High-temperature ceramic filter tube is composed of a support body with a large pore size and a membrane structure with a small pore size. In practical applications, it has a lot of dust with particle size smaller than 1 ?m, which can move through the membrane structure and deposit the support body finally. It can't be removed by pulse jet cleaning effectively. Particle deposition within the support body and the compression of residual dust cake are responsible for the decreasing permeability and increasing residual pressure drop of high temperature ceramic filter tubes. In this work, on the basis of particle deposition within the filter medium and the compression of residual dust cake can't be measured directly, Bayesian estimation theory was used to establish a state-space model to describe the ceramic filter tubes degradation process using the residual pressure drop measured in the filtration system. This method can incorporate the latest residual pressure drop data and update the model parameter timely, the remaining life of the ceramic filter tube was predicted in real time. At the same time the failure probability density distribution of the remaining life of the ceramic filter tube and the change rate of degeneration status of the ceramic filter tube were predicted. By analyzing the actual data of the ceramic filter tube residual pressure drop from high-temperature experiment device and shell coal gasification process respectively, the prediction accuracy of the remaining life increased gradually with the increase of the residual pressure drop data, the accuracy of the prediction at the later stage was higher than 95%, and the ceramic filter tubes change rate of degradation status gradually decreased. This was consistent with the conclusion that the residual pressure drop of ceramic filter tube increases fast at the early stage and slow at the late stage.
Longfei LIU Zhongli JI Xin LUAN
. Performance degradation model and prediction method of real-time remaining life for high temperature ceramic filter tube[J]. The Chinese Journal of Process Engineering, 2019
, 19(1)
: 165
-172
.
DOI: 10.12034/j.issn.1009-606X.218183
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