Identification of Rotor Unbalance as Inverse Problem of Measurement

Menshikov, Yuri

doi:10.4236/apm.2013.39a1004

Cited by 10 publications

(3 citation statements)

References 4 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the structural characteristic of the thin-disc workpiece, the mass of the workpiece can be taken as a face mass and the unbalance vector of the workpiece can be taken as the unbalance vector of machine chuck head face. Based on the linear reversible principle between the unbalancing excitation and vibration response, the unbalancing vector of the workpiece can be measured and estimated by analyzing the unbalancing vibration difference of the spindle before and after the thin-disc workpiece is clamped (Menshikov, 2013). The online measuring principle for the workpiece unbalancing vector is shown in Figure 1.…”

Section: Unbalancing Measuring Methods For Thin-disc Workpiece Based On Influence Coefficientmentioning

confidence: 99%

Online measuring and estimating methods for the unbalancing vector of thin-disc workpiece based on the adaptive influence coefficient

Zhang

2020

Journal of Vibration and Control

View full text Add to dashboard Cite

The thin-disc part is the common part of the rotary mechanism. Because of the large rotating radius of the thin-disc part, the huge unbalancing vector may be formed even if the unbalancing mass is small. So, the unbalance of the thin-disc part is the important exciting factor of the rotary mechanism vibration. Based on the structural characteristics of the thin-disc part, the measuring and estimating methods for the unbalancing vector of the thin-disc workpiece are proposed based on the single-face influence coefficient method. The least square method is introduced to fit the fundamental frequency component from the vibration monitoring signal, and the fundamental frequency component is taken as the unbalancing vibration signal of spindle first. The influence coefficient between the trial weight face and vibration monitoring point on the spindle is tested by trial weight experiments second. The unbalancing vibration difference of the spindle, before and after the thin-disc workpiece is clamped, is monitored and used to estimate the unbalancing vector of the thin-disc workpiece based on the linear reversible principle of unbalancing excitation and vibration response. The signal separation accuracy of the least square method for unbalancing vibration has been proved by simulation and experiment methods. Considering that the accuracy of the influence coefficient may be influenced by the change of the spindle system kinetic characteristic parameters, the signal measurement, analysis error, etc., the adaptive method for the influence coefficient is proposed and proved by the experiment method in the article. The research results show that the unbalancing vector of the thin-disc workpiece can be measured and estimated before the workpiece is taken down from the machine tool spindle. The proposed method can be used to measure and estimate the unbalancing vector of the thin-disc workpiece without dynamic balancing machine, and the measuring efficiency and accuracy can be improved; the measuring cost can be reduced.

show abstract

Section: Unbalancing Measuring Methods For Thin-disc Workpiece Based On Influence Coefficientmentioning

confidence: 99%

Online measuring and estimating methods for the unbalancing vector of thin-disc workpiece based on the adaptive influence coefficient

Zhang

2020

Journal of Vibration and Control

View full text Add to dashboard Cite

show abstract

“…With the rapid development of high speed and heavy power rotating machinery, detecting and eliminating faults of the rotor system have always been a hot issue in the field of rotating machinery design, research, and development. In the past decades, the research contents of rotor fault detection and elimination include the identification of initial unbalance [4][5][6], the resonance, flutter and damage monitoring of the blade [7][8][9], the looseness [10][11][12], the rotor/stator rubbing [13][14][15][16], crack [17][18][19], and misalignment effects [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Dynamic‐Balancing Testing System Designed for Flexible Rotor

Zhao

Ren

Liu

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

In this paper, a dynamic-balancing testing system is designed. The innovative feature of the testing system is the dynamic balancing of the rotor system with robustness and high balance efficiency which meets the requirements of engineering application. The transient characteristic-based balancing method (TCBM) interface and the influence coefficient method (ICM) interface are designed in the testing system. The TCBM calculates the unbalance by the transient vibration responses while accelerating rotor operating without trail-weight. The ICM calculates the unbalance by the steady-state vibration responses while the rotor system operates with trail-weight and constant speed. The testing system has the functions of monitoring operations synchronously, measuring and recording the required vibration responses, analyzing the dynamic characteristics, and identifying the unbalance parameters. Experiments of the single disc rotor system are carried out, and the maximum deflection of the measuring point has decreased by 73.11% after balancing by the TCBM interface. The maximum amplitude of the measuring point at 2914 r/min has decreased by 77.74% after balancing by ICM interface, while the maximum deflection during the whole operation has decreased by 70.00%. The experiments prove the effectiveness of the testing system, while the testing system has advantages of convenient and intuitive operation, high balance efficiency, and security.

show abstract

“…Menshikov [20] have investigated Krylov inverse problem, the early diagnostics of a rotor unbalance and the probablistic solutions of an inverse problem, whose steady solutions are obtained by algorithms based on Tikhonov regularization. Menshikov [21] considered the identification of the characteristics of the unbalance in a rotor with two supports as the basis for the measurements inverse problem. Specific assumptions were made to extract the exact solutions and obtain estimates of real unbalance characteristics.…”

Section: Introductionmentioning

confidence: 99%

Identification and optimization of unbalance parameters in rotor-bearing systems

Yao

Liu

Yang

et al. 2018

Journal of Sound and Vibration

View full text Add to dashboard Cite

The paper describes the identification and optimization of unbalance parameters in rotorbearing systems. Two methods are proposed for the identification of the unbalance characteristics: the first is based on modal expansion combined with the use of optimization algorithms, while the second relates to the use of modal expansion technique applied to the inverse problem. In this work, the modal expansion technique is used to overcome the issue related to the use of a reduced number of measuring points. The equivalent unbalance forces can then be estimated by expanding the modal displacements into generalized coordinates of the equations of motion of the rotor system. An error due to the use of a modal expansion is however inevitable, and to solve the issue we propose the adoption of an inverse problem formulation to avoid the computation of the displacements at each measurement point. The axial location of the unbalance must be however known in advance, if the inverse problem approach is used to identify the unbalance parameters. We therefore propose in this work an integrated modal expansion/inverse problem methodology combined with an optimization procedure. The technique allows to identify the axial location of the unbalance, its magnitude and phase. Simulation and experimental investigations are carried out to verify the validity of the proposed methods in a double-disk rotor-bearing system. The results show that identification and optimization procedure for the integrated modal expansion/inverse problem approach provides more accurate predictions than the ones given by the pure modal expansion method.

show abstract

Identification of Rotor Unbalance as Inverse Problem of Measurement

Cited by 10 publications

References 4 publications

Online measuring and estimating methods for the unbalancing vector of thin-disc workpiece based on the adaptive influence coefficient

Online measuring and estimating methods for the unbalancing vector of thin-disc workpiece based on the adaptive influence coefficient

A Dynamic‐Balancing Testing System Designed for Flexible Rotor

Identification and optimization of unbalance parameters in rotor-bearing systems

Contact Info

Product

Resources

About