Quantification of performance of sensor networks for fault diagnosis

Safety and optimality are crucial requirements in every industrial process. The success of any fault diagnosis technique depends critically on the sensors measuring the important process variables. Choosing an appropriate sensor network is a combinatorially difficult problem, especially when the number of potential measurements is large. There has been considerable amount of work that has been done on developing algorithms for sensor network design for fault diagnosis based on quantitative and qualitative 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 or benefit accrued is usually not quantified in a manner that is transparent to the user. This is an important aspect that needs to be addressed if these algorithms have to be assimilated into industrial practice. An approach for characterizing the value of a sensor network from a fault diagnosis perspective is proposed. This notion of value can be used directly in sensor network design algorithms. The proposed concepts are explained through a simple example and numerical simulations of a CSTR. (c) 2007 American Institute of Chemical Engineers.