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| 1 | Multi-objective genetic algorithms based structural optimization and experimental investigation of the planet carrier in wind turbine gearbox显示文摘为了改进动态表演并且在风汽轮机 gearbox ,一个多客观的优化方法,它被最大的变丑驾驶,最大的压力和最小减少行星搬运人的重量,学习部分集中,被在这份报纸联合反应表面方法和基因算法建议。第一,为行星搬运人的设计变量的设计点分发与中央合成设计(电荷耦合器件) 被建立方法。基于有限元素分析(FEA ) 的计算结果,然后,反应表面分析被进行发现设计变量值的合适的集合。并且一个多客观的基因算法(MOGA ) 被使用决定优化的方向。也,这个方法被使用在 1.5MW 风汽轮机 gearbox,其结果被试验性的形式的测试验证设计并且优化行星搬运人。与原来的设计相比,团和优化行星搬运人的压力被 9.3% 和 40% 分别地减少。因而,行星搬运人的费用极大地被减少,它的稳定性也被改进。 | Pengxing YI Lijian DONG Tielin SHI | 2014 | Frontiers of Mechanical Engineering2014，9，4： | 4 |
| 2 | Numerical analysis and experimental investigation of modalproperties for the gearbox in wind turbine显示文摘Wind turbine gearbox (WTG), which functionsas an accelerator, ensures theof wind turbine systems.performance and service lifeThis paper examines thedistinctive modal properties of WTGs through finiteelement (FE) and experimental modal analyses. Thestudy is performed in two parts. First, a whole systemmodel is developed to investigate the first 10 modalfrequencies and mode shapes of WTG using flexible multi-body modeling techniques. Given the complex structureand operating conditions of WTG, this study applies springelements to the model and quantifies how the beatings andgear pair interactions affect the dynamic characteristics ofWTGs. Second, the FE modal results are validated throughexperimental modal analyses of a 1.5 WM WTG using thefrequency response function method of single pointexcitation and multi-point response. The natural frequen-cies from the FE and experimental modal analyses showfavorable agreement and reveal that the characteristicfrequency of the studied gearbox avoids its eigen-frequency very well. | Pengxing YI Peng HUANG Tielin SHI | 2016 | Frontiers of Mechanical Engineering2016，11，4： | 2 |
| 3 | DISTRIBUTED MONITORING SYSTEM RELIABILITY ESTIMATION WITH CONSIDERATION OF STATISTICAL UNCERTAINTY显示文摘Taking into account the whole system structure and the component reliability estimation uncertainty, a system reliability estimation method based on probability and statistical theory for distributed monitoring systems is presented. The variance and confidence intervals of the system reliability estimation are obtained by expressing system reliability as a linear sum of products of higher order moments of component reliability estimates when the number of component or system survivals obeys binomial distribution. The eigenfunction of binomial distribution is used to determine the moments of component reliability estimates, and a symbolic matrix which can facilitate the search of explicit system reliability estimates is proposed. Furthermore, a case of application is used to illustrate the procedure, and with the help of this example, various issues such as the applicability of this estimation model, and measures to improve system reliability of monitoring systems are discussed. | Yi Pengxing Yang Shuzi Du Runsheng Wu Bo Liu Shiyuan | 2005 | Chinese Journal of Mechanical Engineering2005，18，4： | 2 |
| 4 | The Multi-objective Optimization Of The Planet Carrier In Wind Turbine Gearbox显示文摘 | Pengxing Yi Lijian Dong Yuanxin Chen | 2012 | Applied Mechanics and Materials2012，，： | 1 |
| 5 | System Reliability Analysis of Redundant Condition Monitoring Systems显示文摘The development and application of new reliability models and methods are presented to analyze the system relia- bility of complex condition monitoring systems.The methods include a method analyzing failure modes of a type of redundant con- dition monitoring systems (RCMS) by invoking failure tree model,Markov modeling techniques for analyzing system reliability of RCMS,and methods for estimating Markov model parameters.Furthermore,a computing case is investigated and many conclu- sions upon this case are summarized.Results show that the method proposed here is practical and valuable for designing condition monitoring systems and their maintenance. | YI Pengxing~1 HU Youming~1 YANG Shuzi~1 WU Bo~1 CUI Feng~2 1.Department of Mechaironic Engineering,School of Mechanical Science & Engineering,Huazhong University of Science and Technology,Wuhan 430074,China 2.State Running Jianghe Chemical Factory,CNNG,Yichang 444200,China | 2006 | 武汉理工大学学报2006，28，S2： | 0 |
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