一个多特色的因素分析和动态窗口纠正方法,以预测滚动轴承的剩余使用寿命
Cheng Peng1,2, Yuanyuan Zhao1, Changyun Li1
1School of Computer, Hunan University of Technology, Zhuzhou 412007, China.
Entropy (Basel, Switzerland)
|November 24, 2023
概括
本研究引入了一种用于预测旋转机械剩余使用寿命 (RUL) 的新方法,通过使用健康指标 (HI) 构建和动态窗口整顿来减少波动来提高准确性.
科学领域:
- 机械工程 机械工程
- 可靠性工程可靠性工程
- 数据科学数据科学数据科学
背景情况:
- 对旋转机械的准确剩余使用寿命 (RUL) 预测对于工业可靠性和维护至关重要.
- 噪音等环境因素可能会对RUL预测准确性产生负面影响.
- 现有的方法往往侧重于健康指标 (HI) 构建和第一个预测时间 (FPT) 确定.
研究的目的:
- 开发一种改进的方法来预测轴承的RUL,解决由复杂的工业环境引起的准确性问题.
- 提高旋转机械的RUL估计的稳定性和可靠性.
主要方法:
- 一种新的健康指标 (HI) 构建方法,利用多特征因子分析来识别隐藏的共同因素.
- 基于在旋转后最大化偏差贡献的HI构造.
- 一种动态窗口纠正技术,以减轻HI中的随机波动.
- 通过HI轨迹的累积梯度变化来确定第一次预测时间 (FPT).
- 一个基于回归的自适应预测模型来学习HI趋势并估计RUL.
主要成果:
- 拟议的方法在RUL预测准确度方面显示了与现有技术相比的优势.
- 因子分析有效地从多个特征中挖掘出隐藏的共同因素,以实现强大的HI结构.
- 动态窗口纠正成功地减少了健康指标的波动.
- 在两个公共承载数据集上的实验验证证证了该方法的有效性.
结论:
- 开发的方法提供了一个更准确和可靠的方法来预测轴承的剩余使用寿命 (RUL).
- 整合因子分析和动态校正可提高RUL预测在工业环境中的稳定性.
- 这种方法有助于减少计划外维护,提高整体机器可靠性.
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