No abstract

Fault detection is an important part of process supervision, especially in processes where there are strict requirements on the process outputs like in wastewater treatment. Statistical control charts such as Shewhart charts, cumulative sum (CUSUM) charts, and exponentially weighted moving average (EWMA) charts are common univariate fault detection methods. These methods have different strengths and weaknesses that are dependent on the characteristics of the fault. To account for this the methods in their base forms were tested with drift and bias sensor faults of different sizes to determine the overall performance of each method. Additionally, the faults were detected using two different sensors in the system to see how the presence of active process control influenced fault detectability. The EWMA method performed best for both fault types, specifically the drift faults, with a low false alarm rate and good detection time in comparison to the other methods. It was shown that decreasing the detection time can effectively reduce excess energy consumption caused by sensor faults. Additionally, it was shown that monitoring a manipulated variable has advantages over monitoring a controlled variable as set-point tracking hides faults on controlled variables; lower missed detection rates are observed using manipulated variables.

Process control is an important part of any industrial system. In a wastewater reuse system this remains true. Process monitoring and fault detection (FD) are important to ensure that the control system has access to reliable data which can be used in making decisions about the operation of the process. The reuse scenario being considered in this work is that of utilizing the nutrients from the wastewater as fertilizer to agricultural soil along with using the water for irrigation purposes. This paper identifies variables that are important to the control of the process and should be a focus of monitoring and FD. In wastewater treatment these variables include temperatures, pressures, liquid levels, flow rates, pH, conductivity, biomass content, suspended solids concentration, dissolved oxygen content, total organic carbon, and the concentrations of nitrate and ammonium. The variables of interest in the reuse of nutrients and water for agriculture include soil moisture, ambient conditions, plant height, biomass content, photosynthetic activity of the crop, leaf area and leaf water content, as well as the concentrations of several ions both in the soil and in the plant. Challenges associated with process monitoring and FD specific to the two processes are also discussed, examples of these are the high dimensionality of the problem, the harsh conditions that sensors must operate in and the non-linear relationships between variables. This information will be used in future work when comparing specific FD methods to ensure that methods chosen are capable of overcoming the commonly encountered problems. I. INTRODUCTION One of the UN's sustainable development goals is clean water and sanitation. It states that everyone on the planet should have access to safe drinking water. However, according to Mekonnen & Hoekstra [1], a large part of the global population (66%) live under conditions of severe water scarcity at least 1 month every year. In Europe by 2014