On-line monitoring of oil in water using transmitted-scattered lights and clustering-based hierarchical TSK fuzzy systems

This paper presents an online content prediction system of oil in water using transmitted-scattered lights and clustering based hierarchical Takagi-Sugeno-Kang (TSK) fuzzy systems. The measurement of transmitted-scattered lights would be suggested with methods that it can use rapidly, continuously, conveniently, and accurately. TSK fuzzy systems offer the prediction model that is the conversion of non-linear dynamic light intensities into oil content. The proposed clustering based hierarchical TSK fuzzy system is evaluated using measured light of oily water. When compared to the conventional adaptive network-based fuzzy inference system and proposed models, the developed method exhibits results with high accuracy and smaller size of fuzzy rules. This measurement method and prediction model would be applied oil discharge monitoring control equipment in oil tanker vessels.