A Bidirectional Diagnosis Algorithm of Fuzzy Petri Net Using Inner-Reasoning-Path

Symmetry

Kai-Qing Zhou¹  Wei-Hua Gui¹  Li-Ping Mo²  AzlanMohd Zain³ 

[1] College of Information Science and Engineering, Central South University, Changsha 410083, China;College of Information Science and Engineering, Jishou University, Jishou 416000, China;Soft Computing Research Group, Faculty of computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia;

关键词: fuzzy petri net;    fault diagnosis;    inner-reasoning-path;    correctness;    algorithm complexity;   

DOI  :  10.3390/sym10060192

来源: DOAJ

【 摘 要 】

Fuzzy Petri net (FPN) is a powerful tool to execute the fault diagnosis function for various industrial applications. One of the most popular approaches for fault diagnosis is to calculate the corresponding algebra forms which record flow information and three parameters of value of all places and transitions of the FPN model. However, with the rapid growth of the complexity of the real system, the scale of the corresponding FPN is also increased sharply. It indicates that the complexity of the fault diagnosis algorithm is also raised due to the increased scale of vectors and matrix. Focusing on this situation, a bidirectional adaptive fault diagnosis algorithm is presented in this article to reduce the complexity of the fault diagnosis process via removing irrelevant places and transitions of the large-scale FPN, followed by the correctness and algorithm complexity of the proposed approach that are also discussed in detail. A practical example is utilized to show the feasibility and efficacy of the proposed method. The results of the experiments illustrated that the proposed algorithm owns the ability to simplify the inference process and to reduce the algorithm complexity due to the removal of unnecessary places and transitions in the reasoning path of the appointed output place.

【 授权许可】

Unknown