Wind turbine operators typically check an oil analysis report for increases in metal concentration values and ISO codes as indicators of an impending failure. However, without a full understanding of the procedures used to calculate these numbers, operators may draw the wrong conclusions about the health of their systems. Traditional methods of oil sampling include Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) or Rotating Disk Electrode Atomic Emission Spectroscopy (RDE-AES). While these techniques can be useful for detecting changing levels of additive elements and contamination, they are unsuited for wear metal analyses pertaining to gearbox health.
Optical particle counting is another common technique used to monitor the health of wind turbine gearbox oil. Since optical particle counting only looks at scattered light, often they cannot determine the composition of the particles detected, sometimes even detecting air bubbles as particulate. Dirt, dust, and other soft particles cannot be distinguished from metallic particles, yet metallic particles are a much more important indicator of gearbox health than soft particles. Furthermore, since these counts are measured in ISO cleanliness codes, there can be huge variation from one rating to the next.
Online wear debris monitoring provides real-time information about the health of the gearbox that cannot be reliably determined from offline oil analysis. Research conducted by Poseidon Systems found that offline analysis had little-to-no correlation to gearbox health for a number of different reasons, and that online oil analysis did a far superior job in detecting faults early and had less false alarms than when using offline analysis. Download this white paper to learn more about how offline and online oil analysis can be combined to provide the best value!
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