提高测量可靠性的多传感器数据融合有偏估计方法

岳元龙; 左信; 罗雄麟

doi:10.3724/SP.J.1004.2014.01843

提高测量可靠性的多传感器数据融合有偏估计方法

doi: 10.3724/SP.J.1004.2014.01843

1.
中国石油大学(北京) 自动化系北京 102249

基金项目:

国家重点基础研究发展计划（973计划）（2012CB720500），国家自然科学基金（21006127，61104218），中国石油大学（北京）科研基金资助项目（YJRC-2013-12）资助

详细信息

作者简介:
岳元龙中国石油大学（北京）自动化系博士生.主要研究方向为测量、估计与可靠性.

通讯作者:
罗雄麟中国石油大学（北京）自动化系教授.主要研究方向为过程控制与实时优化，机器学习与智能控制，预测控制，过程系统工程.本文通信作者.E-mail：luoxl@cup.edu.cn

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- 文章访问数: 2216
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- 被引次数: 0
出版历程
- 收稿日期: 2013-05-31
- 修回日期: 2014-02-26
- 刊出日期: 2014-09-20

Improving Measurement Reliability with Biased Estimation for Multi-sensor Data Fusion

1.
Department of Automation, China University of Petroleum, Beijing 102249

Funds:

Supported by the National Basic Research Program of China (973 Program) (2012CB720500), National Natural Science Foundation of China (21006127, 61104218), and the Science Foundation of China University of Petroleum (YJRC-2013-12)

摘要

摘要: 为了提高测量数据可靠性，多传感器数据融合在过程控制领域得到了广泛应用. 本文基于有偏估计能够减小最小二乘无偏估计方差的思想，提出采用多传感器有偏估计数据融合改善测量数据可靠性的方法. 首先，基于岭估计提出了有偏测量过程，并给出了测量数据可靠性定量表示方法，同时证明了有偏测量可靠度优于无偏测量可靠度. 其次，提出了多传感器有偏估计数据融合方法，证明了现有集中式与分布式无偏估计数据融合之间的等价性. 最后，证明了多传感器有偏估计数据融合收敛于无偏估计数据融合. 实例应用验证了方法的有效性.
- 测量 /
- 可靠性 /
- 数据融合 /
- 有偏估计 /
- 岭估计
Abstract: The multi-sensor data fusion method is widely adopted in the process control community to improve the reliability of measured data. Based on the idea that biased estimation can reduce the variance of least square estimation, a multi-sensor biased estimation data fusion method is proposed to improve the measurement reliability. Firstly, biased measurement is presented based on ridge estimation, and a quantitative description method evaluating the reliability of the measurement data is proposed. The biased measurement reliability superior to the unbiased one is also verified. Secondly, a multi-sensor biased estimation data fusion scheme, which synthesizes the merits of the biased measurement and multi-sensor data fusion, is proposed, and the conclusion that is proven to decentralized unbiased estimation data fusion is equal to the centralized one is proved. Thirdly, the proposed fusion method is proven to converge to the unbiased estimation data fusion. Finally, a laboratory scale experiment illustrates that the presented method is effective.
- Measurement /
- reliability /
- data fusion /
- biased estimation /
- ridge estimation

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参考文献(23)

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提高测量可靠性的多传感器数据融合有偏估计方法

doi: 10.3724/SP.J.1004.2014.01843

作者简介:
岳元龙中国石油大学（北京）自动化系博士生.主要研究方向为测量、估计与可靠性.

通讯作者:
罗雄麟中国石油大学（北京）自动化系教授.主要研究方向为过程控制与实时优化，机器学习与智能控制，预测控制，过程系统工程.本文通信作者.E-mail：luoxl@cup.edu.cn

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Improving Measurement Reliability with Biased Estimation for Multi-sensor Data Fusion

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提高测量可靠性的多传感器数据融合有偏估计方法

doi: 10.3724/SP.J.1004.2014.01843

作者简介: 岳元龙 中国石油大学（北京）自动化系博士生.主要研究方向为测量、估计与可靠性.

通讯作者: 罗雄麟 中国石油大学（北京）自动化系教授.主要研究方向为过程控制与实时优化，机器学习与智能控制，预测控制，过程系统工程.本文通信作者.E-mail：luoxl@cup.edu.cn

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出版历程

Improving Measurement Reliability with Biased Estimation for Multi-sensor Data Fusion

计量

出版历程

目录

作者简介:
岳元龙中国石油大学（北京）自动化系博士生.主要研究方向为测量、估计与可靠性.

通讯作者:
罗雄麟中国石油大学（北京）自动化系教授.主要研究方向为过程控制与实时优化，机器学习与智能控制，预测控制，过程系统工程.本文通信作者.E-mail：luoxl@cup.edu.cn