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Fuzzy decision fusion system for fault classification with analytic hierarchy process approach

机译:具有分析层次处理方法的故障分类模糊决策融合系统

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Performance of the most existing fault detection and classification methods can only be guaranteed when each of their own assumptions are met. In other words, a method works well in one condition may not perform well in another. In this paper, a new analytic hierarchy process (AHP) based fuzzy decision fusion system is proposed to tackle the fault classification problem. The AHP approach is introduced to determine the priorities of different classifiers, which are further utilized as the weights in ensemble system. Comparing to conventional equal weighted fusion system, the proposed fuzzy fusion system is able to provide more rational and convincing fault classification result. Effectiveness of the proposed fuzzy fusion system with model evaluation is verified through the Tennessee Eastman (TE) benchmark process. (C) 2017 Elsevier B.V. All rights reserved.
机译:当每个自己的假设都满足每个假设时,才能保证最现有的故障检测和分类方法的性能。 换句话说,一种方法在一个条件下运行良好可能在另一个条件中表现不佳。 本文提出了一种基于新的分析层次过程(AHP)的模糊决策融合系统来解决故障分类问题。 引入AHP方法以确定不同分类器的优先级,其进一步利用作为集合系统的权重。 比较传统的等加权融合系统,所提出的模糊融合系统能够提供更多的理性和令人信服的故障分类结果。 通过田纳西州伊斯特曼(TE)基准进程验证了模型评估的建议模糊融合系统的有效性。 (c)2017 Elsevier B.v.保留所有权利。

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