The filtration and backwashing performances of the deep bed filtration system using unique filter media made of long length poly-propylene fibers weaved into ring shape were investigated. The dynamic behavior of concentration of particles in filter bed during filtration, i.e. breakthrough curve, was observed. The filtration behavior was evaluated with the deep bed filtration model as filtration coefficient λ₀, which is an index of particle capture efficiency, and filtration capacity σ_s. The effects of feed concentration and flow rate on the filtration performance were analyzed with the deep bed filtration model. The results showed that the filtration performances depended on the amount of filtered particles regardless of feed concentration and flow rate. The backwashing of filtration column was conducted with upward two-phase flow, which consisted of water and air. The change in turbidity of effluent showed two stage exponential changes, suggesting that, the particles can be classified into two groups which are particles easy to remove and particles difficult to remove. A mathematical model evaluating the backwashing behavior was developed for optimizing of backwashing condition. The effects of water flow rate and air flow rates were analyzed with this model and the optimal backwashing condition was determined.

研究了使用由编织成环状的长聚丙烯纤维制成的独特过滤介质的深床过滤系统的过滤和反冲洗性能。观察到过滤过程中滤床中颗粒浓度的动态行为，即穿透曲线。与深床过滤模型的过滤行为评价为过滤系数λ ₀，其中是的粒子捕获效率的指标，并且过滤能力σ_小号。用深床过滤模型分析了进料浓度和流速对过滤性能的影响。结果表明，无论进料浓度和流速如何，过滤性能都取决于所过滤颗粒的数量。过滤塔的反洗是由水和空气组成的向上两相流进行的。出水浊度的变化呈现出两阶段的指数变化，表明颗粒可分为易去除颗粒和难去除颗粒两类。建立了评估反冲洗行为的数学模型，以优化反冲洗条件。用该模型分析了水流量和空气流量的影响，并确定了最佳的反冲洗条件。