Nonlinear modeling, dynamics, and chaos in a large deflection model of a rotor–disk–bearing system under geometric eccentricity and mass unbalance

Phadatare, Hanmant P.; Pratiher, Barun

doi:10.1007/s00707-019-02559-9

Cited by 20 publications

(6 citation statements)

References 22 publications

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“…Due to the manufacturing error of the single-stage disk, it makes the coaxiality error of the disk at all levels after the completion of assembly, and the existence of coaxiality error leads to the deviation of the disk inertia axis and rotation axis, which changes the eccentricity of the unbalanced mass [27]. In addition, the roughness between the contact surfaces can lead to inconsistent preload on the bolts, which can further distort the disk connection surfaces and affect the rotor's mass eccentricity.…”

Section: Disk Assembly Quality Influencing Factorsmentioning

confidence: 99%

Unbalance Prediction of Low Pressure Rotor Based on Mechanism and Data Fusion

et al. 2022

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The assembly, as the core part of low-pressure rotor manufacturing, is of great importance to ensure its unbalance. Low-voltage rotor assembly is a multi-process process influenced by the quality of part machining, assembly process, and assembly quality, resulting in unbalance that is difficult to predict during the assembly process. The unbalance measurement in the assembly process is important for the subsequent process optimization. Therefore, in order to achieve the prediction of unbalance measurement in the assembly process, this paper proposes an unbalance measurement prediction method based on mechanism and data fusion. Firstly, through research and analysis, the influencing factors of unbalance are determined, the low-pressure rotor blade sequencing mechanism model is established, and the blade sequencing optimization is realized by using reinforcement learning. Then, since the unbalance is formed after all the processes are completed and the subsequent work steps in the assembly process have not been carried out yet, the actual process parameters cannot be obtained, the semi-physical simulation method is used to combine the actual data of the assembled work steps with the theoretical data of the unassembled work steps to build a prediction model of the unbalance based on the BRNN (bidirectional recurrent neural network) network to achieve the prediction of the unbalance measurement in the assembly process. Finally, the model was validated using actual assembly process data, which proved the feasibility and effectiveness of the method.

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Section: Disk Assembly Quality Influencing Factorsmentioning

confidence: 99%

Unbalance Prediction of Low Pressure Rotor Based on Mechanism and Data Fusion

et al. 2022

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“…Ku (1998) and Kalita and Kakoty (2004) used the finite element method to model the rotor system and calculated the critical speed of the rotor-bearing system in consideration of the bearing dynamic characteristic coefficient according to the change of rotational speed. Lu et al (2019), Phadatare and Pratiher (2020) and Li et al (2019) formulated the kinematics equation of the rotor system, taking into account the gravities, geometric eccentricity and mass imbalance, gyroscopic effect. Yan et al (2020) and Luo et al (2020) studied a kinematics equation of the rotor system taking into account the unbalance excitations of the two rotors, vertical constant forces acting on the rotor system and an improved transfer-matrix method for investigating the steady-state response of complex rotor-bearing systems based in mathematical model of the system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling analysis of the gas turbine engine rotor system with SFD

CholUk¹,

Ri²,

ZhunHyok³

et al. 2022

AEAT

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Purpose As a core rotating component of power machinery and working machinery, the rotor system is widely used in the fields of machinery, electric power and aviation. When the system operates at high speed, the system stability is of great importance. To enhance the system stability, squeeze film damper (SFD) is being installed in the rotor system to alleviate vibration. The purpose of this paper is to first classify the rotor system into two types, the dual rotor system and the single rotor system, and to comprehensively and specifically mention the method of generating the dynamic model. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range. Design/methodology/approach In this paper, first, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. Here, the dynamic model of the rotor system was derived in detail for the single rotor system and the dual rotor system with and without SFD. Next, based on the establishment of a dynamic model with and without SFD in the rotor system, the optimization design of the rotor system with SFD was carried out using a genetic algorithm. The sensitivity analysis of the unbalanced response was carried out to determine the design variables of the optimization design. Through sensitivity analysis, SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system, and the objective function was the minimization of the maximum amplitude of the rotor system with SFD within the operation speed range. Findings SFD clearance, shaft stiffness and oil viscosity were determined as design variables of the rotor system through sensitivity analysis of the unbalanced response. These three variables are basic factors affecting the amplitude of the rotor system with SFD. Originality/value In the existing studies, only a dynamic model of a single rotor system with SFD was created, and the characteristic values of pure SFD were selected as optimization variables and optimization design was carried out. But in this study, the rotor system was classified into two types, namely, the dual rotor system and the single rotor system, and the method of creating a dynamic model was comprehensively and specifically mentioned. In addition, optimization design variables were selected and optimized design was performed through sensitivity analysis on the unbalanced response of factors affecting the vibration characteristics of the rotor system.

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“…Shan et al established a high-speed motorized spindle bearing-rotor dynamics model and analyzed the relationship between high speed and the transfer function of the milling cutter tip point [4]. Phadatare and Pratiher conducted a nonlinear dynamic analysis of a lightweight flexible rotordisk-bearing system with geometric eccentricity and mass unbalance [5]. Wang and Jiang used Runge-Kutta method to successfully numerically solve the control equation of the dual-rotor system with unbalanced and unaligned coupling faults [6].…”

Section: Introductionmentioning

confidence: 99%

Study on the Unbalanced Fault Dynamic Characteristics of Eccentric Motorized Spindle considering the Effect of Magnetic Pull

Wang

et al. 2021

Shock and Vibration

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Unbalanced fault is the most common fault of high-speed motorized spindle, which is the main factor affecting the machining accuracy of high-speed spindle. Due to the unbalanced magnetic pull produced by the air gap eccentricity of the stator and rotor, the unbalanced vibration of the motorized spindle will be further aggravated. In order to explore the dynamic behavior and motion law of the unbalanced fault motorized spindle under the eccentric state, a dynamic model of the unbalanced fault of the high-speed motorized spindle considering the unbalanced magnetic pull was established. Taking the eccentric motorized spindle customized by the research group as the research object, the dynamic model is established, simulated, and analyzed, and the response change law of motorized spindle under the effect of different speed, unbalance, and air gap is obtained. The simulation results show that the unbalanced magnetic pull caused by static eccentricity will increase the unbalanced vibration of motorized spindle, and the unbalanced vibration will also increase with the increase of static eccentricity. The vibration caused by unbalanced magnetic pull does not increase with the increase of rotating speed. In frequency-domain analysis, when there is unbalanced magnetic pull, the peak appears at 0 Hz, and the amplitude of fundamental frequency vibration will increase with the increase of eccentricity. The experimental results show that the greater the eccentricity is, the greater the unbalance vibration of the motorized spindle is. The experimental results are consistent with the simulation results, which further verify the accuracy of the model. The research results lay a theoretical basis for fault analysis and diagnosis of coupling fault motorized spindle.

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Nonlinear modeling, dynamics, and chaos in a large deflection model of a rotor–disk–bearing system under geometric eccentricity and mass unbalance

Cited by 20 publications

References 22 publications

Unbalance Prediction of Low Pressure Rotor Based on Mechanism and Data Fusion

Unbalance Prediction of Low Pressure Rotor Based on Mechanism and Data Fusion

Dynamic modeling analysis of the gas turbine engine rotor system with SFD

Study on the Unbalanced Fault Dynamic Characteristics of Eccentric Motorized Spindle considering the Effect of Magnetic Pull

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