Optimal Design of a Vibration Isolation Mount Using Physical Programming

Wilson, Bruce H.; Erin, Cem; Messac, Achille

doi:10.1115/1.2802451

Cited by 10 publications

(5 citation statements)

References 13 publications

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“…Additionally, equation (11) indicates that the dynamic stiffness of the mount is equal to the rubber stiffness, K e , at low frequencies, assuming that the damping condition in equation (15) is satisfied. At higher frequencies, equations (11) and (15) imply that the dynamic stiffness can be approximated by…”

Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

“…According to equations (15) and (16), the fluid resonant frequency o rs is always greater than the notch frequency o ns . Additionally, equation (11) indicates that the dynamic stiffness of the mount is equal to the rubber stiffness, K e , at low frequencies, assuming that the damping condition in equation (15) is satisfied.…”

Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

“…The fluid mount model of figure 3 has two different energy domains: a hydraulic domain representing the dynamics of the fluid, and a mechanical domain for the elastomer's dynamics. The bond graph technique is used in this study due to its ability to conveniently model multi-domain systems [15,25]. Drawing on the similar models that have been suggested for fluid mounts by past researchers, we establish the bond graph model according to figure 6 for the double pumper fluid mount that is considered here.…”

Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

See 2 more Smart Citations

Optimal design of an engine mount using an enhanced genetic algorithm with simplex method

Ahn

Kim²,

Yang

et al. 2005

Vehicle System Dynamics

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This study provides an analysis of the applications of optimization routines for designing fluid mounts. After summarizing the concept of fluid mounts and their dynamic characteristics, we review the importance of the notch and resonance peak that occur in dynamic stiffness of fluid mounts. Fluid mounts are tuned for specific application so that their notch frequency coincides with the disturbance frequency, by selecting the proper parameters for the mount. Additionally, the mount parameters are selected such that the notch remains as deep (close to zero) as possible and the resonance peak is kept as short as possible. The notch depth and resonance peak present opposing requirements for the selection of mount parameters in the sense that lowering one will result in increasing the other. Using a bond graph model, this study will evaluate the effect of various parameters on the mount notch depth and resonance peak height characteristics. The results show that different parameters can have a varying effect on the notch frequency and depth, as well as the resonance frequency and peak height. The results of the study are extended by examining the effectiveness of two different optimization methods-namely, the Enhanced Genetic Algorithm (EGA) and Sequential Quadratic Programming (SQP)-for selecting the combination of parameters that can yield the deepest notch and shortest resonance peak. Using two different design cases, the study shows that SQP exhibits much more sensitivity to the initial conditions that are selected for the mount parameters than EGA. Both methods, however, are able to converge to an optimal solution within the constraints that are selected for the parameters. For both cases, EGA is able to converge to the set of parameters that provide a deep notch and a short resonance peak.

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Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

Section: Fluid Mount Mathematical Modelmentioning

confidence: 99%

See 1 more Smart Citation

Optimal design of an engine mount using an enhanced genetic algorithm with simplex method

Ahn

Kim²,

Yang

et al. 2005

Vehicle System Dynamics

View full text Add to dashboard Cite

show abstract

“…The class of the preference function associated with the second objective is 1S while the third objective's preference function is defined as Class 1H. Wilson et al [74] design a vibration isolation mount using PP. All design preferences (viz., minimization of the peak transmissibility, minimization of the transmissibility at 3 Hz, minimization of the transmissibility at 10 Hz, minimization of the settling time and minimization of the peak actuator force) are modeled as Class 1S.…”

Section: Designmentioning

confidence: 99%

Physical Programming: A Review of the State of the Art

Ilgın¹,

Gupta²

2012

SIC

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Most traditional multi-criteria optimization techniques require that the decision maker construct an aggregate objective function using the weights determined as a result of a trial and error process. Physical programming (PP) eliminates this tedious weight assignment process by providing decision makers with a flexible and more natural problem formulation. In PP, the decision maker specifies ranges of different degrees of desirability instead of defining weights. In this paper, we present a comprehensive review of PP studies by classifying them into four major categories (viz., methodological papers, industrial engineering applications, mechanical engineering applications and other applications). Insights from the review and future research directions conclude the paper.

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“…Actively controlled pneumatic vibration isolation tables are employed to protect semiconductor manufacturing and precision measurement equipment from vibration (1)(2)(3)(4) . A pneumatic isolation table is mounted on air springs which are actively controlled by servo valves.…”

Section: Introductionmentioning

confidence: 99%

Flow Disturbance Compensation Based on Off-Line Estimated Signal for a Pneumatic Isolation Table

Shirani

Nakamura

Wakui

2013

JAMDSM

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The flow disturbance to a pneumatic vibration isolation table causes periodic fluctuation of the table. In current study, one cycle of flow disturbance is estimated offline using a disturbance observer. The time series data of one cycle estimated disturbance is then stored in the memory of digital signal processor. The program codes are prepared which can detect every cycle of the flow disturbance based on the threshold of table position. The estimated signal is then repeatedly injected from the memory through a compensator to the servo valve to suppress table fluctuation due to periodic actual flow disturbance. The effectiveness of this method is demonstrated by experimental results.

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Optimal Design of a Vibration Isolation Mount Using Physical Programming

Cited by 10 publications

References 13 publications

Optimal design of an engine mount using an enhanced genetic algorithm with simplex method

Optimal design of an engine mount using an enhanced genetic algorithm with simplex method

Physical Programming: A Review of the State of the Art

Flow Disturbance Compensation Based on Off-Line Estimated Signal for a Pneumatic Isolation Table

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