A model-based method for an online diagnostic knowledge-based system

Fault diagnosis is very important for modern production technology and has received increasing theoretical and practical attention during the last few years. This paper presents a model-based diagnostic method for industrial systems. An online, real-time, deep knowledge based fault detection system has been developed by combining different development environments and tool s. The system diagnoses, predicts and compensates faults by coupling symbol ic and numerical data in a new environment suitable for the interaction of different sources of knowledge and has been successfully implemented and te sted on a real hydraulic system.