Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots
In this work, a fuzzy design optimization-based fatigue reliability analysis technique is addressed to obtain the optimal fatigue reliability of the structures with random parameters under the minimum fluctuation of fatigue life. The challenge of the problem lies in uncertainties involved from both...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9051682/ |
| _version_ | 1818330144360628224 |
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| author | Pengpeng Zhi Yonghua Li Bingzhi Chen Xiaoning Bai Ziqiang Sheng |
| author_facet | Pengpeng Zhi Yonghua Li Bingzhi Chen Xiaoning Bai Ziqiang Sheng |
| author_sort | Pengpeng Zhi |
| collection | DOAJ |
| description | In this work, a fuzzy design optimization-based fatigue reliability analysis technique is addressed to obtain the optimal fatigue reliability of the structures with random parameters under the minimum fluctuation of fatigue life. The challenge of the problem lies in uncertainties involved from both structural parameters and loads, which renders the fatigue reliability becoming the primary problem to be considered in evaluating structural performance. In order to obtain the optimal fatigue reliability, the optimal mathematical models aiming at the mass and fatigue life of welding robots are constructed respectively, and the genetic particle swarm optimization algorithm and radial basis function neural network (GAPSO-RBFNN) based surrogate model is then presented. Moreover, fuzzy constraints are introduced into the optimization model, and the improved non-dominated sorting genetic algorithm (INSGA-III) optimization strategy is proposed to solve it, which can effectively reduce the workload by increasing the diversity of Pareto solutions during the iterative process. Finally, the optimized structure combined with numerical simulation method is adopted to analyze the fatigue reliability. After analysis steps are given in detail, a practical welding robot structure is presented to demonstrate the validity and reasonability of the developed methodology. |
| first_indexed | 2024-12-13T12:59:17Z |
| format | Article |
| id | doaj.art-697c8d89c5f841d794dd4d07b20ea26d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T12:59:17Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-697c8d89c5f841d794dd4d07b20ea26d2022-12-21T23:45:04ZengIEEEIEEE Access2169-35362020-01-018649066491710.1109/ACCESS.2020.29846949051682Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding RobotsPengpeng Zhi0https://orcid.org/0000-0003-1537-8455Yonghua Li1https://orcid.org/0000-0001-7935-9152Bingzhi Chen2https://orcid.org/0000-0003-3136-5873Xiaoning Bai3Ziqiang Sheng4School of Mechanical Engineering, Dalian Jiaotong University, Dalian, ChinaSchool of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaSchool of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaSchool of Locomotive and Rolling Stock Engineering, Dalian Jiaotong University, Dalian, ChinaSchool of Mechanical Engineering, Dalian Jiaotong University, Dalian, ChinaIn this work, a fuzzy design optimization-based fatigue reliability analysis technique is addressed to obtain the optimal fatigue reliability of the structures with random parameters under the minimum fluctuation of fatigue life. The challenge of the problem lies in uncertainties involved from both structural parameters and loads, which renders the fatigue reliability becoming the primary problem to be considered in evaluating structural performance. In order to obtain the optimal fatigue reliability, the optimal mathematical models aiming at the mass and fatigue life of welding robots are constructed respectively, and the genetic particle swarm optimization algorithm and radial basis function neural network (GAPSO-RBFNN) based surrogate model is then presented. Moreover, fuzzy constraints are introduced into the optimization model, and the improved non-dominated sorting genetic algorithm (INSGA-III) optimization strategy is proposed to solve it, which can effectively reduce the workload by increasing the diversity of Pareto solutions during the iterative process. Finally, the optimized structure combined with numerical simulation method is adopted to analyze the fatigue reliability. After analysis steps are given in detail, a practical welding robot structure is presented to demonstrate the validity and reasonability of the developed methodology.https://ieeexplore.ieee.org/document/9051682/Fuzzy design optimizationfatigue reliabilitywelding robotssurrogate model |
| spellingShingle | Pengpeng Zhi Yonghua Li Bingzhi Chen Xiaoning Bai Ziqiang Sheng Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots IEEE Access Fuzzy design optimization fatigue reliability welding robots surrogate model |
| title | Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots |
| title_full | Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots |
| title_fullStr | Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots |
| title_full_unstemmed | Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots |
| title_short | Fuzzy Design Optimization-Based Fatigue Reliability Analysis of Welding Robots |
| title_sort | fuzzy design optimization based fatigue reliability analysis of welding robots |
| topic | Fuzzy design optimization fatigue reliability welding robots surrogate model |
| url | https://ieeexplore.ieee.org/document/9051682/ |
| work_keys_str_mv | AT pengpengzhi fuzzydesignoptimizationbasedfatiguereliabilityanalysisofweldingrobots AT yonghuali fuzzydesignoptimizationbasedfatiguereliabilityanalysisofweldingrobots AT bingzhichen fuzzydesignoptimizationbasedfatiguereliabilityanalysisofweldingrobots AT xiaoningbai fuzzydesignoptimizationbasedfatiguereliabilityanalysisofweldingrobots AT ziqiangsheng fuzzydesignoptimizationbasedfatiguereliabilityanalysisofweldingrobots |