The mesh load factor, K 3, describes how loads are shared between planet gears and has become one of the key design challenges in modern wind turbine gearboxes. Planet load sharing directly impacts tooth root stresses, a critical driver of torque density and gearbox reliability. Experimental evaluation of K 3 is typically performed from sun gear tooth root strain gauge measurements, which are complex. Furthermore, such measurements can only provide an average value of load sharing. The present study describes an alternative method to evaluate the mesh load factor in wind turbine gearboxes based on fiber-optic strain sensors installed on the outer surface of the fixed ring gear. We present the results of an extensive measurement campaign to evaluate this novel sensing solution installed on the input planetary stage of a 2-MW wind turbine gearbox at the National Renewable Energy Laboratory's Flatirons Campus (Colorado, USA). The number of strain sensors on the ring gear was selected as an integer multiple of the number of planets, which has enabled an instantaneous evaluation of the mesh load factor. The effect of operating conditions on the planet load-sharing behavior of the gearbox has been investigated. The mesh load factor measured for operating conditions close to rated was below 1.05, well below IEC 61400-4 standard requirements.

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The significant increase in rotor diameters seen in modern wind turbines has pushed gearbox manufacturers to introduce technological innovations to increase the torque density of current designs. Driven by the need to lower the cost of energy from wind and size limitations imposed by logistic constraints in onshore wind, a trend has emerged to increase the number of planetary stages and the number of planet gears per stage. One of the main challenges of next-generation gearbox designs is sharing the load evenly between a high number of planets. This paper presents an experimental evaluation of the mesh load factor of a modern 6MW wind turbine gearbox with five planets in the first planetary stage. Results from the traditional method, based on tooth root strain gauges, and from strain measurements in the outer surface of the ring gear are described and assessed. Both experimental approaches have yielded lower mesh load factor values than the default values required in the standard "Design requirements for wind turbine gearboxes"IEC 61400-4. Since the mesh load factor is used for gear rating and sizing, a lower value allows a more optimized gearbox design, which leads to a significant improvement in torque density and cost.

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Accurate knowledge of the input torque in wind turbine gearboxes is key to improving their reliability. Traditionally, rotor torque is measured using strain gauges bonded to the shaft. Transferring the resulting signal from the rotating shaft to a stationary data acquisition system while powering the sensing devices is complex and costly. The magnitude of the torques involved in wind turbine gearboxes and the high stiffness of the input shaft pose additional difficulties. This paper presents a new alternative method to measure the input torque in wind turbine gearboxes based on deformation measurements of the static first-stage ring gear. We have measured deformation using fiber-optic strain sensors based on fiber Bragg gratings because of their advantages compared to conventional electrical strain gauges. The present study was conducted on a Siemens Gamesa Renewable Energy gearbox with a rated power of 6 MW, in which a total of 54 fiber-optic strain sensors were installed on the outer surface of the first-stage ring gear. The gear mesh forces between the planets and the ring gear cause measurable deformations on the outer surface of the stationary ring gear. The measured strains exhibit a dynamic behavior. The strain values change depending on the relative position of the strain sensors to the planet gears, the instantaneous variations of the input torque, and the way load is shared between planets. A satisfactory correlation has been found between the strain signals measured on the static ring gear and torque. Two signal processing strategies are presented in this paper. The first procedure is based on the peak-to-peak strain values computed for the gear mesh events, and therefore torque can only be estimated when a gear mesh event is detected. The second signal processing procedure combines the strain signals from different sensors using a Coleman coordinate transformation and tracks the magnitude of the fifth harmonic component. With this second procedure, it is possible to estimate torque whenever strain data of all sensors are available, leading to an improved frequency resolution up to the sampling frequency used to acquire strain data. The method presented in this paper could make measuring gearbox torque more cost-effective, which would facilitate its adoption in serial wind turbines and enable novel data-driven control strategies, as well as a more accurate assessment of the consumed fatigue life of the gearboxes throughout their operation.@en

Wind turbine technology has seen remarkable advancements in the last decades. Most notably, the rated power and size of wind turbines have grown considerably to reduce the cost of energy from wind. The increase in rotor diameters has pushed gearbox manufacturers to introduce multiple technological innovations to boost the torque density of current designs. One of the critical challenges of next-generation gearbox designs is to optimize structural components and gears. Complex models are needed to predict the gearbox components' load-carrying capacity and fatigue life. These tools need to be demonstrated and validated through experimental evaluation. Through physical testing, this study evaluates the structural calculation models used for a modern 6MW wind turbine gearbox. The measurement system is composed of fifty-four fiber Bragg gratings. Optical strain sensors have been used because they offer a higher signal-to-noise ratio, are immune to electromagnetic interference, and allow a more straightforward installation than conventional electrical strain gauges. A good correlation between the structural models and the test results in a full-scale back-to-back test bench has been achieved. This enables studying the effect of a range of design parameters through simulations. Hence, without the need to carry out physical testing for each design. Increasing the confidence in structural models through experimental data leads to more optimized gearbox designs and significant improvements in torque density and overall cost of the gearbox.

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The gearbox is a critical component of modern MW wind turbines. An accurate model of the gearbox dynamics is needed to improve gearbox design, develop advanced control algorithms, and more effective fault diagnosis tools which could lead to lower the cost of energy from wind. The objective of this paper is to investigate how torque measurements can be used in a data-driven framework to build dynamic models of wind turbine gearboxes. An initial torsional model has been derived from first principles considering the stiffness of the gears, shafts, and structural components in the gearbox together with the mechanical components of the test bench. This model has been used to create simulated data of the experiments performed on gearboxes and to apply system identification techniques to the simulated signals, with a focus on predictor based subspace identification methods. System identification has been applied to torque and speed data measured on physical tests of two 3.4MW gearboxes. Gearbox excitation frequencies and their harmonics dominate the measured signals and disturb the system identification algorithms. Several techniques have been investigated to remove the shaft rotation and gear mesh frequency harmonics of the torque and rotational speed signals based on time synchronous averaging.@en