Real-time Detector for Time-variant Oscillation with Modified Intrinsic Time-scale Decomposition

Abstract An online detector for time-variant oscillation in a univariate time-series is proposed. This paper is motivated by the fact that it is still an open issue to implement the realtime oscillation detector which is applicable to non-linear, non-stationary and intermittent oscillations. The proposed procedure is based on Intrinsic Time-scale Decomposition (ITD) and contains an improved iteration termination condition of ITD. A novel hypothesis test with an improved statistic of variation coefficient enables the online monitoring of the time-variant oscillations. Simulation examples and industrial applications are provided to demonstrate the effectiveness of the online detector.

[1]  Lei Xie,et al.  An autonomous valve stiction detection system based on data characterization , 2013 .

[2]  T.I. Salsbury,et al.  A new approach for ARMA pole estimation using higher-order crossings , 2005, Proceedings of the 2005, American Control Conference, 2005..

[3]  Nina F. Thornhill,et al.  Advances and new directions in plant-wide disturbance detection and diagnosis , 2007 .

[4]  Tore Hägglund.  Industrial implementation of on-line performance monitoring tools , 2005 .

[5]  Sirish L. Shah,et al.  Detection and Diagnosis of Plant-wide Oscillations From Industrial Data using the Spectral Envelope Method ? , 2007 .

[6]  Toru Matsuo,et al.  Detection and Diagnosis of Oscillations in Process Plants , 2003, KES.

[7]  Ahmed N. Albatineh,et al.  A comparison of some confidence intervals for estimating the population coefficient of variation: a simulation study , 2012 .

[8]  Raghunathan Rengaswamy,et al.  A modified empirical mode decomposition (EMD) process for oscillation characterization in control loops , 2007 .

[9]  Nina F. Thornhill,et al.  Detection of multiple oscillations in control loops , 2003 .

[10]  I. Osorio,et al.  Intrinsic time-scale decomposition: time–frequency–energy analysis and real-time filtering of non-stationary signals , 2007, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  Biao Huang,et al.  Improved DCT-based method for online detection of oscillations in univariate time series☆ , 2013 .