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Evaluation using online support-vector-machines and fuzzy reasoning.Application to condition monitoring of speeds rolling process

机译:在线支持向量机和模糊推理的评估在速度轧制过程状态监测中的应用

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摘要

A method for process condition monitoring and evaluation, which combines the online support vector machine (SVM) regression and the fuzzy sets methods, is proposed. To account for the time dependence, the proposed approach is based on moving windows in order to take into account the past and new data for the model's adaptation. The fuzzy analysis is then applied to the generated residual data to give an evaluation of the condition monitoring. The proposed approach is applied to hot rolling for constructing a complementary condition monitoring system, which permits an online quality evaluation in the rolling process. Simulation results based on residual data show that the new approach is easily implementable.
机译:提出了一种在线支持向量机回归与模糊集相结合的过程状态监测与评估方法。考虑到时间依赖性,建议的方法基于移动窗口,以便考虑过去和新数据以适应模型。然后将模糊分析应用于所生成的残差数据,以对状态监视进行评估。所提出的方法被应用于热轧,以构建补充状态监测系统,该系统允许在轧制过程中进行在线质量评估。基于残差数据的仿真结果表明,该新方法易于实施。

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