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Fault signatures and bias progression in dissolved oxygen sensors

机译:溶解氧传感器中的故障签名和偏置进展

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Biofilm fouling is known to impact the data quality of sensors, but little is known about the exact effects. We studied the effects of artificial and real biofilm fouling on dissolved oxygen (DO) sensors in full-scale water resource recovery facilities, and how this can automatically be detected. Biofilm fouling resulted in different drift direction and bias magnitudes for optical (OPT) and electrochemical (MEC) DO sensors. The OPT-sensor was more affected by biofilm fouling compared to the MEC-sensor, especially during summer conditions. A bias of 1 mg/L was detected by analysing the impulse response (IR) of the automatic air cleaning system in the DO sensor. The IR is an effect of a temporal increase in DO concentration during the automatic air cleaning. The IRs received distinct pattern changes that were matched with faults including: biofilm fouling, disturbances in the air supply to the cleaning system, and damaged sensor membrane, which can be used for fault diagnosis. The results highlight the importance of a condition-based sensor maintenance schedule in contrast to fixed cleaning intervals. Further, the results stress the importance of understanding and detecting bias due to biofilm fouling, in order to maintain a robust and resource-efficient process control.
机译:已知生物膜结垢会影响传感器的数据质量,但对确切效果知之甚少。我们研究了人工和真正的生物膜污染在全尺寸水资源恢复设施中溶解氧(DO)传感器的影响,以及如何自动检测到这一点。生物膜污染导致光学(OPT)和电化学(MEC)的不同漂移方向和偏置幅度。与MEC传感器相比,替代品污染的选择液更大,特别是在夏季条件下。通过分析DO传感器中的自动空气清洁系统的脉冲响应(IR)来检测1mg / L的偏差。 IR是在自动空气清洁过程中浓度的时间增加的效果。美国国税局收到了与故障相匹配的不同模式变化,包括:生物膜污染,空气供应中的干扰,以及损坏的传感器膜,可用于故障诊断。结果突出了与固定清洁间隔相比的条件为基于传感器维护计划的重要性。此外,结果强调了理解和检测由于生物膜污染而检测偏差的重要性,以保持稳健和资源有效的过程控制。

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