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Fault Diagnosis with Spiking Neural P Systems

  • Gexiang Zhang,
  • Sergey Verlan,
  • Tingfang Wu,
  • Francis George C. Cabarle,
  • Jie Xue,
  • David Orellana-Martín,
  • Jianping Dong,
  • Luis Valencia-Cabrera,
  • Mario J. Pérez-Jiménez

摘要

As a representative rule-based fault diagnosis method, SNP systems with reasoning are a kind of graphic modeling approaches, which offer an intuitive illustration based on a strictly mathematical expression, a good fault-tolerant capacity due to its handling of incomplete and uncertain messages in a parallel manner, a good description for the relationships between causes and faults, and an understandable diagnosis model-building process. This chapter focuses on the models and algorithms of fuzzy reasoning numerical SNP systems and their applications in electrical systems like induction motors and electromechanical systems like aircraft engines to fully present the strengths of SNP systems in fault diagnosis of real-world complex systems.