Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

Shrivastava, Akash; Mohanty, Amiya Ranjan

doi:10.1016/j.jsv.2017.11.020

Cited by 35 publications

(29 citation statements)

References 28 publications

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“…Let controllers be C 10 � k 2 z and C 11 � k 2 q. Put the controller on the bearing's model, and the model becomes equation (17). en, we can get equation (18) by the orthogonal polynomial approximation theory as used before:…”

Section: Linear Feedback Control Methodmentioning

confidence: 99%

See 1 more Smart Citation

Hopf Bifurcation and Control of Magnetic Bearing System with Uncertain Parameter

Wang

Hao³

et al. 2019

Complexity

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In this paper, the Hopf bifurcation and control of the magnetic bearing system under an uncertain parameter are investigated. Firstly, the two-degree-of-freedom magnetic bearing system model with uncertain parameter is established. The method of orthogonal polynomial approximation is used to obtain the equivalent magnetic bearing model which is deterministic. Secondly, combining mathematical analysis tools and numerical simulations, the Hopf bifurcation of the equivalent model is analyzed. Finally, a hybrid feedback control method (linear feedback control method combined with nonlinear stochastic feedback control method) is introduced to control the Hopf bifurcation behavior of the magnetic bearing system.

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Section: Linear Feedback Control Methodmentioning

confidence: 99%

“…Kiani et al [16] designed a segmented linear form of hybrid controller to stabilize the magnetic bearing system. Shrivastava and his team proposed a model-based method to estimate unbalanced rotor plane parameters, using Kalman filter and recursive least squares input force estimation technique in [17].…”

Section: Introductionmentioning

confidence: 99%

Hopf Bifurcation and Control of Magnetic Bearing System with Uncertain Parameter

Wang

Hao³

et al. 2019

Complexity

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“…The Kalman filter is a system dynamic estimation algorithm which produces an estimation of unknown variables using a series of measurements observed over time containing statistical noise and other inaccuracies. This method has been used successfully in the estimation of the critical parameters of the system, such as force [19][20][21][22], structural damage diagnosis [23], inverse heat conduction [24], pore water electrical conductivity [25], and mobile-robot attitude [26] and dynamic state [27][28][29]. Additionally, compared with other algorithms, such as dual Kalman filter [30], join Kalman filter [31], and even recursive least squares (RLS) [32], Kalman filtering is not only easier to achieve for estimating the main parameters in the discrete-time dynamic system, but also can save computing time.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for the Dynamic Coefficients Identification of Journal Bearings Using Kalman Filter

Kang

Shi

Zhang

et al. 2020

Sensors

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The dynamic coefficients identification of journal bearings is essential for instability analysis of rotation machinery. Aiming at the measured displacement of a single location, an improvement method associated with the Kalman filter is proposed to estimate the bearing dynamic coefficients. Firstly, a finite element model of the flexible rotor-bearing system was established and then modified by the modal test. Secondly, the model-based identification procedure was derived, in which the displacements of the shaft at bearings locations were estimated by the Kalman filter algorithm to identify the dynamic coefficients. Finally, considering the effect of the different process noise covariance, the corresponding numerical simulations were carried out to validate the preliminary accuracy. Furthermore, experimental tests were conducted to confirm the practicality, where the real stiffness and damping were comprehensively identified under the different operating conditions. The results show that the proposed method is not only highly accurate, but also stable under different measured locations. Compared with the conventional method, this study presents a more than high practicality approach to identify dynamic coefficients, including under the resonance condition. With high efficiency, it can be extended to predict the dynamic behaviour of rotor-bearing systems.

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“…Unbalance is one of the most common faults existing in rotating machinery. 1 The rotating unbalance can be categorized into initial unbalance and sudden unbalance based on the form of generation. The initial unbalance arises due to some reasons such as porosity in casting, non-uniform density of material and manufacturing tolerance, 2 while the sudden unbalance is generally caused by gain or loss of material during operation.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the transient response of a speed-varying rotor with sudden unbalance and its application in the unbalance identification

Xia

Ren

Qin

et al. 2019

Journal of Low Frequency Noise, Vibration and Active Control

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It is well known that the sudden unbalance is harmful for rotor systems, since it is in huge amount and has a strong impact. Thus, it is difficult to identify the unbalance from the sudden unbalance response of rotor and very few studies have been done on this topic. This paper focuses on the transient response characteristics of the speed-varying rotor when the sudden unbalance occurs, and the inherent correlation between the unbalance and the transient characteristic quantity. First, different time-dependent functions modelling the loading process of sudden unbalance are derived and compared with the experiment results of the test rotor. The selection principles of function type and duration value are presented. Analyses of transient response characteristics are conducted over the run-up process of the rotor with different parameters of sudden unbalance. Variations of transient response characteristics are summarized into three forms. The varying laws and interrelations of characteristic quantities, and the corresponding parameter region of sudden unbalance are illustrated for each form. Based on the transient analysis results, the momentary positions and angular variations of the rotor disc at some key time instants are illustrated via introducing the key-phase signal. A novel transient-vibration-based method for unbalance identification is proposed. Only a single run-up measurement is required. Numerical experiments verify the effectiveness of the method. In summary, the proposed method can provide a new way for the unbalance identification using the transient response.

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Estimation of single plane unbalance parameters of a rotor-bearing system using Kalman filtering based force estimation technique

Cited by 35 publications

References 28 publications

Hopf Bifurcation and Control of Magnetic Bearing System with Uncertain Parameter

Hopf Bifurcation and Control of Magnetic Bearing System with Uncertain Parameter

A Novel Method for the Dynamic Coefficients Identification of Journal Bearings Using Kalman Filter

Investigation on the transient response of a speed-varying rotor with sudden unbalance and its application in the unbalance identification

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