Fuzzy Reasoning Numerical Spiking Neural P Systems for Induction Motor Fault Diagnosis

dc.contributor.authorYin, Xiu
dc.contributor.authorLiu, Xiyu
dc.contributor.authorSun, Minghe
dc.contributor.authorDong, Jianping
dc.contributor.authorZhang, Gexiang
dc.date.accessioned2022-10-26T11:08:07Z
dc.date.available2022-10-26T11:08:07Z
dc.date.issued2022-09-28
dc.date.updated2022-10-26T11:08:08Z
dc.description.abstractThe fuzzy reasoning numerical spiking neural P systems (FRNSN P systems) are proposed by introducing the interval-valued triangular fuzzy numbers into the numerical spiking neural P systems (NSN P systems). The NSN P systems were applied to the SAT problem and the FRNSN P systems were applied to induction motor fault diagnosis. The FRNSN P system can easily model fuzzy production rules for motor faults and perform fuzzy reasoning. To perform the inference process, a FRNSN P reasoning algorithm was designed. During inference, the interval-valued triangular fuzzy numbers were used to characterize the incomplete and uncertain motor fault information. The relative preference relationship was used to estimate the severity of various faults, so as to warn and repair the motors in time when minor faults occur. The results of the case studies showed that the FRNSN P reasoning algorithm can successfully diagnose single and multiple induction motor faults and has certain advantages over other existing methods.
dc.description.departmentManagement Science and Statistics
dc.identifierdoi: 10.3390/e24101385
dc.identifier.citationEntropy 24 (10): 1385 (2022)
dc.identifier.urihttps://hdl.handle.net/20.500.12588/1149
dc.rightsAttribution 4.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectfuzzy reasoning numerical spiking neural P systems
dc.subjectinterval-valued triangular fuzzy numbers
dc.subjectfault diagnosis
dc.titleFuzzy Reasoning Numerical Spiking Neural P Systems for Induction Motor Fault Diagnosis
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
entropy-24-01385-v2.pdf
Size:
2.41 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.86 KB
Format:
Item-specific license agreed upon to submission
Description: