Fault Detection in Wastewater Treatment : Process Supervision to Improve Wastewater Reuse

Sammanfattning: As wastewater treatment plants transition to water resource recovery facilities, the need for improved control and consequently supervision increases. Despite the large volume of research that has been performed on this topic, the use in industry is scarce. Practical implementation is challenging due to the nature of the process, and a lack of standardisation in the research results in uncertainty as to the state of the art. This is one of the main challenges identified. Experimental work is performed using the Benchmark Simulation Model No. 1 to identify monitoring requirements and evaluate the performance of univariate fault detection methods. For the former, residual based process fault signatures are used to determine minimal sensor requirements based on detectability and isolability goals. Sensor faults are the focus of the latter issue, using the Shewhart, cumulative sum, and exponentially weighted moving average control charts to detect bias and drift faults in a controlled variable sensor. The use of a standard model and known fault detection methods is useful to establish a baseline for future work. Given the lack of standardised use in industry this is considered critical. Both proposed methods emphasise ease of visualisation which is beneficial for industrial implementation.