Department of Chemical Engineering, Hefei University of Technology, Hefei, 230009, China.
Bioresour Technol. 2012 Oct;121:161-8. doi: 10.1016/j.biortech.2012.06.093. Epub 2012 Jul 5.
An integrated approach incorporating response surface methodology (RSM), grey relational analysis, and fuzzy logic analysis was developed to quantitatively evaluate the conditioning chemicals in sludge dewatering process. The polyacrylamide (PAM), ferric chloride (FeCl(3)) and calcium-based mineral powders were combined to be used as the sludge conditioners in a pilot-scale sludge dewatering process. The performance of conditioners at varied dosages was comprehensively evaluated by taking into consideration the sludge dewatering efficiency and chemical cost of conditioner. In the evaluation procedure, RSM was employed to design the experiment and to optimize the dosage of each conditioner. The grey-fuzzy logic was established to quantify the conditioning performance on the basis of grey relational coefficient generation, membership function construction, and fuzzy rule description. Based on the evaluation results, the optimal chemical composition for conditioning was determined as PAM at 4.62 g/kg DS, FeCl(3) at 55.4 g/kg DS, and mineral powders at 30.0 g/kg DS.
采用响应面法(RSM)、灰色关联分析和模糊逻辑分析相结合的综合方法,定量评价污泥脱水过程中的调理化学品。在中试规模的污泥脱水过程中,将聚丙烯酰胺(PAM)、氯化铁(FeCl(3))和钙基矿物粉末组合用作污泥调理剂。通过考虑污泥脱水效率和调理剂的化学成本,综合评估了不同剂量下的调理剂的性能。在评估过程中,采用 RSM 设计实验并优化每个调理剂的剂量。基于灰色关联系数生成、隶属函数构建和模糊规则描述,建立灰色模糊逻辑来量化调理性能。根据评估结果,确定最佳的调理化学成分组合为 PAM 4.62 g/kg DS、FeCl(3)55.4 g/kg DS 和矿物粉末 30.0 g/kg DS。