Prediction of Fatigue Life for a New 2-DOF Compliant Mechanism by Clustering-Based ANFIS Approach

Two-degree-of-freedom (2-DOF) compliant mechanism has some outstanding characteristics in accurate positioning systems. Studying the fatigue life for the 2-DOF compliant mechanism is a meaningful task to ensure a long working. However, a study for fatigue life prediction of this mechanism has not been conducted so far. In this article, a method for fatigue life prediction of 2-DOF compliant mechanism is developed for the first time. This method is the combining of the differential evolution algorithm and the adaptive neuro-fuzzy inference system (ANFIS) with subtractive clustering. The numerical results on two case studies consisting of material steel A-36 and the material AL 6061-T6 show that the accuracy of the proposed method is very high. Compared to the actual fatigue life, the root mean square error of the proposed method lies in the range [1.7, 3.97] cycles for Case 1 and [2.03, 10.38] cycles for Case 2. The statistical test also indicates that the proposed method outperforms the traditional method using triangular membership function, bell-shape, and Gaussian membership function, with the significance level from 0.05 to 0.1. These results demonstrate the feasibility of the proposed approach in fatigue life prediction of 2-DOF compliant mechanism.