A STATE-PARAMETER ESTIMATION IN TWO ENGINEERING DOMAINS: AN EXTENDED KALMAN FILTER APPROACH

L. Cot, S. Déjean, Carole Saudejaud
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Abstract

This paper intends to present a synthesis of works based on the study of the behavior of the Kalman filters in two different domains. The first area is dedicated to the flocculation process occurring in water treatment. The second one covers aircraft structural damage based on SHM approach. The general methodology consists in modeling a state-parameter observer to perform estimations using the joint EKF. The robustness and efficiency of the Kalman filters is addressed in order to allow a cross-fertilization in the two area. Model propagation and accurate prognostics are therefore allowed due to the improvement of model parameter knowledge. In the context of the flocculation, the prediction of the time evolution of the characteristic diameters is much more efficient than QMOM. For fatigue damage prognostic, the best initial conditions leading to accurate estimation are highlighted according to materials. Whatever the problem is, the estimation error magnitude is known.
两个工程领域的状态参数估计:一种扩展卡尔曼滤波方法
本文在卡尔曼滤波器在两个不同领域的行为研究的基础上,综合了前人的研究成果。第一个区域专门用于水处理中的絮凝过程。第二部分是基于SHM方法的飞机结构损伤。一般的方法包括对状态参数观测器进行建模,使用联合EKF进行估计。卡尔曼滤波器的鲁棒性和效率是为了使这两个领域的交叉受精。由于模型参数知识的提高,模型传播和准确预测成为可能。在絮凝条件下,对特征粒径时间演化的预测比QMOM更有效。在疲劳损伤预测中,根据材料的不同,突出了能准确估计疲劳损伤的最佳初始条件。无论问题是什么,估计误差的大小是已知的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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