Reliability analysis of a nonlinear rotor/stator contact system in the presence of aleatory and epistemic uncertainty

Yang, Lechang; He, Ketai; Guo, Yuandong

doi:10.1007/s12206-018-0808-2

Cited by 14 publications

(4 citation statements)

References 29 publications

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“…It is obviously not easy to obtain sufficient statistical data because of the limited samples and high expenses for long-time tests. Occasionally, hybrid uncertainty modeling can be a better choice [13,36,118,[133][134][135][136]. For example, the probability-interval hybrid uncertain model [137] is widely employed for mechanical systems subject to both probabilistic and non-probabilistic uncertain parameters.…”

Section: Classificationsmentioning

confidence: 99%

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A state-of-the-art review on uncertainty analysis of rotor systems

Sinou

Zhu

et al. 2023

Mechanical Systems and Signal Processing

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Section: Classificationsmentioning

confidence: 99%

“…Further, the reliability sensitivity was obtained by derivatives [267]. Yang et al [118] used a likelihood-based approach for reliability analysis of the nonlinear rub rotor/stator system with mixed aleatory and epistemic uncertainties. Bayesian techniques were employed to reduce the cost of computation.…”

Section: Reliability Assessmentmentioning

confidence: 99%

A state-of-the-art review on uncertainty analysis of rotor systems

Sinou

Zhu

et al. 2023

Mechanical Systems and Signal Processing

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“…Some important assumptions that introduce epistemic uncertainty in the models are the independence among components, the renewal assumption o the constant operational condition and external factors [9]. Such premises and suppositions are the cause of epistemic uncertainty, reducible by integrating new information on the contrary of aleatory uncertainty, which comes from the stochastic character of the problem [10]. Therefore, if the models-based methods aim at accurately quantify the reliability, it is a requisite for them to integrate the effect of epistemic uncertainties [3].…”

Section: Motivation and Researchmentioning

confidence: 99%

Dynamic artificial neural network-based reliability considering operational context of assets.

Izquierdo

Márquez

Uribetxebarria

2019

Reliability Engineering & System Safety

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Assets reliability is a key issue to consider in the maintenance management policy and given its importance several estimation methods and models have been proposed within the reliability engineering discipline. However, these models involve certain assumptions which are the source of different uncertainties inherent to the estimations. An important source of uncertainty is the operational context in which the assets operate and how it affects the different failures. Therefore, this paper contributes to the reduction of the uncertainty coming from the operational context with the proposal of a novel method and its validation through a case study. The proposed model specifically addresses changes in the operational context by implementing dynamic capabilities in a new conception of the Proportional Hazards Model. It also allows to model interactions among working environment variables as well as hidden phenomena thanks to the integration within the model of artificial neural network methods.

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“…Lu et al [5] studied the vibrational behaviors of a dual-rotor bearing system with rub-impact coupling faults. Yang et al [6] adopted an approach to evaluating the reliability of a rotor system. Hou et al [7] investigated the gap of bearing and Hertzian contact exponent under dynamic loads, and the results show that the dynamic loads have differences of vibrational modes to the system at different rotating speeds.…”

Section: Introductionmentioning

confidence: 99%

Misalignment and Rub-Impact Coupling Dynamics of Power Turbine Rotor with Offset Disk

Nan,

Yang,

2024

Applied Sciences

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When the dual rotor system of the aircraft engine is operating, the mass eccentricity of the power turbine rotor and the misalignment of the shaft coupling or the bearing will cause too large vibration of the rotor; this vibration leads to the rub-impact between the rotor and the casing. The power turbine rotor from the dual rotor system is taken as the research object in this paper. Considering the misalignment, the resulting rub-impact faults, the imbalance of rotor and the disk offset, the equation of motion for the system is developed according to the Lagrangian Equation, and then the Range-Kutta Method is adopted to solve the equation. The influence of the key parameters such as the rotating speed, the misalignment angle and the rub-impact clearance on the dynamics of the system is studied; the finite element analysis was carried out to validate the correctness of the theoretical modeling method. The results show that the rub-impact increases the stiffness of the system; the Hopf bifurcation occurs in the misalignment and rub-impact coupling system; the vibrational stability near the half of the switching speed slumps with the increase of the misalignment angle; with increasing of the stiffness, the number of the chaotic zone increases, and the range of the chaos is widening; enlarging the rub-impact clearance is beneficial to reduce the degree of the rub-impact system and enhance the stability of the system.

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Reliability analysis of a nonlinear rotor/stator contact system in the presence of aleatory and epistemic uncertainty

Cited by 14 publications

References 29 publications

A state-of-the-art review on uncertainty analysis of rotor systems

A state-of-the-art review on uncertainty analysis of rotor systems

Dynamic artificial neural network-based reliability considering operational context of assets.

Misalignment and Rub-Impact Coupling Dynamics of Power Turbine Rotor with Offset Disk

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