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基于铁谱分析的颗粒分类识别方法与应用
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国家科技支撑计划项目(2015BAA06B02)


Method and Application of Particle Classification Based on Analytical Ferrography
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    摘要:

    铁谱颗粒分析是机器磨损状态监测与维修决策制定最有效的油液分析方法。通过近年来开展工业企业机器油液监测积累的大量铁谱磨粒图像,进行基于不同的颗粒特征的分类识别探究,并基于不同颗粒形成机制与原因提出切合工业现场的润滑管理维保策略。应用实践表明,铁谱分析方法在机器磨损状态监测、润滑磨损诊断机制判别以及企业润滑管理提升活动中仍发挥着积极作用。

    Abstract:

    Ferrographic analysis is becoming the most effective oil analysis method for monitoring machine wear condition and making the maintenance strategy.A large number of debris images accumulated during the machine oil monitoring were classified based on different characteristics of the wear particles in industrial enterprises in recent years, and relevant lubrication management maintenance strategies were proposed based on the forming mechanism and reasons of the deferent debris.Application shows that ferrographic analysis plays an important role in monitoring machine wear condition,distinguishing lubrication and wear mechanism, and promoting the enterprise lubrication management activities.

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冯伟,李秋秋,贺石中.基于铁谱分析的颗粒分类识别方法与应用[J].润滑与密封,2015,40(12):125-130.
. Method and Application of Particle Classification Based on Analytical Ferrography[J]. Lubrication Engineering,2015,40(12):125-130.

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  • 在线发布日期: 2020-04-24
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