Study of On-Line Condition Monitoring System for Roller Based on HMM

Abstract:

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A kind of signal build mould and identification tool for roller of rolling mill was discussed. Basic algorithm of Hidden Markov model (HMM) theory was presented. For ψ500×2 shrewd roller of rolling mill, the paper led Short-time Fourier transform (STFT) into draw the feature of roller signal and chose Continues Gaussian Hidden Markov Model (CGHMM) to build and identify mould. The experiment installation major included: ψ500×2 shrewd rollers and roller performance test control work of rolling mill control machine as well as a set of online state inspection system. The experiment data was collected by two kinds: roller rotational speed from low to high and from high to low. The experiment shows that this system has better identification rate, and proves that this system is effective.

Info:

Periodical:

Advanced Materials Research (Volumes 139-141)

Edited by:

Liangchi Zhang, Chunliang Zhang and Tielin Shi

Pages:

2546-2549

DOI:

10.4028/www.scientific.net/AMR.139-141.2546

Citation:

Y. H. Tang et al., "Study of On-Line Condition Monitoring System for Roller Based on HMM", Advanced Materials Research, Vols. 139-141, pp. 2546-2549, 2010

Online since:

October 2010

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Price:

$35.00

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