摘要
The hydraulic excitation acting on a hydro-turbine generator unit exhibits obvious non-stationary characteristics.In order to account for these characteristics,this study focuses on the non-stationary random vibration reliability of the hydro-turbine generator unit.Firstly,the non-stationary characteristics of the hydraulic excitation are analyzed,and a mathematical ex-pression is constructed using the virtual excitation method.Secondly,a dynamic model of the unit is established to demonstrate the non-stationary random vibration characteristics under hydraulic excitation.Thirdly,an active learning non-stationary vibration reliability analysis method AK-MCS-T-H is proposed combining the Kriging model,the Monte Carlo simulation(MCS)method,and the information entropy learning function H.This method reveals the influence of the non-stationary hydraulic excitation on the random vibration reliability of the hydro-turbine generator unit.Finally,an example is presented to analyze the random vibration reliability.The study shows that the AK-MCS-T-H proposed in this paper can solve the problem of non-stationary random vibration reliability of the Francis hydro-turbine generator unit more effectively.
水轮发电机组的水流激励具有明显的非平稳特性.为了研究水流激励的非平稳特性,本文对水轮发电机组的非平稳随机振动可靠性方法展开研究.首先,分析了水流激励的非平稳特性,并利用虚拟激励法建立了水流激励的数学表达式.其次,建立了水轮发电机组的动力学模型,探明了水流激励下机组的非平稳随机振动特性.再次,将Kriging模型、蒙特卡罗模拟(MCS)方法和信息熵学习函数H相结合,提出了一种基于主动学习的非平稳振动可靠性分析方法AK-MCS-T-H.该方法揭示了非平稳水流激励对水轮发电机组随机振动可靠性的影响.最后,通过实例分析了水轮发电机组的随机振动可靠性.研究表明,本文提出的AK-MCS-T-H能够有效地解决混流式水轮发电机组的非平稳随机振动可靠性问题.
基金
supported by the National Natural Science Foundation of China(Grant Nos.51465001 and 51905113)
the Natural Science Foundation of Changsha City(Grant No.kq2208085)。
