Abstract
In this paper, a data-driven scheme of key performance indicator (KPI) monitoring, prediction and KPI related fault detection is applied to the wastewater treatment process (WWTP). By means of a data-driven realization of the so-called left coprirne factorization (LCF) of the process, the efficient monitoring and prediction of chemical oxygen demand (COD) concentration in the effluent flow are realized both for the situation that COD is measurable and unmeasurable. The well established Benchmark Simulation Model no. 1 (BSM1) is utilized for the demonstration of the effectiveness of this approach.
| Original language | English |
|---|---|
| Pages (from-to) | 627-632 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 28 |
| Issue number | 21 |
| DOIs | |
| State | Published - 1 Sep 2015 |
| Event | 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015 - Paris, France Duration: 2 Sep 2015 → 4 Sep 2015 |
Keywords
- Data-driven
- KPI prediction
- Process monitoring
- Wastewater treatment process
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