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The MBR Membrane Life Prediction in Universities' Waste Water Treatment through Big Data Technology—Taking Xi'an Siyuan University as an Example

李东; 张学梅; 付波; 秦宝兰; 马青华
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摘要

The 3520 days operation data of the A2/O-MBR system of Xi'an Siyuan University has been processed using big data mean clustering analysis. The daily industrial permeability of each membrane pool was calculated according to the definition. After eliminating the five kinds of anomaly points, the effective daily industrial water permeability days of membrane tank 1#, 2# and 3# were 2474 days, 2725 days and 2652 days, respectively. The industrial water permeability of every 25 effective days was divided into a calculation unit, and the arithmetic mean and standard deviation of the unit were calculated. The arithmetic mean of the computing units for each membrane pool was arranged in order and returned to the industrial permeability decay equation. The intercept of the linear equation indicates the industrial permeability at the beginning. The negative slope of the linear equation implies that the industrial permeability is declining with the operating time. Based on the industrial permeability decay equation of each membrane pool, it can be determined that the annual industrial permeability rates of the 1#, 2#, and 3# membrane pools are 4.36%/Y, 4.10%/Y, and 4.54%/Y, respectively.

关键词

大数据技术日工业透水率有效日工业透水率工业透水率年衰减率Big Data TechnologyDaily Industrial PermeabilityEffective Daily Industrial PermeabilityAnnual Attenuation Rate of Industrial Permeability

出版信息

论文状态
公开发表
期刊名称
应用数学进展
发表日期
2022
卷
11
期
01
页码
-
DOI
10.12677/AAM.2022.111065

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