关键液压元件的剩余使用寿命预测基于长寿命测试和贝叶斯联合模型与数据增强
Weijie Li1, Xinyuan Chen1, Xinbo Qian1
1Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China.
ISA transactions
|June 7, 2025
概括
这项研究引入了一种新的方法,用于预测液压元件的剩余使用寿命 (RUL),使用长寿命测试和贝叶斯联合模型与数据增强来提高准确性.
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:
- 剩余使用寿命 (RUL) 预测对于液压系统的可靠性至关重要.
- 目前的RUL预测方法通常依赖于有限的数据或模拟,阻碍长期准确性.
研究的目的:
- 开发一个更准确,更可靠的RUL预测方法,用于液压部件.
- 通过结合长寿命测试和先进建模来解决当前RUL预测方法的局限性.
主要方法:
- 在七个电磁上进行了长寿命测试,持续了20个月 (220万个周期).
- 采用数据增强技术来扩展RUL预测培训数据集.
- 开发了贝叶斯联合模型来分析条件监测,检查和事件数据之间的关系.
主要成果:
- 拟议的方法证明了对RUL预测的验证准确性和信心.
- 长寿命测试为评估预测模型提供了一个强大的数据集.
- 数据增强有效地增加了训练集大小,以提高模型性能.
结论:
- 拟议的RUL预测方法结合了长寿命测试,数据增强和贝叶斯联合模型,提高了预测的准确性和可靠性.
- 这种方法为确保液压系统的运行可靠性提供了更强大的解决方案.
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