基于SDG的集群打印系统故障智能诊断研究

doi:10.12052/gdutxb.200052

Abstract

Abstract: With the development of online shopping, the demand for order printing has increased, and the cluster printing system can effectively improve efficiency. However, the cluster system requires high robustness and reliability, so order monitoring and handling of printing equipment failures have become the core issues of the cluster printing system. The SDG technology with the characteristics of real-time monitoring node data and revealing the fault propagation path is applied to the cluster printing system. The fault diagnosis reasoning rules of the cluster printing system are established, and the “If-Then” form of diagnosis rule base is formed. In addition, an order-full-life tracking model is constructed, and fault tasks are identified and managed in combination with a diagnostic rule base to implement fault task transfer and self-recovery of the cluster printing system.

Key words: intelligent diagnosis, Signed Directed Graph(SDG), life tracking, diagnostic rule base

CLC Number:

TN915.04

Xie Guang-qiang, Chen Jun-yu, Guo Xiao-quan. A Research on Intelligent Fault Diagnosis of Cluster Printing System Based on SDG[J].Journal of Guangdong University of Technology, 2020, 37(04): 15-20.

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