...
首页> 外文期刊>International journal of comadem >Detection of spiral bevel gear damage modes using oil debris particle distributions
【24h】

Detection of spiral bevel gear damage modes using oil debris particle distributions

机译:使用油屑颗粒分布检测螺旋锥齿轮损坏模式

获取原文
获取原文并翻译 | 示例

摘要

Damage progression tests were performed in the NASA Glenn Spiral Bevel Gear Fatigue Rig. During testing, debris generated were measured with an inductance type oil debris sensor, while different classes, modes and degrees of damage occurred on the gear teeth. Debris particle counts, their approximate size and mass were measured by the oil debris sensor. Tooth damage was documented with photographs at the start of the test, when damage occurred on one gear or pinion tooth and when damage transferred to two or more teeth. American Gear Manufacturers Association (AGMA) and American Society for Testing (ASTM) standards were used to describe gear tooth damage. Discrete thresholds based on counts and mass were defined for three gear set states: Healthy, Inspect and Damage. Histograms of particle size distributions were plotted for eight tests at the three gear states. Methods to predict particle size based on gear design and operating conditions were also presented. Results found monitoring oil debris mass provided a good indication of damage progression for slow progressing fatigue failures, while monitoring counts alone did not provide a good indication. The oil debris sensor could not be used to detect scuffing failure modes. Scuffing transfers material between the meshing gears and is less likely to generate debris. If historical data is unavailable, gear geometry and operational conditions could be used to estimate a threshold on mass and average particle size for indicating a contact fatigue damage state.
机译:在NASA Glenn螺旋锥齿轮疲劳钻机中进行了损伤进展测试。在测试过程中,使用电感式油屑传感器测量了产生的碎屑,而齿轮齿上出现了不同类别,模式和损坏程度。碎片颗粒计数,它们的近似大小和质量由油渣传感器测量。在测试开始时,当一个齿轮或小齿轮上发生损坏并且当损坏转移到两个或多个牙齿上时,照片中记录了牙齿损坏。美国齿轮制造商协会(AGMA)和美国测试协会(ASTM)标准用于描述齿轮齿损坏。为三种齿轮状态定义了基于计数和质量的离散阈值:“健康”,“检查”和“损坏”。绘制了三种齿轮状态下八次测试的粒度分布直方图。还提出了基于齿轮设计和运行条件预测粒度的方法。结果发现,监测油屑质量可以很好地指示缓慢进展的疲劳故障所造成的损害进展,而仅监测计数并不能提供良好的指示。油屑传感器无法用于检测划伤故障模式。刮伤会在啮合齿轮之间传递材料,并且不太可能产生碎屑。如果没有历史数据,则可以使用齿轮的几何形状和运行条件来估计质量和平均粒度的阈值,以指示接触疲劳损坏状态。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号