A recursive formulation based on corotational frame for flexible planar beams with large displacement

Wu, Tong; Liu, Zhuyong; Hong, Jin

doi:10.1007/s11771-018-3730-y

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…Although down sampling may reduce the image texture information and the face recognition rate, it can effectively reduce the dimension of the face image. In this algorithm, the down sampling recurrent neural network is not only used for face recognition [ 10 , 11 ], but also used to detect the occluded coverage, it makes up for the time-consuming shortcomings of the conventional sparse recognition algorithm in processing high-dimensional data, and can keep the overall texture structure of the face unchanged, and can detect the occluded or damaged areas of the face relatively accurately. As shown in Fig.…”

Section: Recognition Algorithm Of Partially Occluded Face Image Basedmentioning

confidence: 99%

A Local Occlusion Face Image Recognition Algorithm Based on the Recurrent Neural Network

Wang

Qiu

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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The recognition rate of traditional face recognition algorithm to the face image with occlusion is not high, resulting in poor recognition effect. Therefore, this paper proposes a partial occlusion face recognition algorithm based on recurrent neural network. According to the different light sources, the high filtering function is used to analyze the halo effect of the image, realize the preprocessing of partially occluded face image, set up the global face feature area and the local face feature area according to the image features, and extract the global and local features of the image; based on the time and structure features of the recursive neural network, establish the local subspace, and realize the local face image recognition Law. The experimental results show that: compared with the traditional algorithm, the face recognition algorithm studied in this paper has a higher recognition rate, and can accurately recognize the partially occluded face image, which meets the basic requirements of the current face image recognition.

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Section: Recognition Algorithm Of Partially Occluded Face Image Basedmentioning

confidence: 99%

A Local Occlusion Face Image Recognition Algorithm Based on the Recurrent Neural Network

Wang

Qiu

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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show abstract

“…For typical harmonic drive, Ghorbel and colleagues 5 , 6 established the model of harmonic reducer and verified the influence of reducer flexibility on motion through theoretical and experimental analysis. Hong and colleagues 7 – 9 used the basic principle of continuum mechanics to establish a rigid-flexible coupling dynamic equation, which has a high accuracy of coupling terms. Based on the principle of virtual displacement, Lu et al 10 supplemented and improved Kinetic Elastic Dynamic equation when modeling, and included the coupling term between elastic deformation and nominal motion of rigid body, which effectively improved the accuracy of the model.…”

Section: Introductionmentioning

confidence: 99%

Frequency response analysis of heavy-load palletizing robot considering elastic deformation

Sun

Wang

et al. 2019

Science Progress

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For the palletizing robot's operating characteristics of high speed, high acceleration, and heavy load, it is necessary to make a research on the structure optimization focusing on the vibration characteristics according to the mechanical and dynamic performance analysis. This article first introduces the mechanical feature and working principle of high-speed and heavy-load robot palletizer. Kinematics analysis is carried out by using D-H parameter method, which obtains positive kinematics solution and workspace. Jacobian matrix is deduced, and the relationship between joint space and Cartesian space is established. Second, for the reason that joint flexibility has a great influence on the vibration performance of the robot, a rigid-flexible coupling dynamic model is established based on the simplified model of the flexible reducer and Lagrange's second equation to describe the joint flexibility of high-speed and heavy-load palletizing robot, and the vibration modes of the robot are analyzed. The influence of different joint stiffness on the frequency response of the system reveals the inherent properties of the heavy-load palletizing robot, which provides a theoretical basis for the optimal design and control of the heavy-load palletizing robot. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).With the wide application of high-speed and heavy-load palletizing robots in automobile, metallurgy, and logistics industries, automated production lines put forward higher requirements for the speed, load capacity, acceleration, and positioning accuracy of robots. The high-speed and heavy-load palletizing robot not only reduces the positioning accuracy of the palletizing robot but also limits the speed of the robot. 1,2 In view of the high-speed, high-acceleration, and heavyload working characteristics of high-speed and heavy-load palletizing robot, it is not enough to complete structural analysis only at the kinematics level. It is necessary to carry out dynamic analysis of the robot body.Many achievements have been made in the study of flexible models. Bridges and Dawson 3 took into account the non-linear flexibility such as transmission friction, which made the flexible joint model more appropriate. On the basis of considering the non-linear links including backlash, Murphy et al. 4 established a complete flexible dynamic model of the robot by using Newton Euler method. For typical harmonic drive, Ghorbel and colleagues 5,6 established the model of harmonic reducer and verified the influence of reducer flexibility on motion through theoretical and experimental analysis. Hong and colleagues 7-9 used the basic principle of continuum ...

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An efficient recursive rotational-coordinate-based formulation of a planar Euler–Bernoulli beam

Fan

2021

Multibody Syst Dyn

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A recursive formulation based on corotational frame for flexible planar beams with large displacement

Cited by 6 publications

References 34 publications

A Local Occlusion Face Image Recognition Algorithm Based on the Recurrent Neural Network

A Local Occlusion Face Image Recognition Algorithm Based on the Recurrent Neural Network

Frequency response analysis of heavy-load palletizing robot considering elastic deformation

An efficient recursive rotational-coordinate-based formulation of a planar Euler–Bernoulli beam

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