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Probability Boxes and DS Structures' Research Prospects in the Mechanical Fault Signals Data Fusion

机译:机械故障信号数据融合中的概率框和DS结构的研究前景

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In the traditional machinery fault diagnosis, the feature extraction leads information loss and the different information sources' space-time registration is a difficult problem. The Probability boxes and Dempster-Shafer Structure Theory can provide a new way to solve above difficulties. This theory has a large advantage in solving uncertainties. It can be adapted for the inconstant machinery environment. In this paper, firstly the concepts of this theory are summarized and some methods of getting probability boxes are given. Secondly the method's feasibility is discussed. Finally some promising research directions of this theory's applications in the machinery fault diagnosis are advanced.
机译:在传统的机器故障诊断中,特征提取引线信息丢失和不同的信息来源的时空注册是一个难题。概率箱和Dempster-Shafer结构理论可以提供解决上述困难的新方法。该理论在解决不确定性方面具有很大的优势。它可以适用于不谐波的机械环境。在本文中,总结了该理论的概念,并给出了一些获取概率箱的方法。其次,讨论了该方法的可行性。最后有一些关于该理论在机械故障诊断中的应用的有前途的研究方向是先进的。

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