Data validation; Gross error detection; Mass balancing; Observability; Redundancy
Although data reconciliation is intensely applied in process engineering, almost none of its powerful methods are employed for validation of operational data from wastewater treatment plants. This is partly due to some prerequisites that are difficult to meet including steady state, known variances of process variables and absence of gross errors. However, an algorithm can be derived from the classical approaches to data reconciliation that allows to find a comprehensive set of equations describing redundancy in the data when measured and unmeasured variables (flows and concentrations) are defined. This is a precondition for methods of data validation based on individual mass balances such as CUSUM charts. The procedure can also be applied to verify the necessity of existing or additional measurements with respect to the improvement of the data's redundancy. Results are given for a large wastewater treatment plant. The introduction aims at establishing a link between methods known from data reconciliation in process engineering and their application in wastewater treatment.
The final publication is available via <a href="https://doi.org/10.1016/j.watres.2014.03.042" target="_blank">https://doi.org/10.1016/j.watres.2014.03.042</a>.