TY - JOUR ID - TI - A Hybrid Neural-Fuzzy Network Based Fault Detection and IsolationSystem for DC Motor of Robot Manipulator AU - Qusay A. Jawad AU - Abbas H. Issa AU - Arkan A. Jassim PY - 2019 VL - 37 IS - 8 part (A) Engineering SP - 326 EP - 331 JO - Engineering and Technology Journal مجلة الهندسة والتكنولوجيا SN - 16816900 24120758 AB - n this paper,the detecting and isolating fault that occursin (actuator and sensor) in robot manipulator, which is used as a mathematical model wereproposed for fault detection, where the neural network was used to detectthefault. The neural network was trained on the data set obtained from the Input /output on the (DC motor).The output ofthesensor or actuatorwascomparedwith the output of the model (neural network) after that the residual signal is used to detect the fault. The fuzzy logic circuitwasused for fault isolation that is depending on the residual signal from any sensor or actuator that faults. There are three types of faults detected and isolated in this study abrupt fault, incipient fault and intermittent fault. The Matlab R2012a was used to the model steady state designed and simulated .The model hasa high capacity fordetecting faults

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