信息缺失的航空发动机传感器数据重构

周媛; 左洪福; 何军

doi:10.13700/j.bh.1001-5965.2015.0350

信息缺失的航空发动机传感器数据重构

doi: 10.13700/j.bh.1001-5965.2015.0350

周媛^1,2,
左洪福^2, ,,
何军¹

1.
南京信息工程大学电子与信息工程学院, 南京 210044
2. 南京航空航天大学民航学院, 南京 210016

基金项目: 国家自然科学基金(61203273,61402236,61079013)

详细信息

作者简介:
周媛女,博士研究生,讲师。主要研究方向:模式识别、航空发动机健康管理。Tel.:025-58731196 E-mail:zhouyuan@nuist.edu.cn;左洪福男,博士,教授,博士生导师。主要研究方向:可靠性工程、维修理论、故障诊断与监控等。Tel.:025-84891098 E-mail:rms@nuaa.edu.cn

通讯作者:
左洪福,Tel.:025-84891098 E-mail:rms@nuaa.edu.cn

中图分类号: V239;TP274
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- 被引次数: 0
出版历程
- 收稿日期: 2015-05-29
- 网络出版日期: 2016-05-20

Aeroengine sensor data reconstruction with missing data

ZHOU Yuan^1,2,
ZUO Hongfu^{2
, ,},
HE Jun¹

1.
College of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

摘要

摘要: 为处理传感器数据缺失问题,利用子空间表示系统演化特征,提出了基于极化增量矩阵填充(PIMC)的航空发动机传感器数据的在线重构模型。该模型通过历史数据获得当前的数据特征表示,并用新增的数据不断更新子空间以跟踪并表示数据发展特征。将本文模型用于仿真数据进行验证,重构结果和无噪数据的归一化均方误差(MSE)均小于1×10^-5,实验结果显示本文模型对于航空发动机传感器数据重构有很好的应用价值,对缺失数据和噪声是鲁棒的。
- 航空发动机 /
- 信息缺失 /
- 传感器数据重构 /
- 子空间 /
- 极化增量矩阵填充(PIMC)
Abstract: Aiming at handling incomplete sensor data, we propose an online-reconstruction model based on the polar incremental matrix completion (PIMC) algorithm for aeroengine sensor data, which can represent the evolving features of system by subspace. The model extracts the current data feature from the history data and updates the subspace to track the evolving features via new data. The proposed model was validated and compared on two simulated datasets and the normalized mean square errors (MSE) between the reconstruction by PIMC and the ground truth are all less than 1×10^-5. The experimental results show that the proposed model is practical for aeroengine sensor data reconstruction, which is robust to missing data and noise.
- aeroengine /
- missing data /
- sensor data reconstruction /
- subspace /
- polar incremental matrix completion (PIMC)

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参考文献(17)

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