Balancing of high-speed machinery: Theory, methods and experimental results

Darlow, Mark S.

doi:10.1016/0888-3270(87)90087-2

Cited by 47 publications

(24 citation statements)

References 2 publications

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“…Thus the responses (forces or displacements) at the bearings are measured in rotor balancing (1S0 1925, 1981Everett. 1987;Darlow, 1987;1989).…”

Section: Introductionmentioning

confidence: 99%

Relation between correction masses and bearing forces in a rigid rotor

Jun

1999

KSME International Journal

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Bearing forces on a rigid rotor are mainly characterized by unbalance distribution. The forces can be divided into two arbitrary planes along a rotor shaft since any unbalance in the rigid rotor is able to be expressed on two planes. The correction mass quantities on two arbitrary planes are analytically found in terms of the bearing force measurements from the basic concept of three-dimensional rigid body dynamics. The quantities are expressed in terms of the geometry of rotor -the distance between t\VO bearings and the positions of two planes from the bearings -and the bearing forces: amplitudes of the alternating component of forces and angular positions of their peak values. The validity of the proposed method is proved using a simulation example.

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“…Thus the responses (forces or displacements) at the bearings are measured in rotor balancing (1S0 1925, 1981Everett. 1987;Darlow, 1987;1989).…”

Section: Introductionmentioning

confidence: 99%

Relation between correction masses and bearing forces in a rigid rotor

Jun

1999

KSME International Journal

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“…The non-contact sensors, typically eddy current sensors, measure the vibration in one-or two-dimensional dynamical responses for rotor systems. Based on the 1D or 2D vibration information, two groups of identification methods have been developed: model-based methods [4] and statistical methods [5]. The model-based methods, for example, the classical influence coefficient method [6] and modal balancing method, identify the parameters by the model emanating from a physics model without considering the uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Identification for Unbalanced Mass of Rotor Systems in Operation

et al. 2018

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Unbalanced mass identification is important for rotor systems. Current methods normally use sensors, which only detect vibration in two-dimensional (2D) space. Actually, the rotor systems vibrate in three-dimensional directions. In this paper, a non-contact method is developed to identify unbalanced mass of rotor systems in 3D space. A stereo video system with a pair of synchronized high-speed cameras is established and a feature point is employed to replace traditional contact transducer for measurement. Checkerboard target on a vibration table is used to implement dynamic calibration. The proposed method is compared with eddy current method and laser displacement method. The comparison experiments verify the detection ability of the unbalanced mass for the proposed method. Overall, the proposed method can provide more information than 2D detection methods, which has the great potential for fault diagnosis of rotating machinery.

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“…The machine rotor unbalance is observed to be one of the frequently occurring problems for any industrial rotating machine. Hence, regular in situ balancing is important to maintain the plant safety, reduce downtime and enhance production [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…Several vibration-based rotor fault identification methods have been proposed in the literature [1][2][3][4][5][6][7][8][9][10]. The influence coefficient (IC) balancing method [11][12][13][14][15], the modal balancing [7] and other balancing methods [16][17][18][19][20][21][22][23][24][25][26][27][28][29] are the most utilized vibration-based unbalance identification methods.…”

Section: Introductionmentioning

confidence: 99%

Rotor Unbalance Estimation with Reduced Number of Sensors

Shamsah

Sinha

2016

Machines

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Abstract:The most common cause of the excessive vibration in rotating machines is the rotor mass unbalance. If a machine vibration due to mass unbalance exceeds the alarm limits, then it may lead to machine failure. Therefore, rotating machines should be regularly checked to ensure that they are properly balanced. Currently, industries use the influence coefficient (IC) balancing technique for in situ machine balancing. The accepted practice is to use the vibration measurements in both vertical and horizontal directions at the machine-bearing pedestals together with the tachometer signal to estimate the machine rotor unbalance (both mass and phase angle). It is generally believed that the use of the machine vibration measurements in the vertical and horizontal directions represents better machine dynamics, and hence the estimated unbalance is likely to be more accurate. However, this paper applies the same concept of the IC method but with a reduced number of vibration sensors (one sensor per bearing pedestal at 45 • instead of two sensors at the vertical and horizontal directions). The use of one sensor per bearing pedestal at 45 • from both vertical and horizontal directions is likely to have responses from both directions. The reduction in the number of sensors by half will definitely save the instruments and their maintenance cost and reduce the computational effort in the signal processing significantly. The proposed concept is applied on a small-size laboratory rig with two balancing planes. The paper presents the unbalance estimations by using the measured vibration responses in both the vertical and horizontal directions simultaneously and using vibration responses measured at 45 • .

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Balancing of high-speed machinery: Theory, methods and experimental results

Cited by 47 publications

References 2 publications

Relation between correction masses and bearing forces in a rigid rotor

Relation between correction masses and bearing forces in a rigid rotor

Three-Dimensional Identification for Unbalanced Mass of Rotor Systems in Operation

Rotor Unbalance Estimation with Reduced Number of Sensors

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