Xie Guang-qiang, Chen Jun-yu, Guo Xiao-quan. A Research on Intelligent Fault Diagnosis of Cluster Printing System Based on SDG[J]. 2020, 37(4): 15-20.DOI: 10.12052/gdutxb.200052.
A Research on Intelligent Fault Diagnosis of Cluster Printing System Based on SDG
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.
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references
YANG D H, LEI J Y, YAO H. Research on metal structure fault diagnosis of lifting equipment based on intelligent control [J]. Agricultural Equipment and Vehicle Engineering, 2020,58(2): 123-126.
MAO B, YANG S, LI Y S. Improved dynamic causality diagram and fuzzy inference fusion fault diagnosis method [J]. CEA, 2020, 56(3): 259-265.
ZHANG B, YAN J, TIAN C. Study on fault diagnosis system of diesel engine fuel injection system based on BP neural network[C]// ISECS International Colloquium on Computing, Communication, Control and Management.[S.l]: IEEE Computer Society, 2008.
LI C, ZHANG S H, JOSÉ V O. Fault diagnosis for 3D printers using suboptimal networked deep learning [J]. Journal of Mechanical Engineering, 2019, 55(7): 73-80.
LEI Y, YANG B, JIANG X, et al . Applications of machine learning to machine fault diagnosis: a review and roadmap [J ] . Mechanical Systems and Signal Processing, 2020, 138: 106587.
LI Y, ZENG Y, LIU T, et al . Simultaneously learning affinity matrix and data representations for machine fault diagnosis [J ] . Neural Networks, 2020, 122: 395-406.
WANG F, PAZILA M H, ZHANG B W. Research on multiple fault diagnosis method based on signed bond graph [J]. Modern Electronic Technology, 2018, 41(16): 140-143.
XIE G Q, GUO X Q, LI Y, et al . Review of fault diagnosis methods for micro-embedded system [J ] . Application Research of Computers, 2019, 36(5): 1281-1285.
SMAILI R, El H R, ABDELKRIM M N. Fault diagnosis based on graphical tools for multi-energy processes [J]. IFAC Proceedings Volumes, 2014, 47(3): 7073-7078.
吉世明. 基于半定量SDG模型的化工过程故障诊断[D]. 广州: 华南理工大学, 2012.
VEDAM H, VENKATASUBRAMANIAN V. PCA-SDG based process monitoring and fault diagnosis [J]. Control Engineering Practice, 1999, 7(7): 903-917.
ZHANG Z Q, WU C G, ZHANG B K, et al . SDG multiple fault diagnosis by real-time inverse inference [J ] . Reliability Engineering System Safety, 2005, 87(2): 173-189.
TARIFA E E, SCENNA N J. Fault diagnosis for a MSF using a SDG and fuzzy logic [J]. Desalination, 2003, 152(1): 207-214.
LI X X, JI S M. Chemical process fault diagnosis using semi-quantitative SDG model [J]. Journal of Tsinghua University (Science and Technology), 2012, 52(8): 1112-1115.
VENKATASUBRAMANIAN V, RENGASWAMY R, KAVURI S N. A review of process fault detection and diagnosis,Part II: qualitative models and search strategies [J]. Computers Chemical Engineering, 2003, 27(3): 313-326.
VENKAT V, RAGHUNATHAN R, KEWEN Y, et al . A review of process fault detection and diagnosis, Part I: quantitative model-based methods [J ] . Computers Chemical Engineering, 2003, 27(3): 293-311.
PEDRAM M. Power optimization and management in embedded systems[C]//Asia and South Pacific Design Automation Conference, 2001. Yokohama, Japan: IEEE, 2001: 239-244.
TU G, YANG F M, HU G R. Overview of embedded operating systems [J]. Journal of Computer Applications, 2000(11): 4-9.
徐超群. 高可用集群系统关键技术的研究与实现[D].南京: 南京航空航天大学, 2014.
YANG H Z, ZANG K, QIAN F C. Fault reasoning method based on fuzzy hierarchical SDG model [J]. Application of Computer Systems, 2017, 26(4): 104-109.
LIU H G, WU J J, CHEN X Q, et al . Study on the SDG- based intelligent fault diagnosis method [J ] . System Engineering and Electronics, 2002, 24(1): 103-104.
WANG B, CHEN J D. A design method for power failure protection of embedded system [J]. Industrial Control Computer, 2005(9): 58-59.
WENG H Y, YU J M, YE D P. Design and implementation of a single chip power-down protection system based on LM358 [J]. Electronic World, 2013(4): 3.