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 be...
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| Veröffentlicht in: | Mathematical problems in engineering 2021-03, Vol.2021, p.1-14 |
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| creator | Tran, Ngoc Thoai Dao, Thanh-Phong Nguyen-Trang, Thao Ha, Che-Ngoc |
| description | 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. |
| doi_str_mv | 10.1155/2021/6672811 |
| format | Article |
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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.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2021/6672811</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Adaptive algorithms ; Adaptive systems ; Algorithms ; Artificial neural networks ; Behavior ; Civil engineering ; Clustering ; Degrees of freedom ; Engineering ; Evolutionary algorithms ; Evolutionary computation ; Fatigue life ; Fuzzy logic ; Fuzzy sets ; Kinematics ; Life prediction ; Neural networks ; Partial differential equations ; Statistical tests</subject><ispartof>Mathematical problems in engineering, 2021-03, Vol.2021, p.1-14</ispartof><rights>Copyright © 2021 Ngoc Thoai Tran et al.</rights><rights>Copyright © 2021 Ngoc Thoai Tran et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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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. 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| subjects | Adaptive algorithms Adaptive systems Algorithms Artificial neural networks Behavior Civil engineering Clustering Degrees of freedom Engineering Evolutionary algorithms Evolutionary computation Fatigue life Fuzzy logic Fuzzy sets Kinematics Life prediction Neural networks Partial differential equations Statistical tests |
| title | Prediction of Fatigue Life for a New 2-DOF Compliant Mechanism by Clustering-Based ANFIS Approach |
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