国外文献 > 1.轴承 > 5. 监测与诊断 > 寿命与维护
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| 标 题： |
A Bayesian Damage Prognosis Approach Applied to Bearing Failure
贝叶斯损伤预测方法在轴承失效中的应用 |
| 作 者： |
Zhu Mao
Michael Todd |
| 关键词： |
Bayesian decision-making [贝叶斯决策]
Structural health monitoring [ 结构健康监测]
Damage prognosis [ 损伤预后]
Remaining useful life [ 剩余使用寿命]
Particle filter [ 粒子滤波器] |
| 出版年： |
2014 |
| 文集名： |
Model Validation and Uncertainty Quantification - Proceedings of the 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014
模型验证与不确定性量化——第32届IMAC结构动力学会议暨展览论文集，2014年 |
| 会议名： |
32nd IMAC, A Conference and Exposition on Structural Dynamics
第32届IMAC结构动力学会议与展览会 |
| 届 次： |
32nd |
| 摘 要： |
Bearings are one of the most important components in rotating machinery, and their failure can cause catastrophic consequences. Conventional damage detection technologies have been successfully applied to make early warning of defect occurrence, mostly via vibration-related quantities due to damage-induced rattling. However, when the operational environment is highly variable and the online data suffer large uncertainties, robust early detection becomes challenging. Beyond simple detection, however, in-situ prognosis is even of greater interest, since it seeks to determine the remaining useful life (RUL), given condition monitoring data. Under realistic conditions, the nominal operation life, usually in terms of L10, is not practical when the prognosis is subject to the aforementioned uncertainties. This paper aims at updating the most plausible model parameters to obtain an accurate failure curve. From this Bayesian model updating process, the prediction of RUL is therefore made, associated with posterior probability. Vibration data are collected from the SpectraQuest machinery fault simulator, with gradually deteriorating bearings subject to fine foreign particles in the lubrication.
轴承是旋转机械中最重要的部件之一，其失效可能造成灾难性后果。传统损伤检测技术已成功应用于缺陷发生前的预警，主要通过振动相关参数实现，因为损伤会导致部件产生颤振。然而，当运行环境变化剧烈且在线数据存在较大不确定性时，实现鲁棒的早期检测变得十分困难。除了简单的检测之外，现场预测更受关注，因为它旨在根据状态监测数据确定剩余使用寿命（RUL）。在实际条件下，若预测过程受到上述不确定性影响，则通常以L10表示的额定使用寿命往往难以实现。本文旨在更新最合理的模型参数，以获得准确的失效曲线。基于此贝叶斯模型更新过程，可得到与后验概率关联的剩余使用寿命预测。振动数据来自SpectraQuest机械故障模拟器，轴承在润滑中逐渐受到细小异物颗粒的影响而发生劣化。 |
| 中文内容为网络AI翻译，专业术语未必准确，仅供参考。 |
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