Expert System for the Control of Effluent TN Excedance of AAO Process

Xingguan Ma, Zhiyi Wang, Hongyu Shi, Li Zhang

2023

Abstract

Based on the mechanism of microbial denitrification and the principle of wastewater treatment process control, an expert system is built for the purpose of dealing with the exceeding of TN standard, and the data information collected from the equipment of the wastewater treatment plant is combined with intelligent diagnostic means to make a technical analysis of the factors triggering the exceeding of TN standard in accordance with the wastewater treatment logic. According to the structure characteristics of the activated sludge AAO process, the causes of TN exceedance are analyzed step by step and the system is adjusted with the predetermined response strategy to achieve effective control of TN exceedance in the effluent, taking a wastewater treatment plant in Liaoning Province as an example to make a detailed diagnosis and provide a solution

Paper Citation

in Harvard Style

Ma X., Wang Z., Shi H. and Zhang L. (2023). Expert System for the Control of Effluent TN Excedance of AAO Process. In Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS; ISBN 978-989-758-675-0, SciTePress, pages 79-88. DOI: 10.5220/0012149800003562

in Bibtex Style

@conference{icdpcs23,
author={Xingguan Ma and Zhiyi Wang and Hongyu Shi and Li Zhang},
title={Expert System for the Control of Effluent TN Excedance of AAO Process},
booktitle={Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS},
year={2023},
pages={79-88},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012149800003562},
isbn={978-989-758-675-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Processing, Control and Simulation - Volume 1: ICDPCS
TI - Expert System for the Control of Effluent TN Excedance of AAO Process
SN - 978-989-758-675-0
AU - Ma X.
AU - Wang Z.
AU - Shi H.
AU - Zhang L.
PY - 2023
SP - 79
EP - 88
DO - 10.5220/0012149800003562
PB - SciTePress