Ammonium Sensor Fault Detection in Wastewater Treatment Plants

David Tena, Ignacio Peñarrocha-Alós, Roberto Sanchis, Rubén Moliner-Heredia


We develop a fault detection strategy for the output ammonium sensor present in wastewater treatment plants. The only assumed measurements are the output ammonium concentration, the aeration of the reactor and the incoming volumetric flow to the plant. The incoming ammonium concentration is not measured, resulting in an important source of uncertainty. We use a IIR model based on Volterra series for predicting the ammonium measurement and we design a fault detector based on a filter applied on the prediction error and a threshold comparator to decide whether the sensor is faulty or not. The faults in the sensor are assumed to produce a slowly decreasing gain due to dirtiness in its surface. The fault detector design is based on the trade-off between fault detection sensitivity and disturbance rejection (due to measurement noise and model uncertainty). The design parameters are based in understandable fault indices: time needed to detect the fault, gain deviation at the time of detection, and poured volume of ammonium until the fault is detected. We use the benchmark BSM1 to validate the results as a common frame in the study of waste water treatment plants.


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