增强卡尔曼滤波在虚点状态输入估计中的研究进展及频域误差分析

IF 10.2 1区 工程技术 Q1 ENGINEERING, MECHANICAL Mechanical Systems and Signal Processing Pub Date : 2025-03-15 Epub Date: 2025-02-01 DOI:10.1016/j.ymssp.2025.112338
Julian Staiger , Rafael S.O. Dias , Alessandro Zucchini , Milena Martarelli , Frank Naets
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引用次数: 0

摘要

在本文中,我们通过利用模态状态空间模型来表征虚点上的力,研究了增广卡尔曼滤波器在求解逆问题中的应用。模块化工程方法需要精确的界面力表征,由于界面不可接近,在实际操作中很难获得。然而,通过连接元件传递的力在声音中起着至关重要的作用。振动工程以及寿命分析和控制。在这项工作中,我们通过使用两种依赖于使用虚拟点变换(VPT)方法的不同策略来比较通过橡胶支架传递的力的估计。在第一种策略中,通过应用VPT来转换估计的施加力集来确定感兴趣的力。相反,在第二种方法中,通过利用使用VPT方法定义的投入减少模型直接估计感兴趣的力。该策略需要使用输入减少模型的增强状态空间表示,本文将对此进行推导。此外,提出了一种确定状态空间模型的新方法,将其简化为虚拟点,从而实现了与现有技术相比的低阶模型的计算。增广卡尔曼滤波(AKF)方案的频率相关估计误差源于建模误差,在一般意义上推导出用于位移和加速度测量的情况。研究表明,VPT引入了一个频率相关的误差项,该误差项会对输入简化模型得到的估计产生偏差。通过数值算例说明了这一理论频率相关误差,并对使用未简化模型和输入简化模型得到的结果进行了比较和分析。最后,以某工业橡胶衬套为例进行了实验分析。在时域和频域的预定义虚点上重构了施加在该分量中的力的激励效应。在时域和频域对各种激励都得到了良好的输入估计。然而,由于VPT的频率相关误差,使用输入简化模型获得的结果精度较低,这验证了对AKF频率相关估计误差的理论分析。
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Advancements and frequency domain error analysis for state-input estimation in virtual points via the augmented Kalman filter
In this paper, we investigate the usage of the augmented Kalman filter to solve inverse problems by exploiting modal state-space models to characterize forces in a virtual point. Modular engineering approaches require precise interface force characterization, which is challenging to obtain in operation due to the inaccessibility of the interface. However, forces transmitting through connecting components play a crucial role in sound & vibration engineering as well as in lifetime analysis and control. In this work, we compare the estimation of forces transmitting through a rubber mount by using two different strategies that rely on the use of the Virtual Point Transformation (VPT) method. In the first strategy, the forces of interest are determined by applying VPT to transform the estimated set of applied forces. Conversely, in the second methodology, the forces of interest are directly estimated by exploiting input-reduced models defined using the VPT method. This strategy requires the use of an augmented state-space representation of input-reduced models, which is derived in this article. Moreover, a novel approach to determine state-space models reduced into virtual points is proposed, leading to the computation of lower-order models compared to the ones computed with the state-of-the-art technique. The frequency-dependent estimation error of the Augmented Kalman Filter (AKF) scheme, stemming from modelling errors, is derived in a general sense for the cases where displacement and acceleration measurements are exploited. It is shown that the VPT introduces a frequency-dependent error term that biases the estimation obtained with the input-reduced model. This theoretical frequency-dependent error is illustrated in a numerical example, and the results obtained using unreduced and input-reduced models are compared and analysed. Subsequently, an experimental example is analysed, focusing on an industrial rubber bushing. The excitation effects of the forces applied in this component are reconstructed at pre-defined virtual points in both time and frequency domains. Good input estimates are obtained for all kinds of excitation in the time and frequency domains. However, it is found that the results obtained with the input-reduced model are less accurate due to the frequency-dependent error stemming from the VPT, which validates the performed theoretical analysis on the frequency-dependent estimation error of the AKF.
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来源期刊
Mechanical Systems and Signal Processing
Mechanical Systems and Signal Processing 工程技术-工程:机械
CiteScore
14.80
自引率
13.10%
发文量
1183
审稿时长
5.4 months
期刊介绍: Journal Name: Mechanical Systems and Signal Processing (MSSP) Interdisciplinary Focus: Mechanical, Aerospace, and Civil Engineering Purpose:Reporting scientific advancements of the highest quality Arising from new techniques in sensing, instrumentation, signal processing, modelling, and control of dynamic systems
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