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    A Physics-Based Model-Data-Driven Method for Spindle Health Diagnosis—Part III: Model Training and Fault Detection 

    Source: Journal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 008:;page 81006-1
    Author(s): Tai, Chung-Yu; Altintas, Yusuf
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The primary goal of the paper is to monitor the health of the spindle in machine tools to ensure optimal performance and reduce costly downtimes. Spindle health monitoring is essential to detect wear and cracks in spindle ...
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    A Physics-Based Model-Data-Driven Method for Spindle Health Diagnosis, Part II: Dynamic Simulation and Validation 

    Source: Journal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 008:;page 81005-1
    Author(s): Tai, Chung-Yu; Altintas, Yusuf
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Mathematical modeling of bearing faults, worn tool holder taper contact interface, and unbalance are presented and integrated into a digital dynamic model of spindles in Part I of this paper. These faults lead to changes ...
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    A Physics-Based Model-Data-Driven Method for Spindle Health Diagnosis, Part I: Modeling of Geometric Faults 

    Source: Journal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 008:;page 81004-1
    Author(s): Tai, Chung-Yu; Altintas, Yusuf
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The spindle determines the performance of machine tools; hence, monitoring its health is essential to maintain machining productivity and avoid costly downtimes. The magnitudes and locations of wear and cracks in the bearing ...
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