BibTeX:

@article{IJIRSTV3I8049,
     title={Artificial Intelligence Fuzzy Inference System based Fault Detection and Isolation Scheme for Pneumatic Actuator},
     author={Prabakaran K, Sathish E, Revathy G and Maris Murugan T},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={8},
     pages={39--44},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I8049.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Fault diagnosis is an ongoing significant research field, due to the constant increasing need for maintainability, reliability and safety of industrial plants. The pneumatic actuators are installed mainly in harsh environment: high temperature, pressure, aggressive media, vibration, etc. This influenced on the Pneumatic actuator predicted lifetime. The failures in pneumatic actuator cause forces the installation shut down and may also influence the final product quality. A fuzzy logic based approach is implemented to detect the external faults such as Actuator vent blockage, Diaphragm leakage and incorrect supply pressure. The fuzzy system is able to identify the actuator condition with high accuracy by monitoring five parameters. The parameter selection is based on the committee of DAMADICS. The Fuzzy Inference Systems was implemented using MATLAB® and the simulation result show that the scheme can effectively classify all the types of external faults.

Actuator, DAMADICS, Fuzzy Logic, Pressure