Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Monitoring Method of VOCs Based on PID in Soil-water-gas Environment

Version 1 : Received: 15 January 2024 / Approved: 15 January 2024 / Online: 15 January 2024 (16:30:53 CET)
Version 2 : Received: 17 January 2024 / Approved: 17 January 2024 / Online: 17 January 2024 (09:25:24 CET)

How to cite: Dong, D.; Ren, Y.; Zhang, M.; Feng, X.; Liu, K. Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints 2024, 2024011137. https://doi.org/10.20944/preprints202401.1137.v2 Dong, D.; Ren, Y.; Zhang, M.; Feng, X.; Liu, K. Monitoring Method of VOCs Based on PID in Soil-water-gas Environment. Preprints 2024, 2024011137. https://doi.org/10.20944/preprints202401.1137.v2

Abstract

In the moist environment of soil-water-air, there is a problem of low accuracy in monitoring Volatile Organic Compounds (VOCs) using a Photoionization Detector (PID). This paper analyzes the reasons for the low accuracy of the traditional Support Vector Machine (SVM) regression method. To address the issue, the PID signal is subjected to feature extraction and Principal Component Analysis (PCA) to reduce the data dimensionality. Moreover, the optimal SVM parameters are selected using a Genetic Algorithm (GA), and a combined approach of SVM regression with PCA and GA is utilized for PID signal regression analysis. And the effectiveness of the method is validated through extensive experiments and simulations. Furthermore, the influence of the sample quantity on the regression accuracy is analyzed, enabling accurate monitoring of VOCs concentration in a moist environment.

Keywords

Photoionization detector; VOCs; Principal Component Analysis; Genetic Algorithm

Subject

Environmental and Earth Sciences, Environmental Science

Comments (1)

Comment 1
Received: 17 January 2024
Commenter: Xiujuan Feng
Commenter's Conflict of Interests: Author
Comment: Monitoring Method of VOCs based on PID in Soil-water-gas Environment
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