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http://dx.doi.org/10.5391/JKIIS.2015.25.2.119

Development of Sludge Concentration Estimation Method using Neuro-Fuzzy Algorithm  

Jang, Sang-Bok (Department of Control and Robotics Engineering, Chungbuk University)
Lee, Ho-Hyun (Department of Control and Robotics Engineering, Chungbuk University)
Lee, Dae-Jong (Department of Control and Robotics Engineering, Chungbuk University)
Kweon, Jin-Hee (LETECH Co.Ltd.)
Chun, Myung-Geun (Department of Control and Robotics Engineering, Chungbuk University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.25, no.2, 2015 , pp. 119-125 More about this Journal
Abstract
A concentration meter is widely used at purification plants, sewage treatment plants and waste water treatment plants to sort and transfer high concentration sludge and to control the amount of chemical dosage. When the strange substance is contained in the sludge, however, the attenuation of ultrasonic wave could be increased or not be transmitted to the receiver. At that case, the value of concentration meter is higher than the actual density value or vibrated up and down. It has also been difficult to automate the residuals treatment process according to the problems as sludge attachment or damage of a sensor. Multi-beam ultrasonic concentration meter has been developed to solve these problems, but the failure of the ultrasonic beam of a specific concentration measurement value degrade the performance of the entire system. This paper proposes the method to improve the accuracy of sludge concentration rate by choosing reliable sensor values and learning them by proposed algorithm. The prediction algorithm is chosen as neuro-fuzzy model, which is tested by the various experiments.
Keywords
Ultrasonic density meter; Neuro-fuzzy model; Purification plant; Sewage treatment plant;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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