This paper deals with a state observation approach for Discrete Event Systems with a known behavior. The system behavior is modeled using a Time Petri Net model. The proposed approach exploits temporal constraints to assess the system state and therefore detect and determine faults given partial observability of events. The goal here is to track the system state and to identify the event scenarios which occur on the system. Our approach uses the class graph of the Time Petri Net which models the complete system behavior to develop a state observer which is a base to perform online fault detection and diagnosing.