Rotor Model Validation for an Active Magnetic Bearing Machining Spindle Using Mu-Synthesis Approach

Madden, Ryan J.; Sawicki, Jerzy T.

doi:10.1115/1.4006988

Cited by 12 publications

(3 citation statements)

References 8 publications

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“…The method of model-based identification can be applied to extract the local changes in dynamics brought on by experimentally updating a nominal finite element model [25]. Experimental verification for this study has been completed on a high-speed machining spindle which is levitated on active magnetic bearings.…”

Section: Model Validationmentioning

confidence: 99%

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Control Driven Advances in Smart Rotating Machinery

Sawicki

2013

SSP

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In the last twenty years, there has been significant progress in the design of rotating machinery equipped with smart components and embedded functions. This was accompanied by developments in actuators, sensors and power electronics technologies, advances in data acquisition and signal processing, as well as developments in control theory. This paper will provide a brief overview of the current state of art and it will illustrate examples of the applications of smart technologies applied to rotating machines. Several technologies, either most recently developed or under development will be presented, which involve active control and are relevant to smart solutions applied to rotating machinery.

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Section: Model Validationmentioning

confidence: 99%

“…Fig.7. Frequency responses of the updated rotor (true system) and the nominal rotor (engineering system) due to an input at the front bearing and an output at the front sensor location (left); plot of the controller transfer functions with the same input and output locations[25] …”

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confidence: 99%

Control Driven Advances in Smart Rotating Machinery

Sawicki

2013

SSP

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“…Sawicki and Madden [8] applied model reconciliation with two experimentally tuned models of a rotordynamic system in order to extract the local change in dynamics induced by damage in the shaft of a magnetically levitated experimental rotor rig. The same authors applied a similar approach to an active magnetic bearing machining spindle to identify the dynamics brought on by the shrink fit mating of rotors [9].…”

Section: Introductionmentioning

confidence: 98%

Model Validation for Damage Identification and Determination of Local Damage Dynamics

Madden

Pesch

Sawicki

2015

Proceedings of the 9th IFToMM International Conference on Rotor Dynamics

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Robust control techniques have allowed engineers to create model sets which are robust to deviations from the actual system through the use of model uncertainty in the form of both additive noise and plant perturbations. To ensure the quality of the uncertain model, experimental unfalsification is employed to guarantee that the model set is able to recreate all experimental data points. In previous work, such a robust control relevant model validation technique was employed to identify the presence of damage on a rotordynamic test rig. Additionally, modelbased identification was employed to model the overall change in dynamics due to the damage, as well as to provide a novel quality measure for the identified damage dynamics. In the present work, the technique is extended to include a rotordynamic model. This advancement allows for locating the damage source and to determine the local change in dynamics at the damage location. The method is demonstrated experimentally on a rotordynamic test rig through the identification of a wire EDM cut in the shaft and determination of the local change in dynamics, including axial position along the shaft.

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