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Research Papers

Robust Balancing Approach for Rotating Machines Based on Fuzzy Logic

[+] Author and Article Information
Vinícius Nunes Carvalho

LMEst—Structural Mechanics Laboratory,
School of Mechanical Engineering,
Federal University of Uberlândia,
Av. João Naves de Ávila, 2121,
Uberlândia 38408-196, Minas Gerais, Brazil

Bruno Ferreira Resende Rende, Arinan Dourado Guerra Silva, Valder Steffen, Jr.

LMEst—Structural Mechanics Laboratory,
School of Mechanical Engineering,
Federal University of Uberlândia,
Av. João Naves de Ávila, 2121,
Uberlândia 38408-196, Minas Gerais, Brazil

Aldemir Ap Cavalini, Jr.

LMEst—Structural Mechanics Laboratory,
School of Mechanical Engineering,
Federal University of Uberlândia,
Av. João Naves de Ávila, 2121,
Uberlândia 38408-196, Minas Gerais, Brazil
e-mail: aacjunior@ufu.br

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received August 30, 2017; final manuscript received March 21, 2018; published online May 4, 2018. Assoc. Editor: Costin Untaroiu.

J. Vib. Acoust 140(5), 051018 (May 04, 2018) (9 pages) Paper No: VIB-17-1393; doi: 10.1115/1.4039801 History: Received August 30, 2017; Revised March 21, 2018

Unbalance is one of the most common malfunctions found in rotating machines generating high vibration amplitudes that can lead to fatigue and wear of rotor elements. There are several well-known balancing techniques wherein one of the most widespread approaches is the so-called influence coefficients method (IC method). Aiming to increase the robustness of the standard IC method, in this paper, a revised IC balancing methodology for rotating machines is proposed. In this sense, a preprocessing stage is applied to access the uncertainties affecting the rotating machine. In this sense, measurement data sets evaluated under the fuzzy logic approach are used. Thus, the rotor vibration responses measured over a long period are considered by means of a fuzzy transformation (defining unbalance fuzzy sets). The unbalance condition of the rotating machine is determined through a defuzzification process. This unbalance condition is then introduced in the IC method algorithm aiming at obtaining correction weights and associated angular positions that increase the balancing robustness as compared with the classical approach. Numerical and experimental studies are used to evaluate the effectiveness of the proposed methodology. The obtained results illustrate the capacity to increase the balancing overall robustness.

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References

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Figures

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Fig. 2

Pseudo-code of the fuzzy transformation procedure (Adapted from Pota et al. [12])

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Fig. 3

Defuzzification techniques represented by a pseudo-trapezoidal membership function

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Fig. 4

Rotor used in the numerical simulation: (a) test rig and (b) FE model

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Fig. 5

Membership functions obtained by the considered transformation approach: (a) vibration amplitude of D1, (b) phase angle of D1, (c) vibration amplitude of D2, and (d) phase angle of D2

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Fig. 6

Vibration responses obtained at the disk D1 considering the robust and deterministic IC methods (○ unbalanced; □ balanced): (a) bisector, (b) SOM, (c) LOM, and (d) deterministic

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Fig. 7

Proximity sensors located close to the oil film bearing

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Fig. 8

Experimental membership functions obtained by the considered transformation approach: (a) vibration amplitude and (b) phase angle

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Fig. 9

Experimental vibration responses obtained by using the robust and deterministic IC methods (○ unbalanced; □ balanced/deterministic; + balanced/robust): (a) horizontal and (b) vertical

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Fig. 10

Extrapolation of the rotation speeds considering the robust and deterministic IC method (□ deterministic; ○ robust): (a) horizontal direction and (b) vertical direction

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