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Journal of Control Science and Engineering
Volume 2017, Article ID 7097561, 8 pages
Research Article

Modeling of Complex Life Cycle Prediction Based on Cell Division

Institute of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

Correspondence should be addressed to Fucheng Zhang; moc.qq@468125574

Received 9 August 2017; Accepted 16 October 2017; Published 3 December 2017

Academic Editor: Chunhui Zhao

Copyright © 2017 Fucheng Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.