对于水处理厂（WTP）运营商来说，确定过滤器运行是否接近突破性条件是一项日常挑战。目前的技术是寻找过滤出水的浊度或颗粒数的上升趋势。然而，这并不总是预测过滤器的实际突破。本研究的目的是确定是否可以更好地利用来自不同粒子检测技术的数据来表征过滤器的性能。将使用简单的统计技术来检查基线过滤器出水值的稳定性。本研究利用传统和新的颗粒检测技术来监测整个过滤器运行过程中的过滤废水。每种技术（颗粒计数器、调节浊度计和激光浊度计）将在每次过滤器运行时分别进行评估，以确定哪种技术在基线稳定性和过滤器性能之间产生最佳相关性。 将评估每种粒子检测技术预测过滤器突破的能力。最终，这项研究将确定这种相关性是否可以提供解释过滤器性能的确定方法，然后可以用于预测过滤器突破。将使用中试规模工厂的完整过滤器运行数据。过滤器运行的数据可以通过突破进行，这将有助于确定这些信息是否可以预测突破。此外，还分析了几座大型水处理厂的出水数据，并给出了一个实例。这些信息将用于确认中试工厂数据，并提高中试研究模型的可信度。 结果表明，当使用激光浊度计和（在较小程度上）粒子计数器来监测过滤器出水时，随着过滤器运行的进行，测量基线稳定性降低（噪声级增加）。在过滤废水监测过程中观察到的测量稳定性下降通常归因于仪器中的电子噪声。这项研究提供的证据表明，噪声不是由激光浊度计引起的，而是由样品中的细微变化引起的。包括3个参考文献、表格、图表。

Determining if a filter run is approaching a breakthrough condition is a daily challenge for water treatment plant (WTP) operators. Current techniques look for upward trends in either turbidity or particle counts of the filter effluent. However, this does not consistently predict actual filter breakthrough. This study's objective is to determine if data from different particle detection technologies can be better utilized to characterize filter performance. Simple statistical techniques will be used to interrogate the stability of the baseline filter effluent water values. This study utilizes both traditional and new particle detection technologies to monitor filter effluent for the entire filter run. Each type of technology (particle counters, regulatory turbidimeters, and laser nephelometers) will be evaluated separately on each filter run to determine which generates the best correlation between baseline stability and filter performance. The ability of each of these particle detection technologies to predict filter breakthrough will be evaluated. Ultimately, this study will determine if such correlations can provide a definitive means of interpreting filter performance and can then be used to predict filter breakthrough. Data from complete filter runs at a pilot-scale plant will be used. The data from the filter runs, which were allowed to proceed through breakthrough, will help determine if this information can actually predict breakthrough. In addition, effluent data from several full-scale water treatment plant runs are analyzed and an example is presented. This information will be used to confirm the pilot-plant data and increase the credibility of the pilot study model. Results have shown that when laser nephelometers, and (to a lesser degree) particle counters, are used to monitor filter effluent, the measurement baseline stability decreases (the noise level increases) as the filter run progresses. The decrease in measurement stability, when observed during filter effluent monitoring is often attributed to electronic noise in the instrument. This study provides evidence that the noise is not attributed to the laser nephelometer, but instead, is due to subtle changes in the sample. Includes 3 references, table, figures.