Diagnosing wear faults - High-throughput screening of wind-turbine gearbox samples using the LaserNet 230 and automatic sample processor (ASP).
The major issue for premature failure in wind-turbine gearboxes is bearing failure, which leads to gearbox failure. A wind-turbine gearbox will not survive if the oil is not clean and especially if the hard ferrous particles are not removed from around the bearings.
The LaserNet 230 particle counter and ferrous debris monitor has been shown to be an excellent analytical tool for end users to diagnose wear faults in various machine applications such as gearboxes, engines, and transmissions. The wear generated in a wind-turbine gearbox is a function of load, speed, and lubricant condition. The lubricant must be correctly specified for the turbine gearbox’s idealized operating load and speed, and its condition must be carefully monitored in order to maintain the required lubricant film thickness in these regimes.
Ever-changing wind conditions and large variations in climates make wind-turbine condition monitoring extremely challenging. As a result, careful continuous automated monitoring of these critical and expensive assets is required. The National Renewable Energy Laboratory (NREL) uses the Lasernet Fines (LNF) technology in drive-train wind-turbine monitoring. It has demonstrated and recommended that condition-monitoring using the LNF is critical to avoiding premature failures in wind turbines.
Existing particle counter/auto sampler setups are not ideally suited for processing heavy batches of wind-turbine oil samples that also can vary considerably in contamination level. Extra dilution steps for the viscosity and the contamination levels are required, making them unsuitable compared to the standard clean oil hydraulic applications they were initially designed for.
GEARBOX WEAR PARTICLES
The abnormal wear generated in any gear system typically comes from the pitch line of the gear tooth (fatigue) or the tip of the gear (severe sliding). At the pitch line, the contact is rolling, so the particles will be similar to rolling contact fatigue particles. The gear contact has an increased sliding component as the root or tip is approached, and the particles will show signs of sliding morphology.
This morphological wear data is extremely beneficial to the end user, and abnormalities in the gearboxes caused by large particle generation are easily identifiable when trends are established that can distinguish ferrous from non-ferrous material. Another critical feature of a wind-turbine gearbox is the bearings are both on the low- and high-speed stages, and any misalignment of these will induce failure.
HIGH THROUGHPUT
Online techniques are offered as site solutions for customers with multiple windfarms, but these are costly and not sensitive enough. Centralizing the testing analysis by sending samples to a regional service center offers the best cost to monitoring benefit when large volumes of turbine samples are involved. Contract labs with the right high-throughput screening tools are well-equipped to turn around data quickly and can recommend further action and/or testing if necessary.
In a high sample-throughput scenario, such as a contract lab running more than 100 samples per day, it’s important to be able to screen samples accurately so a more thorough and in-depth ferrography analysis can be done on those select samples that show abnormal LNF/ferrous readings.
Ferrography is still one of the leading root-cause analysis techniques, but it requires a complimentary screening methodology that closely links particle size distributions, morphology, and ferrous content.
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