Title :
On-line diagnosis system with Bayesian networks for WWTP
Author :
Cheon, Seong-Pyo ; Baek, Gyeongdong ; Kim, Sungshin
Author_Institution :
Dept. of Electr. Eng., Pusan Nat. Univ., Busan
Abstract :
Nowadays, due to development of automatic control devices and various sensors, one operator can freely handle several remote plants and processes. Automatic diagnosis and warning systems have been adopted in various fields, in order to prepare an operatorpsilas absence for patrolling plants. In this paper, a Bayesian networks based on-line diagnosis system is proposed for a wastewater treatment process. Especially, the suggested system is included learning structure, which can continuously update conditional probabilities in the networks. To evaluate performance of proposed model, we made a lab-scale five-stage step-feed enhanced biological phosphorous removal process plant and applied on-line diagnosis system to this plant in the summer.
Keywords :
belief networks; chemical engineering computing; chemical industry; industrial plants; production engineering computing; wastewater treatment; Bayesian networks; automatic control devices; biological phosphorous removal process plant; conditional probabilities; learning structure; online diagnosis system; warning systems; wastewater treatment process; Automatic control; Bayesian methods; Chemical analysis; Chemical sensors; Communication system control; Fault diagnosis; Intelligent sensors; Intelligent systems; Plants (biology); Wastewater treatment;
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
DOI :
10.1109/ICIAS.2007.4658552