Process fault diagnosis (PFD) allows a control system to maintain the operation of a process under the presence of faults. This is a critical feature for a discontinuous activated sludge waste water treatment (WWT) process in a sequencing batch reactor (SBR), treating waste water contaminated with organic toxic compounds. Here, a methodology for diagnosis based on the extraction of characteristics from the respiration signal, a known indicator for biological activity in aerobic WWT processes, and their classification is proposed. The usefulness of the signal for the detection and classification of a set of defined abnormal conditions was verified through sensitivity analysis. The analysis not only shows the effects of parameter deviations but also indicates the characteristics to be extracted from the respiration signal for a successful classification. Results obtained by simulation indicate that the signal based PFD can successfully cope with uncertainties common in this type of bioprocesses, which prevent the straightforward application of analytical PFD approaches.