Image Analysis of Sludge Aggregates in Palm Oil Mill Effluent (POME) - Rizal Song, Ian Norman (IRC, 2015)
Palm oil mill effluent (POME) is a wastewater produced by palm oil milling activities which generated from crude oil clarification process, sterilization process and cracked mixture separation process. Palm oil mill effluent (POME) is a highly polluting material and activated sludge system is now commonly used for the process of purification of the wastewater. Activated sludge system is a complex ecosystem in which the efficiency is quite dependent on the operating conditions of the process. Due to its complexity, any imbalance between the different types of microorganism may take place and affect the efficiency of the plant with profound economic and environmental consequences. To observe and regulate activated sludge system, bright field microscopy is acquired to monitor the sludge aggregates in palm oil mill effluent (POME). Furthermore, the association of image processing and analysis methodologies with microscopy allows a precise evaluation of the activated sludge status. The most common problems on activated sludge is filamentous bulking due to the extensive growth of the filamentous bacteria which led to poor sludge settling ability and poor thickening characteristics of the sludge thus increase the sludge volume index (SVI). Therefore, the main objectives of the research work is to develop image analysis algorithm by using Matlab in order to identify aggregates characterization in activated sludge system and to develop a correlation between image data obtained and sludge volume index (SVI) for POME. In this research work, two samples will be obtained which are fresh POME collected from the mill and POME undergo Fenton Reagent process. A few process will be prepared for the sample collected namely calculating sludge volume index, image acquisition using microscopy, image processing and analysis, identify image analysis parameter and plot the correlation between SVI with determine parameter. By conducting this research, image analysis algorithm can be developed to monitor sludge aggregates in POME. Thus, this algorithm can be used to identify bulking problems in the POME and establish the true nature of the phenomenon occurring inside the activated sludge system which normally will affect the quality of the effluent