基于Haar小波分析改进的多元线性回归算法在MBR中的应用

Application of Improved Multivariate Linear Regression Algorithm Based on Haar Wavelet Analysis in MBR

摘要: 用MBR系统进行污水处理时，经常会遇到有大量的污泥被截留在膜表面的现象，该现象会造成膜污染，影响MBR系统处理污水的效果，因此我们需要解决的问题就是如何预测MBR系统中的污泥量以便及时清理污泥。为了解决该问题，本文利用基于Haar小波分析改进的多元线性回归算法对MBR系统中的污泥表观产率系数进行预测。通过实验，我们将预测结果与实际系统结果做对比，发现该算法达到了能够准确预测污泥表观产率系数的预期效果，解决了预测MBR系统中污泥量的问题，对提高MBR系统处理污水效果具有一定的价值。

Abstract: When using the MBR system for wastewater treatment, it is often encountered that a large amount of sludge is trapped on the surface of the membrane. This phenomenon will cause membrane fouling and affect the effect of the MBR system in treating sewage. Therefore, the problem we need to solve is how to predict the MBR. The amount of sludge in the system is used to clean the sludge in time. In order to solve this problem, this paper uses the improved multiple linear regression algorithm based on Haar wavelet analysis to predict the apparent yield coefficient of sludge in MBR system. Through experiments, we compare the predicted results with the actual system results, and find that the algorithm achieves the expected effect of accurately predicting the apparent yield co-efficient of the sludge, solves the problem of predicting the amount of sludge in the MBR system, and improves the processing of the MBR system. The sewage effect has a certain value.