Blind-Kriging based natural frequency modeling of industrial Robot

Li, Shuwei; Fan, Shutian; Gu, Jinan; Li, Xingjia; Huang, Zedong

doi:10.1016/j.precisioneng.2021.11.008

Cited by 9 publications

(4 citation statements)

References 33 publications

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“…Among them, the Kriging method aims to conduct random interpolation based on the least square algorithm for spatial modeling and prediction calculation of random process or random field with the covariance weight function. 31 This temperature-driven model assumes that modal frequency is strongly linearly correlated with temperature variation. 32 Besides, Bayesian linear regression (BLR) and Bayesian dynamic linear model (BDLM) can be utilized as temperature-driven models to capture the modal variability.…”

Section: Correlation Modeling Methodsmentioning

confidence: 99%

“…The linear regression (LR) model is the simplest and most widely used method to track temperature‐induced frequency variation, which includes the least squares regression (LSR), the weighted least squares regression (WLSR), and the Kriging method. Among them, the Kriging method aims to conduct random interpolation based on the least square algorithm for spatial modeling and prediction calculation of random process or random field with the covariance weight function 31 . This temperature‐driven model assumes that modal frequency is strongly linearly correlated with temperature variation 32 .…”

Section: Elimination Of Modal Variability Based On Input–output Model...mentioning

confidence: 99%

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Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Wang

Yang

et al. 2022

Structural Contr & Hlth

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Modal frequencies are widely used for vibration-based structural health monitoring (SHM) and for capturing the dynamics of a monitored structure to reveal possible failures. However, changing environmental and operational conditions (i.e., temperature, humidity, wind load, and traffic load) may submerge the modal variability induced by structural damage, thereby falsely identifying damage of interest. This paper presents a comprehensive summary review of SHM for the prediction of modal frequency and the elimination of environment-induced masking effects based on the data normalization method. The influence mechanisms of external variations on modal frequencies extensively reported in the literature are first described. Next, the research progress in predicting and eliminating the operational modal variability is reviewed emphatically; this progress can be primarily divided into an inputoutput method that focuses on the establishment of the relationship model between structural frequency and environmental conditions and an outputonly method that separates the embedded environmental variable-induced changes depending on whether the environmental measurements are measured. Finally, the conclusions and future studies are summarized and discussed. As an overview, the major contribution of this paper is to provide objective technical references for engineers and owners and to further evaluate structural safety conditions more effectively and in a timely manner.

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Section: Correlation Modeling Methodsmentioning

confidence: 99%

Section: Elimination Of Modal Variability Based On Input–output Model...mentioning

confidence: 99%

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Wang

Yang

et al. 2022

Structural Contr & Hlth

View full text Add to dashboard Cite

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“…Kriging theory is a spatial statistical method originating from geostatistics that can realize unbiased estimation based on known sampling information with full consideration of the spatial correlation of variables. [23][24][25] In recent years, Kriging theory has been rapidly growing and widely used in the engineering field as the interpolation method of experimental or simulation data. In this paper, as the deformation to be predicted which is a function of the coordinates of motion axes, the Kriging method is adopted to construct an approximate model predicting the unknown stiffness information in the workspace of the DMRS.…”

Section: Kriging Methods Principlementioning

confidence: 99%

Deformation prediction and compensation of a dual-machine riveting system for aircraft assembly

Liu

Zhu

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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Automatic riveting systems play a crucial role in the field of aircraft manufacturing. In the riveting process, the machine tool bears a large axial squeezing force, and the resulting deformation will inevitably affect the riveting quality. In this paper, a dual-machine riveting system is developed first, the kinematic chain model and the lower-numbered body of the system structure are constructed sequentially. Then, considering the interaction and coupling effect of the two machines in the actual riveting process, the relative stiffnesses of the dual machine in the resisting state are identified by loading tests. Based on the stiffness data at a combination of postures within the workspace, a Kriging prediction model is established to describe the relationship between stiffness and postures. According to the prediction results, the influence of rotational and translational axes on the spatial stiffness distribution of the riveting system is revealed. Finally, the online deformation compensation is realized by modifying the displacement of the feed axis on both sides. A riveting experiment is carried out, and the results demonstrate that the riveting quality is significantly improved after compensation.

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“…The surrogate model significantly reduced the complexity of the analysis of the flexible manipulator. Fei et al 22 used the deep learning to establish the surrogate model of a flexible manipulator, and Li et al 23 adopted the Kriging technique to establish the surrogate model. Wang et al 24 employed the digital twin to build the surrogate model of a flexible manipulator.…”

Section: Introductionmentioning

confidence: 99%

An active control method for vibration reduction of a single-link flexible manipulator

Peng-yu

Xia

Wang

et al. 2022

Journal of Low Frequency Noise, Vibration and Active Control

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There are three motion stages for an industrial robot manipulator, including the acceleration stage, the constant velocity stage, and the deceleration stage. Aiming at reducing the residual vibration of the manipulator after the movement of the deceleration, a new method is proposed by configuring the movement parameters of the flexible manipulator. Firstly, we conduct experiments to verify a numerical vibration model of the manipulator, and then, we analyze the vibration suppression effect under different conditions based on the numerical model. The results show that in the range of one movement, the residual vibration can be well suppressed when the acceleration and deceleration time are set as a positive integer to the natural period of the manipulator operation; otherwise, the vibration suppression effect is not obvious and proportional to the difference between the acceleration/deceleration time and the manipulator natural period.

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Blind-Kriging based natural frequency modeling of industrial Robot

Cited by 9 publications

References 33 publications

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Eliminating environmental and operational effects on structural modal frequency: A comprehensive review

Deformation prediction and compensation of a dual-machine riveting system for aircraft assembly

An active control method for vibration reduction of a single-link flexible manipulator

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