Online oscillation detection in the presence of signal intermittency. (October 2016) - Xie, Lei; Lang, Xun; Horch, Alexander; Yang, Yuxi
Abstract: A novel online detector for multiple oscillations in process industry is proposed. This article is motivated by the fact that it is still an open problem to design a real-time monitor which is suitable for detecting multiple oscillations with signal intermittency and non-linear/non-stationary properties. The proposed approach of Intrinsic Time-scale Decomposition (ITD) with Robust Zero crossing intervals Clustering (ITD-RZC) (i) provides an experimental statistic to remove noisy zero-crossings intervals (ZCIs), (ii) develops a novel adaptive robust K-means ZCI clustering which enables the reconstructed Proper Rotation Component (PRC) to encapsulate the sporadic oscillation and (iii) proposes an effective online-cluster-updating mechanism for real-time intermittent oscillations detection. ITD-RZC approach is computationally efficient and capable of preserving nonlinear features of the process variables which facilitates subsequent oscillation diagnosis. Simulation examples and industrial cases study are provided to demonstrate the effectiveness of the proposed online oscillation detector. Abstract : Highlights: A detector is proposed for non-stationary oscillations with signal intermittency. The level-jumping problem can be mitigated by zero-crossing intervals filtering and clustering. The updating mechanism is applicable for real-time intermittent oscillation detection.