涡轮机
风力发电
机油分析
海洋工程
状态监测
碎片
汽车工程
环境科学
工程类
计算机科学
机械工程
地质学
电气工程
海洋学
作者
Jack Poley,Michael Dines
摘要
Wind turbines are frequently located in remote, hard-to-reach locations, making it difficult to apply traditional oil analysis sampling of the machine's critical gearset at timely intervals. Metal detection sensors are excellent candidates for sensors designed to monitor machine condition in vivo. Remotely sited components, such as wind turbines, therefore, can be comfortably monitored from a distance. Online sensor technology has come of age with products now capable of identifying onset of wear in time to avoid or mitigate failure. Online oil analysis is now viable, and can be integrated with onsite testing to vet sensor alarms, as well as traditional oil analysis, as furnished by offsite laboratories. Controlled laboratory research data were gathered from tests conducted on a typical wind turbine gearbox, wherein total ferrous particle measurement and metallic particle counting were employed and monitored. The results were then compared with a physical inspection for wear experienced by the gearset. The efficacy of results discussed herein strongly suggests the viability of metallic wear debris sensors in today's wind turbine gearsets, as correlation between sensor data and machine trauma were very good. By extension, similar components and settings would also seem amenable to wear particle sensor monitoring. To our knowledge no experiments such as described herein, have previously been conducted and published.
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