1. A method of monitoring, validation and analysis for a process control system having normal process data and sensors, and represented by a plurality of primary process models and a plurality of process variables, comprising: generating a plurality of primary residual process models derived from said primary process models, said normal process data, and one or more statistical parameters corresponding to said normal process data; measuring real-time sensor data; computing primary residual values of said primary residual process models corresponding to said real-time sensor data; comparing said primary residual values to expected values; computing a certainty factor for a possible fault using fuzzy logic.