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Evolving fuzzy model in fault detection system

机译:故障检测系统中的演化模糊模型

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Evolving methods for on-line learning of nonlinear models can play an important role in future monitoring and fault detection systems. The ability to model nonlinear relationships between the measured variables and to adapt the model to changing variable relations can decrease the number of false alarms and ensure a more robust and stable monitoring system. In this paper an example of the waste water treatment process monitoring system based on evolving fuzzy model is presented.
机译:不断发展的用于非线性模型在线学习的方法可以在未来的监视和故障检测系统中发挥重要作用。对测量变量之间的非线性关系进行建模并使模型适应变化的变量关系的能力可以减少错误警报的数量,并确保更健壮和稳定的监视系统。本文给出了一个基于演化模糊模型的废水处理过程监控系统实例。

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