基于空间时间相似性计算的轮风扇发动机健康评估
Cheng Peng1,2, Xin Hu1, Zhaohui Tang2
1School of Computer, Hunan University of Technology, Zhuzhou 412007, China.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
这项研究引入了一种新的方法,通过计算时空相似性来预测航空风扇发动机的剩余使用寿命. 该方法通过提高样本一致性和相似性来提高预测准确性,优于现有模型.
科学领域:
- 航空航天工程 航空航天工程
- 机械工程 机械工程
- 数据科学数据科学数据科学
背景情况:
- 航空轮风扇发动机剩余使用寿命 (RUL) 预测的准确性通常受到复杂的操作条件和传感器噪声的限制.
- 准确的RUL预测对于有效的发动机运行和维护决策至关重要.
研究的目的:
- 为航空风扇发动机提出一种新的剩余使用寿命预测方法.
- 为了解决由复杂的操作数据和传感器噪声引起的RUL预测中的低准确性问题.
- 为了提高轮风扇发动机的RUL预测的可靠性和准确性.
主要方法:
- 提出了一种空间时间相似性计算方法,涉及自适应序列匹配.
- 该方法构建时空轨迹序列,以实现最佳的样本匹配和相似性计算.
- 使用一个带有两个分配算法的权力训练模块和一个生命预测模块来确定最终的RUL.
主要成果:
- 拟议的方法证明了FD004数据集的RUL预测准确度的提高,根平均平方误差 (RMSE) 降低了12.6%,健康评分 (Score) 降低了14.8%.
- 在其他数据集中,RMSE仍然可比,而Score指数下降了约10%.
- 该方法通过序列匹配来增强样本相似性,从而导致更准确的RUL预测.
结论:
- 开发的基于时空相似性的方法显著提高了航空风扇发动机剩余使用寿命预测的准确性.
- 这种方法为复杂的发动机数据和传感器噪声所带来的运行挑战提供了强大的解决方案.
- 这些发现为优化轮风扇发动机的运行和维护策略提供了宝贵的支持.
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