INVESTIGATION OF VIBRATION BASED FAULT DETECTION METHODS FOR SPINDLE BEARINGS

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2022-12

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Karakaş, Mert

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Spindles are hearth of the CNC lathes and condition of them are critical for the industry. In this thesis, effects of bearing defect on spindles are investigated and condition of spindles are determined using vibration data collected at working conditions. After a comprehensive literature survey, a bearing model including effects of defects is constructed. Afterwards, a finite element model of a spindle is created, and outputs of the bearing model are used as inputs for the FEM. Using the model, effects of bearing defects on point FRF of spindle and tool point FRF are observed. Results are compared with the experiment done on a spindle before and after maintenance. In addition, vibration data measured from five different spindles at different working conditions are analyzed in detail for detecting bearing defects alongside with the common shaft faults.

Subject Keywords

Fault Detection, Condition Monitoring, Bearing Defect

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https://hdl.handle.net/11511/101288

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

M. Karakaş, “INVESTIGATION OF VIBRATION BASED FAULT DETECTION METHODS FOR SPINDLE BEARINGS,” M.S. - Master of Science, Middle East Technical University, 2022.