一种改进的SR-CDKF算法及其在早期微小故障检测中的应用

陈业; 胡昌华; 周志杰; 张伟; 王华国

doi:10.3724/SP.J.1004.2013.01703

一种改进的SR-CDKF算法及其在早期微小故障检测中的应用

doi: 10.3724/SP.J.1004.2013.01703

1.
第二炮兵工程大学自动化系西安 710025;
2.
第二炮兵工程大学信息工程系西安 710025;
3.
第二炮兵驻7102厂代表室成都 610100

基金项目:

国家杰出青年科学基金(61025014), 国家自然科学基金(61004069), 陕西省自然科学基金(2011JQ8007)资助

详细信息

作者简介:
胡昌华博士,第二炮兵工程大学教授.主要研究方向为控制理论与应用,故障预报、诊断与可靠性工程.E-mail:hch6603@263.net

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出版历程
- 收稿日期: 2012-03-13
- 修回日期: 2012-07-05
- 刊出日期: 2013-10-20

Method of Improving Square-root Center Difference Kalman Filter with Application to Incipient Failure Detection

1.
Department of Automation, Xi'an Institute of Hi-Tech, Xi'an 710025;
2.
Department of Information Technology, Xi'an Institute of Hi-Tech, Xi'an 710025;
3.
Representative of the Second Artillery Forces 7102 Plant Room, Chengdu 610100

Funds:

Supported by National Science Fund for Distinguished Youth Scholars of China (61025014), National Natural Science Foundation of China (61004069), and the Natural Science Foundation of Shaanxi Province (2011JQ8007)

摘要

摘要: 复杂设备早期微小故障检测是故障检测与诊断领域的难题,系统状态和参数发生阶跃变化或者缓慢漂移是这类故障的主要特征. 本文在正交性原理的基础上,提出一种强跟踪平方根中心差分卡尔曼滤波(Square-root center difference Kalman filter, SR-CDKF), 即SSR-CDKF,并将SSR-CDKF应用于复杂设备的早期微小故障检测中. 仿真结果表明, SSR-CDKF能够更准确地估计系统状态和参数,更迅速地跟踪系统和参数突变情况. 通过仿真计算比较滤波器在不同参数取值下的方差值,得出了选择合适参数的方法. 最后利用该算法检测出了陀螺仪的早期微小故障.
- 非线性复杂系统 /
- 早期微小故障 /
- 平方根中心差分卡尔曼滤波 /
- 强跟踪
Abstract: It is difficult to detect the incipient failure of the complex facility in the failure detecting and diagnose field. The main characteristic of the incipient failure is the step change or gradual change of the states and parameters. Based on the orthogonality principle, this paper proposes a strong tracking square-root center difference Kalman filter (SR-CDKF) that is named as SSR-CDKF and applied to detect the incipient failure of the complex system afterwards. Simulation results demonstrate that the proposed filter can estimate the system state and parameter more accurately and track the step change state and parameter quicker than the SR-CDKF, the method of how to select the parameters appropriately is proposed by comparing the variance when selecting different parameters. At last, the incipient failure of gyro is detected by the proposed SSR-CDKF.
- Nonlinear complex system /
- incipient failure /
- square root center difference Kalman filter (SR-CDKF) /
- strong tracking

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参考文献(19)

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