Anomaly detection for equipment condition via cross-correlation approximate entropy

In this paper, a new method named cross-correlation approximate entropy is proposed based on the correlation analysis and the approximate entropy theory. It can detect anomaly of running state in a quantitative manner without any priori knowledge. The method takes a section of signal with fixed-length of running state of equipment as a window. By sliding the window through the state signal, the paper calculates the cross-correlation function of the first window and latter ones, and then figure out their approximate entropy values. This paper sets the approximate entropy value of cross-correlation function of the first and second windows as the standard value. If there is an anomaly, the approximate entropy value of cross-correlation function of windows will be far larger than the standard value. Finally, a case is studied to test the validity and stability of this method by using the normal vibration signals of normal and faulty rolling bearing.

[1]  A L Goldberger,et al.  Gender- and age-related differences in heart rate dynamics: are women more complex than men? , 1994, Journal of the American College of Cardiology.

[2]  A. Ray,et al.  An information-theoretic measure for anomaly detection in complex dynamical systems , 2009 .

[3]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Mark M. Owen,et al.  Practical Signal Processing , 2007 .

[5]  D. Levy,et al.  Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics. , 1997, Circulation.

[6]  A L Goldberger,et al.  Physiological time-series analysis: what does regularity quantify? , 1994, The American journal of physiology.

[7]  Asok Ray,et al.  Data driven anomaly detection via symbolic identification of complex dynamical systems , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[8]  S. Pincus,et al.  Randomness and degrees of irregularity. , 1996, Proceedings of the National Academy of Sciences of the United States of America.