Support vector methods and use of hidden variables for power plant monitoring

This paper has three contributions to the fields of power plant monitoring. First, we differentiate out-of-range detection from fault detection. An out-of-range refers to a normal operating range of a power plant unseen in the training data. In the case of an out-of-range, instead of producing a fault alarm, the system should notify the operator to include more training data which capture this new operating range. Second, we apply a support vector one-class classifier to out-of-range detection for its good volume modeling ability. Third, we propose to use hidden variables in regression models for fault detection. This is shown to be much better than prior work in terms of spillover reduction.