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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 219710, 12 pages
Research Article

Process Monitoring and Fault Diagnosis for Shell Rolling Production of Seamless Tube

1State Key Laboratory of Synthetical Automation for Process Industries, Northeast University, Shenyang 110004, China
2Information Science and Engineering School, Northeastern University, Shenyang 110004, China
3College of Science, Liaoning Industry University, Jinzhou 121000, China
4College of Resources and Civil Engineering, Northeastern University, Shenyang 110004, China

Received 6 November 2014; Revised 9 January 2015; Accepted 14 January 2015

Academic Editor: Sangmin Lee

Copyright © 2015 Dong Xiao 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.


Continuous rolling production process of seamless tube has many characteristics, including multiperiod and strong nonlinearity, and quickly changing dynamic characteristics. It is difficult to build its mechanism model. In this paper we divide production data into several subperiods by -means clustering algorithm combined with production process; then we establish a continuous rolling production monitoring and fault diagnosis model based on multistage MPCA method. Simulation experiments show that the rolling production process monitoring and fault diagnosis model based on multistage MPCA method is effective, and it has a good real-time performance, high reliability, and precision.