Document Type

Article

Publication Date

9-23-2021

Publisher

Institute of Electrical and Electronics Engineers

Source Publication

IEEE Transactions on Instrumentation and Measurement

Source ISSN

0018-9456

Abstract

Microwave measurements and machine learning algorithms are presented to estimate metal ion concentrations in drinking water. A novel block loop gap resonator (BLGR) as a microwave probe is designed and fabricated to estimate Pb ion concentrations in city water as low as 1 ppb with an rms error of 0.18 ppb. No physical contact between the BLGR probe and the water sample allows on-site/in situ continuous detection of ppb-level metal ion concentrations. The S11 raw data (amplitude and phase) from the BLGR are used to classify and estimate metal ion concentrations using a support vector regression algorithm. The performance of the proposed method to estimate Pb concentrations in the presence of interfering metal ions (Cu 2+ , Fe 3+ , and Zn 2+ ) is also evaluated, and it is found that the average measurement error remains less than 13%.

Comments

Accepted version. IEEE Transactions on Instrumentation and Measurement, Vol. 70 (September 23, 2021): 9513909. DOI. © 2021 Institute of Electrical and Electronics Engineers. Used with permission.

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