Integration of a failure monitoring within a hybrid dynamic simulation environment

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Fault Localization Models in Debugging

Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it is quite difficult to overcome all the faults of software programs. Thus, it is still remains as a real challenge for software debugging and maintenance community. In this paper, we briefly introduced software anomalies and faults classification and then explained different fault localization models using theory of diagnosis. Furthermore, we compared and contrasted between value based and dependencies based models in accordance with different real misbehaviours and presented some insight information for the debugging process. Moreover, we discussed the results of both models and manifested the shortcomings as well as advantages of these models in terms of debugging and maintenance.Comment: 58-6