基于子集模拟法的风机叶片可靠度分析

风机叶片是风机机组中最重要的组件之一,其可靠性对整个发电系统的健康运行十分关键。传统的蒙特卡罗法可靠度计算效率较低,本文将子集模拟法应用到风机叶片的可靠度计算中,通过合理选取中间失效事件临界值和建议概率密度函数,采用Metropolis算法模拟产生一系列的样本,极大地提高了抽样效率。结果表明,子集模拟法在风机叶片可靠度计算中精度较高,且结构的失效概率越小,相比于传统蒙特卡罗法效率更高,可以极大地减轻计算压力。

Reliability computation of wind turbine blades based on subset simulation algorithm

Blades are one of the most important components in a wind turbine,thus their reliability is essential for the healthy operation of a wind turbine.The traditional Monte Carlo method is not efficient in reliability calculation.In this paper,the subset simulation method is applied to the reliability calculation of wind turbine blades.By reasonably selecting the critical value of intermediate failure events and the suggested probability density function,a series of samples are simulated by using Metropolis algorithm,which greatly improves the sampling efficiency.The results show that the subset simulation method is accurate and renders a higher efficiency for the reliability calculation of wind turbine blades,compared with traditional Monte Carlo simulation in the situation of very small failure probability.