Dynamic Reliability Analysis of Gear Transmission System of Wind Turbine in Consideration of Randomness of Loadings and Parameters

A dynamic model of gear transmission system of wind turbine is built with consideration of randomness of loads and parameters. The dynamic response of the system is obtained using the theory of random sampling and the Runge-Kutta method. According to rain flow counting principle, the dynamic meshing forces are converted into a series of luffing fatigue load spectra. The amplitude and frequency of the equivalent stress are obtained using equivalent method of Geber quadratic curve. Moreover, the dynamic reliability model of components and system is built according to the theory of probability of cumulative fatigue damage. The system reliability with the random variation of parameters is calculated and the influence of random parameters on dynamic reliability of components is analyzed. In the end, the results of the proposed method are compared with that of Monte Carlo method. This paper can be instrumental in the design of wind turbine gear transmission system with more advantageous dynamic reliability.

[1]  Huijun Gao,et al.  Active Suspension Control With Frequency Band Constraints and Actuator Input Delay , 2012, IEEE Transactions on Industrial Electronics.

[2]  Caichao Zhu,et al.  ANALYSIS OF NONLINEAR COUPLING DYNAMIC CHARACTERISTICS OF GEARBOX SYSTEM ABOUT WIND-DRIVEN GENERATOR , 2005 .

[3]  J.N. Yang,et al.  Residual Strength Degradation Model and Theory of Periodic Proof Tests for Graphite/Epoxy Laminates* , 1977 .

[4]  Liu Jian-guo.  Dynamic analysis and optimization of gear trains in a megawatt level wind turbine , 2009 .

[5]  Paul Sas,et al.  Analysis of internal drive train dynamics in a wind turbine , 2004 .

[6]  Lambros S. Katafygiotis,et al.  Domain Decomposition Method for Calculating the Failure Probability of Linear Dynamic Systems Subjected to Gaussian Stochastic Loads , 2006 .

[7]  Xiao Ling Wu,et al.  Effects of Gear Manufacturing Error on the Dynamic Characteristics of Planetary Gear Transmission System of Wind Turbine , 2011 .

[8]  Huijun Gao,et al.  Finite Frequency H∞ Control for Vehicle Active Suspension Systems , 2011 .

[9]  P. Franchin.  Reliability of uncertain inelastic structures under earthquake excitation , 2004 .

[10]  Jiangf Xiang-lin.  Stochastic Volatility Models Based Bayesian Method and Their Application , 2005 .

[11]  Qiao Hong-wei.  DYNAMIC RELIABILITY ANALYSIS OF STOCHASTIC STRUCTURES UNDER STATIONARY RANDOM EXCITATION USING HERMITE POLYNOMIALS APPROXIMATION , 2009 .

[12]  S. Butterfield,et al.  Improving Wind Turbine Gearbox Reliability , 2007 .

[13]  Yao Qian-feng.  EFFICIENT ESTIMATION OF DYNAMIC RELIABILITY BASED ON SIMPLE ADDITIVE RULES OF PROBABILITY , 2010 .

[14]  Yi-Kuei Lin,et al.  Network reliability evaluation for computer networks: A case of the taiwan advanced research and education network , 2013 .

[15]  Guo-fu Zhai,et al.  COMBINATION FORECASTING METHOD FOR STORAGE RELIABILITY PARAMETERS OF AEROSPACE RELAYS BASED ON GREY-ARTIFICIAL NEURAL NETWORKS , 2013 .

[16]  Datong Qin,et al.  Optimization Design of System Parameters of the Gear Transmission of Wind Turbine Based on Dynamics and Reliability , 2008 .

[17]  Ren Qingwen,et al.  STUDY OF NON-LINEAR CONSTITUTIVE MODEL FOR JOINTED ROCK MASSES , 2010 .

[18]  Paolo Franchin,et al.  Seismic risk evaluation of RC bridge structures , 2003 .

[19]  Lambros S. Katafygiotis,et al.  Wedge simulation method for calculating the reliability of linear dynamical systems , 2004 .

[20]  Huijun Gao,et al.  Finite Frequency $H_{\infty }$ Control for Vehicle Active Suspension Systems , 2011, IEEE Transactions on Control Systems Technology.