Paper breaking prediction control in papermaking process based on analysis of 1.5 dimension cepstrum

The problem that paper breaking can be caused by many factors in papermaking process, the dynamic transition of paper breaking must be reflected to the change of some random variables including speed of paper machines, consistency of pulp, quantitative and moisture of paper, which is called paper breaking parameters, by way of non-stationary random signals. The non-stationarity of these random signals will boost up rapidly with paper breaking process. According to the phenomenon a new method predicting paper breaking based on analyzing con-stationary property of random signals of paper breaking parameters is presented here. During the prediction process, the non-stationarizing amplitude of these random signals are estimated by the distance of 1.5 dimension cepstrum, and a paper breaking predictor is formed by proportional-integral-derivative algorithm of 1.5 dimension cepstrum of paper breaking random signals on line so that paper breaking can be judged in time from variation of 1.5 dimension cepstrum. The correctness and the practicality of this method are shown by application results.