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.NOMENCLATURE f = frequency in Hertz m = material exponent for fatigue m n = n th spectral moment p(S) = stress range probability density function D = cumulative fatigue damage fraction EFL = constant-amplitude equivalent fatigue load K = material parameter for fatigue damage at failure N = number of stress cycles N F = number of stress cycles at failure P = peaks per second P s = power spectral density function for stress range, S S = stress range T = lifetime of structure Z = normalized stress range

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One of the load cases that must be evaluated per the International Electrotechnical

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