Model companions of theories of graphs

Takeuchi, Kota; Tanaka, Yuichi; Tsuboi, Akito

doi:10.1002/malq.201400019

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…These diagnosis strategies are mostly based on a certain fault diagnostic models, such as directed causality graph, fault tree model, Petri net model, Markov model, neural network model and Bayesian network. Graph theory is widely used because it is simple to model and easy to understand (Takeuchi et al 2015;Manes et al 2012;Yu et al 2003;Bhattacharyya et al 2011;Sheng et al 2015;Zhao et al 2016). But because of the fault location based on the incidence, or even consider the degree of fault severity and the degree of difficulty in detection, but also rely on the subjective experience of experts.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis strategy of CNC machine tools based on cascading failure

Zhang

Guixiang

et al. 2017

J Intell Manuf

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To ensure the safe operation of CNC machines, a fault diagnosis strategy based on cascading failure is proposed. According to fault mechanism analysis, a directed graph model of fault propagation between components in machine tool systems is established. In this study, the interpretative structural model method is used to realize the hierarchical structure of fault propagation model by matrix transformation and decomposition. Subsequently, the PageRank algorithm is introduced to evaluate the failure effects of the machine tool system components. The Johnson method is then applied to correct the component fault sequence and establish the model of rate of occurrence of failures that is based on time correlation. Finally, the fault diagnosis strategy is formulated through the component rate of the occurrence of failure, fault influence and fault propagation model, to identify the main cause of the fault and provide the basis for fault diagnosis. In the end, a machine tool equipment is used as an example for application to verify the validity of the method.

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Section: Introductionmentioning

confidence: 99%