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国外文献 > 1.轴承 > 2. 轴承类型与部件 > 滑动轴承

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标 题： A Bayesian approach for shaft centre localisation in journal bearings
用于轴心中心定位的贝叶斯方法在滚动轴承中的应用
作 者： Beamish S.
Dwyer-Joyce R.S.
Dervilis N.
Worden K.
Lindley C.A.
关键词： Bayesian statistics  [贝叶斯统计]
Gaussian Process  [ 高斯过程]
Journal bearing  [ 圆柱滚子轴承]
Oil film thickness measurement  [ 油膜厚度测量]
Shaft centre localisation  [ 轴心位置定位]
Ultrasound  [ 超声波]
出版年： 2022
期刊名： Mechanical Systems & Signal Processing
机械系统与信号处理
年卷期： 2022, vol.174
摘 要： It has been shown that ultrasonic techniques work well for online measuring of circumferential oil film thickness profile in journal bearings; unfortunately, they can be limited by their measuring range and unable to capture details of the film all around the bearing circumference. Attempts to model the film thickness over the full range of the bearing rely on deterministic approaches, which assume the observations to be true with absolute certainty. Unaccounted uncertainties of the film thickness may lead to a cascade of inaccurate predictions for subsequent calculations of hydrodynamic parameters. In the present work, a probabilistic framework is proposed to model the film thickness with Gaussian Processes. The results are then used to estimate the location of the bearing shaft under various operational conditions. A further step in the process involves using the newly-constructed dataset to generate likelihood maps displaying the probable location of the shaft centre, given the bearing rotational speed and applied static load. The results offer the possibility to visualise the confidence of the predictions and allow the true location to be found within an area of high probability within the bearing's bore.

研究表明，超声波技术适用于对滚动轴承中环向油膜厚度分布进行在线测量； 遗憾的是，由于测量范围的限制，它们无法全面捕捉轴承周长上薄膜的细节。若试图在轴承整个范围内建模薄膜厚度，通常依赖于确定性方法，这些方法假设观测结果具有绝对的准确性。而薄膜厚度中未被考虑的不确定性可能导致后续水动力参数计算中一系列预测不准确。在本研究中，提出了一种基于高斯过程的概率框架来建模薄膜厚度，并利用所得结果估算轴承轴心在不同运行条件下的位置。进一步步骤是使用新构建的数据集生成似然图，以显示在给定轴承转速和施加静载荷时轴心中心的可能位置。这些结果使得能够可视化预测的置信度，并在轴承孔内高概率区域内找到真实轴心位置。
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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