污水处理厂的故障检测

2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2017-05-22 DOI:10.1109/ATSIP.2017.8075523

I. Baklouti, M. Mansouri, H. Nounou, M. Slima, A. Hamida

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引用次数: 5

摘要

本文提出了一种基于指数加权移动平均(EWMA)的无气味卡尔曼滤波(UKF)用于污水处理厂的故障检测。在基于UKF的EWMA中，利用UKF技术计算真实变量与估计变量之间的残差，并利用EWMA控制图进行故障检测。故障检测技术将使用模拟成本废水处理ASM1模型进行测试。采用虚警率(FAR)、平均运行长度(ARL1)和漏检率(MDR)三个故障检测标准对基于ukf的EWMA技术的检测结果进行了评价。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fault detection in a wastewater treatment plant

In this paper, Unscented Kalman filter (UKF) based Exponentially Weighted Moving Average (EWMA) is proposed for fault detection in a Wastewater Treatment Plant (WWTP). In the developed UKF-based EWMA, the UKF technique is used to compute the residual between the true and the estimated variable and the EWMA control chart is applied to detect the faults. The fault detection technique will be tested using simulated COST wastewater treatment ASM1 model. The detection results of the UKF-based EWMA technique are evaluated using three fault detection criteria: the false alarm rate (FAR), Average Run Length (ARL1) and the missed detection rate (MDR).

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2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

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