Research on the detection method for abnormal data of wastewater treatment plants based on statistical theory

DOI

10.2991/icaees-15.2015.145How to use a DOI?

Keywords

Statistical theory, wastewater treatment plant, abnormal data detection, t-test method, online monitoring, significant difference analysis

Abstract

In this study, statistical theory is employed to identify abnormal online monitoring data and substandard effluent water quality in a wastewater treatment plant (WTP) of northern China. The effluent water quality can be monitored and checked by the national standard (GB18918-2002). The detection of abnormal data is achieved for daily monitoring data by single-side t-test and two-side t-test methods. Meanwhile, significance difference analysis between manual data and online monitoring date is investigated to check whether there is abnormity in manual data. The established method is then applied to an actual case. The result indicates that the method can effectively identify the abnormal data in WTPs and provide powerful technical measures for regulatory authorities.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liang Guo
AU  - Ying Zhao
AU  - Fuyi Cui
PY  - 2015/07
DA  - 2015/07
TI  - Research on the detection method for abnormal data of wastewater treatment plants based on statistical theory
BT  - Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015
PB  - Atlantis Press
SP  - 793
EP  - 797
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaees-15.2015.145
DO  - 10.2991/icaees-15.2015.145
ID  - Guo2015/07
ER  -