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Research Papers

Probabilistic Performance of Helical Compound Planetary System in Wind Turbine

[+] Author and Article Information
Fisseha M. Alemayehu

Department of Mechanical Engineering,
Texas Tech University,
Lubbock, TX 79409
e-mails: fisseha.alemayehu@ttu.edu; fma12@psu.edu

Stephen Ekwaro-Osire

Department of Mechanical Engineering,
Whitacre College of Engineering,
Texas Tech University,
Lubbock, TX 79409
e-mail: stephen.ekwaro-osire@ttu.edu

1Current address: Penn State, Hazleton, Hazleton, PA 18202.

2Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received November 11, 2013; final manuscript received June 24, 2014; published online April 2, 2015. Assoc. Editor: Carlo L. Bottasso.

J. Comput. Nonlinear Dynam 10(4), 041003 (Jul 01, 2015) (12 pages) Paper No: CND-13-1275; doi: 10.1115/1.4027921 History: Received November 11, 2013; Revised June 24, 2014; Online April 02, 2015

The dynamics of contact, stress and failure analysis of multibody systems is highly nonlinear. Nowadays, several commercial and other analysis software dedicated for this purpose are available. However, these codes do not consider the uncertainty involved in loading, design, and assembly parameters. One of these systems with a combined high nonlinearity and uncertainty of parameters is the gearbox of wind turbines (WTs). Wind turbine gearboxes (WTG) are subjected to variable torsional and nontorsional loads. In addition, the manufacturing and assembly process of these devices results in uncertainty of the design parameters of the system. These gearboxes are reported to fail in their early life of operation, within three to seven years as opposed to the expected twenty years of operation. Their downtime and maintenance process is the most costly of any failure of subassembly of WTs. The objective of this work is to perform a probabilistic multibody dynamic analysis (PMBDA) of a helical compound planetary stage of a selected wind turbine gearbox that considers ten random variables: two loading (the rotor speed, generator side torque), and eight design parameters. The reliability or probabilities of failure of each gear and probabilistic sensitivities of the input variables toward two performance functions have been measured and conclusions have been drawn. The results revealed that PMBDA has demonstrated a new approach of gear system design beyond a traditional deterministic approach. The method demonstrated the components' reliability or probability of failure and sensitivity results that will be used as a tool for designers to make sound decisions.

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References

Figures

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Fig. 1

Schematic of the 1.5 MW compound WTGs

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Fig. 2

Loaded flexible MBD model of the 1.5 MW WTG and power flow

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Fig. 3

Stochastic upstream wind velocity at hub-height

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Fig. 4

Determination of extreme value (Gumbel) distribution parameters using MLE (a) rotor speed, NLSS and (b) torque on ISS, TISS

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Fig. 5

Distribution fitting to 40 s loading data (a) NLSS and (b) TISS

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Fig. 6

Flexible MBD model of CPHS of the 1.5 MW WTG

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Fig. 7

Second R-PP tooth mesh (a) tooth mesh force (b) contact incidence location along the face width

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Fig. 8

Second SP-PG tooth mesh (a) tooth mesh force (b) contact incidence location along the face width

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Fig. 9

Convergence test of GSTIFF-SI2 and HHT-I3 integrators through x-component mesh force results (a) SP-PG1 and (b) R-PP1

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Fig. 10

CDF of the tangential component of the (a) R-PP tooth mesh force and (b) SP-PG tooth mesh force

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Fig. 11

Probabilistic sensitivity factor of the tooth mesh force of the SP and PG with respect to (a) the mean of and (b) the SD of all random variables

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Fig. 12

CDF of the root bending stress of the (a) ring and (b) PP

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Fig. 13

CDF of root bending stress with picture of failed ring and PP

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Fig. 14

CDF of the root bending stress of the SP and PG

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