Abstract This work presents a new method for an online measurement of particles detached from a starch fouling layer during a cleaning process. This was achieved by designing the Automated Particle Analyser for Cleaning (APAC) by combining a flow channel with a laser diffraction particle size analyser. A method for the online measurement of particle size for different sets of parameters (flow velocity, temperature and addition of Sodium Hydroxide) was developed, monitoring cleaning progress and behaviour. The influence of the variation of the parameters on the progress of cleaning as well as their balance could be shown. Low temperature or velocity cause increasing cleaning time and vice versa. Overall detachment of small particles indicating cohesive failure could be observed as characteristic for starch based fouling layers. A narrow particle size distribution (PSD) of small particles indicates a cohesive failure and a steady disintegration of the fouling layer from top to bottom. On the contrary a PSD of larger size and broader shape prevails for adhesive failure and detachment of large patches of the fouling layer.

中文翻译：

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一种新的在线表征分离颗粒同时清洁淀粉污垢层的方法

摘要 这项工作提出了一种在线测量清洗过程中从淀粉污垢层分离的颗粒的新方法。这是通过将流道与激光衍射粒度分析仪相结合来设计用于清洁的自动颗粒分析仪 (APAC) 来实现的。开发了一种在线测量不同参数组（流速、温度和氢氧化钠添加量）的粒度的方法，用于监控清洁进程和行为。可以显示参数变化对清洁进度及其平衡的影响。低温或流速低会导致清洁时间增加，反之亦然。可以观察到表明内聚力破坏的小颗粒的整体分离是淀粉基污垢层的特征。小颗粒的窄粒度分布 (PSD) 表明结垢层从上到下发生内聚破坏和稳定分解。相反，较大尺寸和较宽形状的 PSD 会导致粘附失效和污垢层大块的脱离。