Activated sludge monitoring of a wastewater treatment plant using image analysis and partial least squares regression (original) (raw)
Related papers
Evaluation of activated sludge systems by image analysis procedures
2008
Biomass inspection under optical microscopy coupled to automated image analysis methodologies is, nowadays, increasingly used. Image analysis is presently considered a powerful tool to identify and quantify biomass morphological and physiological changes. In this work, an image analysis program was developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in six different wastewater treatment plants.
Chemosphere, 2011
The present study proposes an image analysis methodology for the identification of different types of disturbances in wastewater treatment activated sludge systems. Up to date, most reported image analysis methodologies have been used in activated sludge processes with the aim of filamentous bulking detection, however, other disturbances could be foreseen in wastewater treatment plants. Such disturbances can lead to fluctuations in the biomass contents, affecting the mixed liquor suspended solids (MLSS), and in the sludge settling ability, affecting the sludge volume index (SVI). Therefore, this work focuses on predicting the MLSS and SVI parameters for different types of disturbances affecting an activated sludge system. Four experiments were conducted simulating filamentous bulking, zoogleal or viscous bulking, pinpoint floc formation, and normal operating conditions. Alongside the MLSS and SVI determination, the aggregated and filamentous biomass contents and morphology were studied as well as the biomass Gram and viability status, by means of image analysis.
Automatic identification of activated sludge disturbances and assessment of operational parameters
Chemosphere, 2013
Activated sludge systems are prone to be affected by changes in operating conditions leading to problems such as pinpoint flocs formation, filamentous bulking, dispersed growth, and viscous bulking. These problems are often related with the floc structure and filamentous bacteria contents. In this work, a lab-scale activated sludge system was operated sequentially obtaining filamentous bulking, pinpoint floc formation, viscous bulking and normal conditions. Image processing and analysis techniques were used to characterize the contents and structure of aggregated biomass and the contents of filamentous bacteria. Further principal component and decision trees analyses permitted the identification of different conditions from the collected morphological data. Furthermore, a partial least squares analysis allowed to estimate the sludge volume index and suspended solids key parameters. The obtained results show the potential of image analysis procedures, associated with chemometric techniques, in activated sludge systems monitoring.► Automatic image analysis methodology was evaluated to monitor activated sludge. ► Principal component analysis and decision trees identified different operating conditions. ► Partial least squares estimated sludge volume index and total suspended solids. ► An invaluable method in quality assessment of activated sludge was established.
Characterization of activated sludge abnormalities by image analysis and chemometric techniques
Analytica Chimica Acta, 2011
This work focuses on the use of chemometric techniques for identifying activated sludge process abnormalities. Chemometric methods combined with image analysis can improve activated sludge systems monitoring and minimize the need of analytical measurements. For that purpose data was collected from aggregated and filamentous biomass, biomass composition on Gram-positive/Gram-negative bacteria and viable/damaged bacteria, and operational parameters. Principal component analysis (PCA) was subsequently applied to identify activated sludge abnormalities, allowing the identification of several disturbances, namely filamentous bulking, pinpoint flocs formation, and zoogleal bulking as well as normal conditions by grouping the collected samples in corresponding clusters.
2009
In the last years there has been an increase on the research of the activated sludge processes, and mainly on the solid–liquid separation stage, considered of critical importance, due to the different problems that may arise affecting the compaction and the settling of the sludge. Furthermore, image analysis procedures are, nowadays considered to be an adequate method to characterize both aggregated and filamentous bacteria, and increasingly used to monitor bulking events in pilot plants.
Bioprocess and Biosystems Engineering, 2009
In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid-liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.
New insights in morphological analysis for managing activated sludge systems
Water science and technology : a journal of the International Association on Water Pollution Research, 2018
In activated sludge (AS) process, the impact of the operational parameters on process efficiency is assumed to be correlated with the sludge properties. This study provides a better insight into these interactions by subjecting a laboratory-scale AS system to a sequence of operating condition modifications enabling typical situations of a wastewater treatment plant to be represented. Process performance was assessed and AS floc morphology (size, circularity, convexity, solidity and aspect ratio) was quantified by measuring 100,000 flocs per sample with an automated image analysis technique. Introducing 3D distributions, which combine morphological properties, allowed the identification of a filamentous bulking characterized by a floc population shift towards larger sizes and lower solidity and circularity values. Moreover, a washout phenomenon was characterized by smaller AS flocs and an increase in their solidity. Recycle ratio increase and COD:N ratio decrease both promoted a slig...
Digital Image Processing and Analysis for Activated Sludge Wastewater Treatment
Advances in Experimental Medicine and Biology, 2014
Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.