Paper
5 August 1997 Application of forcasting algorithms in the optical fiber coal dust burner monitoring system
Waldemar Wojcik, T. Bieganski, Andrzej Kotyra, Andrzej Smolarz
Author Affiliations +
Proceedings Volume 3189, Technology and Applications of Light Guides; (1997) https://doi.org/10.1117/12.285618
Event: Technology and Applications of Lightguides, 1996, Krasnobrod, Poland
Abstract
In this article we discuss the properties of autoregression (AR) and moving average (MA) processes, as well as non- parametrical and parametrical identification of their models describing real time-series. We have shown the principles of calculating one-step forecasts with the smallest average square error for real time series, which describe flame blinking in a coal burner working in a boiler of the 200 MW energetic block. We have calculated ARMA (p,q) and ARIMA (p,d,q) mixed models, which, in turn, helped us to calculate one-step forecasts. The results, in the form of a measured time series, with marked one-step forecasts, are shown in enclosed figures.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Waldemar Wojcik, T. Bieganski, Andrzej Kotyra, and Andrzej Smolarz "Application of forcasting algorithms in the optical fiber coal dust burner monitoring system", Proc. SPIE 3189, Technology and Applications of Light Guides, (5 August 1997); https://doi.org/10.1117/12.285618
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KEYWORDS
Autoregressive models

Optical fibers

Combustion

Stochastic processes

Control systems

Process modeling

Time metrology

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