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.
Fault propagation behaviour analysis is the basis of fault diagnosis and health maintenance. Traditional fault propagation studies are mostly based on a priori knowledge of a causality model combined with rule-based reasoning, disregarding the limitations of experience and the dynamic characteristics of the system that cause deviations in the identification of critical fault sources. Thus, this paper proposes a dynamic analysis method for fault propagation behaviour of machining centres that combines fault propagation mechanisms with model structure characteristics. This paper uses the design structure matrix (DSM) to establish the fault propagation hierarchy structure model. Considering the correlation of fault time, the fault probability function of a component is obtained and the fault influence degree of nodes are calculated. By introducing the Copula and Coupling degree functions, the fault influence degree of the edges between the same level and different levels are calculated, respectively. This paper constructs a fault propagation intensity model by integrating the edge betweenness and uses it as an index to analyze real-time fault propagation behaviour. Finally, a certain type of machining centre is taken as an example for specific application. This study can provide as a reference for the fault maintenance and reliability growth of a machining centre.
The risk assessment of the failure mode of the traditional machining center component rarely considers the topological characteristics of the system and the influence of propagation risks, which makes the failure risk assessment results biased. Therefore, this paper proposes a comprehensive failure risk assessment method of a machining center component based on topology analysis. On the basis of failure mode and cause analysis, considering the correlation of failure modes, Analytic Network Process (ANP) is used to calculate the influence degree of failure modes, and it is combined with component failure mode frequency ratio and failure rate function to calculate independent failure risk. The ANP model of the machining center is transformed into a topological model, and the centrality measurement of network theory is used to analyze the topology of the machining center. The weight of the topological structure index is measured by subjective and objective weighting methods, and then the importance degree of the machining center component is calculated. In this paper, the coupling degree function is introduced to calculate the importance of the connection edge, which is combined with the failure probability to calculate the failure propagation influence degree, and the component propagation failure risk is calculated based on this. Finally, the independent failure risk and the propagation failure risk of the component are integrated to realize the failure risk assessment of the component. Taking a certain type of machining center as an example to illustrate the application, compared with the traditional assessment method, the effectiveness and advancement of the method proposed in this paper have been verified.
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