A new three step closed loop subspace identifications algorithm based on an already existing algorithm and the Kalman filter properties is presented. The Kalman filter contains noise free states which implies that the states and innovation are uneorre lated. The idea is that a Kalman filter found by a good subspace identification algorithm will give an output which is sufficiently uncorrelated with the noise on the output of the actual process. Using feedback from the output of the estimated Kalman filter in the closed loop system a subspace identification algorithm can be used to estimate an unbiased model

With increased focus on integrity management to maximize uptime and output, asset surveillance and integrity management are increasingly becoming core elements of subsea field developments. Condition and Performance Monitoring (CPM) provides critical real-time data to the operator which can prevent unplanned shutdowns saving millions of dollars in lost production and ensuring system integrity. Today, subsea pumps, boosting and compression systems are expected to function properly for 30 years under demanding operating conditions. However, the subsea industry has historically had limited advanced feedback on the mechanical fitness, electrical condition and operating performance of subsea rotating machinery in contrast with the advances made in condition monitoring systems commonplace now in automobiles. Subsea pumping systems are now available with a comprehensive top down approach to predicting equipment failure from a modal analysis. Advanced instrumentation, such as vibration sensors, are now available and designed specifically to monitor equipment condition and not simply for operational control of the pump system.

No abstract