Study of On-Line Condition Monitoring System for Roller Based on HMM
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.
Liangchi Zhang, Chunliang Zhang and Tielin Shi
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