Title :
Research on online trend omen extraction algorithm of sludge bulking
Author :
Yu Guang-ping;Wang Jing-yang;Yuan Ming-zhe;Yu Yang
Author_Institution :
Shenyang Institute of Automation. Guangzhou. Chinese, Academy of Science, Guangzhou, Guangdong Province, China
fDate :
6/1/2015 12:00:00 AM
Abstract :
Sludge bulking is one of the most serious abnormal conditions in the sewage treatment process, which has important influence on the normal operation of sewage treatment plants. Achieving online trend omen extraction of sludge bulking is helpful to the prediction of sludge bulking, and plays an important role in the prevention of sludge bulking. Basing on the development of trend analysis technology, we improved the offline trend extraction method in order to make it better adapt to the online trend extraction. This method can effectively extract the trend information of process data with relatively low computational complexity, which can be applied on industrial online process and provide support for the trend information demand of expert system.
Keywords :
"Conferences","Automation","Control systems","Intelligent systems","Erbium"
Conference_Titel :
Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8728-3
DOI :
10.1109/CYBER.2015.7288187