IBB-Institute for Biotechnology and Bioengineering, Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057 Braga, Portugal.
Chemosphere. 2011 Oct;85(4):643-52. doi: 10.1016/j.chemosphere.2011.07.012. Epub 2011 Aug 12.
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.
本研究提出了一种用于识别废水处理活性污泥系统中不同类型干扰的图像分析方法。迄今为止，大多数已报道的图像分析方法都已用于活性污泥工艺，目的是检测丝状菌膨胀，但是，在污水处理厂中也可能会出现其他干扰。这些干扰会导致生物量含量波动，影响混合液悬浮固体（MLSS），并影响污泥沉降性能，影响污泥体积指数（SVI）。因此，这项工作侧重于预测影响活性污泥系统的不同类型干扰的 MLSS 和 SVI 参数。进行了四项实验，模拟丝状菌膨胀、菌胶团或粘性膨胀、针状絮体形成以及正常运行条件。除了确定 MLSS 和 SVI 之外，还通过图像分析研究了聚集和丝状生物量含量和形态以及生物量革兰氏染色和活力状态。
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