涡轮机
风力发电
可靠性(半导体)
塔楼
背景(考古学)
航程(航空)
涡轮叶片
循环计数
海洋工程
时域
计算机科学
环境科学
可靠性工程
结构工程
工程类
功率(物理)
地质学
机械工程
运筹学
电气工程
古生物学
航空航天工程
物理
量子力学
计算机视觉
作者
Patrick Ragan,Lance Manuel
标识
DOI:10.1260/030952407781494494
摘要
Fatigue analysis for wind turbines is typically carried out in the time domain, using cycle counting techniques such as ASTM's Rainflow Cycle-Counting Algorithm. As an alternative, earlier workers investigated the feasibility of estimating wind turbine fatigue loads using spectral techniques such as Dirlik's method to estimate stress range probability distributions that are based on spectral moments of the load in question. The present paper re-examines this approach with a particular view to assessing its limitations and advantages in the context of modern, large-scale wind turbines and design methods. These relative advantages are considered in terms of accuracy, statistical reliability, and efficiency of calculation. Field data on loads from a utility-scale 1.5 MW turbine near Lamar, Colorado in the Colorado Green Wind Farm are analyzed here as a representative example. The results show that valuable and reliable information about tower loads can be obtained very efficiently. By contrast, the limitations of the Dirlik method are highlighted by poor results for edgewise blade loads.
科研通智能强力驱动
Strongly Powered by AbleSci AI