Abstract
A robust fault diagnosis strategy in mechanical systems based on the use of Pythagorean fuzzy sets is presented. A variant of the FCM algorithm called Pythagorean Fuzzy C-Means (PyFCM) is obtained modifying the original FCM algorithm by using Pythagorean fuzzy sets. Furthermore, with the aim to obtain greater separability among classes, and reduce classification errors a kernel version of PyFCM (KPyFCM) is obtained. The proposed strategy is applied to the Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems (DAMADICS) benchmark. A comparative analysis with other algorithms that use standard and non-standard membership grades is made. The satisfactory results obtained by the proposal indicates its feasibility.
National Program of Research and Innovation - ARIA, Project No. 27, CITMA, Cuba.
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Rodríguez Ramos, A., Verdegay Galdeano, J.L., Llanes-Santiago, O. (2021). A Robust Fault Diagnosis Strategy in Mechanical Systems Using Pythagorean Fuzzy Sets. In: Hernández Heredia, Y., Milián Núñez, V., Ruiz Shulcloper, J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2021. Lecture Notes in Computer Science(), vol 13055. Springer, Cham. https://doi.org/10.1007/978-3-030-89691-1_20
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