(untitled) (Research, Society and Development, 2020)
The work proposes a methodology for the development of structural integrity monitoring based on intelligent computation techniques, with the purpose of detecting structural faults in a rotor using the technique of artificial negative and clonal selection immune systems. The method makes it possible to compose the diagnostic system able to learn continuously, covering two situations of damage, without the need to restart the learning process. The negative selection algorithm is responsible for the pattern recognition process and the clonal selection algorithm is responsible for the continuous learning process. To evaluate the methodology, an experimental bench was set up that produces a signal which, from which captured and treated, can be identified, classified and even defined the prognosis of the test behavior. The results demonstrate robustness and precision of the proposed methodology.