Chaos concepts as diagnostic tools for assessing rotating machinery vibration signatures

Adams, Maurice; Loparo, Kenneth A.

doi:10.1063/1.51043

Cited by 13 publications

(17 citation statements)

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“…The complicated motion and the sensitivity of the dynamics to parameters in the presence of rub impact are clearly indicated, this confirms the previous simulation and experimental results of [20], and [21] indicating the existence of chaotic dynamics during rub impact.…”

Section: Simulation Of the Rub Impact Modelsupporting

confidence: 89%

Fault detection of rotating machinery using model-based techniques

Abdel-Magied

Loparo²,

Horattas³

et al.

Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH

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This work formulates the problem of incipient fault detection and diagnostics for rotating machinery in a statistical model-based framework. This includes problem description, modeling of rotating machinery and fault mechanisms, formulation of the detection and diagnostics problem, and an implementation of the proposed scheme in a simulation environment to test the feasibility of this approach. More specifically, a multiple model nonlinear filtering algorithm is proposed for fault detection and diagnostics in a statistical framework. A simulation study, which includes normal and different fault modes, illustrates the potential of the proposed approach, especially in the presence of measurement noise and process uncertainty.

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Section: Simulation Of the Rub Impact Modelsupporting

confidence: 89%

Fault detection of rotating machinery using model-based techniques

Abdel-Magied

Loparo²,

Horattas³

et al.

Proceedings of the IECON'97 23rd International Conference on Industrial Electronics, Control, and Instrumentation (Cat. No.97CH

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show abstract

“…A further analysis was carried out considering the application of chaos theory on acquired signals to evaluate the possibility of early detection of surge incipient condition [32,34]. It is assumed that phenomena related to the condition of incipient surge generate a system response with non-linear contributions [35,36]. For this reason, it seems coherent to apply chaos quantifiers to diagnose the occurrence of the phenomenon.…”

Section: Vibration and Acoustic Analysismentioning

confidence: 99%

Experimental Dynamic Analysis on a T100 Microturbine Connected With Different Volume Sizes

Ferrari

Silvestri

Pascenti

et al. 2017

Journal of Engineering for Gas Turbines and Power

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This paper shows experimental results obtained from a T100 microturbine connected with different volume sizes. The activity was carried out with the test rig developed at the University of Genoa for hybrid system emulation. However, these results apply to all the advanced cycles where a microturbine is connected with an additional external component responsible for volume size increase. Even if the tests were performed with a microturbine, similar analyses can be extended to large size turbines. A modular vessel was used to perform and to compare the tests with different volume sizes. To highlight the volume size effect, preliminary experimental results were carried out considering the transient response due to an on/off bleed valve operation. So, the main differences between system parameters obtained for a bleed line closing operation are compared considering three different volume sizes. The main results reported in this paper are related to surge operations. To produce surge conditions in this test rig, a valve operating in the main air path was closed to generate unstable behavior for the three different volume sizes. Particular focus was devoted to the operational curve plotted on the compressor map. The vibration frequency analysis showed significant amplitude increase not only during surge events but also close to the unstable condition. In details, possible surge precursor indicators were obtained to be used for the detection of risky machine operations. The experimental data collected during these tests are analyzed with the objective of designing control systems to prevent surge conditions

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“…The numerical results show the importance of nonlinear behavior for journal operation at low eccentricities where nonlinearities increase as the journal is suddenly displaced to a larger eccentric operating point. Adams et al (14), (15) present transient studies of point-mass rotors supportecl on cylindrical journal bearings and tilting-pad bearings which address the phenomena of pad flutter at subsynchronous frequencies and the appearance of chaotic phenomena under particular operating and loading conditions. Hashimoto e t al.…”

Section: Llterature Reviewmentioning

confidence: 99%

Andrés

1997

Tribology Transactions

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The transient response of a point-mass rotor supported i n turbulent and hydrostatic bearings under a variety of external loadc are preflow, externally pressurized fluid film bearings is presented. The equasented. Transient responses based on a n approximate model which lions of motion are solved numerically with local linearization at uses constant rotordynamic f m e coeflicienls are also included and each integration time step. The bearing reaction f m e s are calculated shown to compare well with the full nonlinear responses. The nonporn the numerical solution of unsteady bulk-flow equations includlinear model needs small time steps with large execution times, while ing fluid inertia, turbulence, variable fluid properlies and thermal the simple linear model provides reliable resulh i n a minute fraction energy transport. Examples fbr the transient response of damper seals of time. A x , AY = rotor accelerations [m/s2] C = radial clearance function [m] c~ = fluid specific heat u/kg 'K] Cxx, CXY. CYX, CYY = damping force (linear) coefficients [Ns/ml c d = orifice discharge coefficient D = 2 R; bearing diameter [m] Dx(r) 9 D Y (~) =journal (rotor) center displacements in inertial coordinates [m] do = orifice diameter [m] = turbulent flow friction factors at journal and bearing surfaces 1,. 1 = bearing axial leng~h, recess axial length [ml M = point rotor mass [kg] Mxx, MXY, M Y X , MYY = bearing (linear) inertia force coefficients [kg] p, p, = fluid pressure, recess pressure [~/ m~] 9, = external supply pressure [~/ m~) Re = (RC/p)*; nominal circumferential flow Reynolds number RJ3 RB = flow Reynolds numbers relative to journal and bearing surfaces ' j 7 rt J a,+j = 0.001375 bM = 500,000 , CM = lo4. x. Y eM = 3.0 Fx, I.; = bearing fluid film forces along {X,Y} axes 1, 1, [Nl 7; 7; H = C + D x ( t ) cos0 + D y ( t ) sine; film u thickness [m] ' -J.xP uY H, = recess depth [m] Kxx, KXY. KYX. Kw = bearing (linear) force stiffness coefficients "x. "Y [N/ml W X ( I ) , W Y ( I ) 147 = roughness depths atjournal and bearing surfaces [m] = (Re, %) circumferential and axial flow coordinates = time coordinate [s], initial time [s] = temperature, supply temperature [OK] = rotor imbalance displacement [m] = bulk-flow velocities in circumferential ( x ) and axial (y) directions [m/s] =journal (rotor) velocity components [m/s] = external loads applied on rotor [N] Downloaded by [Ryerson University Library] at 02:01 06 June 2016 I 3 7.

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Chaos concepts as diagnostic tools for assessing rotating machinery vibration signatures

Cited by 13 publications

References 0 publications

Fault detection of rotating machinery using model-based techniques

Fault detection of rotating machinery using model-based techniques

Experimental Dynamic Analysis on a T100 Microturbine Connected With Different Volume Sizes

Transient Response of Externally Pressurized Fluid Film Bearings©

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