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Title: Extending the lifetime of wind turbine gearboxes
Author: Igba, Joel Ejiroghene
ISNI:       0000 0004 6057 329X
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2017
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Wind turbines (WTs) are a proven source of clean energy with wind power energy harvesting technologies supplying about 3% of global electricity consumption in 2014. However there is an increasing demand on maintenance and operational improvements since turbines have been plagued with downtime problems ofmajor components e.g. gearboxes, which in particular are known to have a higher downtime per failure than other WT subassemblies. This is as a result of two reasons. First, WT gearboxes have historically suffered from early failures due to the underestimation of operational load conditions. Second, WT gearboxes have very complex repair procedures needing heavy lifting equipment such as external cranes for repair and replacement. This downtime results in revenue loss for the customer. Hence, for a company like Vestas Wind Systems AlS, who designs, manufactures and services WTs dealing with the gearbox downtime issue is of great importance. This thesis focuses on the gearbox challenge specific to Vestas organisational context based on a research journey undertaken by the author whilst embedded in Vestas as an employee. It focuses on the 2MW fleet of gearboxes serviced by Vesias globally. Furthermore, the thesis addresses two dimensions of the industrial problem - (i) investigating the gearbox problem, i.e. the issue with reliability and maintainability, and identifying solutions for improving these, and (ii) improvement of Vestas internal processes which contribute to delivering maintenance and repair solutions for gearboxes e.g. the capturing and reusing of maintenance and repair data for failure and reliability analysis. These two strands of the research equip decision makers within Vestas with tools and techniques for making decisions concerning the maintenance and repair challenges. Hence, enabling the company to improve performance of the gearboxes and extending the life of gearboxes. The main outcomes of this thesis are the development of new and novel in-service decision-making models (and tools) which are currently adding 'value to Vestas. First, a preventive maintenance optimisation model was developed by applying state of the art approaches used in industries like aerospace and marine, to historical gearbox in-service data from Vestas operational WTs. This model estimates the optimal interval for preventive replacements, repair and inspections of gearboxes. The benefit to Vestas is that the model helps WT managers to make timely decisions regarding planning and scheduling maintenance, which can reduce the downtime considerably and avoid consequential failures, hence resulting in cost savings for the company. Second, a novel extreme vibration model was developed using the automated condition monitoring data from operational gearboxes. This model can help in detecting failures on the high speed and intermediate speed stages of the gearbox as early as one month in advance. The model was recently developed and validated and is soon to be implemented in the organisation but it is expected to help avoid consequential failures and reduce downtime due to the ability to plan and schedule maintenance early as soon as a fault is detected. Third, a decision support framework (with an accompanying tool) for repair cost estimation, gearbox damage classification and feedback of repair data to design, was developed using a soft systems approach. In addition, a data repository has been created which contains repair statistics that is used for analysis purposes for guiding repair decisions and of the design of new gearboxes. The developed models, framework and tools are now being used across the organisation by engineers and service personnel, and by Vestas external repair providers, which has led to savings for Vestas in the order of hundreds of thousands of Euros yearly.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (D.Eng.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available