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<p>One of the leading challenges in Water Resource Recovery Facility monitoring and control is the poor data quality and sensor consistency due to the tough and complex circumstances of the process operation. This paper presents a new principal component analysis fault detection approach for the nitrate and nitrite concentration sensor based on Water Resource Recovery Facility measurements, together with the Fisher Discriminant Analysis identification of fault types. Five malfunction cases were considered: constant additive error, ramp changing error in time, incorrect amplification error, random additive error, and unchanging sensor value error. The faults’ implementation, fault detection, and identification methods are presented and evaluated in terms of accuracy and promptitude. The models are originating from a municipal plant. The amount of required electrical energy and greenhouse gas released during the Water Resource Recovery Facility operation were assessed for the cases of nitrates and nitrites NO sensor normal and malfunctioning regimes. The environmental and economic evaluations show the benefits of detecting and identifying nitrates and nitrites NO sensor defects aimed at providing efficient and environmentally friendly operation of the Water Resource Recovery Facility. The fault-affected operation cases showed increased values, up to 10% for the total energy demand and 4% for the total greenhouse gas emissions, when they are compared to the normal operation case.</p>

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Fault detection and diagnosis of the wastewater nitrate and nitrite sensors using PCA and FDA combined with assessment of the economic and environmental impact of the faults

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月2日

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  • Alexandra-Veronica Luca,
  • Melinda Simon-Várhelyi,
  • Norbert-Botond Mihály,
  • Vasile-Mircea Cristea

摘要

One of the leading challenges in Water Resource Recovery Facility monitoring and control is the poor data quality and sensor consistency due to the tough and complex circumstances of the process operation. This paper presents a new principal component analysis fault detection approach for the nitrate and nitrite concentration sensor based on Water Resource Recovery Facility measurements, together with the Fisher Discriminant Analysis identification of fault types. Five malfunction cases were considered: constant additive error, ramp changing error in time, incorrect amplification error, random additive error, and unchanging sensor value error. The faults’ implementation, fault detection, and identification methods are presented and evaluated in terms of accuracy and promptitude. The models are originating from a municipal plant. The amount of required electrical energy and greenhouse gas released during the Water Resource Recovery Facility operation were assessed for the cases of nitrates and nitrites NO sensor normal and malfunctioning regimes. The environmental and economic evaluations show the benefits of detecting and identifying nitrates and nitrites NO sensor defects aimed at providing efficient and environmentally friendly operation of the Water Resource Recovery Facility. The fault-affected operation cases showed increased values, up to 10% for the total energy demand and 4% for the total greenhouse gas emissions, when they are compared to the normal operation case.