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 new method for the estimation of bearing health state and remaining useful life based on the moving average cross-correlation of power spectral density
基于功率谱密度移动平均互相关的新方法用于轴承健康状态和剩余使用寿命的估计 |
| 作 者： |
Xu, Lang
Pennacchi, Paolo
Chatterton, Steven |
| 关键词： |
Bearing condition monitoring [轴承状态监测]
Remaining useful life [ 剩余使用寿命]
Power spectral density [ 功率谱密度]
Health index [ 健康指数]
Health state [ 健康状况]
Moving average cross-correlation coefficient [ 移动平均互相关系数] |
| 出版年： |
2020 |
| 期刊名： |
Mechanical Systems & Signal Processing
机械系统与信号处理 |
| 年卷期： |
2020, vol.139 |
| 摘 要： |
In the broad framework of condition-based maintenance, the final objective of bearing condition monitoring is to evaluate the health state and to estimate the remaining useful life of the bearings. The latter is a particularly challenging task, considering that remaining useful life is inextricably linked to a projection of what will happen in the future. Often, health indices, whose reliability relies on their effectiveness and consistency, are used for bearing condition monitoring. Most of the existing health indices pursue the property of monotonicity, but generally there are no obvious boundaries between the different health states of the bearings. Hence, it is quite difficult to give an objective and independent estimation of the health states, especially in real applications under different operating conditions and in the presence of noise. Furthermore, it is also difficult to set the failure threshold for a given health index when it is employed in different applications. In this paper, a new health index called 'MAC(2)PSD' is proposed, based on the moving average cross-correlation (MAC(2)) of the power spectral density (PSD) of the vibration signals. An interesting property of MAC(2)PSD is its capability to track the health condition and to discriminate clearly between the different health states. As shown in the paper, the MAC(2)PSD can also be used to estimate the remaining useful life by using its values during the defect-propagation phase. The effectiveness of MAC(2)PSD is shown by means of two different cases of bearing runto-failure experimental data, from two different test rigs. Additionally, the capability to avoid false positives is evaluated by means of bearing vibration data measured on a locomotive in commercial service. (C) 2020 Elsevier Ltd. All rights reserved.
在基于状态的维护总体框架下，轴承状态监测的最终目标是评估其健康状况并估算剩余使用寿命。后者是一项尤为艰巨的任务，因为剩余使用寿命与对未来发展趋势的预测密不可分。通常，轴承状态监测会采用一些健康指数，而这些指数的可靠性依赖于其有效性与一致性。目前大多数现有的健康指数都追求单调性，但不同轴承健康状态之间往往缺乏明确的界限，因此很难对健康状态进行客观且独立的评估，尤其是在实际应用中存在多种运行条件和噪声干扰的情况下。此外，在不同应用场景中使用同一健康指数时，也难以设定合适的失效阈值。本文提出一种名为“MAC(2)PSD”的新型健康指数，该指数基于振动信号功率谱密度（PSD）的移动平均互相关（MAC(2)）。MAC(2)PSD的一个有趣特性是其能够追踪健康状况，并清晰地区分不同的健康状态。如论文所示，MAC(2)PSD还可利用其在缺陷传播阶段的数值来估算剩余使用寿命。通过两个不同试验台的轴承从运行到失效实验数据案例，展示了MAC(2)PSD的有效性。此外，还通过在商用机车上的振动数据评估了其避免误报的能力。（C）2020 Elsevier Ltd. 保留所有权利。 |
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