A threshold for the use of Tikhonov regularization in inverse force determination

Choi, Hyun-Ki; Thite, A.N.; Thompson, D.J.

doi:10.1016/j.apacoust.2005.11.003

Cited by 44 publications

(22 citation statements)

References 14 publications

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“…Researchers in Refs. [4][5][6][7][8][9] have also proposed various new regularization methods to solve these ill-posed problems. Turco [10][11][12] used the inverse strategy to identify the external static loads and external dynamic loads of pin-jointed truss from the stress or strains responses data, and the numerical results demonstrate the feasibility and effectiveness of the inverse strategy.…”

Section: Introductionmentioning

confidence: 99%

Random dynamic load identification based on error analysis and weighted total least squares method

Jia

Yang

Guo

et al. 2015

Journal of Sound and Vibration

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Section: Introductionmentioning

confidence: 99%

Random dynamic load identification based on error analysis and weighted total least squares method

Jia

Yang

Guo

et al. 2015

Journal of Sound and Vibration

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“…Djamaa et al [3] had further understood about the dynamic loads distribution of the thin pilaster structure using the finite differential method; and eliminated the error amplification through normalized. Choi et al [4,5] improved the stability of the load identification results and studied the affect on loads identification accuracy selecting different normalization parameter. In order to identify a two-dimensional dynamic loads distribution, Paper [6] utilized the tensor theory to generate the high-dimensional moment basis function in the high dimensional orthogonal space and then represented the unknown two-dimensional dynamic load distribution with the undetermined coefficient in the form of high dimensional orthogonal function series.…”

Section: Introductionmentioning

confidence: 99%

“…Paper [8] put forward the condition number weighted algorithm based on inverse pseudo-excitation method, which improves the error amplifier problems of the identification results generated when matrix is "sick" in random loads identification. The methods offered in [2][3][4][5][6][7][8] solve the problem of identifying the dynamic loads mathematically, but they were all limited to be academic because of the complexities of the theory and the difficulty of large amount of calculation.…”

Section: Introductionmentioning

confidence: 99%

On the Identification Technology for the Random Load Spectrums

Li¹,

Wang²,

Qiu³

et al. 2015

Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

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Abstract-This paper deduces the relationship between the frequency response and loads for a structure within the frequency domain, and puts forward a new method for identifying the random loads spectrum. Firstly, the response power spectrum of structural control points is calculated based on the white noise loads spectrum. Then in order to get the corresponding random loads spectrum, the response power spectrum and the desired output response spectrum are compared. Finally, a specific cabin structure is analyzed by using the above method. The FEA (Finite Element Analysis) simulation results show that the method is valid in identifying the fundamental acceleration loads spectrum.

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“…Many methods are used for this purpose [30,31]. Among them, the condition number is an important judgment method and is expressed by…”

mentioning

confidence: 99%

A New Sampling Approach for Response Surface Method Based Reliability Analysis and Its Application

Meng

Jing

Zhang

et al. 2014

Advances in Mechanical Engineering

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A response surface method based on the all sample point interpolation approach (ASPIA) is proposed to improve the efficiency of reliability computation. ASPIA obtains new sample points through linear interpolation. These new sample points are occasionally extremely dense, thus easily generating an ill-conditioned problem for approximation functions. A mobile most probable failure point strategy is used to solve this problem. The advantage of the proposed method is proven by two numerical examples. With the ASPIA, the approximated process can rapidly approach the actual limit equation with accuracy. Additionally, there are no difficulties in applying the proposed ASPIA to the response surface model with or without cross terms. Solution results for the numerical examples indicate that the use of the response surface function with cross terms increases time cost, but result accuracy cannot be improved significantly. Finally, the proposed method is successfully used to analyze the reliability of the hydraulic cylinder of a forging hydraulic press by combining MATLAB and ANSYS software. The engineering example confirms the practicality of this method.

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A threshold for the use of Tikhonov regularization in inverse force determination

Cited by 44 publications

References 14 publications

Random dynamic load identification based on error analysis and weighted total least squares method

Random dynamic load identification based on error analysis and weighted total least squares method

On the Identification Technology for the Random Load Spectrums

A New Sampling Approach for Response Surface Method Based Reliability Analysis and Its Application

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