Vibration Reduction for a Flexible Arm Using Magnetorheological Elastomer Vibration Absorber

Magnetorheological (MR) elastomers become one of the most powerful smart and advanced materials that can be tuned reversibly, finely, and quickly in terms of their mechanical and viscoelastic properties by an input magnetic field. They are composite materials in which magnetizable particles are dispersed in solid base elastomers. Their distinctive behaviors are relying on the type and size of dispersed magnetic particles, the type of elastomer matrix, and the type of non-magnetic fillers such as plasticizer, carbon black, and crosslink agent. With these controllable characteristics, they can be applied to various applications such as vibration absorber, isolator, magnetoresistor, and electromagnetic wave absorption. This review provides a summary of the fabrication, properties, and applications of MR elastomers made of various elastomeric materials.

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“… Schematic diagram of ( a ) MRE vibration absorber (Reprinted with permission from [ 145 ] and ( b ) MRE isolation system [ 146 ]. …”

Section: Figurementioning

confidence: 99%

Magnetorheological Elastomers: Fabrication, Characteristics, and Applications

et al. 2020

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“…In order to solve this problem, researchers have made a lot of exploration and opened up a new idea of control with the help of neural network. Neural network can become a powerful tool for engineering mechanical arm control, which is determined by its strong nonlinear mapping ability, self-learning ability, and adaptive ability [22,23].…”

Section: Neural Network Control Methods Of Engineering Mechanical Armmentioning

confidence: 99%

Vibration and Trajectory Tracking Control of Engineering Mechanical Arm Based on Neural Network

Lei

2022

Computational Intelligence and Neuroscience

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We offer a neural network-based control method to control the vibration of the engineering mechanical arm and the trajectory in order to solve the problem of large errors in tracking the path when the engineering mechanical arm is unstable and under the influence of the outside world. A mechanical arm network is used to perform tasks related to learning the unknown dynamic properties of a engineering mechanical arms keyboard without the need for prior learning. Given the dynamic equations of the engineering mechanical arm, the dynamic properties of the mechanical arm were studied using a positive feedback network. The adaptive neural network management system was developed, and the stability and integrity of the closed-loop system were proved by Lyapunov’s function. Engineering mechanical arm motion trajectory control errors were modeled and validated in the Matlab/Simulink environment. The simulation results show that the management of the adaptive neural network is able to better control the desired path of the engineering mechanical arm in the presence of external interference, and the fluctuation range of input torque is small. The PID control has a large error in the expected trajectory tracking of the engineering mechanical arm, the fluctuation range of the input torque is as high as 20, and the jitter phenomenon is more serious. The use of detailed comparisons and adaptive neural network monitoring can perform well in manipulating the trajectory of the engineering mechanical arm. The engineering mechanical arm uses an adaptive neural network control method, in which the control precision of engineering mechanical arm motion trajectory can be improved and the out-of-control phenomenon of mechanical arm motion can be reduced.

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“…To broaden the working frequency bandwidth, adaptive DVAs that can adjust their resonant frequency via external control inputs have been recently developed in order to cope with shifting harmonic excitation. Several studies using electromagnets [8,9], piezoelectric materials [10,11], shape memory allosy [12,13], and magnetorheological elastomer (MRE) [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] have been reported to implement adaptive DVAs.…”

Section: Introductionmentioning

confidence: 99%

Vibration Isolation Performance of an Adaptive Magnetorheological Elastomer-Based Dynamic Vibration Absorber

Choi

Wereley²

2022

Actuators

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This study evaluates the vibration isolation performance of an adaptive magnetorheological elastomer (MRE)-based dynamic vibration absorber (MRE-DVA) for mitigating the high frequency vibrations (100–250 Hz) of target devices. A simple and effective MRE-DVA design was presented and its vibration isolation performance was experimentally measured. A cylindrical shaped MRE pad was configured to be operated in shear mode and also worked as a semi-actively tunable spring for achieving adaptive DVA. A complex stiffness analysis for the damper force cycle was conducted and it was experimentally observed that the controllable dynamic stiffness range of the MRE-DVA was greater than two over the tested frequency range. The transmissibility of a target system was measured and used as a performance index to evaluate its vibration isolation performance. It was also experimentally demonstrated that a better vibration isolation performance of the target device exposed to the high frequency vibrations could be achieved by using the adaptive MRE-DVA.

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Vibration Reduction for a Flexible Arm Using Magnetorheological Elastomer Vibration Absorber

Cited by 9 publications

References 23 publications

Magnetorheological Elastomers: Fabrication, Characteristics, and Applications

Magnetorheological Elastomers: Fabrication, Characteristics, and Applications

Vibration and Trajectory Tracking Control of Engineering Mechanical Arm Based on Neural Network

Vibration Isolation Performance of an Adaptive Magnetorheological Elastomer-Based Dynamic Vibration Absorber

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