As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is part...As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is particularly important.However,as a complex mechanical and electrical equipment,the traditional reliability importance analysis method is too simple.In order to solve this problem,this passage proposes to establish the reliability model of each part of the machining center,and then analyze its dynamic importance,which improves the limitation of only reliability importance analysis.Through the analysis the reliability importance and criticality importance,and then rank the result of importance analysis,finally it can get that the ranking results of the key components accord with the fact,so the results can provide support for the importance research of machining center.展开更多
Simulation based structural reliability analysis suffers from a heavy computational burden, as each sample needs to be evaluated on the performance function, where structural analysis is performed. To alleviate the co...Simulation based structural reliability analysis suffers from a heavy computational burden, as each sample needs to be evaluated on the performance function, where structural analysis is performed. To alleviate the computational burden, related research focuses mainly on reduction of samples and application of surrogate model, which substitutes the performance function. However,the reduction of samples is achieved commonly at the expense of loss of robustness, and the construction of surrogate model is computationally expensive. In view of this, this paper presents a robust and efficient method in the same direction. The present method uses radial-based importance sampling (RBIS) to reduce samples without loss of robustness. Importantly, Kriging is fully used to efficiently implement RBIS. It not only serves as a surrogate to classify samples as we all know, but also guides the procedure to determine the optimal radius, with which RBIS would reduce samples to the highest degree. When used as a surrogate, Kriging is established through active learning, where the previously evaluated points to determine the optimal radius are reused. The robustness and efficiency of the present method are validated by five representative examples, where the present method is compared mainly with two fundamental reliability methods based on active learning Kriging.展开更多
【正】Dear Sir,W e have read with attention and interest the systematic review on the effectiveness and safety of bevacizumab and ranibizumab in the treatment of age-related macular degeneration(AMD)written by Zhang e...【正】Dear Sir,W e have read with attention and interest the systematic review on the effectiveness and safety of bevacizumab and ranibizumab in the treatment of age-related macular degeneration(AMD)written by Zhang et al[1]and published on number of April 2014 of International Journal of Ophthalmology.The authors,who collected data from 4randomized clinical trials(RCTs)and 11 observational展开更多
文摘As an important part of CNC machine tools,machining center’s reliability,efficiency and accuracy measure the machining level of a CNC machine tool.Therefore,the research on the importance of CNC machine tools is particularly important.However,as a complex mechanical and electrical equipment,the traditional reliability importance analysis method is too simple.In order to solve this problem,this passage proposes to establish the reliability model of each part of the machining center,and then analyze its dynamic importance,which improves the limitation of only reliability importance analysis.Through the analysis the reliability importance and criticality importance,and then rank the result of importance analysis,finally it can get that the ranking results of the key components accord with the fact,so the results can provide support for the importance research of machining center.
基金supported by the National Natural Science Foundation of China (Grant No. 11421091)the Fundamental Research Funds for the Central Universities (Grant No. HIT.MKSTISP.2016 09)
文摘Simulation based structural reliability analysis suffers from a heavy computational burden, as each sample needs to be evaluated on the performance function, where structural analysis is performed. To alleviate the computational burden, related research focuses mainly on reduction of samples and application of surrogate model, which substitutes the performance function. However,the reduction of samples is achieved commonly at the expense of loss of robustness, and the construction of surrogate model is computationally expensive. In view of this, this paper presents a robust and efficient method in the same direction. The present method uses radial-based importance sampling (RBIS) to reduce samples without loss of robustness. Importantly, Kriging is fully used to efficiently implement RBIS. It not only serves as a surrogate to classify samples as we all know, but also guides the procedure to determine the optimal radius, with which RBIS would reduce samples to the highest degree. When used as a surrogate, Kriging is established through active learning, where the previously evaluated points to determine the optimal radius are reused. The robustness and efficiency of the present method are validated by five representative examples, where the present method is compared mainly with two fundamental reliability methods based on active learning Kriging.
文摘【正】Dear Sir,W e have read with attention and interest the systematic review on the effectiveness and safety of bevacizumab and ranibizumab in the treatment of age-related macular degeneration(AMD)written by Zhang et al[1]and published on number of April 2014 of International Journal of Ophthalmology.The authors,who collected data from 4randomized clinical trials(RCTs)and 11 observational
