Artificial Neural Network Approach for Fault Recognition in a Wastewater Treatment Process

被引：0
|
作者：
Miron, Mihaela [1 ]
Frangu, Laurentiu [1 ]
Caraman, Sergiu [1 ]
Luca, Laurentiu [1 ]
机构：
[1] Dunarea de Jos Univ Galati, Fac Automat Comp Elect Engn & Elect, Galati, Romania
来源：
2018 22ND INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC) | 2018年
关键词：
wastewater treatment process; neural networks; fault isolation; fault recognition; actuator fault; sensor fault; process diagnosis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper deals with fault detection and recognition for WWTP (Wastewater Treatment Plant). The chosen classifier is a feed-forward neural network. Its input is a high-size vector of measured variables, rather than a smallsize compressed feature vector. The output of the network points to the recognized fault class. The test was performed on a simulated WWTP, disturbed by 6 different types of faults (sensors and actuators). The results of the test proved a good ability of the neural network to recognize the faults, in 97.2% of the analysed cases.
引用
收藏
页码：634 / 639
页数：6
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