Shuangwen Sheng, Ph.D.
Affiliations: | 2008 | Mechanical Engineering | University of Massachusetts, Amherst, Amherst, MA |
Area:
Mechanical EngineeringGoogle:
"Shuangwen Sheng"Parents
Sign in to add mentor| Robert X. Gao | grad student | 2008 | U Mass Amherst | |
| (Multi-Time Scale Modeling strategy for bearing life prognosis.) | ||||
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Publications
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| Guo Y, Sheng S, Phillips C, et al. (2020) A methodology for reliability assessment and prognosis of bearing axial cracking in wind turbine gearboxes Renewable and Sustainable Energy Reviews. 127: 109888 |
| Verstraeten T, Nowe A, Keller J, et al. (2019) Fleetwide data-enabled reliability improvement of wind turbines Renewable & Sustainable Energy Reviews. 109: 428-437 |
| Hong L, Qu Y, Dhupia JS, et al. (2017) A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement Mechanical Systems and Signal Processing. 94: 14-32 |
| Gao Z, Sheng S. (2017) Real-time monitoring, prognosis, and resilient control for wind turbine systems Renewable Energy. 116: 1-4 |
| Sheng S. (2016) Monitoring of Wind Turbine Gearbox Condition through Oil and Wear Debris Analysis: A Full-Scale Testing Perspective Tribology Transactions. 59: 149-162 |
| Yan R, Chen X, Li W, et al. (2014) Mathematical Methods and Modeling in Machine Fault Diagnosis Mathematical Problems in Engineering. 2014: 1-3 |
| Yampikulsakul N, Byon E, Huang S, et al. (2014) Condition Monitoring of Wind Power System With Nonparametric Regression Analysis Ieee Transactions On Energy Conversion. 29: 288-299 |
| Zappalá D, Tavner PJ, Crabtree CJ, et al. (2014) Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis Iet Renewable Power Generation. 8: 380-389 |
| Hong L, Dhupia JS, Sheng S. (2014) An explanation of frequency features enabling detection of faults in equally-spaced planetary gearbox Mechanism and Machine Theory. 73: 169-183 |
| Luo H, Hatch C, Kalb M, et al. (2014) Effective and accurate approaches for wind turbine gearbox condition monitoring Wind Energy. 17: 715-728 |