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Standardization of the Limit of Stokesian Settling Measurement Using Simple Image Data Analysis (Manuscript)

机译:使用简单图像数据分析标准化斯托克斯沉降测量的极限(手稿)

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In wastewater treatment, clarifiers are critical to maintain clear effluent. The limit of stokesian settling (LOSS) parameter measures the total suspended solids (TSS) concentration at which clarifier failures occur. This parameter characterizes a wastewater transition from a faster settling or flocculent regime to a slower or hindered regime. A limitation in measurement of LOSS was visual subjectivity. In this study, three methods employing grayscale image data were introduced for measuring LOSS. They used simple linear regression, sigmoid fitting, noise (standard deviations in grayscale index) respectively and were tested for consistency in changing light exposure settings, settling time and sludge quality. Light exposure impacted the measurements at very bright settings, by decreasing the sensitivity of calculations, while longer settling times for taking measurements (> 50 s) also reduced the sensitivity. Noise calculations provided the least variability in LOSS from the methods, and was promising to use as a metric for LOSS.
机译:在废水处理中,澄清剂对于保持澄清的废水至关重要。斯托克斯沉降(LOSS)参数的极限值用于确定澄清器发生故障时的总悬浮固体(TSS)浓度。该参数表征废水从较快的沉降或絮凝状态到较慢或受阻状态的过渡。测量LOSS的局限性是视觉主观性。在这项研究中,介绍了三种使用灰度图像数据的方法来测量LOSS。他们分别使用简单的线性回归,S形拟合,噪声(灰度指数的标准偏差),并在改变曝光设置,沉降时间和污泥质量方面进行了一致性测试。光线暴露会通过降低计算的灵敏度来影响非常明亮的设置下的测量结果,而更长的建立时间(> 50 s)也会降低灵敏度。噪声计算使这些方法的LOSS变异性最小,并且有望用作LOSS的度量标准。

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