Reliability/Maintainability
Wind Turbine Reliability and Maintainability Enhancement through Systemwide Structure Health Monitoring and Modifications to Rotating Components
Project Team:
- Dr. James Steck, Aerospace Engineering, 萝莉社
- Dr. Walter Horn, Aerospace Engineering, 萝莉社
- Sayed Niknam, PhD student, Industrial Engineering, 萝莉社
- Zach Kral, M.S. student, Aerospace Engineering, 萝莉社
- Gigi Pham, B.S. student, Aerospace Engineering, 萝莉社
Preliminary failure mode and effects analysis (FMEA) shows the following reliability issues: (1) misalignment of rotating components of wind turbine caused by improper assembly, inflexibility, and change in operating condition; (2) bending, fatigue, and damage of those rotating components caused by torsion, time-varying and excessive loads, and/or lack of lubrication and cooling; and (3) cracking of turbine blades caused by fatigue and aging. Because of interactions among these components, reliability and maintainability need to be considered at both component and system levels. The long-term goal is to enhance the reliability and maintainability of wind turbines through systemwide health monitoring of the structure and modifications to rotating components. The one-year goal is to identify the point(s) for reliability improvement of the wind turbine, a feasible modification strategy, and the possibility for integrating sensor technology into condition monitoring. The outcomes of will be component/system reliability models, prognostics tools, and feasible sensor technologies used for monitoring the health of critical rotating components and blades. This work is significant because it will reduce the cost of turbine ownership by increasing turbine life and improving system maintainability.
The approach taken in this research is as follows: A redundancy strategy in the design stage will be explored to improve the reliability of critical rotating components, such as bearings. This may improve system reliability without the need for redesigning the component. A system reliability model that considers component reliability, interaction of components, and variable loads will be utilized to assist in determining the redundancy allocation strategy. To ensure the reliability of wind turbines and provide for timely maintenance during operation, continuous structural health monitoring (SHM) will be investigated as a means to provide degradation information of those structural components monitored based on maintenance and service parts management records. A fault diagnostic and prognostic tool will be developed with the help of vibration analysis and results from reliability testing to be conducted in the laboratory. In addition, misalignment detection and analysis will be investigated, which will significantly reduce the risk caused by fatigue loads within the system. Probe sensors will be utilized to collect vibration for orbit analysis and system calibration. Wear debris and oil analysis will be considered for monitoring the health status of a gearbox. Furthermore, it is difficult to predict the fatigue life of a turbine blade because of the inconsistency of blade material and time-varying operating conditions. To overcome this challenge, various sensor technologies, such as acoustic emission, will be investigated for monitoring cracks. A novel prognostic tool will be developed by incorporating a degradation/load model based on accelerated fatigue testing and Bayes updating.
The milestones and deliverables for this one year project are as follows:
- Develop a system reliability model through computer simulation, feasible system redundancy strategy, and justification for cost vs. benefit. Obtain possible component modifications and estimate of the system.
- Develop a testbed for accelerated degradation testing of bearings, collect vibration data, and develop degradation-feature extraction techniques. Obtain test data for bearings and a degradation/stress model.
- Develop diagnostic and prognostic tools based on degradation features and a bearing-degradation/stress model. Develop a set of software tools incorporating mathematical models and algorithms.
- Study the aging properties of wind turbine blade material and feasibility of integrating sensors into the blade structure. Identify appropriate sensors for in-service monitoring.
Contact Information:
James E. Steck, Ph.D.
Professor, Aerospace Engineering
College of Engineering
萝莉社
james.steck@wichita.edu
Supported by the Department of Energy
DOE DE-FG36-08GO88149
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