Automated approach to trend monitoring based on fractal analysis

Scott A. Starks; James Hamilton; Nitin Okhade

doi:10.1117/12.150160

20 August 1993 Automated approach to trend monitoring based on fractal analysis

Scott A. Starks, James Hamilton, Nitin Okhade

Proceedings Volume 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques; (1993) https://doi.org/10.1117/12.150160
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

Abstract

As systems become more complex, the monitoring and interpretation of measurement data related to the health of the system becomes increasingly more difficult. Trend monitoring is an important task that involves a prediction of the future state of system health based upon past observations. In many systems, sensors or suites of sensors gather data about the state of health of the system and its processes. Analysis of the power spectrum of the time series resulting from this sort of data collection provides insight into the trends inherent. In this paper, we present a fractal-based approach to the interpretation of the power spectrum of the time series. Using fractal analysis enables the characterization of the power spectrum using a minimal set of parameters. A computational algorithm for the calculation of these parameters is presented and shows promise as a basis for trend monitoring.

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Scott A. Starks, James Hamilton, and Nitin Okhade "Automated approach to trend monitoring based on fractal analysis", Proc. SPIE 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques, (20 August 1993); https://doi.org/10.1117/12.150160

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