Characterization of Value for Sensor Networks for Process Fault Diagnosis

Safety and optimality are crucial requirements in every industrial process. Modern day chemical plants, in particular, require comprehensive fault diagnosis procedures to function smoothly. The success of any fault diagnosis technique depends critically on the sensors measuring the important process variables. With thousands of possible measurements in a typical plant, the selection of variables for sensor placement is not an easy task. There has been considerable amount of work that has been done on developing algorithms for sensor network design for fault diagnosis based on qualitative graph models. Various objectives such as cost, reliability and fault resolution have been used in the sensor network design. While these design algorithms can provide the best design locations for a given cost, the value of the sensor network for fault diagnosis is usually not quantified. This is an important aspect that needs to be addressed if these algorithms have to be assimilated into industrial practice