Outlining Process Monitoring and Fault Detection in a Wastewater Treatment and Reuse System

Abstract

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

Comparing statistical process control charts for fault detection in wastewater treatment

“…Limit sensing is not particularly sensitive or robust because it ignores interactions between different variables, this makes it a univariate technique (Chiang et al 2000). When considering FD in an industrial process, like the WWTP, there are advantages to investigating simple univariate FD methods despite the high level of complexity of the system (Marais et al 2020). Some of the primary benefits of evaluating univariate methods are to obtain a benchmark to evaluate the performance of more advanced and costly FD methods against, as well as in their potential to be combined with advanced methods.…”