Industrial Applications VI, 111890F (18 November 2019); doi: 10.1117/12.2537616
Show Author Affiliations
Yushuai Yuan, Xinjiang Univ. (China)
Cheng Chen, Xinjiang Univ. (China)
Chen Chen, Xinjiang Univ. (China)
Ziwei Yan, Xinjiang Univ. (China)
Ziwei Zhang, Xinjiang Univ. (China)
Xiaoyi Lv Sr., Xinjiang Univ. (China)
Shengya Feng, Xinjiang Zijing Optical-Electrical Technology Co., Ltd. (China)


Published in SPIE Proceedings Vol. 11189:
Optical Metrology and Inspection for Industrial Applications VI
Sen Han; Toru Yoshizawa; Song Zhang; Benyong Chen, Editor(s)

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