Cargando…
Sensor Fault Diagnosis Using a Machine Fuzzy Lyapunov-Based Computed Ratio Algorithm
Anomaly identification for internal combustion engine (ICE) sensors has become an important research area in recent years. In this work, a proposed indirect fuzzy Lyapunov-based computed ratio observer integrated with a support vector machine (SVM) was designed for sensor fault classification. The p...
Autores principales: | TayebiHaghighi, Shahnaz, Koo, Insoo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029274/ https://www.ncbi.nlm.nih.gov/pubmed/35458960 http://dx.doi.org/10.3390/s22082974 |
Ejemplares similares
-
CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning
por: Saeed, Umer, et al.
Publicado: (2021) -
Fuzzy logic and Lyapunov‐based non‐linear controllers for HCV infection
por: Hamza, Ali, et al.
Publicado: (2021) -
Decision Fault Tree Learning and Differential Lyapunov Optimal Control for Path Tracking
por: Bose, S. Subash Chandra, et al.
Publicado: (2023) -
Fault diagnosis for cooling dehumidifier based on fuzzy classifier optimized by adaptive genetic algorithm
por: Gao, Yunguang, et al.
Publicado: (2022) -
A Novel Adaptive Sensor Fault Estimation Algorithm in Robust Fault Diagnosis
por: Pazera, Marcin, et al.
Publicado: (2022)