Reliability Assessment Of Wind Turbines Research Articles

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains

Due to the high failure rates and the high cost of operation and maintenance of wind turbines, not only manufacturers but also service providers try many ways to improve the reliability of some critical components and subsystems. In reality, redundancy design is commonly used to improve the reliability of critical components and subsystems. The load dependencies and failure dependencies among redundancy components and subsystems are crucial to the reliability assessment of wind turbines. However, the redundancy components are treated as a parallel system, and the load correlations among them are ignored in much literature, which may lead to the wrong system’s reliability and much higher costs. For this reason, this article explores the influences of load-sharing on system reliability. The whole system’s reliability is quantitatively evaluated using fault tree analysis and the Markov-chain method. Following this, the optimisation of the redundancy allocation problem considering the load-sharing is conducted to maximise the system reliability and reduce the total cost of the system subjecting to the available system cost and space. The results produced by this methodology can show a realistic reliability assessment of the entire wind turbine from a quantitative point of view. The realistic reliability assessment can help to design a cost-effective and more reliable system and significantly reduce the cost of wind turbines.

Reliability assessment of wind turbine bearing based on the degradation-Hidden-Markov model

Wind power develops very quickly in last decade to overcome the energy crisis and environment crisis. Mechanical components of wind turbines usually have characteristic with performance degradation that results in the declining reliability over time. Generally, the reliability data of equipment come from statistical analysis based on extensive experiments and operations. However, wind turbines, as expensive large-scale equipment with long lifetime, face with the dilemma of lacking enough statistical data, and leads to insufficiency reliability data for field operations and thus results in frequent wind turbine faults. A new reliability assessment method based on Hidden-Markov model considering performance degradation, called degradation-Hidden-Markov model, is proposed in this paper. The performance degradation rule of wind turbine component is derived using the monitoring data of performance parameters. Hidden-Markov model is improved by the performance degradation rule of the component to create a new time-correlated state transition probability matrix with degradation feature. The reliability curve is obtained using the state probabilities of the degradation-Hidden-Markov model. Thus, the presented method realizes the reliability assessment of component based on small sample data of wind turbine. Finally, the reliability assessment of a gearbox bearing of a 1.5 MW wind turbine by the degradation-Hidden-Markov model proves its validity.