Integrated design of monitoring, analysis and maintenance for filamentous sludge bulking in wastewater treatment

被引:28
|
作者
Liu, Yiqi [1 ,2 ]
Yuan, Lingling [1 ]
Huang, Shuo [2 ]
Huang, Daoping [1 ]
Liu, Bin [3 ]
机构
[1] South China Univ Technol, Sch Automat Sci & Engn, Wushan Rd, Guangzhou 510640, Peoples R China
[2] City Univ Hong Kong, Dept Syst Engn & Engn Management, Kowloon, Hong Kong, Peoples R China
[3] Univ Strathclyde, Dept Management Sci, Glasgow, Lanark, Scotland
基金
中国国家自然科学基金;
关键词
Fault diagnosis; Maintenance; Wastewater; Filamentous sludge bulking; Virtual measurement; FAULT-DETECTION METHODS; SENSITIVITY-ANALYSIS; MODELS; DIAGNOSIS; CONNECTIVITY; PERFORMANCE; ENTROPY; SIGNALS; SYSTEMS; PCA;
D O I
10.1016/j.measurement.2020.107548
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Stable operation of activated sludge process is often compromised by the occurrence of filamentous sludge bulking in wastewater treatment. Standard maintenance is implemented as a single task, which is inefficiently manipulated based on purely chemical dosage by experiences. This paper proposes a novel and efficient maintenance framework, including a set of activities: incipient fault detection, causality analysis, remaining useful life (RUL) prediction and maintenance schedule, to develop a collective strategy for sludge bulking management. In this framework, Canonical Correlation Analysis (CCA) work together with Kurtosis (KU) and an autoregressive moving average (ARMA) to identify incipient sludge bulking and to capture the evolution of sludge bulking over a long horizon. The proposed framework was tested by the collected the field data. The results showed that the proposed framework is capable of detecting (Type I error, 2.1%; Type II error, 0%), locating (root cause: temperature), calculating RUL (32-days) and maintaining sludge bulking. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
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