Online risk assessment using a bank of Kalman Filters and event tree

Abstract

Early detection of faults in a process plant is important in order to prevent of happening catastrophic events which might cause deaths, economic, and environmental losses. Recently, on-line calculation of risk and its use for monitoring of process faults were proposed by [Bao et al., 2011]. In this study, a new methodology is proposed which brings more clarity in the calculation of risk from online monitoring of process data. In the proposed methodology, process faults have been classified into two groups: hardware failure and disturbance type faults. First a “Bank of Kalman Filters” is used to detect and diagnose possible failures occurred in the system. Based on the fault category, if it is a disturbance type fault, the estimated states are used directly to calculate the probability of fault. On the other hand, for hardware failure, residuals obtained from Kalman Filter are used to update the probabilities of the affected gates of the “Event Tree”, and the probability of occurrence of a catastrophic event is calculated. Next, the risk of operating system under the current condition is calculated using the updated probability and severity. Results show that using the combination of “bank of Kalman Filter” and “Event Tree Analysis” brings more clarity to risk calculation and improves the detection time of the failure. Based on the calculated risk, operators can prioritize the faults and take appropriate action to the most critical one which ensures process safety.