Fault detection using dynamic time warping (DTW) algorithm and discriminant analysis for swine wastewater treatment

This paper proposes a diagnosis system using dynamic time warping (DTW) and discriminant analysis with oxidation-reduction potential (ORP) and dissolved oxygen (DO) values for swine wastewater treatment. A full-scale sequencing batch reactor (SBR), which has an effective volume of 20 m(3), was auto-controlled, and the reaction phase was performed by a sub-cycle operation consisting of a repeated short cycle of the anoxic-aerobic step. Using ORP and DO profiles, SBR status was divided into four categories of normal and abnormal cases; these were influent disturbance, aeration controller fault, instrument trouble and inadequate raw wastewater feeding. Through the DTW process, difference values (D) were determined and classified into seven cases. In spite of the misclassification of high loading rates, the ORP profile provided good diagnosis results. However, the DO profiles detected five misclassifications that indicated different statuses. After the DTW process, several statistical values, including maximum value, minimum value, average value, standard deviation value and three quartile values, were extracted and applied to establish the discriminant function. The discriminant analysis allows one to classify seven cases with a percentage of 100% and 92.7% for ORP and DO profiles, respectively. Consequently, the study showed that ORP profiles are more efficient than DO profiles as diagnosis parameters and DTW diagnosis algorithms and discriminants.