Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Hybrid approaches for approximate reasoning
A fuzzy model for human fall detection in infrared video
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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This paper describes a fault diagnosis system (FDS) for non-linear plants based on fuzzy logic. The proposed approach, named VisualBlock-FIR, runs under the Simulink framework and enables early fault detection, isolation, and identification. During fault detection, the FDS should recognize that the plant behavior is abnormal, and therefore, that the plant is not working properly. During fault isolation/identification, the FDS should conclude, which type of failure has occurred. The enveloping and acceptability measures introduced in VisualBlock-FIR enhance the robustness of the overall process. The proposed approach is used for tackling faults of the DAMADICS benchmark, and the results are compared with those obtained by other FDS.