A time delay method to solve non-collocated input estimation problems

Nordström, Lars; Nordberg, T. Patrik

doi:10.1016/j.ymssp.2004.02.006

Cited by 22 publications

(5 citation statements)

References 10 publications

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“…A review of the major developments in inversion of linear systems can be found in [3]. Alternative methods, namely the so-called deconvolution methods, are instead proposed in [4] and [5], while a review of frequency domain methods can be found in [6]. Of the previously mentioned approaches, only some can reconstruct both inputs and states of the system, while the reconstruction of states is also important in this work.…”

Section: Indirectly Measuring the Inputs Of A Mechanical Systemmentioning

confidence: 99%

Multibody model based estimation of multiple loads and strain field on a vehicle suspension system

Risaliti

Tamarozzi

Vermaut

et al. 2019

Mechanical Systems and Signal Processing

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This work proposes an augmented extended Kalman filter based state-input estimator for mechanical systems defined by implicit equations of motion which is then applied to estimate the six wheel center loads and the strain field on a vehicle suspension test rig.Implicit equations of motion typically arise in the definition of flexible multibody models and also in their time resolution, because implicit time-discretization schemes are normally employed to obtain a stable solution. The presented methodology can be applied to such case and analytical expressions are derived for the necessary linearizations, providing the means for a computationally efficient estimation procedure.The six wheel center loads and the strain field on a vehicle suspension system are valuable quantities during the vehicle design phase (e.g. for durability analysis), hence they are often directly measured during elaborate full vehicle testing campaigns. This work demonstrates that a flexible multibody model representation allows to accurately reconstruct the time domain signals of the six loads and of the full strain field, starting from a minimal set of six measured strains, hence providing an appealing alternative to direct measurement methods. The experimental validation on the suspension test rig shows that all estimated quantities can be accurately reconstructed, given that the system simulation model incorporates an adequate level of accuracy.

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Section: Indirectly Measuring the Inputs Of A Mechanical Systemmentioning

confidence: 99%

Multibody model based estimation of multiple loads and strain field on a vehicle suspension system

Risaliti

Tamarozzi

Vermaut

et al. 2019

Mechanical Systems and Signal Processing

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“…Based on the model of system state, an improved algorithm -Delayed Multistep ISF (DMISF) space is proposed by Allen to identify the time-domain load [16]. Nordström studied the load identification problem of the collocated system and non-collocated system based on the discrete state space model of the system, and used the time delay method to transform the identification of the ill-posed problem into a well-behaved one [19]. Because the inverse system method is not separated from the system state space model, it is necessary to know the prior knowledge of the system, so the application of the inverse system method is limited.…”

Section: Introductionmentioning

confidence: 99%

Torque identification based on LMS adaptive delay inverse system method

Li¹,

Song²,

Wang³

et al. 2020

J. meas. eng.

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In order to relieve the dependence of load estimation upon the prior knowledge of mechanical system, an adaptive delayed inverse model is proposed for identifying the torque time history based on adaptive delay inverse system identification method. The LMS (least mean square) algorithm was used to identify the inverse model of the rotating system, which instead of system characteristic matrix inversion in common determination methods and ill-posed problem is avoided consequently. The adaptive delayed inverse model was used to identify the time-domain torque by analyzing the angular acceleration response data of the working state. The single-point time-domain torque of the bare shaft was identified by the angular acceleration response in the case of noiseless interference. The simulation results illustrate that the recognition results of this method is satisfied. It is proved by the experiment that the method is also feasible to the shaft system with disk coupling. The proposed method can be applied in practical engineering as it is not necessary to grip the mathematical model and system parameters in advance.

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“…The FRF-based input estimation is an ill-posed problem in general, so the presence of noise and small deviations will cause significant errors that are far from reality [ 4 , 5 , 6 , 7 ]. To overcome this issue for FRF-based methods, additional information, e.g., spatial distribution of loads, must be needed to have a unique solution [ 8 , 9 ]. Classical time and frequency domain methods for input identification also suffer from the requirement of needing an exact model, which is not possible in practice [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties

Khodabandeloo

Melvin

2017

Sensors

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Direct measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well.

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A time delay method to solve non-collocated input estimation problems

Cited by 22 publications

References 10 publications

Multibody model based estimation of multiple loads and strain field on a vehicle suspension system

Multibody model based estimation of multiple loads and strain field on a vehicle suspension system

Torque identification based on LMS adaptive delay inverse system method

Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties

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