首页> 外文期刊>IFAC PapersOnLine >A new scheme for fault detection based on Optimal Upper Bounded Interval Kalman Filter
【24h】

A new scheme for fault detection based on Optimal Upper Bounded Interval Kalman Filter

机译:基于最优上限间隔Kalman滤波器的故障检测新方案

获取原文
           

摘要

This paper deals with a sensor fault detection approach using the Optimal Upper Bounded Interval Kalman Filter (OUBIKF) and an adaptive degree of freedom χ2-statistics method. It is devoted to discrete time linear model subjected to mixed uncertainties in terms of observations and noises. Mixed uncertainties mean both bounded and stochastic uncertainties. The degrees of freedom of this χ2 hypothesis test method are adaptively chosen thanks to amplifier coefficients improving the detection of the sensor faults. The proposed approach is an extension of a result developped in Lu et al. (2019). Application on a vehicle bicycle model highlights the efficiency of the proposed approach. Comparisons with other efficient estimation and fault detection strategies are provided to discuss the accuracy of the obtained results.
机译:本文涉及使用最佳上限间隔Kalman滤波器(Oubikf)和自由度χ2统计方法的传感器故障检测方法。 它致力于离散时间线性模型在观察和噪声方面进行混合不确定性。 混合不确定性意味着有界和随机的不确定性。 由于放大器系数提高了传感器故障的检测,自适应地选择了这种假设试验方法的自由度。 所提出的方法是在Lu等人开发的结果的延伸。 (2019)。 在车辆自行车模型上的应用突出了所提出的方法的效率。 提供了具有其他有效估计和故障检测策略的比较,以讨论所获得的结果的准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号