A quantitive fault diagnosis system for backfill hydrocyclones using modelling and parameter estimation was developed. The system was evaluated using simulation, thereby allowing arbitrary process variable fault levels and combinations of faults to be introduced into the system, as well as controlled levels of random noise in the process output measurements. The fault diagnosis system determines that point in the search space that minimises the difference between the measured process outputs and the process outputs predicted by previously determined process models by simultaneously adjusting the model parameters. At the minimum, estimates of the unmeasurable process variables are provided by the model parameters. A gradual increase in the feed - 75 micron fraction was considered, as well as a simultaneous increase in both the vortex finder and spigot diameters. Faults could clearly be identified by observing the trends in inferred variable values over time. Subjective decisions as to the level of incipiency of faults can be reduced by performing quantitative alarm analysis on these values. Both non-parametric and parametric alarm analysis was evaluated and it was found that a combination of these methods would enable timeous detection of both gradual and abrupt faults. The use of quantitative fault diagnosis to detect incipient faults in process parameters could be of great value in maintaining production levels, planning maintenance and optimising system performance.