This paper describes a real-time on-line fault detection and diagnosis approach using PCA (Principal Component Analysis) and KBS (Knowledge-Based system). Then this paper applies the approach to a refinery process simulation that produces cyclohexane using benzene and hydrogen. The result shows that both sensor faults and process faults can be quickly detected and sensor faults can be clearly differentiated from process faults by using the intelligent PCA approach.