全生命周期污泥膨胀的智能检测和诊断分析

Full Life-Cycle Intelligent Detection and Diagnosis Analysis for Sludge Bulking

活性污泥法是我国最常用的污水处理工艺,然而,污泥膨胀的发生是活性污泥工艺稳定可靠运行难以回避和亟待解决的问题。为此,文中提出了一种新的全生命周期故障诊断方法,用于监测污泥膨胀,并在准确地预警故障后提供合理的决策支持。为了充分挖掘污泥膨胀数据的隐含信息,文中利用典型相关分析(CCA)和绝对平均振幅值(AMAV)提取相关特征并用于故障检测,通过重排历史观测样本的方法改进贡献图并用于故障分离;根据故障预警结果,提出了基于AMAV的特征提取和多元格兰杰因果(MVGC)分析的故障传播定位方法。使用在污水厂采集的现场数据进行实验,结果表明,所提方法能及时有效地检测、分离和分析污泥膨胀的发生。

Activated sludge process is the most commonly used sewage treatment process in China.The occurrence of sludge bulking is an unavoidable and urgent problem for the stable and reliable operation of activated sludge process.To solve this problem,this paper proposed a new full life-cycle fault diagnosis method to monitor sludge bulking and provide reasonable decision support after accurate fault warning.In order to fully mine the hidden information of sludge bulking data,this paper used the canonical correlation analysis(CCA)and absolute average amplitude value(AMAV)to extract the relevant features and apply them to fault detection.The contribution plots were improved by rearranging historical observation samples and applied to fault isolation.According to the results of fault warning,a fault propagation location method based on feature extraction of AMAV and multivariate Granger causality(MVGC)analysis was proposed.The field data collected in a sewage plant were used for experiments.The results show that the proposed method can detect,separate and analyze the occurrence of sludge bulking timely and effectively.